Giftedness and Genetics: The Emergenic-Epigenetic Model and Its Implications

ERIC Educational Resources Information Center

Simonton, Dean Keith

2005-01-01

The genetic endowment underlying giftedness may operate in a far more complex manner than often expressed in most theoretical accounts of the phenomenon. First, an endowment may be emergenic. That is, a gift may consist of multiple traits (multidimensional) that are inherited in a multiplicative (configurational), rather than an additive (simple)…

A genome-wide survey of transgenerational genetic effects in autism.

PubMed

Tsang, Kathryn M; Croen, Lisa A; Torres, Anthony R; Kharrazi, Martin; Delorenze, Gerald N; Windham, Gayle C; Yoshida, Cathleen K; Zerbo, Ousseny; Weiss, Lauren A

2013-01-01

Effects of parental genotype or parent-offspring genetic interaction are well established in model organisms for a variety of traits. However, these transgenerational genetic models are rarely studied in humans. We have utilized an autism case-control study with 735 mother-child pairs to perform genome-wide screening for maternal genetic effects and maternal-offspring genetic interaction. We used simple models of single locus parent-child interaction and identified suggestive results (P<10(-4)) that cannot be explained by main effects, but no genome-wide significant signals. Some of these maternal and maternal-child associations were in or adjacent to autism candidate genes including: PCDH9, FOXP1, GABRB3, NRXN1, RELN, MACROD2, FHIT, RORA, CNTN4, CNTNAP2, FAM135B, LAMA1, NFIA, NLGN4X, RAPGEF4, and SDK1. We attempted validation of potential autism association under maternal-specific models using maternal-paternal comparison in family-based GWAS datasets. Our results suggest that further study of parental genetic effects and parent-child interaction in autism is warranted.

The genetics of mental illness: implications for practice.

PubMed Central

Hyman, S. E.

2000-01-01

Many of the comfortable and relatively simple models of the nature of mental disorders, their causes and their neural substrates now appear quite frayed. Gone is the idea that symptom clusters, course of illness, family history and treatment response would coalesce in a simple way to yield valid diagnoses. Also too simple was the concept, born of early pharmacological successes, that abnormal levels of one or more neurotransmitters would satisfactorily explain the pathogenesis of depression or schizophrenia. Gone is the notion that there is a single gene that causes any mental disorder or determines any behavioural variant. The concept of the causative gene has been replaced by that of genetic complexity, in which multiple genes act in concert with non-genetic factors to produce a risk of mental disorder. Discoveries in genetics and neuroscience can be expected to lead to better models that provide improved representation of the complexity of the brain and behaviour and the development of both. There are likely to be profound implications for clinical practice. The complex genetics of risk should reinvigorate research on the epidemiology and classification of mental disorders and explain the complex patterns of disease transmission within families. Knowledge of the timing of the expression of risk genes during brain development and of their function should not only contribute to an understanding of gene action and the pathophysiology of disease but should also help to direct the search for modifiable environmental risk factors that convert risk into illness. The function of risk genes can only become comprehensible in the context of advances at the molecular, cellular and systems levels in neuroscience and the behavioural sciences. Genetics should yield new therapies aimed not just at symptoms but also at pathogenic processes, thus permitting the targeting of specific therapies to individual patients. PMID:10885164

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

"Chromoseratops Meiosus": A Simple, Two-Phase Exercise to Represent the Connection between Meiosis & Increased Genetic Diversity

ERIC Educational Resources Information Center

Eliyahu, Dorit

2014-01-01

I present an activity to help students make the connection between meiosis and genetic variation. The students model meiosis in the first phase of the activity, and by that process they produce gametes of a fictitious reptilobird species, "Chromoseratops meiosus." Later on, they will "mate" their gametes and produce a zygote…

Anomalies as a Catalyst for Middle School Students' Knowledge Construction and Scientific Reasoning during Science Inquiry.

ERIC Educational Resources Information Center

Echevarria, Marissa

2003-01-01

Knowledge construction and scientific reasoning were examined during a unit in genetics, in which anomalies were used as a catalyst for student learning. Students used genetics simulation software to develop hypotheses and run tests of fruit fly crosses to develop mental models of simple dominance trait transmission. Instruction was intended to…

Evaluating the contribution of genetics and familial shared environment to common disease using the UK Biobank.

PubMed

Muñoz, María; Pong-Wong, Ricardo; Canela-Xandri, Oriol; Rawlik, Konrad; Haley, Chris S; Tenesa, Albert

2016-09-01

Genome-wide association studies have detected many loci underlying susceptibility to disease, but most of the genetic factors that contribute to disease susceptibility remain unknown. Here we provide evidence that part of the 'missing heritability' can be explained by an overestimation of heritability. We estimated the heritability of 12 complex human diseases using family history of disease in 1,555,906 individuals of white ancestry from the UK Biobank. Estimates using simple family-based statistical models were inflated on average by ∼47% when compared with those from structural equation modeling (SEM), which specifically accounted for shared familial environmental factors. In addition, heritabilities estimated using SNP data explained an average of 44.2% of the simple family-based estimates across diseases and an average of 57.3% of the SEM-estimated heritabilities, accounting for almost all of the SEM heritability for hypertension. Our results show that both genetics and familial environment make substantial contributions to familial clustering of disease.

A minimally sufficient model for rib proximal-distal patterning based on genetic analysis and agent-based simulations

PubMed Central

Mah, In Kyoung

2017-01-01

For decades, the mechanism of skeletal patterning along a proximal-distal axis has been an area of intense inquiry. Here, we examine the development of the ribs, simple structures that in most terrestrial vertebrates consist of two skeletal elements—a proximal bone and a distal cartilage portion. While the ribs have been shown to arise from the somites, little is known about how the two segments are specified. During our examination of genetically modified mice, we discovered a series of progressively worsening phenotypes that could not be easily explained. Here, we combine genetic analysis of rib development with agent-based simulations to conclude that proximal-distal patterning and outgrowth could occur based on simple rules. In our model, specification occurs during somite stages due to varying Hedgehog protein levels, while later expansion refines the pattern. This framework is broadly applicable for understanding the mechanisms of skeletal patterning along a proximal-distal axis. PMID:29068314

Ciona Genetics

PubMed Central

Veeman, Michael T.; Chiba, Shota; Smith, William C.

2010-01-01

Ascidians, such as Ciona, are invertebrate chordates with simple embryonic body plans and small, relatively non-redundant genomes. Ciona genetics is in its infancy compared to many other model systems, but it provides a powerful method for studying this important vertebrate outgroup. Here we give basic methods for genetic analysis of Ciona, including protocols for controlled crosses both by natural spawning and by the surgical isolation of gametes; the identification and propagation of mutant lines; and strategies for positional cloning. PMID:21805273

Complex and unexpected dynamics in simple genetic regulatory networks

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Revising and assessing explanatory models in a high school genetics class: A comparison of unsuccessful and successful performance

NASA Astrophysics Data System (ADS)

Johnson, Susan K.; Stewart, Jim

2002-07-01

In this paper we describe the model-revising problem-solving strategies of two groups of students (one successful, one unsuccessful) as they worked (in a genetics course we developed) to revise Mendel's simple dominance model to explain the inheritance of a trait expressed in any of four variations. The two groups described in this paper were chosen with the intent that the strategies that they employed be used to inform the design of model-based instruction. Differences were found in the groups' abilities to recognize anomalous data, use existing models as templates for revisions, and assess revised models.

Robust PD Sway Control of a Lifted Load for a Crane Using a Genetic Algorithm

NASA Astrophysics Data System (ADS)

Kawada, Kazuo; Sogo, Hiroyuki; Yamamoto, Toru; Mada, Yasuhiro

PID control schemes still continue to be widely used for most industrial control systems. This is mainly because PID controllers have simple control structures, and are simple to maintain and tune. However, it is difficult to find a set of suitable control parameters in the case of time-varying and/or nonlinear systems. For such a problem, the robust controller has been proposed.Although it is important to choose the suitable nominal model in designing the robust controller, it is not usually easy.In this paper, a new robust PD controller design scheme is proposed, which utilizes a genetic algorithm.

iACP-GAEnsC: Evolutionary genetic algorithm based ensemble classification of anticancer peptides by utilizing hybrid feature space.

PubMed

Akbar, Shahid; Hayat, Maqsood; Iqbal, Muhammad; Jan, Mian Ahmad

2017-06-01

Cancer is a fatal disease, responsible for one-quarter of all deaths in developed countries. Traditional anticancer therapies such as, chemotherapy and radiation, are highly expensive, susceptible to errors and ineffective techniques. These conventional techniques induce severe side-effects on human cells. Due to perilous impact of cancer, the development of an accurate and highly efficient intelligent computational model is desirable for identification of anticancer peptides. In this paper, evolutionary intelligent genetic algorithm-based ensemble model, 'iACP-GAEnsC', is proposed for the identification of anticancer peptides. In this model, the protein sequences are formulated, using three different discrete feature representation methods, i.e., amphiphilic Pseudo amino acid composition, g-Gap dipeptide composition, and Reduce amino acid alphabet composition. The performance of the extracted feature spaces are investigated separately and then merged to exhibit the significance of hybridization. In addition, the predicted results of individual classifiers are combined together, using optimized genetic algorithm and simple majority technique in order to enhance the true classification rate. It is observed that genetic algorithm-based ensemble classification outperforms than individual classifiers as well as simple majority voting base ensemble. The performance of genetic algorithm-based ensemble classification is highly reported on hybrid feature space, with an accuracy of 96.45%. In comparison to the existing techniques, 'iACP-GAEnsC' model has achieved remarkable improvement in terms of various performance metrics. Based on the simulation results, it is observed that 'iACP-GAEnsC' model might be a leading tool in the field of drug design and proteomics for researchers. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

PubMed Central

Su, Guosheng; Christensen, Ole F.; Ostersen, Tage; Henryon, Mark; Lund, Mogens S.

2012-01-01

Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP) markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects (MAD), and 4) a full model including all three genetic components (MAED). Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions. PMID:23028912

Evaluation of Genetic Algorithm Concepts using Model Problems. Part 1; Single-Objective Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2003-01-01

A genetic-algorithm-based optimization approach is described and evaluated using a simple hill-climbing model problem. The model problem utilized herein allows for the broad specification of a large number of search spaces including spaces with an arbitrary number of genes or decision variables and an arbitrary number hills or modes. In the present study, only single objective problems are considered. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all problems attempted. The most difficult problems - those with large hyper-volumes and multi-mode search spaces containing a large number of genes - require a large number of function evaluations for GA convergence, but they always converge.

Implementation of the Realized Genomic Relationship Matrix to Open-Pollinated White Spruce Family Testing for Disentangling Additive from Nonadditive Genetic Effects

PubMed Central

Gamal El-Dien, Omnia; Ratcliffe, Blaise; Klápště, Jaroslav; Porth, Ilga; Chen, Charles; El-Kassaby, Yousry A.

2016-01-01

The open-pollinated (OP) family testing combines the simplest known progeny evaluation and quantitative genetics analyses as candidates’ offspring are assumed to represent independent half-sib families. The accuracy of genetic parameter estimates is often questioned as the assumption of “half-sibling” in OP families may often be violated. We compared the pedigree- vs. marker-based genetic models by analysing 22-yr height and 30-yr wood density for 214 white spruce [Picea glauca (Moench) Voss] OP families represented by 1694 individuals growing on one site in Quebec, Canada. Assuming half-sibling, the pedigree-based model was limited to estimating the additive genetic variances which, in turn, were grossly overestimated as they were confounded by very minor dominance and major additive-by-additive epistatic genetic variances. In contrast, the implemented genomic pairwise realized relationship models allowed the disentanglement of additive from all nonadditive factors through genetic variance decomposition. The marker-based models produced more realistic narrow-sense heritability estimates and, for the first time, allowed estimating the dominance and epistatic genetic variances from OP testing. In addition, the genomic models showed better prediction accuracies compared to pedigree models and were able to predict individual breeding values for new individuals from untested families, which was not possible using the pedigree-based model. Clearly, the use of marker-based relationship approach is effective in estimating the quantitative genetic parameters of complex traits even under simple and shallow pedigree structure. PMID:26801647

Genetic and molecular dosimetry of HZE radiation (7-IML-1)

NASA Technical Reports Server (NTRS)

Nelson, Gregory A.

1992-01-01

The objectives of the study are to determine the kinetics of production and to characterize the unique aspects of genetic and developmental lesion induced in animal cells by radiation present in the space environment. Special attention is given to heavy charged particles. The organism Caenorhabditis elegans, a simple nematode, is used as a model system for a coordinated set of ground-based and flight experiments.

Genetic mixed linear models for twin survival data.

PubMed

Ha, Il Do; Lee, Youngjo; Pawitan, Yudi

2007-07-01

Twin studies are useful for assessing the relative importance of genetic or heritable component from the environmental component. In this paper we develop a methodology to study the heritability of age-at-onset or lifespan traits, with application to analysis of twin survival data. Due to limited period of observation, the data can be left truncated and right censored (LTRC). Under the LTRC setting we propose a genetic mixed linear model, which allows general fixed predictors and random components to capture genetic and environmental effects. Inferences are based upon the hierarchical-likelihood (h-likelihood), which provides a statistically efficient and unified framework for various mixed-effect models. We also propose a simple and fast computation method for dealing with large data sets. The method is illustrated by the survival data from the Swedish Twin Registry. Finally, a simulation study is carried out to evaluate its performance.

A simple model for pollen-parent fecundity distributions in bee-pollinated forage legume polycrosses

USDA-ARS?s Scientific Manuscript database

Random mating or panmixis is a fundamental assumption in quantitative genetic theory. Random mating is sometimes thought to occur in actual fact although a large body of empirical work shows that this is often not the case in nature. Models have been developed to model many non-random mating phenome...

A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

NASA Astrophysics Data System (ADS)

Danandeh Mehr, Ali; Kahya, Ercan

2017-06-01

Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.

Genetic change and rates of cladogenesis

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

Avise, J.C.; Ayala, F.J.

1975-12-01

Models are introduced which predict ratios of mean levels of genetic divergence in species-rich versus species-poor phylads under two competing assumptions: (1) genetic differentiation is a function of time, unrelated to the number of cladogenetic events and (2) genetic differentiation is proportional to the number of speciation events in the group. The models are simple, general, and biologically real, but not precise. They lead to qualitatively distinct predictions about levels of genetic divergence depending upon the relationship between rates of speciation and amount of genetic change. When genetic distance between species is a function of time, mean genetic distances inmore » speciose and depauperate phylads of equal evolutionary age are very similar. On the contrary, when genetic distance is a function of the number of speciations in the history of a phylad, the ratio of mean genetic distances separating species in speciose versus depauperate phylads is greater than one, and increases rapidly as the frequency of speciations in one group relative to the other increases. The models may be tested with data from natural populations to assess (1) possible correlations between rates of anagenesis and cladogenesis and (2) the amount of genetic differentiation accompanying the speciation process. The data collected in electrophoretic surveys and other kinds of studies can be used to test the predictions of the models. For this purpose genetic distances need to be measured in speciose and depauperate phylads of equal evolutionary age. The limited information presently available agrees better with the model predicting that genetic change is primarily a function of time, and is not correlated with rates of speciation. Further testing of the models is, however, required before firm conclusions can be drawn. (auth)« less

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.

Adaptive Topographies and Equilibrium Selection in an Evolutionary Game

PubMed Central

Osinga, Hinke M.; Marshall, James A. R.

2015-01-01

It has long been known in the field of population genetics that adaptive topographies, in which population equilibria maximise mean population fitness for a trait regardless of its genetic bases, do not exist. Whether one chooses to model selection acting on a single locus or multiple loci does matter. In evolutionary game theory, analysis of a simple and general game involving distinct roles for the two players has shown that whether strategies are modelled using a single ‘locus’ or one ‘locus’ for each role, the stable population equilibria are unchanged and correspond to the fitness-maximising evolutionary stable strategies of the game. This is curious given the aforementioned population genetical results on the importance of the genetic bases of traits. Here we present a dynamical systems analysis of the game with roles detailing how, while the stable equilibria in this game are unchanged by the number of ‘loci’ modelled, equilibrium selection may differ under the two modelling approaches. PMID:25706762

Multitrait, random regression, or simple repeatability model in high-throughput phenotyping data improve genomic prediction for wheat grain yield

USDA-ARS?s Scientific Manuscript database

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat (Triticum aestivum L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect s...

Computational principles underlying recognition of acoustic signals in grasshoppers and crickets.

PubMed

Ronacher, Bernhard; Hennig, R Matthias; Clemens, Jan

2015-01-01

Grasshoppers and crickets independently evolved hearing organs and acoustic communication. They differ considerably in the organization of their auditory pathways, and the complexity of their songs, which are essential for mate attraction. Recent approaches aimed at describing the behavioral preference functions of females in both taxa by a simple modeling framework. The basic structure of the model consists of three processing steps: (1) feature extraction with a bank of 'LN models'-each containing a linear filter followed by a nonlinearity, (2) temporal integration, and (3) linear combination. The specific properties of the filters and nonlinearities were determined using a genetic learning algorithm trained on a large set of different song features and the corresponding behavioral response scores. The model showed an excellent prediction of the behavioral responses to the tested songs. Most remarkably, in both taxa the genetic algorithm found Gabor-like functions as the optimal filter shapes. By slight modifications of Gabor filters several types of preference functions could be modeled, which are observed in different cricket species. Furthermore, this model was able to explain several so far enigmatic results in grasshoppers. The computational approach offered a remarkably simple framework that can account for phenotypically rather different preference functions across several taxa.

High school students' understanding and problem solving in population genetics

NASA Astrophysics Data System (ADS)

Soderberg, Patti D.

This study is an investigation of student understanding of population genetics and how students developed, used and revised conceptual models to solve problems. The students in this study participated in three rounds of problem solving. The first round involved the use of a population genetics model to predict the number of carriers in a population. The second round required them to revise their model of simple dominance population genetics to make inferences about populations containing three phenotype variations. The third round of problem solving required the students to revise their model of population genetics to explain anomalous data where the proportions of males and females with a trait varied significantly. As the students solved problems, they were involved in basic scientific processes as they observed population phenomena, constructed explanatory models to explain the data they observed, and attempted to persuade their peers as to the adequacy of their models. In this study, the students produced new knowledge about the genetics of a trait in a population through the revision and use of explanatory population genetics models using reasoning that was similar to what scientists do. The students learned, used and revised a model of Hardy-Weinberg equilibrium to generate and test hypotheses about the genetics of phenotypes given only population data. Students were also interviewed prior to and following instruction. This study suggests that a commonly held intuitive belief about the predominance of a dominant variation in populations is resistant to change, despite instruction and interferes with a student's ability to understand Hardy-Weinberg equilibrium and microevolution.

Restricted maximum likelihood estimation of genetic principal components and smoothed covariance matrices

PubMed Central

Meyer, Karin; Kirkpatrick, Mark

2005-01-01

Principal component analysis is a widely used 'dimension reduction' technique, albeit generally at a phenotypic level. It is shown that we can estimate genetic principal components directly through a simple reparameterisation of the usual linear, mixed model. This is applicable to any analysis fitting multiple, correlated genetic effects, whether effects for individual traits or sets of random regression coefficients to model trajectories. Depending on the magnitude of genetic correlation, a subset of the principal component generally suffices to capture the bulk of genetic variation. Corresponding estimates of genetic covariance matrices are more parsimonious, have reduced rank and are smoothed, with the number of parameters required to model the dispersion structure reduced from k(k + 1)/2 to m(2k - m + 1)/2 for k effects and m principal components. Estimation of these parameters, the largest eigenvalues and pertaining eigenvectors of the genetic covariance matrix, via restricted maximum likelihood using derivatives of the likelihood, is described. It is shown that reduced rank estimation can reduce computational requirements of multivariate analyses substantially. An application to the analysis of eight traits recorded via live ultrasound scanning of beef cattle is given. PMID:15588566

Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation.

PubMed

Stephan, Wolfgang

2016-01-01

In the past 15 years, numerous methods have been developed to detect selective sweeps underlying adaptations. These methods are based on relatively simple population genetic models, including one or two loci at which positive directional selection occurs, and one or two marker loci at which the impact of selection on linked neutral variation is quantified. Information about the phenotype under selection is not included in these models (except for fitness). In contrast, in the quantitative genetic models of adaptation, selection acts on one or more phenotypic traits, such that a genotype-phenotype map is required to bridge the gap to population genetics theory. Here I describe the range of population genetic models from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and I also consider the case of polygenic selection characterized by subtle allele frequency shifts at many loci. Furthermore, I present an overview of the statistical tests that have been proposed based on these population genetics models to detect evidence for positive selection in the genome. © 2015 John Wiley & Sons Ltd.

Motor impairment: a new ethanol withdrawal phenotype in mice

PubMed Central

Philibin, Scott D.; Cameron, Andy J.; Metten, Pamela; Crabbe, John C.

2015-01-01

Alcoholism is a complex disorder with genetic and environmental risk factors. The presence of withdrawal symptoms is one criterion for alcohol dependence. Genetic animal models have followed a reductionist approach by quantifying various effects of ethanol withdrawal separately. Different ethanol withdrawal symptoms may have distinct genetic etiologies, and therefore differentiating distinct neurobiological mechanisms related to separate signs of withdrawal would increase our understanding of various aspects of the complex phenotype. This study establishes motor incoordination as a new phenotype of alcohol withdrawal in mice. Mice were made physically dependent on ethanol by exposure to ethanol vapor for 72 h. The effects of ethanol withdrawal in mice from different genetic backgrounds were measured on the accelerating rotarod, a simple motor task. Ethanol withdrawal disrupted accelerating rotarod behavior in mice. The disruptive effects of withdrawal suggest a performance rather than a learning deficit. Inbred strain comparisons suggest genetic differences in magnitude of this withdrawal phenotype. The withdrawal-induced deficits were not correlated with the selection response difference in handling convulsion severity in selectively bred Withdrawal Seizure-Prone and Withdrawal Seizure-Resistant lines. The accelerating rotarod seems to be a simple behavioral measure of ethanol withdrawal that is suitable for comparing genotypes. PMID:18690115

Simulated breeding with QU-GENE graphical user interface.

PubMed

Hathorn, Adrian; Chapman, Scott; Dieters, Mark

2014-01-01

Comparing the efficiencies of breeding methods with field experiments is a costly, long-term process. QU-GENE is a highly flexible genetic and breeding simulation platform capable of simulating the performance of a range of different breeding strategies and for a continuum of genetic models ranging from simple to complex. In this chapter we describe some of the basic mechanics behind the QU-GENE user interface and give a simplified example of how it works.

Heuristic Identification of Biological Architectures for Simulating Complex Hierarchical Genetic Interactions

PubMed Central

Moore, Jason H; Amos, Ryan; Kiralis, Jeff; Andrews, Peter C

2015-01-01

Simulation plays an essential role in the development of new computational and statistical methods for the genetic analysis of complex traits. Most simulations start with a statistical model using methods such as linear or logistic regression that specify the relationship between genotype and phenotype. This is appealing due to its simplicity and because these statistical methods are commonly used in genetic analysis. It is our working hypothesis that simulations need to move beyond simple statistical models to more realistically represent the biological complexity of genetic architecture. The goal of the present study was to develop a prototype genotype–phenotype simulation method and software that are capable of simulating complex genetic effects within the context of a hierarchical biology-based framework. Specifically, our goal is to simulate multilocus epistasis or gene–gene interaction where the genetic variants are organized within the framework of one or more genes, their regulatory regions and other regulatory loci. We introduce here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating data in this manner. This approach combines a biological hierarchy, a flexible mathematical framework, a liability threshold model for defining disease endpoints, and a heuristic search strategy for identifying high-order epistatic models of disease susceptibility. We provide several simulation examples using genetic models exhibiting independent main effects and three-way epistatic effects. PMID:25395175

Brachypodium distachyon genetic resources

USDA-ARS?s Scientific Manuscript database

Brachypodium distachyon is a well-established model species for the grass family Poaceae. It possesses an array of features that make it suited for this purpose, including a small sequenced genome, simple transformation methods, and additional functional genomics tools. However, the most critical to...

An overview of C. elegans biology.

PubMed

Strange, Kevin

2006-01-01

The establishment of Caenorhabditis elegans as a "model organism" began with the efforts of Sydney Brenner in the early 1960s. Brenner's focus was to find a suitable animal model in which the tools of genetic analysis could be used to define molecular mechanisms of development and nervous system function. C. elegans provides numerous experimental advantages for such studies. These advantages include a short life cycle, production of large numbers of offspring, easy and inexpensive laboratory culture, forward and reverse genetic tractability, and a relatively simple anatomy. This chapter will provide a brief overview of C. elegans biology.

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:29547617

Evaluation of Genetic Algorithm Concepts Using Model Problems. Part 2; Multi-Objective Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2003-01-01

A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. Several new features including a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. The binning algorithm generally provides pareto front quality enhancements and moderate convergence efficiency improvements for most of the model problems. The gene-space transformation procedure provides a large convergence efficiency enhancement for problems with non-convoluted pareto fronts and a degradation in efficiency for problems with convoluted pareto fronts. The most difficult problems --multi-mode search spaces with a large number of genes and convoluted pareto fronts-- require a large number of function evaluations for GA convergence, but always converge.

The ecology and evolution of animal medication: genetically fixed response versus phenotypic plasticity.

PubMed

Choisy, Marc; de Roode, Jacobus C

2014-08-01

Animal medication against parasites can occur either as a genetically fixed (constitutive) or phenotypically plastic (induced) behavior. Taking the tritrophic interaction between the monarch butterfly Danaus plexippus, its protozoan parasite Ophryocystis elektroscirrha, and its food plant Asclepias spp. as a test case, we develop a game-theory model to identify the epidemiological (parasite prevalence and virulence) and environmental (plant toxicity and abundance) conditions that predict the evolution of genetically fixed versus phenotypically plastic forms of medication. Our model shows that the relative benefits (the antiparasitic properties of medicinal food) and costs (side effects of medicine, the costs of searching for medicine, and the costs of plasticity itself) crucially determine whether medication is genetically fixed or phenotypically plastic. Our model suggests that animals evolve phenotypic plasticity when parasite risk (a combination of virulence and prevalence and thus a measure of the strength of parasite-mediated selection) is relatively low to moderately high and genetically fixed medication when parasite risk becomes very high. The latter occurs because at high parasite risk, the costs of plasticity are outweighed by the benefits of medication. Our model provides a simple and general framework to study the conditions that drive the evolution of alternative forms of animal medication.

Diverse data supports the transition of filamentous fungal model organisms into the post-genomics era

DOE PAGES

McCluskey, Kevin; Baker, Scott E.

2017-02-17

As model organisms filamentous fungi have been important since the beginning of modern biological inquiry and have benefitted from open data since the earliest genetic maps were shared. From early origins in simple Mendelian genetics of mating types, parasexual genetics of colony colour, and the foundational demonstration of the segregation of a nutritional requirement, the contribution of research systems utilising filamentous fungi has spanned the biochemical genetics era, through the molecular genetics era, and now are at the very foundation of diverse omics approaches to research and development. Fungal model organisms have come from most major taxonomic groups although Ascomycetemore » filamentous fungi have seen the most major sustained effort. In addition to the published material about filamentous fungi, shared molecular tools have found application in every area of fungal biology. Likewise, shared data has contributed to the success of model systems. Furthermore, the scale of data supporting research with filamentous fungi has grown by 10 to 12 orders of magnitude. From genetic to molecular maps, expression databases, and finally genome resources, the open and collaborative nature of the research communities has assured that the rising tide of data has lifted all of the research systems together.« less

Diverse data supports the transition of filamentous fungal model organisms into the post-genomics era

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

McCluskey, Kevin; Baker, Scott E.

As model organisms filamentous fungi have been important since the beginning of modern biological inquiry and have benefitted from open data since the earliest genetic maps were shared. From early origins in simple Mendelian genetics of mating types, parasexual genetics of colony colour, and the foundational demonstration of the segregation of a nutritional requirement, the contribution of research systems utilising filamentous fungi has spanned the biochemical genetics era, through the molecular genetics era, and now are at the very foundation of diverse omics approaches to research and development. Fungal model organisms have come from most major taxonomic groups although Ascomycetemore » filamentous fungi have seen the most major sustained effort. In addition to the published material about filamentous fungi, shared molecular tools have found application in every area of fungal biology. Likewise, shared data has contributed to the success of model systems. Furthermore, the scale of data supporting research with filamentous fungi has grown by 10 to 12 orders of magnitude. From genetic to molecular maps, expression databases, and finally genome resources, the open and collaborative nature of the research communities has assured that the rising tide of data has lifted all of the research systems together.« less

Why a fly? Using Drosophila to understand the genetics of circadian rhythms and sleep.

PubMed

Hendricks, Joan C; Sehgal, Amita

2004-03-15

Among simple model systems, Drosophila has specific advantages for neurobehavioral investigations. It has been particularly useful for understanding the molecular basis of circadian rhythms. In addition, the genetics of fruit-fly sleep are beginning to develop. This review summarizes the current state of understanding of circadian rhythms and sleep in the fruit fly for the readers of Sleep. We note where information is available in mammals, for comparison with findings in fruit flies, to provide an evolutionary perspective, and we focus on recent findings and new questions. We propose that sleep-specific neural activity may alter cellular function and thus accomplish the restorative function or functions of sleep. In conclusion, we sound some cautionary notes about some of the complexities of working with this "simple" organism.

Theory and applications of a deterministic approximation to the coalescent model

PubMed Central

Jewett, Ethan M.; Rosenberg, Noah A.

2014-01-01

Under the coalescent model, the random number nt of lineages ancestral to a sample is nearly deterministic as a function of time when nt is moderate to large in value, and it is well approximated by its expectation E[nt]. In turn, this expectation is well approximated by simple deterministic functions that are easy to compute. Such deterministic functions have been applied to estimate allele age, effective population size, and genetic diversity, and they have been used to study properties of models of infectious disease dynamics. Although a number of simple approximations of E[nt] have been derived and applied to problems of population-genetic inference, the theoretical accuracy of the formulas and the inferences obtained using these approximations is not known, and the range of problems to which they can be applied is not well understood. Here, we demonstrate general procedures by which the approximation nt ≈ E[nt] can be used to reduce the computational complexity of coalescent formulas, and we show that the resulting approximations converge to their true values under simple assumptions. Such approximations provide alternatives to exact formulas that are computationally intractable or numerically unstable when the number of sampled lineages is moderate or large. We also extend an existing class of approximations of E[nt] to the case of multiple populations of time-varying size with migration among them. Our results facilitate the use of the deterministic approximation nt ≈ E[nt] for deriving functionally simple, computationally efficient, and numerically stable approximations of coalescent formulas under complicated demographic scenarios. PMID:24412419

A Genetic Algorithm Tool (splicer) for Complex Scheduling Problems and the Space Station Freedom Resupply Problem

NASA Technical Reports Server (NTRS)

Wang, Lui; Valenzuela-Rendon, Manuel

1993-01-01

The Space Station Freedom will require the supply of items in a regular fashion. A schedule for the delivery of these items is not easy to design due to the large span of time involved and the possibility of cancellations and changes in shuttle flights. This paper presents the basic concepts of a genetic algorithm model, and also presents the results of an effort to apply genetic algorithms to the design of propellant resupply schedules. As part of this effort, a simple simulator and an encoding by which a genetic algorithm can find near optimal schedules have been developed. Additionally, this paper proposes ways in which robust schedules, i.e., schedules that can tolerate small changes, can be found using genetic algorithms.

Scalability problems of simple genetic algorithms.

PubMed

Thierens, D

1999-01-01

Scalable evolutionary computation has become an intensively studied research topic in recent years. The issue of scalability is predominant in any field of algorithmic design, but it became particularly relevant for the design of competent genetic algorithms once the scalability problems of simple genetic algorithms were understood. Here we present some of the work that has aided in getting a clear insight in the scalability problems of simple genetic algorithms. Particularly, we discuss the important issue of building block mixing. We show how the need for mixing places a boundary in the GA parameter space that, together with the boundary from the schema theorem, delimits the region where the GA converges reliably to the optimum in problems of bounded difficulty. This region shrinks rapidly with increasing problem size unless the building blocks are tightly linked in the problem coding structure. In addition, we look at how straightforward extensions of the simple genetic algorithm-namely elitism, niching, and restricted mating are not significantly improving the scalability problems.

Performance of Geno-Fuzzy Model on rainfall-runoff predictions in claypan watersheds

USDA-ARS?s Scientific Manuscript database

Fuzzy logic provides a relatively simple approach to simulate complex hydrological systems while accounting for the uncertainty of environmental variables. The objective of this study was to develop a fuzzy inference system (FIS) with genetic algorithm (GA) optimization for membership functions (MF...

Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

PubMed Central

Zhang, Lun; Zhang, Meng; Yang, Wenchen; Dong, Decun

2015-01-01

This paper presents the modelling and analysis of the capacity expansion of urban road traffic network (ICURTN). Thebilevel programming model is first employed to model the ICURTN, in which the utility of the entire network is maximized with the optimal utility of travelers' route choice. Then, an improved hybrid genetic algorithm integrated with golden ratio (HGAGR) is developed to enhance the local search of simple genetic algorithms, and the proposed capacity expansion model is solved by the combination of the HGAGR and the Frank-Wolfe algorithm. Taking the traditional one-way network and bidirectional network as the study case, three numerical calculations are conducted to validate the presented model and algorithm, and the primary influencing factors on extended capacity model are analyzed. The calculation results indicate that capacity expansion of road network is an effective measure to enlarge the capacity of urban road network, especially on the condition of limited construction budget; the average computation time of the HGAGR is 122 seconds, which meets the real-time demand in the evaluation of the road network capacity. PMID:25802512

Implications of sex-specific selection for the genetic basis of disease.

PubMed

Morrow, Edward H; Connallon, Tim

2013-12-01

Mutation and selection are thought to shape the underlying genetic basis of many common human diseases. However, both processes depend on the context in which they occur, such as environment, genetic background, or sex. Sex has widely known effects on phenotypic expression of genotype, but an analysis of how it influences the evolutionary dynamics of disease-causing variants has not yet been explored. We develop a simple population genetic model of disease susceptibility and evaluate it using a biologically plausible empirically based distribution of fitness effects among contributing mutations. The model predicts that alleles under sex-differential selection, including sexually antagonistic alleles, will disproportionately contribute to genetic variation for disease predisposition, thereby generating substantial sexual dimorphism in the genetic architecture of complex (polygenic) diseases. This is because such alleles evolve into higher population frequencies for a given effect size, relative to alleles experiencing equally strong purifying selection in both sexes. Our results provide a theoretical justification for expecting a sexually dimorphic genetic basis for variation in complex traits such as disease. Moreover, they suggest that such dimorphism is interesting - not merely something to control for - because it reflects the action of natural selection in molding the evolution of common disease phenotypes.

A comparison of the genetic basis of wing size divergence in three parallel body size clines of Drosophila melanogaster.

PubMed Central

Gilchrist, A S; Partridge, L

1999-01-01

Body size clines in Drosophila melanogaster have been documented in both Australia and South America, and may exist in Southern Africa. We crossed flies from the northern and southern ends of each of these clines to produce F(1), F(2), and first backcross generations. Our analysis of generation means for wing area and wing length produced estimates of the additive, dominance, epistatic, and maternal effects underlying divergence within each cline. For both females and males of all three clines, the generation means were adequately described by these parameters, indicating that linkage and higher order interactions did not contribute significantly to wing size divergence. Marked differences were apparent between the clines in the occurrence and magnitude of the significant genetic parameters. No cline was adequately described by a simple additive-dominance model, and significant epistatic and maternal effects occurred in most, but not all, of the clines. Generation variances were also analyzed. Only one cline was described sufficiently by a simple additive variance model, indicating significant epistatic, maternal, or linkage effects in the remaining two clines. The diversity in genetic architecture of the clines suggests that natural selection has produced similar phenotypic divergence by different combinations of gene action and interaction. PMID:10581284

The Zebrafish Brain in Research and Teaching: A Simple in Vivo and in Vitro Model for the Study of Spontaneous Neural Activity

ERIC Educational Resources Information Center

Vargas, R.; Johannesdottir, I. P.; Sigurgeirsson, B.; Porsteinsson, H.; Karlsson, K. AE.

2011-01-01

Recently, the zebrafish ("Danio rerio") has been established as a key animal model in neuroscience. Behavioral, genetic, and immunohistochemical techniques have been used to describe the connectivity of diverse neural circuits. However, few studies have used zebrafish to understand the function of cerebral structures or to study neural circuits.…

Towards a Model for Protein Production Rates

NASA Astrophysics Data System (ADS)

Dong, J. J.; Schmittmann, B.; Zia, R. K. P.

2007-07-01

In the process of translation, ribosomes read the genetic code on an mRNA and assemble the corresponding polypeptide chain. The ribosomes perform discrete directed motion which is well modeled by a totally asymmetric simple exclusion process (TASEP) with open boundaries. Using Monte Carlo simulations and a simple mean-field theory, we discuss the effect of one or two "bottlenecks" (i.e., slow codons) on the production rate of the final protein. Confirming and extending previous work by Chou and Lakatos, we find that the location and spacing of the slow codons can affect the production rate quite dramatically. In particular, we observe a novel "edge" effect, i.e., an interaction of a single slow codon with the system boundary. We focus in detail on ribosome density profiles and provide a simple explanation for the length scale which controls the range of these interactions.

Effect of genetic algorithm as a variable selection method on different chemometric models applied for the analysis of binary mixture of amoxicillin and flucloxacillin: A comparative study

NASA Astrophysics Data System (ADS)

Attia, Khalid A. M.; Nassar, Mohammed W. I.; El-Zeiny, Mohamed B.; Serag, Ahmed

2016-03-01

Different chemometric models were applied for the quantitative analysis of amoxicillin (AMX), and flucloxacillin (FLX) in their binary mixtures, namely, partial least squares (PLS), spectral residual augmented classical least squares (SRACLS), concentration residual augmented classical least squares (CRACLS) and artificial neural networks (ANNs). All methods were applied with and without variable selection procedure (genetic algorithm GA). The methods were used for the quantitative analysis of the drugs in laboratory prepared mixtures and real market sample via handling the UV spectral data. Robust and simpler models were obtained by applying GA. The proposed methods were found to be rapid, simple and required no preliminary separation steps.

Highly Informative Simple Sequence Repeat (SSR) Markers for Fingerprinting Hazelnut

USDA-ARS?s Scientific Manuscript database

Simple sequence repeat (SSR) or microsatellite markers have many applications in breeding and genetic studies of plants, including fingerprinting of cultivars and investigations of genetic diversity, and therefore provide information for better management of germplasm collections. They are repeatab...

The null distribution of the heterogeneity lod score does depend on the assumed genetic model for the trait.

PubMed

Huang, J; Vieland, V J

2001-01-01

It is well known that the asymptotic null distribution of the homogeneity lod score (LOD) does not depend on the genetic model specified in the analysis. When appropriately rescaled, the LOD is asymptotically distributed as 0.5 chi(2)(0) + 0.5 chi(2)(1), regardless of the assumed trait model. However, because locus heterogeneity is a common phenomenon, the heterogeneity lod score (HLOD), rather than the LOD itself, is often used in gene mapping studies. We show here that, in contrast with the LOD, the asymptotic null distribution of the HLOD does depend upon the genetic model assumed in the analysis. In affected sib pair (ASP) data, this distribution can be worked out explicitly as (0.5 - c)chi(2)(0) + 0.5chi(2)(1) + cchi(2)(2), where c depends on the assumed trait model. E.g., for a simple dominant model (HLOD/D), c is a function of the disease allele frequency p: for p = 0.01, c = 0.0006; while for p = 0.1, c = 0.059. For a simple recessive model (HLOD/R), c = 0.098 independently of p. This latter (recessive) distribution turns out to be the same as the asymptotic distribution of the MLS statistic under the possible triangle constraint, which is asymptotically equivalent to the HLOD/R. The null distribution of the HLOD/D is close to that of the LOD, because the weight c on the chi(2)(2) component is small. These results mean that the cutoff value for a test of size alpha will tend to be smaller for the HLOD/D than the HLOD/R. For example, the alpha = 0.0001 cutoff (on the lod scale) for the HLOD/D with p = 0.05 is 3.01, while for the LOD it is 3.00, and for the HLOD/R it is 3.27. For general pedigrees, explicit analytical expression of the null HLOD distribution does not appear possible, but it will still depend on the assumed genetic model. Copyright 2001 S. Karger AG, Basel

Estimating directional epistasis

PubMed Central

Le Rouzic, Arnaud

2014-01-01

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

Simple Model of Mating Preference and Extinction Risk

NASA Astrophysics Data System (ADS)

PȨKALSKI, Andrzej

We present a simple model of a population of individuals characterized by their genetic structure in the form of a double string of bits and the phenotype following from it. The population is living in an unchanging habitat preferring a certain type of phenotype (optimum). Individuals are unisex, however a pair is necessary for breeding. An individual rejects a mate if the latter's phenotype contains too many bad, i.e. different from the optimum, genes in the same places as the individual's. We show that such strategy, analogous to disassortative mating based on the major histocompatibility complex, avoiding inbreeding and incest, could be beneficial for the population and could reduce considerably the extinction risk, especially in small populations.

Genetic Algorithm Approaches for Actuator Placement

NASA Technical Reports Server (NTRS)

Crossley, William A.

2000-01-01

This research investigated genetic algorithm approaches for smart actuator placement to provide aircraft maneuverability without requiring hinged flaps or other control surfaces. The effort supported goals of the Multidisciplinary Design Optimization focus efforts in NASA's Aircraft au program. This work helped to properly identify various aspects of the genetic algorithm operators and parameters that allow for placement of discrete control actuators/effectors. An improved problem definition, including better definition of the objective function and constraints, resulted from this research effort. The work conducted for this research used a geometrically simple wing model; however, an increasing number of potential actuator placement locations were incorporated to illustrate the ability of the GA to determine promising actuator placement arrangements. This effort's major result is a useful genetic algorithm-based approach to assist in the discrete actuator/effector placement problem.

Quantitative genetic properties of four measures of deformity in yellowtail kingfish Seriola lalandi Valenciennes, 1833.

PubMed

Nguyen, N H; Whatmore, P; Miller, A; Knibb, W

2016-02-01

The main aim of this study was to estimate the heritability for four measures of deformity and their genetic associations with growth (body weight and length), carcass (fillet weight and yield) and flesh-quality (fillet fat content) traits in yellowtail kingfish Seriola lalandi. The observed major deformities included lower jaw, nasal erosion, deformed operculum and skinny fish on 480 individuals from 22 families at Clean Seas Tuna Ltd. They were typically recorded as binary traits (presence or absence) and were analysed separately by both threshold generalized models and standard animal mixed models. Consistency of the models was evaluated by calculating simple Pearson correlation of breeding values of full-sib families for jaw deformity. Genetic and phenotypic correlations among traits were estimated using a multitrait linear mixed model in ASReml. Both threshold and linear mixed model analysis showed that there is additive genetic variation in the four measures of deformity, with the estimates of heritability obtained from the former (threshold) models on liability scale ranging from 0.14 to 0.66 (SE 0.32-0.56) and from the latter (linear animal and sire) models on original (observed) scale, 0.01-0.23 (SE 0.03-0.16). When the estimates on the underlying liability were transformed to the observed scale (0, 1), they were generally consistent between threshold and linear mixed models. Phenotypic correlations among deformity traits were weak (close to zero). The genetic correlations among deformity traits were not significantly different from zero. Body weight and fillet carcass showed significant positive genetic correlations with jaw deformity (0.75 and 0.95, respectively). Genetic correlation between body weight and operculum was negative (-0.51, P < 0.05). The genetic correlations' estimates of body and carcass traits with other deformity were not significant due to their relatively high standard errors. Our results showed that there are prospects for genetic selection to improve deformity in yellowtail kingfish and that measures of deformity should be included in the recording scheme, breeding objectives and selection index in practical selective breeding programmes due to the antagonistic genetic correlations of deformed jaws with body and carcass performance. © 2015 John Wiley & Sons Ltd.

Multi-scale genetic dynamic modelling II: application to synthetic biology: an algorithmic Markov chain based approach.

PubMed

Kirkilionis, Markus; Janus, Ulrich; Sbano, Luca

2011-09-01

We model in detail a simple synthetic genetic clock that was engineered in Atkinson et al. (Cell 113(5):597-607, 2003) using Escherichia coli as a host organism. Based on this engineered clock its theoretical description uses the modelling framework presented in Kirkilionis et al. (Theory Biosci. doi: 10.1007/s12064-011-0125-0 , 2011, this volume). The main goal of this accompanying article was to illustrate that parts of the modelling process can be algorithmically automatised once the model framework we called 'average dynamics' is accepted (Sbano and Kirkilionis, WMI Preprint 7/2007, 2008c; Kirkilionis and Sbano, Adv Complex Syst 13(3):293-326, 2010). The advantage of the 'average dynamics' framework is that system components (especially in genetics) can be easier represented in the model. In particular, if once discovered and characterised, specific molecular players together with their function can be incorporated. This means that, for example, the 'gene' concept becomes more clear, for example, in the way the genetic component would react under different regulatory conditions. Using the framework it has become a realistic aim to link mathematical modelling to novel tools of bioinformatics in the future, at least if the number of regulatory units can be estimated. This should hold in any case in synthetic environments due to the fact that the different synthetic genetic components are simply known (Elowitz and Leibler, Nature 403(6767):335-338, 2000; Gardner et al., Nature 403(6767):339-342, 2000; Hasty et al., Nature 420(6912):224-230, 2002). The paper illustrates therefore as a necessary first step how a detailed modelling of molecular interactions with known molecular components leads to a dynamic mathematical model that can be compared to experimental results on various levels or scales. The different genetic modules or components are represented in different detail by model variants. We explain how the framework can be used for investigating other more complex genetic systems in terms of regulation and feedback.

Genetic algorithm optimized rainfall-runoff fuzzy inference system for row crop watersheds with claypan soils

USDA-ARS?s Scientific Manuscript database

The fuzzy logic algorithm has the ability to describe knowledge in a descriptive human-like manner in the form of simple rules using linguistic variables, and provides a new way of modeling uncertain or naturally fuzzy hydrological processes like non-linear rainfall-runoff relationships. Fuzzy infe...

A simple approach to lifetime learning in genetic programming-based symbolic regression.

PubMed

Azad, Raja Muhammad Atif; Ryan, Conor

2014-01-01

Genetic programming (GP) coarsely models natural evolution to evolve computer programs. Unlike in nature, where individuals can often improve their fitness through lifetime experience, the fitness of GP individuals generally does not change during their lifetime, and there is usually no opportunity to pass on acquired knowledge. This paper introduces the Chameleon system to address this discrepancy and augment GP with lifetime learning by adding a simple local search that operates by tuning the internal nodes of individuals. Although not the first attempt to combine local search with GP, its simplicity means that it is easy to understand and cheap to implement. A simple cache is added which leverages the local search to reduce the tuning cost to a small fraction of the expected cost, and we provide a theoretical upper limit on the maximum tuning expense given the average tree size of the population and show that this limit grows very conservatively as the average tree size of the population increases. We show that Chameleon uses available genetic material more efficiently by exploring more actively than with standard GP, and demonstrate that not only does Chameleon outperform standard GP (on both training and test data) over a number of symbolic regression type problems, it does so by producing smaller individuals and it works harmoniously with two other well-known extensions to GP, namely, linear scaling and a diversity-promoting tournament selection method.

A Simple Negative Interaction in the Positive Transcriptional Feedback of a Single Gene Is Sufficient to Produce Reliable Oscillations

PubMed Central

Miró-Bueno, Jesús M.; Rodríguez-Patón, Alfonso

2011-01-01

Negative and positive transcriptional feedback loops are present in natural and synthetic genetic oscillators. A single gene with negative transcriptional feedback needs a time delay and sufficiently strong nonlinearity in the transmission of the feedback signal in order to produce biochemical rhythms. A single gene with only positive transcriptional feedback does not produce oscillations. Here, we demonstrate that this single-gene network in conjunction with a simple negative interaction can also easily produce rhythms. We examine a model comprised of two well-differentiated parts. The first is a positive feedback created by a protein that binds to the promoter of its own gene and activates the transcription. The second is a negative interaction in which a repressor molecule prevents this protein from binding to its promoter. A stochastic study shows that the system is robust to noise. A deterministic study identifies that the dynamics of the oscillator are mainly driven by two types of biomolecules: the protein, and the complex formed by the repressor and this protein. The main conclusion of this paper is that a simple and usual negative interaction, such as degradation, sequestration or inhibition, acting on the positive transcriptional feedback of a single gene is a sufficient condition to produce reliable oscillations. One gene is enough and the positive transcriptional feedback signal does not need to activate a second repressor gene. This means that at the genetic level an explicit negative feedback loop is not necessary. The model needs neither cooperative binding reactions nor the formation of protein multimers. Therefore, our findings could help to clarify the design principles of cellular clocks and constitute a new efficient tool for engineering synthetic genetic oscillators. PMID:22205920

Counting statistics for genetic switches based on effective interaction approximation

NASA Astrophysics Data System (ADS)

Ohkubo, Jun

2012-09-01

Applicability of counting statistics for a system with an infinite number of states is investigated. The counting statistics has been studied a lot for a system with a finite number of states. While it is possible to use the scheme in order to count specific transitions in a system with an infinite number of states in principle, we have non-closed equations in general. A simple genetic switch can be described by a master equation with an infinite number of states, and we use the counting statistics in order to count the number of transitions from inactive to active states in the gene. To avoid having the non-closed equations, an effective interaction approximation is employed. As a result, it is shown that the switching problem can be treated as a simple two-state model approximately, which immediately indicates that the switching obeys non-Poisson statistics.

Correlation not Causation: The Relationship between Personality Traits and Political Ideologies

PubMed Central

Verhulst, Brad; Eaves, Lindon J.; Hatemi, Peter K.

2013-01-01

The assumption in the personality and politics literature is that a person's personality motivates them to develop certain political attitudes later in life. This assumption is founded on the simple correlation between the two constructs and the observation that personality traits are genetically influenced and develop in infancy, whereas political preferences develop later in life. Work in psychology, behavioral genetics, and recently political science, however, has demonstrated that political preferences also develop in childhood and are equally influenced by genetic factors. These findings cast doubt on the assumed causal relationship between personality and politics. Here we test the causal relationship between personality traits and political attitudes using a direction of causation structural model on a genetically informative sample. The results suggest that personality traits do not cause people to develop political attitudes; rather, the correlation between the two is a function of an innate common underlying genetic factor. PMID:22400142

Correlation not causation: the relationship between personality traits and political ideologies.

PubMed

Verhulst, Brad; Eaves, Lindon J; Hatemi, Peter K

2012-01-01

The assumption in the personality and politics literature is that a person's personality motivates them to develop certain political attitudes later in life. This assumption is founded on the simple correlation between the two constructs and the observation that personality traits are genetically influenced and develop in infancy, whereas political preferences develop later in life. Work in psychology, behavioral genetics, and recently political science, however, has demonstrated that political preferences also develop in childhood and are equally influenced by genetic factors. These findings cast doubt on the assumed causal relationship between personality and politics. Here we test the causal relationship between personality traits and political attitudes using a direction of causation structural model on a genetically informative sample. The results suggest that personality traits do not cause people to develop political attitudes; rather, the correlation between the two is a function of an innate common underlying genetic factor.

A fully humanized transgenic mouse model of Huntington disease

PubMed Central

Southwell, Amber L.; Warby, Simon C.; Carroll, Jeffrey B.; Doty, Crystal N.; Skotte, Niels H.; Zhang, Weining; Villanueva, Erika B.; Kovalik, Vlad; Xie, Yuanyun; Pouladi, Mahmoud A.; Collins, Jennifer A.; Yang, X. William; Franciosi, Sonia; Hayden, Michael R.

2013-01-01

Silencing the mutant huntingtin gene (muHTT) is a direct and simple therapeutic strategy for the treatment of Huntington disease (HD) in principle. However, targeting the HD mutation presents challenges because it is an expansion of a common genetic element (a CAG tract) that is found throughout the genome. Moreover, the HTT protein is important for neuronal health throughout life, and silencing strategies that also reduce the wild-type HTT allele may not be well tolerated during the long-term treatment of HD. Several HTT silencing strategies are in development that target genetic sites in HTT that are outside of the CAG expansion, including HD mutation-linked single-nucleotide polymorphisms and the HTT promoter. Preclinical testing of these genetic therapies has required the development of a new mouse model of HD that carries these human-specific genetic targets. To generate a fully humanized mouse model of HD, we have cross-bred BACHD and YAC18 on the Hdh−/− background. The resulting line, Hu97/18, is the first murine model of HD that fully genetically recapitulates human HD having two human HTT genes, no mouse Hdh genes and heterozygosity of the HD mutation. We find that Hu97/18 mice display many of the behavioral changes associated with HD including motor, psychiatric and cognitive deficits, as well as canonical neuropathological abnormalities. This mouse line will be useful for gaining additional insights into the disease mechanisms of HD as well as for testing genetic therapies targeting human HTT. PMID:23001568

Molecular genetics made simple

PubMed Central

Kassem, Heba Sh.; Girolami, Francesca; Sanoudou, Despina

2012-01-01

Abstract Genetics have undoubtedly become an integral part of biomedical science and clinical practice, with important implications in deciphering disease pathogenesis and progression, identifying diagnostic and prognostic markers, as well as designing better targeted treatments. The exponential growth of our understanding of different genetic concepts is paralleled by a growing list of genetic terminology that can easily intimidate the unfamiliar reader. Rendering genetics incomprehensible to the clinician however, defeats the very essence of genetic research: its utilization for combating disease and improving quality of life. Herein we attempt to correct this notion by presenting the basic genetic concepts along with their usefulness in the cardiology clinic. Bringing genetics closer to the clinician will enable its harmonious incorporation into clinical care, thus not only restoring our perception of its simple and elegant nature, but importantly ensuring the maximal benefit for our patients. PMID:25610837

DNA as Genetic Material: Revisiting Classic Experiments through a Simple, Practical Class

ERIC Educational Resources Information Center

Malago, Wilson, Jr.; Soares-Costa, Andrea; Henrique-Silva, Flavio

2009-01-01

In 1928, Frederick Griffith demonstrated a transmission process of genetic information by transforming "Pneumococcus". In 1944, Avery et al. demonstrated that Griffith's transforming principle was DNA. We revisited these classic experiments in a practical class for undergraduate students. Both experiments were reproduced in simple, adapted forms.…

Always look on both sides: Phylogenetic information conveyed by simple sequence repeat allele sequences

USDA-ARS?s Scientific Manuscript database

Simple sequence repeat (SSR) markers are widely used tools for inferences about genetic diversity, phylogeography and spatial genetic structure. Their applications assume that variation among alleles is essentially caused by an expansion or contraction of the number of repeats and that, accessorily,...

MIP models and hybrid algorithms for simultaneous job splitting and scheduling on unrelated parallel machines.

PubMed

Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk

2014-01-01

We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.

Genetic profiling of two phenotypically distinct outbred rats derived from a colony of the Zucker fatty rats maintained at Tokyo Medical University

PubMed Central

Nakanishi, Satoshi; Kuramoto, Takashi; Kashiwazaki, Naomi; Yokoi, Norihide

2016-01-01

The Zucker fatty (ZF) rat is an outbred rat and a well-known model of obesity without diabetes, harboring a missense mutation (fatty, abbreviated as fa) in the leptin receptor gene (Lepr). Slc:Zucker (Slc:ZF) outbred rats exhibit obesity while Hos:ZFDM-Leprfa (Hos:ZFDM) outbred rats exhibit obesity and type 2 diabetes. Both outbred rats have been derived from an outbred ZF rat colony maintained at Tokyo Medical University. So far, genetic profiles of these outbred rats remain unknown. Here, we applied a simple genotyping method using Ampdirect reagents and FTA cards (Amp-FTA) in combination with simple sequence length polymorphisms (SSLP) markers to determine genetic profiles of Slc:ZF and Hos:ZFDM rats. Among 27 SSLP marker loci, 24 loci (89%) were fixed for specific allele at each locus in Slc:ZF rats and 26 loci (96%) were fixed in Hos:ZFDM rats, respectively. This indicates the low genetic heterogeneity in both colonies of outbred rats. Nine loci (33%) showed different alleles between the two outbred rats, suggesting considerably different genetic profiles between the two outbred rats in spite of the same origin. Additional analysis using 72 SSLP markers further supported these results and clarified the profiles in detail. This study revealed that genetic profiles of the Slc:ZF and Hos:ZFDM outbred rats are different for about 30% of the SSLP marker loci, which is the underlying basis for the phenotypic difference between the two outbred rats. PMID:27795491

Risk assessment model for development of advanced age-related macular degeneration.

PubMed

Klein, Michael L; Francis, Peter J; Ferris, Frederick L; Hamon, Sara C; Clemons, Traci E

2011-12-01

To design a risk assessment model for development of advanced age-related macular degeneration (AMD) incorporating phenotypic, demographic, environmental, and genetic risk factors. We evaluated longitudinal data from 2846 participants in the Age-Related Eye Disease Study. At baseline, these individuals had all levels of AMD, ranging from none to unilateral advanced AMD (neovascular or geographic atrophy). Follow-up averaged 9.3 years. We performed a Cox proportional hazards analysis with demographic, environmental, phenotypic, and genetic covariates and constructed a risk assessment model for development of advanced AMD. Performance of the model was evaluated using the C statistic and the Brier score and externally validated in participants in the Complications of Age-Related Macular Degeneration Prevention Trial. The final model included the following independent variables: age, smoking history, family history of AMD (first-degree member), phenotype based on a modified Age-Related Eye Disease Study simple scale score, and genetic variants CFH Y402H and ARMS2 A69S. The model did well on performance measures, with very good discrimination (C statistic = 0.872) and excellent calibration and overall performance (Brier score at 5 years = 0.08). Successful external validation was performed, and a risk assessment tool was designed for use with or without the genetic component. We constructed a risk assessment model for development of advanced AMD. The model performed well on measures of discrimination, calibration, and overall performance and was successfully externally validated. This risk assessment tool is available for online use.

Wetlands explain most in the genetic divergence pattern of Oncomelania hupensis.

PubMed

Liang, Lu; Liu, Yang; Liao, Jishan; Gong, Peng

2014-10-01

Understanding the divergence patterns of hosts could shed lights on the prediction of their parasite transmission. No effort has been devoted to understand the drivers of genetic divergence pattern of Oncomelania hupensis, the only intermediate host of Schistosoma japonicum. Based on a compilation of two O. hupensis gene datasets covering a wide geographic range in China and an array of geographical distance and environmental dissimilarity metrics built from earth observation data and ecological niche modeling, we conducted causal modeling analysis via simple, partial Mantel test and local polynomial fitting to understand the interactions among isolation-by-distance, isolation-by-environment, and genetic divergence. We found that geography contributes more to genetic divergence than environmental isolation, and among all variables involved, wetland showed the strongest correlation with the genetic pairwise distances. These results suggested that in China, O. hupensis dispersal is strongly linked to the distribution of wetlands, and the current divergence pattern of both O. hupensis and schistosomiasis might be altered due to the changed wetland pattern with the accomplishment of the Three Gorges Dam and the South-to-North water transfer project. Copyright © 2014 Elsevier B.V. All rights reserved.

Coalescence and genetic diversity in sexual populations under selection.

PubMed

Neher, Richard A; Kessinger, Taylor A; Shraiman, Boris I

2013-09-24

In sexual populations, selection operates neither on the whole genome, which is repeatedly taken apart and reassembled by recombination, nor on individual alleles that are tightly linked to the chromosomal neighborhood. The resulting interference between linked alleles reduces the efficiency of selection and distorts patterns of genetic diversity. Inference of evolutionary history from diversity shaped by linked selection requires an understanding of these patterns. Here, we present a simple but powerful scaling analysis identifying the unit of selection as the genomic "linkage block" with a characteristic length, , determined in a self-consistent manner by the condition that the rate of recombination within the block is comparable to the fitness differences between different alleles of the block. We find that an asexual model with the strength of selection tuned to that of the linkage block provides an excellent description of genetic diversity and the site frequency spectra compared with computer simulations. This linkage block approximation is accurate for the entire spectrum of strength of selection and is particularly powerful in scenarios with many weakly selected loci. The latter limit allows us to characterize coalescence, genetic diversity, and the speed of adaptation in the infinitesimal model of quantitative genetics.

Drosophila Melanogaster as an Emerging Translational Model of Human Nephrolithiasis

PubMed Central

Miller, Joe; Chi, Thomas; Kapahi, Pankaj; Kahn, Arnold J.; Kim, Man Su; Hirata, Taku; Romero, Michael F.; Dow, Julian A.T.; Stoller, Marshall L.

2013-01-01

Purpose The limitations imposed by human clinical studies and mammalian models of nephrolithiasis have hampered the development of effective medical treatments and preventative measures for decades. The simple but elegant Drosophila melanogaster is emerging as a powerful translational model of human disease, including nephrolithiasis and may provide important information essential to our understanding of stone formation. We present the current state of research using D. melanogaster as a model of human nephrolithiasis. Materials and Methods A comprehensive review of the English language literature was performed using PUBMED. When necessary, authoritative texts on relevant subtopics were consulted. Results The genetic composition, anatomic structure and physiologic function of Drosophila Malpighian tubules are remarkably similar to those of the human nephron. The direct effects of dietary manipulation, environmental alteration, and genetic variation on stone formation can be observed and quantified in a matter of days. Several Drosophila models of human nephrolithiasis, including genetically linked and environmentally induced stones, have been developed. A model of calcium oxalate stone formation is among the most recent fly models of human nephrolithiasis. Conclusions The ability to readily manipulate and quantify stone formation in D. melanogaster models of human nephrolithiasis presents the urologic community with a unique opportunity to increase our understanding of this enigmatic disease. PMID:23500641

Model-based conservation planning of the genetic diversity of Phellodendron amurense Rupr due to climate change

PubMed Central

Wan, Jizhong; Wang, Chunjing; Yu, Jinghua; Nie, Siming; Han, Shijie; Zu, Yuangang; Chen, Changmei; Yuan, Shusheng; Wang, Qinggui

2014-01-01

Climate change affects both habitat suitability and the genetic diversity of wild plants. Therefore, predicting and establishing the most effective and coherent conservation areas is essential for the conservation of genetic diversity in response to climate change. This is because genetic variance is a product not only of habitat suitability in conservation areas but also of efficient protection and management. Phellodendron amurense Rupr. is a tree species (family Rutaceae) that is endangered due to excessive and illegal harvesting for use in Chinese medicine. Here, we test a general computational method for the prediction of priority conservation areas (PCAs) by measuring the genetic diversity of P. amurense across the entirety of northeast China using a single strand repeat analysis of twenty microsatellite markers. Using computational modeling, we evaluated the geographical distribution of the species, both now and in different future climate change scenarios. Different populations were analyzed according to genetic diversity, and PCAs were identified using a spatial conservation prioritization framework. These conservation areas were optimized to account for the geographical distribution of P. amurense both now and in the future, to effectively promote gene flow, and to have a long period of validity. In situ and ex situ conservation, strategies for vulnerable populations were proposed. Three populations with low genetic diversity are predicted to be negatively affected by climate change, making conservation of genetic diversity challenging due to decreasing habitat suitability. Habitat suitability was important for the assessment of genetic variability in existing nature reserves, which were found to be much smaller than the proposed PCAs. Finally, a simple set of conservation measures was established through modeling. This combined molecular and computational ecology approach provides a framework for planning the protection of species endangered by climate change. PMID:25165526

Prediction of body lipid change in pregnancy and lactation.

PubMed

Friggens, N C; Ingvartsen, K L; Emmans, G C

2004-04-01

A simple method to predict the genetically driven pattern of body lipid change through pregnancy and lactation in dairy cattle is proposed. The rationale and evidence for genetically driven body lipid change have their basis in evolutionary considerations and in the homeorhetic changes in lipid metabolism through the reproductive cycle. The inputs required to predict body lipid change are body lipid mass at calving (kg) and the date of conception (days in milk). Body lipid mass can be derived from body condition score and live weight. A key assumption is that there is a linear rate of change of the rate of body lipid change (dL/dt) between calving and a genetically determined time in lactation (T') at which a particular level of body lipid (L') is sought. A second assumption is that there is a linear rate of change of the rate of body lipid change (dL/dt) between T' and the next calving. The resulting model was evaluated using 2 sets of data. The first was from Holstein cows with 3 different levels of body fatness at calving. The second was from Jersey cows in first, second, and third parity. The model was found to reproduce the observed patterns of change in body lipid reserves through lactation in both data sets. The average error of prediction was low, less than the variation normally associated with the recording of condition score, and was similar for the 2 data sets. When the model was applied using the initially suggested parameter values derived from the literature the average error of prediction was 0.185 units of condition score (+/- 0.086 SD). After minor adjustments to the parameter values, the average error of prediction was 0.118 units of condition score (+/- 0.070 SD). The assumptions on which the model is based were sufficient to predict the changes in body lipid of both Holstein and Jersey cows under different nutritional conditions and parities. Thus, the model presented here shows that it is possible to predict genetically driven curves of body lipid change through lactation in a simple way that requires few parameters and inputs that can be derived in practice. It is expected that prediction of the cow's energy requirements can be substantially improved, particularly in early lactation, by incorporating a genetically driven body energy mobilization.

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

PubMed

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

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

Genetic diversity of Pinus nigra Arn. populations in Southern Spain and Northern Morocco revealed by inter-simple sequence repeat profiles.

PubMed

Rubio-Moraga, Angela; Candel-Perez, David; Lucas-Borja, Manuel E; Tiscar, Pedro A; Viñegla, Benjamin; Linares, Juan C; Gómez-Gómez, Lourdes; Ahrazem, Oussama

2012-01-01

Eight Pinus nigra Arn. populations from Southern Spain and Northern Morocco were examined using inter-simple sequence repeat markers to characterize the genetic variability amongst populations. Pair-wise population genetic distance ranged from 0.031 to 0.283, with a mean of 0.150 between populations. The highest inter-population average distance was between PaCU from Cuenca and YeCA from Cazorla, while the lowest distance was between TaMO from Morocco and MA Sierra Mágina populations. Analysis of molecular variance (AMOVA) and Nei's genetic diversity analyses revealed higher genetic variation within the same population than among different populations. Genetic differentiation (Gst) was 0.233. Cuenca showed the highest Nei's genetic diversity followed by the Moroccan region, Sierra Mágina, and Cazorla region. However, clustering of populations was not in accordance with their geographical locations. Principal component analysis showed the presence of two major groups-Group 1 contained all populations from Cuenca while Group 2 contained populations from Cazorla, Sierra Mágina and Morocco-while Bayesian analysis revealed the presence of three clusters. The low genetic diversity observed in PaCU and YeCA is probably a consequence of inappropriate management since no estimation of genetic variability was performed before the silvicultural treatments. Data indicates that the inter-simple sequence repeat (ISSR) method is sufficiently informative and powerful to assess genetic variability among populations of P. nigra.

Genetic Diversity of Pinus nigra Arn. Populations in Southern Spain and Northern Morocco Revealed By Inter-Simple Sequence Repeat Profiles †

PubMed Central

Rubio-Moraga, Angela; Candel-Perez, David; Lucas-Borja, Manuel E.; Tiscar, Pedro A.; Viñegla, Benjamin; Linares, Juan C.; Gómez-Gómez, Lourdes; Ahrazem, Oussama

2012-01-01

Eight Pinus nigra Arn. populations from Southern Spain and Northern Morocco were examined using inter-simple sequence repeat markers to characterize the genetic variability amongst populations. Pair-wise population genetic distance ranged from 0.031 to 0.283, with a mean of 0.150 between populations. The highest inter-population average distance was between PaCU from Cuenca and YeCA from Cazorla, while the lowest distance was between TaMO from Morocco and MA Sierra Mágina populations. Analysis of molecular variance (AMOVA) and Nei’s genetic diversity analyses revealed higher genetic variation within the same population than among different populations. Genetic differentiation (Gst) was 0.233. Cuenca showed the highest Nei’s genetic diversity followed by the Moroccan region, Sierra Mágina, and Cazorla region. However, clustering of populations was not in accordance with their geographical locations. Principal component analysis showed the presence of two major groups—Group 1 contained all populations from Cuenca while Group 2 contained populations from Cazorla, Sierra Mágina and Morocco—while Bayesian analysis revealed the presence of three clusters. The low genetic diversity observed in PaCU and YeCA is probably a consequence of inappropriate management since no estimation of genetic variability was performed before the silvicultural treatments. Data indicates that the inter-simple sequence repeat (ISSR) method is sufficiently informative and powerful to assess genetic variability among populations of P. nigra. PMID:22754321

An annotated genetic map of loblolly pine based on microsatellite and cDNA markers

USDA-ARS?s Scientific Manuscript database

Previous loblolly pine (Pinus taeda L.) genetic linkage maps have been based on a variety of DNA polymorphisms, such as AFLPs, RAPDs, RFLPs, and ESTPs, but only a few SSRs (simple sequence repeats), also known as simple tandem repeats or microsatellites, have been mapped in P. taeda. The objective o...

Cultivar identification, pedigree verification, and diversity analysis among Peach (Prunus persica L. Batsch) Cultivars based on Simple Sequence Repeat markers

USDA-ARS?s Scientific Manuscript database

The genetic relationships and pedigree inferences among peach (Prunus persica (L.) Batsch) accessions and breeding lines used in genetic improvement were evaluated using 15 simple sequence repeat (SSR) markers. A total of 80 alleles were detected among the 37 peach accessions with an average of 5.53...

An integrated genetic linkage map of watermelon and genetic diversity based on single nucleotide polymorphism (SNP) and simple sequence repeat (SSR) markers

USDA-ARS?s Scientific Manuscript database

Watermelon (Citrullus lanatus var. lanatus) is an important vegetable fruit throughout the world. A high number of single nucleotide polymorphism (SNP) and simple sequence repeat (SSR) markers should provide large coverage of the watermelon genome and high phylogenetic resolution of germplasm acces...

Genetic Variation and Population Differentiation in a Medical Herb Houttuynia cordata in China Revealed by Inter-Simple Sequence Repeats (ISSRs)

PubMed Central

Wei, Lin; Wu, Xian-Jin

2012-01-01

Houttuynia cordata is an important traditional Chinese herb with unresolved genetics and taxonomy, which lead to potential problems in the conservation and utilization of the resource. Inter-simple sequence repeat (ISSR) markers were used to assess the level and distribution of genetic diversity in 226 individuals from 15 populations of H. cordata in China. ISSR analysis revealed low genetic variations within populations but high genetic differentiations among populations. This genetic structure probably mainly reflects the historical association among populations. Genetic cluster analysis showed that the basal clade is composed of populations from Southwest China, and the other populations have continuous and eastward distributions. The structure of genetic diversity in H. cordata demonstrated that this species might have survived in Southwest China during the glacial age, and subsequently experienced an eastern postglacial expansion. Based on the results of genetic analysis, it was proposed that as many as possible targeted populations for conservation be included. PMID:22942696

Genetic variation and population differentiation in a medical herb Houttuynia cordata in China revealed by inter-simple sequence repeats (ISSRs).

PubMed

Wei, Lin; Wu, Xian-Jin

2012-01-01

Houttuynia cordata is an important traditional Chinese herb with unresolved genetics and taxonomy, which lead to potential problems in the conservation and utilization of the resource. Inter-simple sequence repeat (ISSR) markers were used to assess the level and distribution of genetic diversity in 226 individuals from 15 populations of H. cordata in China. ISSR analysis revealed low genetic variations within populations but high genetic differentiations among populations. This genetic structure probably mainly reflects the historical association among populations. Genetic cluster analysis showed that the basal clade is composed of populations from Southwest China, and the other populations have continuous and eastward distributions. The structure of genetic diversity in H. cordata demonstrated that this species might have survived in Southwest China during the glacial age, and subsequently experienced an eastern postglacial expansion. Based on the results of genetic analysis, it was proposed that as many as possible targeted populations for conservation be included.

Additive Genetic Risk from Five Serotonin System Polymorphisms Interacts with Interpersonal Stress to Predict Depression

PubMed Central

Vrshek-Schallhorn, Suzanne; Stroud, Catherine B.; Mineka, Susan; Zinbarg, Richard E.; Adam, Emma K.; Redei, Eva E.; Hammen, Constance; Craske, Michelle G.

2016-01-01

Behavioral genetic research supports polygenic models of depression in which many genetic variations each contribute a small amount of risk, and prevailing diathesis-stress models suggest gene-environment interactions (GxE). Multilocus profile scores of additive risk offer an approach that is consistent with polygenic models of depression risk. In a first demonstration of this approach in a GxE predicting depression, we created an additive multilocus profile score from five serotonin system polymorphisms (one each in the genes HTR1A, HTR2A, HTR2C, and two in TPH2). Analyses focused on two forms of interpersonal stress as environmental risk factors. Using five years of longitudinal diagnostic and life stress interviews from 387 emerging young adults in the Youth Emotion Project, survival analyses show that this multilocus profile score interacts with major interpersonal stressful life events to predict major depressive episode onsets (HR = 1.815, p = .007). Simultaneously, there was a significant protective effect of the profile score without a recent event (HR = 0.83, p = .030). The GxE effect with interpersonal chronic stress was not significant (HR = 1.15, p = .165). Finally, effect sizes for genetic factors examined ignoring stress suggested such an approach could lead to overlooking or misinterpreting genetic effects. Both the GxE effect and the protective simple main effect were replicated in a sample of early adolescent girls (N = 105). We discuss potential benefits of the multilocus genetic profile score approach and caveats for future research. PMID:26595467

Feature extraction from multiple data sources using genetic programming

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Brumby, Steven P.; Pope, Paul A.; Eads, Damian R.; Esch-Mosher, Diana M.; Galassi, Mark C.; Harvey, Neal R.; McCulloch, Hersey D.; Perkins, Simon J.; Porter, Reid B.; Theiler, James P.; Young, Aaron C.; Bloch, Jeffrey J.; David, Nancy A.

2002-08-01

Feature extraction from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. We use the GENetic Imagery Exploitation (GENIE) software for this purpose, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land cover features including towns, wildfire burnscars, and forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.

The emergence of overlapping scale-free genetic architecture in digital organisms.

PubMed

Gerlee, P; Lundh, T

2008-01-01

We have studied the evolution of genetic architecture in digital organisms and found that the gene overlap follows a scale-free distribution, which is commonly found in metabolic networks of many organisms. Our results show that the slope of the scale-free distribution depends on the mutation rate and that the gene development is driven by expansion of already existing genes, which is in direct correspondence to the preferential growth algorithm that gives rise to scale-free networks. To further validate our results we have constructed a simple model of gene development, which recapitulates the results from the evolutionary process and shows that the mutation rate affects the tendency of genes to cluster. In addition we could relate the slope of the scale-free distribution to the genetic complexity of the organisms and show that a high mutation rate gives rise to a more complex genetic architecture.

Rendering the Intractable More Tractable: Tools from Caenorhabditis elegans Ripe for Import into Parasitic Nematodes

PubMed Central

Ward, Jordan D.

2015-01-01

Recent and rapid advances in genetic and molecular tools have brought spectacular tractability to Caenorhabditis elegans, a model that was initially prized because of its simple design and ease of imaging. C. elegans has long been a powerful model in biomedical research, and tools such as RNAi and the CRISPR/Cas9 system allow facile knockdown of genes and genome editing, respectively. These developments have created an additional opportunity to tackle one of the most debilitating burdens on global health and food security: parasitic nematodes. I review how development of nonparasitic nematodes as genetic models informs efforts to import tools into parasitic nematodes. Current tools in three commonly studied parasites (Strongyloides spp., Brugia malayi, and Ascaris suum) are described, as are tools from C. elegans that are ripe for adaptation and the benefits and barriers to doing so. These tools will enable dissection of a huge array of questions that have been all but completely impenetrable to date, allowing investigation into host–parasite and parasite–vector interactions, and the genetic basis of parasitism. PMID:26644478

Nonlinear inversion of potential-field data using a hybrid-encoding genetic algorithm

USGS Publications Warehouse

Chen, C.; Xia, J.; Liu, J.; Feng, G.

2006-01-01

Using a genetic algorithm to solve an inverse problem of complex nonlinear geophysical equations is advantageous because it does not require computer gradients of models or "good" initial models. The multi-point search of a genetic algorithm makes it easier to find the globally optimal solution while avoiding falling into a local extremum. As is the case in other optimization approaches, the search efficiency for a genetic algorithm is vital in finding desired solutions successfully in a multi-dimensional model space. A binary-encoding genetic algorithm is hardly ever used to resolve an optimization problem such as a simple geophysical inversion with only three unknowns. The encoding mechanism, genetic operators, and population size of the genetic algorithm greatly affect search processes in the evolution. It is clear that improved operators and proper population size promote the convergence. Nevertheless, not all genetic operations perform perfectly while searching under either a uniform binary or a decimal encoding system. With the binary encoding mechanism, the crossover scheme may produce more new individuals than with the decimal encoding. On the other hand, the mutation scheme in a decimal encoding system will create new genes larger in scope than those in the binary encoding. This paper discusses approaches of exploiting the search potential of genetic operations in the two encoding systems and presents an approach with a hybrid-encoding mechanism, multi-point crossover, and dynamic population size for geophysical inversion. We present a method that is based on the routine in which the mutation operation is conducted in the decimal code and multi-point crossover operation in the binary code. The mix-encoding algorithm is called the hybrid-encoding genetic algorithm (HEGA). HEGA provides better genes with a higher probability by a mutation operator and improves genetic algorithms in resolving complicated geophysical inverse problems. Another significant result is that final solution is determined by the average model derived from multiple trials instead of one computation due to the randomness in a genetic algorithm procedure. These advantages were demonstrated by synthetic and real-world examples of inversion of potential-field data. ?? 2005 Elsevier Ltd. All rights reserved.

In vivo neuronal calcium imaging in C. elegans.

PubMed

Chung, Samuel H; Sun, Lin; Gabel, Christopher V

2013-04-10

The nematode worm C. elegans is an ideal model organism for relatively simple, low cost neuronal imaging in vivo. Its small transparent body and simple, well-characterized nervous system allows identification and fluorescence imaging of any neuron within the intact animal. Simple immobilization techniques with minimal impact on the animal's physiology allow extended time-lapse imaging. The development of genetically-encoded calcium sensitive fluorophores such as cameleon and GCaMP allow in vivo imaging of neuronal calcium relating both cell physiology and neuronal activity. Numerous transgenic strains expressing these fluorophores in specific neurons are readily available or can be constructed using well-established techniques. Here, we describe detailed procedures for measuring calcium dynamics within a single neuron in vivo using both GCaMP and cameleon. We discuss advantages and disadvantages of both as well as various methods of sample preparation (animal immobilization) and image analysis. Finally, we present results from two experiments: 1) Using GCaMP to measure the sensory response of a specific neuron to an external electrical field and 2) Using cameleon to measure the physiological calcium response of a neuron to traumatic laser damage. Calcium imaging techniques such as these are used extensively in C. elegans and have been extended to measurements in freely moving animals, multiple neurons simultaneously and comparison across genetic backgrounds. C. elegans presents a robust and flexible system for in vivo neuronal imaging with advantages over other model systems in technical simplicity and cost.

Methods for performing crosses in Setaria viridis, a new model system for the grasses.

PubMed

Jiang, Hui; Barbier, Hugues; Brutnell, Thomas

2013-10-01

Setaria viridis is an emerging model system for C4 grasses. It is closely related to the bioenergy feed stock switchgrass and the grain crop foxtail millet. Recently, the 510 Mb genome of foxtail millet, S. italica, has been sequenced (1,2) and a 25x coverage genome sequence of the weedy relative S. viridis is in progress. S. viridis has a number of characteristics that make it a potentially excellent model genetic system including a rapid generation time, small stature, simple growth requirements, prolific seed production (3) and developed systems for both transient and stable transformation (4). However, the genetics of S. viridis is largely unexplored, in part, due to the lack of detailed methods for performing crosses. To date, no standard protocol has been adopted that will permit rapid production of seeds from controlled crosses. The protocol presented here is optimized for performing genetic crosses in S. viridis, accession A10.1. We have employed a simple heat treatment with warm water for emasculation after pruning the panicle to retain 20-30 florets and labeling of flowers to eliminate seeds resulting from newly developed flowers after emasculation. After testing a series of heat treatments at permissive temperatures and varying the duration of dipping, we have established an optimum temperature and time range of 48 °C for 3-6 min. By using this method, a minimum of 15 crosses can be performed by a single worker per day and an average of 3-5 outcross progeny per panicle can be recovered. Therefore, an average of 45-75 outcross progeny can be produced by one person in a single day. Broad implementation of this technique will facilitate the development of recombinant inbred line populations of S. viridis X S. viridis or S. viridis X S. italica, mapping mutations through bulk segregant analysis and creating higher order mutants for genetic analysis.

Admixture, Population Structure, and F-Statistics.

PubMed

Peter, Benjamin M

2016-04-01

Many questions about human genetic history can be addressed by examining the patterns of shared genetic variation between sets of populations. A useful methodological framework for this purpose isF-statistics that measure shared genetic drift between sets of two, three, and four populations and can be used to test simple and complex hypotheses about admixture between populations. This article provides context from phylogenetic and population genetic theory. I review how F-statistics can be interpreted as branch lengths or paths and derive new interpretations, using coalescent theory. I further show that the admixture tests can be interpreted as testing general properties of phylogenies, allowing extension of some ideas applications to arbitrary phylogenetic trees. The new results are used to investigate the behavior of the statistics under different models of population structure and show how population substructure complicates inference. The results lead to simplified estimators in many cases, and I recommend to replace F3 with the average number of pairwise differences for estimating population divergence. Copyright © 2016 by the Genetics Society of America.

Genetic analyses of protein yield in dairy cows applying random regression models with time-dependent and temperature x humidity-dependent covariates.

PubMed

Brügemann, K; Gernand, E; von Borstel, U U; König, S

2011-08-01

Data used in the present study included 1,095,980 first-lactation test-day records for protein yield of 154,880 Holstein cows housed on 196 large-scale dairy farms in Germany. Data were recorded between 2002 and 2009 and merged with meteorological data from public weather stations. The maximum distance between each farm and its corresponding weather station was 50 km. Hourly temperature-humidity indexes (THI) were calculated using the mean of hourly measurements of dry bulb temperature and relative humidity. On the phenotypic scale, an increase in THI was generally associated with a decrease in daily protein yield. For genetic analyses, a random regression model was applied using time-dependent (d in milk, DIM) and THI-dependent covariates. Additive genetic and permanent environmental effects were fitted with this random regression model and Legendre polynomials of order 3 for DIM and THI. In addition, the fixed curve was modeled with Legendre polynomials of order 3. Heterogeneous residuals were fitted by dividing DIM into 5 classes, and by dividing THI into 4 classes, resulting in 20 different classes. Additive genetic variances for daily protein yield decreased with increasing degrees of heat stress and were lowest at the beginning of lactation and at extreme THI. Due to higher additive genetic variances, slightly higher permanent environment variances, and similar residual variances, heritabilities were highest for low THI in combination with DIM at the end of lactation. Genetic correlations among individual values for THI were generally >0.90. These trends from the complex random regression model were verified by applying relatively simple bivariate animal models for protein yield measured in 2 THI environments; that is, defining a THI value of 60 as a threshold. These high correlations indicate the absence of any substantial genotype × environment interaction for protein yield. However, heritabilities and additive genetic variances from the random regression model tended to be slightly higher in the THI range corresponding to cows' comfort zone. Selecting such superior environments for progeny testing can contribute to an accurate genetic differentiation among selection candidates. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Short Communication: Genetic linkage map of Cucurbita maxima with molecular and morphological markers.

PubMed

Ge, Y; Li, X; Yang, X X; Cui, C S; Qu, S P

2015-05-22

Cucurbita maxima is one of the most widely cultivated vegetables in China and exhibits distinct morphological characteristics. In this study, genetic linkage analysis with 57 simple-sequence repeats, 21 amplified fragment length polymorphisms, 3 random-amplified polymorphic DNA, and one morphological marker revealed 20 genetic linkage groups of C. maxima covering a genetic distance of 991.5 cM with an average of 12.1 cM between adjacent markers. Genetic linkage analysis identified the simple-sequence repeat marker 'PU078072' 5.9 cM away from the locus 'Rc', which controls rind color. The genetic map in the present study will be useful for better mapping, tagging, and cloning of quantitative trait loci/gene(s) affecting economically important traits and for breeding new varieties of C. maxima through marker-assisted selection.

Genetic fidelity and variability of micropropagated cassava plants (Manihot esculenta Crantz) evaluated using ISSR markers.

PubMed

Vidal, Á M; Vieira, L J; Ferreira, C F; Souza, F V D; Souza, A S; Ledo, C A S

2015-07-14

Molecular markers are efficient for assessing the genetic fidelity of various species of plants after in vitro culture. In this study, we evaluated the genetic fidelity and variability of micropropagated cassava plants (Manihot esculenta Crantz) using inter-simple sequence repeat markers. Twenty-two cassava accessions from the Embrapa Cassava & Fruits Germplasm Bank were used. For each accession, DNA was extracted from a plant maintained in the field and from 3 plants grown in vitro. For DNA amplification, 27 inter-simple sequence repeat primers were used, of which 24 generated 175 bands; 100 of those bands were polymorphic and were used to study genetic variability among accessions of cassava plants maintained in the field. Based on the genetic distance matrix calculated using the arithmetic complement of the Jaccard's index, genotypes were clustered using the unweighted pair group method using arithmetic averages. The number of bands per primer was 2-13, with an average of 7.3. For most micropropagated accessions, the fidelity study showed no genetic variation between plants of the same accessions maintained in the field and those maintained in vitro, confirming the high genetic fidelity of the micropropagated plants. However, genetic variability was observed among different accessions grown in the field, and clustering based on the dissimilarity matrix revealed 7 groups. Inter-simple sequence repeat markers were efficient for detecting the genetic homogeneity of cassava plants derived from meristem culture, demonstrating the reliability of this propagation system.

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

PubMed Central

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

2010-01-01

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

On Cellular Darwinism: Mitochondria.

PubMed

Bull, Larry

2016-01-01

The significant role of mitochondria within cells is becoming increasingly clear. This letter uses the NKCS model of coupled fitness landscapes to explore aspects of organelle-nucleus coevolution. The phenomenon of mitochondrial diversity is allowed to emerge under a simple intracellular evolutionary process, including varying the relative rate of evolution by the organelle. It is shown how the conditions for the maintenance of more than one genetic variant of mitochondria are similar to those previously suggested as needed for the original symbiotic origins of the relationship using the NKCS model.

Comparison of the theoretical and real-world evolutionary potential of a genetic circuit

NASA Astrophysics Data System (ADS)

Razo-Mejia, M.; Boedicker, J. Q.; Jones, D.; DeLuna, A.; Kinney, J. B.; Phillips, R.

2014-04-01

With the development of next-generation sequencing technologies, many large scale experimental efforts aim to map genotypic variability among individuals. This natural variability in populations fuels many fundamental biological processes, ranging from evolutionary adaptation and speciation to the spread of genetic diseases and drug resistance. An interesting and important component of this variability is present within the regulatory regions of genes. As these regions evolve, accumulated mutations lead to modulation of gene expression, which may have consequences for the phenotype. A simple model system where the link between genetic variability, gene regulation and function can be studied in detail is missing. In this article we develop a model to explore how the sequence of the wild-type lac promoter dictates the fold-change in gene expression. The model combines single-base pair resolution maps of transcription factor and RNA polymerase binding energies with a comprehensive thermodynamic model of gene regulation. The model was validated by predicting and then measuring the variability of lac operon regulation in a collection of natural isolates. We then implement the model to analyze the sensitivity of the promoter sequence to the regulatory output, and predict the potential for regulation to evolve due to point mutations in the promoter region.

Genetic variation affecting host-parasite interactions: different genes affect different aspects of sigma virus replication and transmission in Drosophila melanogaster.

PubMed

Bangham, Jenny; Kim, Kang-Wook; Webster, Claire L; Jiggins, Francis M

2008-04-01

In natural populations, genetic variation affects resistance to disease. Knowing how much variation exists, and understanding the genetic architecture of this variation, is important for medicine, for agriculture, and for understanding evolutionary processes. To investigate the extent and nature of genetic variation affecting resistance to pathogens, we are studying a tractable model system: Drosophila melanogaster and its natural pathogen the vertically transmitted sigma virus. We show that considerable genetic variation affects transmission of the virus from parent to offspring. However, maternal and paternal transmission of the virus is affected by different genes. Maternal transmission is a simple Mendelian trait: most of the genetic variation is explained by a polymorphism in ref(2)P, a gene already well known to affect resistance to sigma. In contrast, there is considerable genetic variation in paternal transmission that cannot be explained by ref(2)P and is caused by other loci on chromosome 2. Furthermore, we found no genetic correlation between paternal transmission of the virus and resistance to infection by the sigma virus following injection. This suggests that different loci affect viral replication and paternal transmission.

Evolving neural networks with genetic algorithms to study the string landscape

NASA Astrophysics Data System (ADS)

Ruehle, Fabian

2017-08-01

We study possible applications of artificial neural networks to examine the string landscape. Since the field of application is rather versatile, we propose to dynamically evolve these networks via genetic algorithms. This means that we start from basic building blocks and combine them such that the neural network performs best for the application we are interested in. We study three areas in which neural networks can be applied: to classify models according to a fixed set of (physically) appealing features, to find a concrete realization for a computation for which the precise algorithm is known in principle but very tedious to actually implement, and to predict or approximate the outcome of some involved mathematical computation which performs too inefficient to apply it, e.g. in model scans within the string landscape. We present simple examples that arise in string phenomenology for all three types of problems and discuss how they can be addressed by evolving neural networks from genetic algorithms.

Unraveling the mechanisms of synapse formation and axon regeneration: the awesome power of C. elegans genetics.

PubMed

Jin, YiShi

2015-11-01

Since Caenorhabditis elegans was chosen as a model organism by Sydney Brenner in 1960's, genetic studies in this organism have been instrumental in discovering the function of genes and in deciphering molecular signaling network. The small size of the organism and the simple nervous system enable the complete reconstruction of the first connectome. The stereotypic developmental program and the anatomical reproducibility of synaptic connections provide a blueprint to dissect the mechanisms underlying synapse formation. Recent technological innovation using laser surgery of single axons and in vivo imaging has also made C. elegans a new model for axon regeneration. Importantly, genes regulating synaptogenesis and axon regeneration are highly conserved in function across animal phyla. This mini-review will summarize the main approaches and the key findings in understanding the mechanisms underlying the development and maintenance of the nervous system. The impact of such findings underscores the awesome power of C. elegans genetics.

Brain-derived neurotrophic factor as a model system for examining gene by environment interactions across development.

PubMed

Casey, B J; Glatt, C E; Tottenham, N; Soliman, F; Bath, K; Amso, D; Altemus, M; Pattwell, S; Jones, R; Levita, L; McEwen, B; Magariños, A M; Gunnar, M; Thomas, K M; Mezey, J; Clark, A G; Hempstead, B L; Lee, F S

2009-11-24

There has been a dramatic rise in gene x environment studies of human behavior over the past decade that have moved the field beyond simple nature versus nurture debates. These studies offer promise in accounting for more variability in behavioral and biological phenotypes than studies that focus on genetic or experiential factors alone. They also provide clues into mechanisms of modifying genetic risk or resilience in neurodevelopmental disorders. Yet, it is rare that these studies consider how these interactions change over the course of development. In this paper, we describe research that focuses on the impact of a polymorphism in a brain-derived neurotrophic factor (BDNF) gene, known to be involved in learning and development. Specifically we present findings that assess the effects of genotypic and environmental loadings on neuroanatomic and behavioral phenotypes across development. The findings illustrate the use of a genetic mouse model that mimics the human polymorphism, to constrain the interpretation of gene-environment interactions across development in humans.

A multi-objective genetic algorithm for a mixed-model assembly U-line balancing type-I problem considering human-related issues, training, and learning

NASA Astrophysics Data System (ADS)

Rabbani, Masoud; Montazeri, Mona; Farrokhi-Asl, Hamed; Rafiei, Hamed

2016-12-01

Mixed-model assembly lines are increasingly accepted in many industrial environments to meet the growing trend of greater product variability, diversification of customer demands, and shorter life cycles. In this research, a new mathematical model is presented considering balancing a mixed-model U-line and human-related issues, simultaneously. The objective function consists of two separate components. The first part of the objective function is related to balance problem. In this part, objective functions are minimizing the cycle time, minimizing the number of workstations, and maximizing the line efficiencies. The second part is related to human issues and consists of hiring cost, firing cost, training cost, and salary. To solve the presented model, two well-known multi-objective evolutionary algorithms, namely non-dominated sorting genetic algorithm and multi-objective particle swarm optimization, have been used. A simple solution representation is provided in this paper to encode the solutions. Finally, the computational results are compared and analyzed.

M13-Tailed Simple Sequence Repeat (SSR) Markers in Studies of Genetic Diversity and Population Structure of Common Oat Germplasm.

PubMed

Onyśk, Agnieszka; Boczkowska, Maja

2017-01-01

Simple Sequence Repeat (SSR) markers are one of the most frequently used molecular markers in studies of crop diversity and population structure. This is due to their uniform distribution in the genome, the high polymorphism, reproducibility, and codominant character. Additional advantages are the possibility of automatic analysis and simple interpretation of the results. The M13 tagged PCR reaction significantly reduces the costs of analysis by the automatic genetic analyzers. Here, we also disclose a short protocol of SSR data analysis.

Evidence for transgenerational metabolic programming in Drosophila

PubMed Central

Buescher, Jessica L.; Musselman, Laura P.; Wilson, Christina A.; Lang, Tieming; Keleher, Madeline; Baranski, Thomas J.; Duncan, Jennifer G.

2013-01-01

SUMMARY Worldwide epidemiologic studies have repeatedly demonstrated an association between prenatal nutritional environment, birth weight and susceptibility to adult diseases including obesity, cardiovascular disease and type 2 diabetes. Despite advances in mammalian model systems, the molecular mechanisms underlying this phenomenon are unclear, but might involve programming mechanisms such as epigenetics. Here we describe a new system for evaluating metabolic programming mechanisms using a simple, genetically tractable Drosophila model. We examined the effect of maternal caloric excess on offspring and found that a high-sugar maternal diet alters body composition of larval offspring for at least two generations, augments an obese-like phenotype under suboptimal (high-calorie) feeding conditions in adult offspring, and modifies expression of metabolic genes. Our data indicate that nutritional programming mechanisms could be highly conserved and support the use of Drosophila as a model for evaluating the underlying genetic and epigenetic contributions to this phenomenon. PMID:23649823

An Efficient, Simple, and Noninvasive Procedure for Genotyping Aquatic and Nonaquatic Laboratory Animals.

PubMed

Okada, Morihiro; Miller, Thomas C; Roediger, Julia; Shi, Yun-Bo; Schech, Joseph Mat

2017-09-01

Various animal models are indispensible in biomedical research. Increasing awareness and regulations have prompted the adaptation of more humane approaches in the use of laboratory animals. With the development of easier and faster methodologies to generate genetically altered animals, convenient and humane methods to genotype these animals are important for research involving such animals. Here, we report skin swabbing as a simple and noninvasive method for extracting genomic DNA from mice and frogs for genotyping. We show that this method is highly reliable and suitable for both immature and adult animals. Our approach allows a simpler and more humane approach for genotyping vertebrate animals.

The molecular basis of ethylene signalling in Arabidopsis

NASA Technical Reports Server (NTRS)

Woeste, K.; Kieber, J. J.; Evans, M. L. (Principal Investigator)

1998-01-01

The simple gas ethylene profoundly influences plants at nearly every stage of growth and development. In the past ten years, the use of a genetic approach, based on the triple response phenotype, has been a powerful tool for investigating the molecular events that underlie these effects. Several fundamental elements of the pathway have been described: a receptor with homology to bacterial two-component histidine kinases (ETR1), elements of a MAP kinase cascade (CTR1) and a putative transcription factor (EIN3). Taken together, these elements can be assembled into a simple, linear model for ethylene signalling that accounts for most of the well-characterized ethylene mediated responses.

The Genetic and Environmental Foundation of the Simple View of Reading in Chinese

PubMed Central

Ho, Connie Suk-Han; Chow, Bonnie Wing-Yin; Wong, Simpson Wai-Lap; Waye, Mary M. Y.; Bishop, Dorothy V. M.

2012-01-01

The Simple View of Reading (SVR) in Chinese was examined in a genetically sensitive design. A total of 270 pairs of Chinese twins (190 pairs of monozygotic twins and 80 pairs of same-sex dizygotic twins) were tested on Chinese vocabulary and word reading at the mean age 7.8 years and reading comprehension of sentences and passages one year later. Results of behavior-genetic analyses showed that both vocabulary and word reading had significant independent genetic influences on reading comprehension, and the two factors together accounted for most but not all of the genetic influences on reading comprehension. In addition, sentence comprehension had a stronger genetic correlation with word reading while passage comprehension showed a trend of stronger genetic overlap with vocabulary. These findings suggest that the genetic foundation of the SVR in Chinese is largely supported in that language comprehension and decoding are two core skills for reading comprehension in nonalphabetic as well as alphabetic written languages. PMID:23112862

Genetic aspects of autism spectrum disorders: insights from animal models

PubMed Central

Banerjee, Swati; Riordan, Maeveen; Bhat, Manzoor A.

2014-01-01

Autism spectrum disorders (ASDs) are a complex neurodevelopmental disorder that display a triad of core behavioral deficits including restricted interests, often accompanied by repetitive behavior, deficits in language and communication, and an inability to engage in reciprocal social interactions. ASD is among the most heritable disorders but is not a simple disorder with a singular pathology and has a rather complex etiology. It is interesting to note that perturbations in synaptic growth, development, and stability underlie a variety of neuropsychiatric disorders, including ASD, schizophrenia, epilepsy, and intellectual disability. Biological characterization of an increasing repertoire of synaptic mutants in various model organisms indicates synaptic dysfunction as causal in the pathophysiology of ASD. Our understanding of the genes and genetic pathways that contribute toward the formation, stabilization, and maintenance of functional synapses coupled with an in-depth phenotypic analysis of the cellular and behavioral characteristics is therefore essential to unraveling the pathogenesis of these disorders. In this review, we discuss the genetic aspects of ASD emphasizing on the well conserved set of genes and genetic pathways implicated in this disorder, many of which contribute to synapse assembly and maintenance across species. We also review how fundamental research using animal models is providing key insights into the various facets of human ASD. PMID:24605088

MIP Models and Hybrid Algorithms for Simultaneous Job Splitting and Scheduling on Unrelated Parallel Machines

PubMed Central

Ozmutlu, H. Cenk

2014-01-01

We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms. PMID:24977204

A twin study of cardiac reactivity and its relationship to parental blood pressure.

PubMed

Carroll, D; Hewitt, J K; Last, K A; Turner, J R; Sims, J

1985-01-01

The cardiac reactivity of 40 monozygotic and 40 dizygotic pairs of young male twins was monitored during psychological challenge, as afforded by a video game. The observed pattern of variation could not be accounted for solely by environmental factors. In fact, a simple genetic model that implicated additive genetic effects, along with those stemming from individual environments, best fitted the data. In addition, cardiac reactions were substantially greater for subjects whose parents both had relatively elevated blood pressure. Overall, these data suggest individual differences in cardiac reactivity have a heritable component, and that high reactivity may be a precursor of elevated blood pressure.

Joint effect of unlinked genotypes: application to type 2 diabetes in the EPIC-Potsdam case-cohort study.

PubMed

Knüppel, Sven; Meidtner, Karina; Arregui, Maria; Holzhütter, Hermann-Georg; Boeing, Heiner

2015-07-01

Analyzing multiple single nucleotide polymorphisms (SNPs) is a promising approach to finding genetic effects beyond single-locus associations. We proposed the use of multilocus stepwise regression (MSR) to screen for allele combinations as a method to model joint effects, and compared the results with the often used genetic risk score (GRS), conventional stepwise selection, and the shrinkage method LASSO. In contrast to MSR, the GRS, conventional stepwise selection, and LASSO model each genotype by the risk allele doses. We reanalyzed 20 unlinked SNPs related to type 2 diabetes (T2D) in the EPIC-Potsdam case-cohort study (760 cases, 2193 noncases). No SNP-SNP interactions and no nonlinear effects were found. Two SNP combinations selected by MSR (Nagelkerke's R² = 0.050 and 0.048) included eight SNPs with mean allele combination frequency of 2%. GRS and stepwise selection selected nearly the same SNP combinations consisting of 12 and 13 SNPs (Nagelkerke's R² ranged from 0.020 to 0.029). LASSO showed similar results. The MSR method showed the best model fit measured by Nagelkerke's R² suggesting that further improvement may render this method a useful tool in genetic research. However, our comparison suggests that the GRS is a simple way to model genetic effects since it does not consider linkage, SNP-SNP interactions, and no non-linear effects. © 2015 John Wiley & Sons Ltd/University College London.

Evolutionary response when selection and genetic variation covary across environments.

PubMed

Wood, Corlett W; Brodie, Edmund D

2016-10-01

Although models of evolution usually assume that the strength of selection on a trait and the expression of genetic variation in that trait are independent, whenever the same ecological factor impacts both parameters, a correlation between the two may arise that accelerates trait evolution in some environments and slows it in others. Here, we address the evolutionary consequences and ecological causes of a correlation between selection and expressed genetic variation. Using a simple analytical model, we show that the correlation has a modest effect on the mean evolutionary response and a large effect on its variance, increasing among-population or among-generation variation in the response when positive, and diminishing variation when negative. We performed a literature review to identify the ecological factors that influence selection and expressed genetic variation across traits. We found that some factors - temperature and competition - are unlikely to generate the correlation because they affected one parameter more than the other, and identified others - most notably, environmental novelty - that merit further investigation because little is known about their impact on one of the two parameters. We argue that the correlation between selection and genetic variation deserves attention alongside other factors that promote or constrain evolution in heterogeneous landscapes. © 2016 John Wiley & Sons Ltd/CNRS.

Genetic basis to hybrid inviability is more complex than hybrid male sterility in Caenorhabditis nematodes.

PubMed

Bundus, Joanna D; Wang, Donglin; Cutter, Asher D

2018-04-07

Hybrid male sterility often evolves before female sterility or inviability of hybrids, implying that the accumulation of divergence between separated lineages should lead hybrid male sterility to have a more polygenic basis. However, experimental evidence is mixed. Here, we use the nematodes Caenorhabditis remanei and C. latens to characterize the underlying genetic basis of asymmetric hybrid male sterility and hybrid inviability. We demonstrate that hybrid male sterility is consistent with a simple genetic basis, involving a single X-autosome incompatibility. We also show that hybrid inviability involves more genomic compartments, involving diverse nuclear-nuclear incompatibilities, a mito-nuclear incompatibility, and maternal effects. These findings demonstrate that male sensitivity to genetic perturbation may be genetically simple compared to hybrid inviability in Caenorhabditis and motivates tests of generality for the genetic architecture of hybrid incompatibility across the breadth of phylogeny.

Powerful multilocus tests of genetic association in the presence of gene-gene and gene-environment interactions.

PubMed

Chatterjee, Nilanjan; Kalaylioglu, Zeynep; Moslehi, Roxana; Peters, Ulrike; Wacholder, Sholom

2006-12-01

In modern genetic epidemiology studies, the association between the disease and a genomic region, such as a candidate gene, is often investigated using multiple SNPs. We propose a multilocus test of genetic association that can account for genetic effects that might be modified by variants in other genes or by environmental factors. We consider use of the venerable and parsimonious Tukey's 1-degree-of-freedom model of interaction, which is natural when individual SNPs within a gene are associated with disease through a common biological mechanism; in contrast, many standard regression models are designed as if each SNP has unique functional significance. On the basis of Tukey's model, we propose a novel but computationally simple generalized test of association that can simultaneously capture both the main effects of the variants within a genomic region and their interactions with the variants in another region or with an environmental exposure. We compared performance of our method with that of two standard tests of association, one ignoring gene-gene/gene-environment interactions and the other based on a saturated model of interactions. We demonstrate major power advantages of our method both in analysis of data from a case-control study of the association between colorectal adenoma and DNA variants in the NAT2 genomic region, which are well known to be related to a common biological phenotype, and under different models of gene-gene interactions with use of simulated data.

Genetic diversity analysis of sugarcane germplasm based on fluorescence-labeled simple sequence repeat markers and a capillary electrophoresis-based genotyping platform

USDA-ARS?s Scientific Manuscript database

Genetic diversity analysis, which refers to the elaboration of total extent of genetic characteristics in the genetic makeup of a certain species, constitutes a classical strategy for the study of diversity, population genetic structure, and breeding practices. In this study, fluorescence-labeled se...

In defence of model-based inference in phylogeography

PubMed Central

Beaumont, Mark A.; Nielsen, Rasmus; Robert, Christian; Hey, Jody; Gaggiotti, Oscar; Knowles, Lacey; Estoup, Arnaud; Panchal, Mahesh; Corander, Jukka; Hickerson, Mike; Sisson, Scott A.; Fagundes, Nelson; Chikhi, Lounès; Beerli, Peter; Vitalis, Renaud; Cornuet, Jean-Marie; Huelsenbeck, John; Foll, Matthieu; Yang, Ziheng; Rousset, Francois; Balding, David; Excoffier, Laurent

2017-01-01

Recent papers have promoted the view that model-based methods in general, and those based on Approximate Bayesian Computation (ABC) in particular, are flawed in a number of ways, and are therefore inappropriate for the analysis of phylogeographic data. These papers further argue that Nested Clade Phylogeographic Analysis (NCPA) offers the best approach in statistical phylogeography. In order to remove the confusion and misconceptions introduced by these papers, we justify and explain the reasoning behind model-based inference. We argue that ABC is a statistically valid approach, alongside other computational statistical techniques that have been successfully used to infer parameters and compare models in population genetics. We also examine the NCPA method and highlight numerous deficiencies, either when used with single or multiple loci. We further show that the ages of clades are carelessly used to infer ages of demographic events, that these ages are estimated under a simple model of panmixia and population stationarity but are then used under different and unspecified models to test hypotheses, a usage the invalidates these testing procedures. We conclude by encouraging researchers to study and use model-based inference in population genetics. PMID:29284924

Additive genetic risk from five serotonin system polymorphisms interacts with interpersonal stress to predict depression.

PubMed

Vrshek-Schallhorn, Suzanne; Stroud, Catherine B; Mineka, Susan; Zinbarg, Richard E; Adam, Emma K; Redei, Eva E; Hammen, Constance; Craske, Michelle G

2015-11-01

Behavioral genetic research supports polygenic models of depression in which many genetic variations each contribute a small amount of risk, and prevailing diathesis-stress models suggest gene-environment interactions (G×E). Multilocus profile scores of additive risk offer an approach that is consistent with polygenic models of depression risk. In a first demonstration of this approach in a G×E predicting depression, we created an additive multilocus profile score from 5 serotonin system polymorphisms (1 each in the genes HTR1A, HTR2A, HTR2C, and 2 in TPH2). Analyses focused on 2 forms of interpersonal stress as environmental risk factors. Using 5 years of longitudinal diagnostic and life stress interviews from 387 emerging young adults in the Youth Emotion Project, survival analyses show that this multilocus profile score interacts with major interpersonal stressful life events to predict major depressive episode onsets (hazard ratio [HR] = 1.815, p = .007). Simultaneously, there was a significant protective effect of the profile score without a recent event (HR = 0.83, p = .030). The G×E effect with interpersonal chronic stress was not significant (HR = 1.15, p = .165). Finally, effect sizes for genetic factors examined ignoring stress suggested such an approach could lead to overlooking or misinterpreting genetic effects. Both the G×E effect and the protective simple main effect were replicated in a sample of early adolescent girls (N = 105). We discuss potential benefits of the multilocus genetic profile score approach and caveats for future research. (c) 2015 APA, all rights reserved).

Genetic hotels for the standard genetic code: evolutionary analysis based upon novel three-dimensional algebraic models.

PubMed

José, Marco V; Morgado, Eberto R; Govezensky, Tzipe

2011-07-01

Herein, we rigorously develop novel 3-dimensional algebraic models called Genetic Hotels of the Standard Genetic Code (SGC). We start by considering the primeval RNA genetic code which consists of the 16 codons of type RNY (purine-any base-pyrimidine). Using simple algebraic operations, we show how the RNA code could have evolved toward the current SGC via two different intermediate evolutionary stages called Extended RNA code type I and II. By rotations or translations of the subset RNY, we arrive at the SGC via the former (type I) or via the latter (type II), respectively. Biologically, the Extended RNA code type I, consists of all codons of the type RNY plus codons obtained by considering the RNA code but in the second (NYR type) and third (YRN type) reading frames. The Extended RNA code type II, comprises all codons of the type RNY plus codons that arise from transversions of the RNA code in the first (YNY type) and third (RNR) nucleotide bases. Since the dimensions of remarkable subsets of the Genetic Hotels are not necessarily integer numbers, we also introduce the concept of algebraic fractal dimension. A general decoding function which maps each codon to its corresponding amino acid or the stop signals is also derived. The Phenotypic Hotel of amino acids is also illustrated. The proposed evolutionary paths are discussed in terms of the existing theories of the evolution of the SGC. The adoption of 3-dimensional models of the Genetic and Phenotypic Hotels will facilitate the understanding of the biological properties of the SGC.

Sexual and apomictic plant reproduction in the genomics era: exploring the mechanisms potentially useful in crop plants.

PubMed

Dwivedi, Sangam L; Perotti, Enrico; Upadhyaya, Hari D; Ortiz, Rodomiro

2010-12-01

Arabidopsis, Mimulus and tomato have emerged as model plants in researching genetic and molecular basis of differences in mating systems. Variations in floral traits and loss of self-incompatibility have been associated with mating system differences in crops. Genomics research has advanced considerably, both in model and crop plants, which may provide opportunities to modify breeding systems as evidenced in Arabidopsis and tomato. Mating system, however, not recombination per se, has greater effect on the level of polymorphism. Generating targeted recombination remains one of the most important factors for crop genetic enhancement. Asexual reproduction through seeds or apomixis, by producing maternal clones, presents a tremendous potential for agriculture. Although believed to be under simple genetic control, recent research has revealed that apomixis results as a consequence of the deregulation of the timing of sexual events rather than being the product of specific apomixis genes. Further, forward genetic studies in Arabidopsis have permitted the isolation of novel genes reported to control meiosis I and II entry. Mutations in these genes trigger the production of unreduced or apomeiotic megagametes and are an important step toward understanding and engineering apomixis.

Mapping of epistatic quantitative trait loci in four-way crosses.

PubMed

He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

2011-01-01

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

Toward unraveling the complexity of simple epithelial keratins in human disease.

PubMed

Omary, M Bishr; Ku, Nam-On; Strnad, Pavel; Hanada, Shinichiro

2009-07-01

Simple epithelial keratins (SEKs) are found primarily in single-layered simple epithelia and include keratin 7 (K7), K8, K18-K20, and K23. Genetically engineered mice that lack SEKs or overexpress mutant SEKs have helped illuminate several keratin functions and served as important disease models. Insight into the contribution of SEKs to human disease has indicated that K8 and K18 are the major constituents of Mallory-Denk bodies, hepatic inclusions associated with several liver diseases, and are essential for inclusion formation. Furthermore, mutations in the genes encoding K8, K18, and K19 predispose individuals to a variety of liver diseases. Hence, as we discuss here, the SEK cytoskeleton is involved in the orchestration of several important cellular functions and contributes to the pathogenesis of human liver disease.

Toward unraveling the complexity of simple epithelial keratins in human disease

PubMed Central

Omary, M. Bishr; Ku, Nam-On; Strnad, Pavel; Hanada, Shinichiro

2009-01-01

Simple epithelial keratins (SEKs) are found primarily in single-layered simple epithelia and include keratin 7 (K7), K8, K18–K20, and K23. Genetically engineered mice that lack SEKs or overexpress mutant SEKs have helped illuminate several keratin functions and served as important disease models. Insight into the contribution of SEKs to human disease has indicated that K8 and K18 are the major constituents of Mallory-Denk bodies, hepatic inclusions associated with several liver diseases, and are essential for inclusion formation. Furthermore, mutations in the genes encoding K8, K18, and K19 predispose individuals to a variety of liver diseases. Hence, as we discuss here, the SEK cytoskeleton is involved in the orchestration of several important cellular functions and contributes to the pathogenesis of human liver disease. PMID:19587454

Modeling Structure-Function Relationships in Synthetic DNA Sequences using Attribute Grammars

PubMed Central

Cai, Yizhi; Lux, Matthew W.; Adam, Laura; Peccoud, Jean

2009-01-01

Recognizing that certain biological functions can be associated with specific DNA sequences has led various fields of biology to adopt the notion of the genetic part. This concept provides a finer level of granularity than the traditional notion of the gene. However, a method of formally relating how a set of parts relates to a function has not yet emerged. Synthetic biology both demands such a formalism and provides an ideal setting for testing hypotheses about relationships between DNA sequences and phenotypes beyond the gene-centric methods used in genetics. Attribute grammars are used in computer science to translate the text of a program source code into the computational operations it represents. By associating attributes with parts, modifying the value of these attributes using rules that describe the structure of DNA sequences, and using a multi-pass compilation process, it is possible to translate DNA sequences into molecular interaction network models. These capabilities are illustrated by simple example grammars expressing how gene expression rates are dependent upon single or multiple parts. The translation process is validated by systematically generating, translating, and simulating the phenotype of all the sequences in the design space generated by a small library of genetic parts. Attribute grammars represent a flexible framework connecting parts with models of biological function. They will be instrumental for building mathematical models of libraries of genetic constructs synthesized to characterize the function of genetic parts. This formalism is also expected to provide a solid foundation for the development of computer assisted design applications for synthetic biology. PMID:19816554

Markov Logic Networks in the Analysis of Genetic Data

PubMed Central

Sakhanenko, Nikita A.

2010-01-01

Abstract Complex, non-additive genetic interactions are common and can be critical in determining phenotypes. Genome-wide association studies (GWAS) and similar statistical studies of linkage data, however, assume additive models of gene interactions in looking for genotype-phenotype associations. These statistical methods view the compound effects of multiple genes on a phenotype as a sum of influences of each gene and often miss a substantial part of the heritable effect. Such methods do not use any biological knowledge about underlying mechanisms. Modeling approaches from the artificial intelligence (AI) field that incorporate deterministic knowledge into models to perform statistical analysis can be applied to include prior knowledge in genetic analysis. We chose to use the most general such approach, Markov Logic Networks (MLNs), for combining deterministic knowledge with statistical analysis. Using simple, logistic regression-type MLNs we can replicate the results of traditional statistical methods, but we also show that we are able to go beyond finding independent markers linked to a phenotype by using joint inference without an independence assumption. The method is applied to genetic data on yeast sporulation, a complex phenotype with gene interactions. In addition to detecting all of the previously identified loci associated with sporulation, our method identifies four loci with smaller effects. Since their effect on sporulation is small, these four loci were not detected with methods that do not account for dependence between markers due to gene interactions. We show how gene interactions can be detected using more complex models, which can be used as a general framework for incorporating systems biology with genetics. PMID:20958249

Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma

PubMed Central

McFadden, David G.; Politi, Katerina; Bhutkar, Arjun; Chen, Frances K.; Song, Xiaoling; Pirun, Mono; Santiago, Philip M.; Kim-Kiselak, Caroline; Platt, James T.; Lee, Emily; Hodges, Emily; Rosebrock, Adam P.; Bronson, Roderick T.; Socci, Nicholas D.; Hannon, Gregory J.; Jacks, Tyler; Varmus, Harold

2016-01-01

Genetically engineered mouse models (GEMMs) of cancer are increasingly being used to assess putative driver mutations identified by large-scale sequencing of human cancer genomes. To accurately interpret experiments that introduce additional mutations, an understanding of the somatic genetic profile and evolution of GEMM tumors is necessary. Here, we performed whole-exome sequencing of tumors from three GEMMs of lung adenocarcinoma driven by mutant epidermal growth factor receptor (EGFR), mutant Kirsten rat sarcoma viral oncogene homolog (Kras), or overexpression of MYC proto-oncogene. Tumors from EGFR- and Kras-driven models exhibited, respectively, 0.02 and 0.07 nonsynonymous mutations per megabase, a dramatically lower average mutational frequency than observed in human lung adenocarcinomas. Tumors from models driven by strong cancer drivers (mutant EGFR and Kras) harbored few mutations in known cancer genes, whereas tumors driven by MYC, a weaker initiating oncogene in the murine lung, acquired recurrent clonal oncogenic Kras mutations. In addition, although EGFR- and Kras-driven models both exhibited recurrent whole-chromosome DNA copy number alterations, the specific chromosomes altered by gain or loss were different in each model. These data demonstrate that GEMM tumors exhibit relatively simple somatic genotypes compared with human cancers of a similar type, making these autochthonous model systems useful for additive engineering approaches to assess the potential of novel mutations on tumorigenesis, cancer progression, and drug sensitivity. PMID:27702896

Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma.

PubMed

McFadden, David G; Politi, Katerina; Bhutkar, Arjun; Chen, Frances K; Song, Xiaoling; Pirun, Mono; Santiago, Philip M; Kim-Kiselak, Caroline; Platt, James T; Lee, Emily; Hodges, Emily; Rosebrock, Adam P; Bronson, Roderick T; Socci, Nicholas D; Hannon, Gregory J; Jacks, Tyler; Varmus, Harold

2016-10-18

Genetically engineered mouse models (GEMMs) of cancer are increasingly being used to assess putative driver mutations identified by large-scale sequencing of human cancer genomes. To accurately interpret experiments that introduce additional mutations, an understanding of the somatic genetic profile and evolution of GEMM tumors is necessary. Here, we performed whole-exome sequencing of tumors from three GEMMs of lung adenocarcinoma driven by mutant epidermal growth factor receptor (EGFR), mutant Kirsten rat sarcoma viral oncogene homolog (Kras), or overexpression of MYC proto-oncogene. Tumors from EGFR- and Kras-driven models exhibited, respectively, 0.02 and 0.07 nonsynonymous mutations per megabase, a dramatically lower average mutational frequency than observed in human lung adenocarcinomas. Tumors from models driven by strong cancer drivers (mutant EGFR and Kras) harbored few mutations in known cancer genes, whereas tumors driven by MYC, a weaker initiating oncogene in the murine lung, acquired recurrent clonal oncogenic Kras mutations. In addition, although EGFR- and Kras-driven models both exhibited recurrent whole-chromosome DNA copy number alterations, the specific chromosomes altered by gain or loss were different in each model. These data demonstrate that GEMM tumors exhibit relatively simple somatic genotypes compared with human cancers of a similar type, making these autochthonous model systems useful for additive engineering approaches to assess the potential of novel mutations on tumorigenesis, cancer progression, and drug sensitivity.

Unlinked Mendelian inheritance of red and black pigmentation in snakes: Implications for Batesian mimicry.

PubMed

Davis Rabosky, Alison R; Cox, Christian L; Rabosky, Daniel L

2016-04-01

Identifying the genetic basis of mimetic signals is critical to understanding both the origin and dynamics of mimicry over time. For species not amenable to large laboratory breeding studies, widespread color polymorphism across natural populations offers a powerful way to assess the relative likelihood of different genetic systems given observed phenotypic frequencies. We classified color phenotype for 2175 ground snakes (Sonora semiannulata) across the continental United States to analyze morph ratios and test among competing hypotheses about the genetic architecture underlying red and black coloration in coral snake mimics. We found strong support for a two-locus model under simple Mendelian inheritance, with red and black pigmentation being controlled by separate loci. We found no evidence of either linkage disequilibrium between loci or sex linkage. In contrast to Batesian mimicry systems such as butterflies in which all color signal components are linked into a single "supergene," our results suggest that the mimetic signal in colubrid snakes can be disrupted through simple recombination and that color evolution is likely to involve discrete gains and losses of each signal component. Both outcomes are likely to contribute to the exponential increase in rates of color evolution seen in snake mimicry systems over insect systems. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Effect of noise in intelligent cellular decision making.

PubMed

Bates, Russell; Blyuss, Oleg; Alsaedi, Ahmed; Zaikin, Alexey

2015-01-01

Similar to intelligent multicellular neural networks controlling human brains, even single cells, surprisingly, are able to make intelligent decisions to classify several external stimuli or to associate them. This happens because of the fact that gene regulatory networks can perform as perceptrons, simple intelligent schemes known from studies on Artificial Intelligence. We study the role of genetic noise in intelligent decision making at the genetic level and show that noise can play a constructive role helping cells to make a proper decision. We show this using the example of a simple genetic classifier able to classify two external stimuli.

Ewing sarcoma: a chronicle of molecular pathogenesis.

PubMed

Kim, Sang Kyum; Park, Yong-Koo

2016-09-01

Sarcomas have traditionally been classified according to their chromosomal alterations regardless of whether they accompany simple or complex genetic changes. Ewing sarcoma, a classic small round cell bone tumor, is a well-known mesenchymal malignancy that results from simple sarcoma-specific genetic alterations. The genetic alterations are translocations between genes of the TET/FET family (TLS/FUS, EWSR1, and TAF15) and genes of the E26 transformation-specific (ETS) family. In this review, we intend to summarize a chronicle of molecular findings of Ewing sarcoma including recent advances and explain resultant molecular pathogenesis. Copyright © 2016 Elsevier Inc. All rights reserved.

Rethinking the dispersal of Homo sapiens out of Africa.

PubMed

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

2015-01-01

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

A hybrid genetic-simulated annealing algorithm for the location-inventory-routing problem considering returns under e-supply chain environment.

PubMed

Li, Yanhui; Guo, Hao; Wang, Lin; Fu, Jing

2013-01-01

Facility location, inventory control, and vehicle routes scheduling are critical and highly related problems in the design of logistics system for e-business. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Many of returned merchandise have no quality defects, which can reenter sales channels just after a simple repackaging process. Focusing on the existing problem in e-commerce logistics system, we formulate a location-inventory-routing problem model with no quality defects returns. To solve this NP-hard problem, an effective hybrid genetic simulated annealing algorithm (HGSAA) is proposed. Results of numerical examples show that HGSAA outperforms GA on computing time, optimal solution, and computing stability. The proposed model is very useful to help managers make the right decisions under e-supply chain environment.

Caenorhabditis elegans in regenerative medicine: a simple model for a complex discipline.

PubMed

Aitlhadj, Layla; Stürzenbaum, Stephen R

2014-06-01

Stem cell research is a major focus of regenerative medicine, which amalgamates diverse disciplines ranging from developmental cell biology to chemical and genetic therapy. Although embryonic stem cells have provided the foundation of stem cell therapy, they offer an in vitro study system that might not provide the best insight into mechanisms and behaviour of cells within living organisms. Caenorhabditis elegans is a well defined model organism with highly conserved cell development and signalling processes that specify cell fate. Its genetic amenability coupled with its chemical screening applicability make the nematode well suited as an in vivo system in which regenerative therapy and stem cell processes can be explored. Here, we describe some of the major advances in stem cell research from the worm's perspective. Copyright © 2014 Elsevier Ltd. All rights reserved.

Genetic architecture of resistance in Daphnia hosts against two species of host-specific parasites.

PubMed

Routtu, J; Ebert, D

2015-02-01

Understanding the genetic architecture of host resistance is key for understanding the evolution of host-parasite interactions. Evolutionary models often assume simple genetics based on few loci and strong epistasis. It is unknown, however, whether these assumptions apply to natural populations. Using a quantitative trait loci (QTL) approach, we explore the genetic architecture of resistance in the crustacean Daphnia magna to two of its natural parasites: the horizontally transmitted bacterium Pasteuria ramosa and the horizontally and vertically transmitted microsporidium Hamiltosporidium tvaerminnensis. These two systems have become models for studies on the evolution of host-parasite interactions. In the QTL panel used here, Daphnia's resistance to P. ramosa is controlled by a single major QTL (which explains 50% of the observed variation). Resistance to H. tvaerminnensis horizontal infections shows a signature of a quantitative trait based in multiple loci with weak epistatic interactions (together explaining 38% variation). Resistance to H. tvaerminnensis vertical infections, however, shows only one QTL (explaining 13.5% variance) that colocalizes with one of the QTLs for horizontal infections. QTLs for resistance to Pasteuria and Hamiltosporidium do not colocalize. We conclude that the genetics of resistance in D. magna are drastically different for these two parasites. Furthermore, we infer that based on these and earlier results, the mechanisms of coevolution differ strongly for the two host-parasite systems. Only the Pasteuria-Daphnia system is expected to follow the negative frequency-dependent selection (Red Queen) model. How coevolution works in the Hamiltosporidium-Daphnia system remains unclear.

Genetic architecture of resistance in Daphnia hosts against two species of host-specific parasites

PubMed Central

Routtu, J; Ebert, D

2015-01-01

Understanding the genetic architecture of host resistance is key for understanding the evolution of host–parasite interactions. Evolutionary models often assume simple genetics based on few loci and strong epistasis. It is unknown, however, whether these assumptions apply to natural populations. Using a quantitative trait loci (QTL) approach, we explore the genetic architecture of resistance in the crustacean Daphnia magna to two of its natural parasites: the horizontally transmitted bacterium Pasteuria ramosa and the horizontally and vertically transmitted microsporidium Hamiltosporidium tvaerminnensis. These two systems have become models for studies on the evolution of host–parasite interactions. In the QTL panel used here, Daphnia's resistance to P. ramosa is controlled by a single major QTL (which explains 50% of the observed variation). Resistance to H. tvaerminnensis horizontal infections shows a signature of a quantitative trait based in multiple loci with weak epistatic interactions (together explaining 38% variation). Resistance to H. tvaerminnensis vertical infections, however, shows only one QTL (explaining 13.5% variance) that colocalizes with one of the QTLs for horizontal infections. QTLs for resistance to Pasteuria and Hamiltosporidium do not colocalize. We conclude that the genetics of resistance in D. magna are drastically different for these two parasites. Furthermore, we infer that based on these and earlier results, the mechanisms of coevolution differ strongly for the two host–parasite systems. Only the Pasteuria–Daphnia system is expected to follow the negative frequency-dependent selection (Red Queen) model. How coevolution works in the Hamiltosporidium–Daphnia system remains unclear. PMID:25335558

An annotated genetic map of loblolly pine based on microsatellite and cDNA markers

Treesearch

Craig S. Echt; Surya Saha; Konstantin V. Krutovsky; Kokulapalan Wimalanathan; John E. Erpelding; Chun Liang; C Dana Nelson

2011-01-01

Previous loblolly pine (Pinus taeda L.) genetic linkage maps have been based on a variety of DNA polymorphisms, such as AFLPs, RAPDs, RFLPs, and ESTPs, but only a few SSRs (simple sequence repeats), also known as simple tandem repeats or microsatellites, have been mapped in P. taeda. The objective of this study was to integrate a large set of SSR markers from a variety...

Evaluation of fire recurrence effect on genetic diversity in maritime pine (Pinus pinaster Ait.) stands using Inter-Simple Sequence Repeat profiles.

PubMed

Lucas-Borja, M E; Ahrazem, O; Candel-Pérez, D; Moya, D; Fonseca, T; Hernández Tecles, E; De Las Heras, J; Gómez-Gómez, L

2016-12-01

The management of maritime pine in fire-prone habitats is a challenging task and fine-scale population genetic analyses are necessary to check if different fire recurrences affect genetic variability. The objective of this study was to assess the effect of fire recurrence on maritime pine genetic diversity using inter-simple sequence repeat markers (ISSR). Three maritime pine (Pinus pinaster Ait.) populations from Northern Portugal were chosen to characterize the genetic variability among populations. In relation to fire recurrence, Seirós population was affected by fire both in 1990 and 2005 whereas Vila Seca-2 population was affected by fire just in 2005. The Vila Seca-1 population has been never affected by fire. Our results showed the highest Nei's genetic diversity (He=0.320), Shannon information index (I=0.474) and polymorphic loci (PPL=87.79%) among samples from twice burned populations (Seirós site). Thus, fire regime plays an important role affecting genetic diversity in the short-term, although not generating maritime pine genetic erosion. Copyright © 2016 Elsevier B.V. All rights reserved.

Long-Distance Dispersal Shaped Patterns of Human Genetic Diversity in Eurasia

PubMed Central

Alves, Isabel; Arenas, Miguel; Currat, Mathias; Sramkova Hanulova, Anna; Sousa, Vitor C.; Ray, Nicolas; Excoffier, Laurent

2016-01-01

Most previous attempts at reconstructing the past history of human populations did not explicitly take geography into account or considered very simple scenarios of migration and ignored environmental information. However, it is likely that the last glacial maximum (LGM) affected the demography and the range of many species, including our own. Moreover, long-distance dispersal (LDD) may have been an important component of human migrations, allowing fast colonization of new territories and preserving high levels of genetic diversity. Here, we use a high-quality microsatellite data set genotyped in 22 populations to estimate the posterior probabilities of several scenarios for the settlement of the Old World by modern humans. We considered models ranging from a simple spatial expansion to others including LDD and a LGM-induced range contraction, as well as Neolithic demographic expansions. We find that scenarios with LDD are much better supported by data than models without LDD. Nevertheless, we show evidence that LDD events to empty habitats were strongly prevented during the settlement of Eurasia. This unexpected absence of LDD ahead of the colonization wave front could have been caused by an Allee effect, either due to intrinsic causes such as an inbreeding depression built during the expansion or due to extrinsic causes such as direct competition with archaic humans. Overall, our results suggest only a relatively limited effect of the LGM contraction on current patterns of human diversity. This is in clear contrast with the major role of LDD migrations, which have potentially contributed to the intermingled genetic structure of Eurasian populations. PMID:26637555

Dog leukocyte antigen class II-associated genetic risk testing for immune disorders of dogs: simplified approaches using Pug dog necrotizing meningoencephalitis as a model.

PubMed

Pedersen, Niels; Liu, Hongwei; Millon, Lee; Greer, Kimberly

2011-01-01

A significantly increased risk for a number of autoimmune and infectious diseases in purebred and mixed-breed dogs has been associated with certain alleles or allele combinations of the dog leukocyte antigen (DLA) class II complex containing the DRB1, DQA1, and DQB1 genes. The exact level of risk depends on the specific disease, the alleles in question, and whether alleles exist in a homozygous or heterozygous state. The gold standard for identifying high-risk alleles and their zygosity has involved direct sequencing of the exon 2 regions of each of the 3 genes. However, sequencing and identification of specific alleles at each of the 3 loci are relatively expensive and sequencing techniques are not ideal for additional parentage or identity determination. However, it is often possible to get the same information from sequencing only 1 gene given the small number of possible alleles at each locus in purebred dogs, extensive homozygosity, and tendency for disease-causing alleles at each of the 3 loci to be strongly linked to each other into haplotypes. Therefore, genetic testing in purebred dogs with immune diseases can be often simplified by sequencing alleles at 1 rather than 3 loci. Further simplification of genetic tests for canine immune diseases can be achieved by the use of alternative genetic markers in the DLA class II region that are also strongly linked with the disease genotype. These markers consist of either simple tandem repeats or single nucleotide polymorphisms that are also in strong linkage with specific DLA class II genotypes and/or haplotypes. The current study uses necrotizing meningoencephalitis of Pug dogs as a paradigm to assess simple alternative genetic tests for disease risk. It was possible to attain identical necrotizing meningoencephalitis risk assessments to 3-locus DLA class II sequencing by sequencing only the DQB1 gene, using 3 DLA class II-linked simple tandem repeat markers, or with a small single nucleotide polymorphism array designed to identify breed-specific DQB1 alleles.

Genetic threshold hypothesis of neocortical spike-and-wave discharges in the rat: An animal model of petit mal epilepsy

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

Vadasz, C.; Fleischer, A.; Carpi, D.

1995-02-27

Neocortical high-voltage spike-and-wave discharges (HVS) in the rat are an animal model of petit mal epilepsy. Genetic analysis of total duration of HVS (s/12 hr) in reciprocal F1 and F2 hybrids of F344 and BN rats indicated that the phenotypic variability of HVS cannot be explained by simple, monogenic Mendelian model. Biometrical analysis suggested the presence of additive, dominance, and sex-linked-epistatic effects, buffering maternal influence, and heterosis. High correlation was observed between average duration (s/episode) and frequency of occurrence of spike-and-wave episodes (n/12 hr) in parental and segregating generations, indicating that common genes affect both duration and frequency of themore » spike-and-wave pattern. We propose that both genetic and developmental - environmental factors control an underlying quantitative variable, which, above a certain threshold level, precipitates HVS discharges. These findings, together with the recent availability of rat DNA markers for total genome mapping, pave the way to the identification of genes that control the susceptibility of the brain to spike-and-wave discharges. 67 refs., 3 figs., 5 tabs.« less

SLiM 2: Flexible, Interactive Forward Genetic Simulations.

PubMed

Haller, Benjamin C; Messer, Philipp W

2017-01-01

Modern population genomic datasets hold immense promise for revealing the evolutionary processes operating in natural populations, but a crucial prerequisite for this goal is the ability to model realistic evolutionary scenarios and predict their expected patterns in genomic data. To that end, we present SLiM 2: an evolutionary simulation framework that combines a powerful, fast engine for forward population genetic simulations with the capability of modeling a wide variety of complex evolutionary scenarios. SLiM achieves this flexibility through scriptability, which provides control over most aspects of the simulated evolutionary scenarios with a simple R-like scripting language called Eidos. An example SLiM simulation is presented to illustrate the power of this approach. SLiM 2 also includes a graphical user interface for simulation construction, interactive runtime control, and dynamic visualization of simulation output, facilitating easy and fast model development with quick prototyping and visual debugging. We conclude with a performance comparison between SLiM and two other popular forward genetic simulation packages. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Drosophila as a genetic and cellular model for studies on axonal growth

PubMed Central

Sánchez-Soriano, Natalia; Tear, Guy; Whitington, Paul; Prokop, Andreas

2007-01-01

One of the most fascinating processes during nervous system development is the establishment of stereotypic neuronal networks. An essential step in this process is the outgrowth and precise navigation (pathfinding) of axons and dendrites towards their synaptic partner cells. This phenomenon was first described more than a century ago and, over the past decades, increasing insights have been gained into the cellular and molecular mechanisms regulating neuronal growth and navigation. Progress in this area has been greatly assisted by the use of simple and genetically tractable invertebrate model systems, such as the fruit fly Drosophila melanogaster. This review is dedicated to Drosophila as a genetic and cellular model to study axonal growth and demonstrates how it can and has been used for this research. We describe the various cellular systems of Drosophila used for such studies, insights into axonal growth cones and their cytoskeletal dynamics, and summarise identified molecular signalling pathways required for growth cone navigation, with particular focus on pathfinding decisions in the ventral nerve cord of Drosophila embryos. These Drosophila-specific aspects are viewed in the general context of our current knowledge about neuronal growth. PMID:17475018

A note on the efficiencies of sampling strategies in two-stage Bayesian regional fine mapping of a quantitative trait.

PubMed

Chen, Zhijian; Craiu, Radu V; Bull, Shelley B

2014-11-01

In focused studies designed to follow up associations detected in a genome-wide association study (GWAS), investigators can proceed to fine-map a genomic region by targeted sequencing or dense genotyping of all variants in the region, aiming to identify a functional sequence variant. For the analysis of a quantitative trait, we consider a Bayesian approach to fine-mapping study design that incorporates stratification according to a promising GWAS tag SNP in the same region. Improved cost-efficiency can be achieved when the fine-mapping phase incorporates a two-stage design, with identification of a smaller set of more promising variants in a subsample taken in stage 1, followed by their evaluation in an independent stage 2 subsample. To avoid the potential negative impact of genetic model misspecification on inference we incorporate genetic model selection based on posterior probabilities for each competing model. Our simulation study shows that, compared to simple random sampling that ignores genetic information from GWAS, tag-SNP-based stratified sample allocation methods reduce the number of variants continuing to stage 2 and are more likely to promote the functional sequence variant into confirmation studies. © 2014 WILEY PERIODICALS, INC.

Concepts in solid tumor evolution.

PubMed

Sidow, Arend; Spies, Noah

2015-04-01

Evolutionary mechanisms in cancer progression give tumors their individuality. Cancer evolution is different from organismal evolution, however, and we discuss where concepts from evolutionary genetics are useful or limited in facilitating an understanding of cancer. Based on these concepts we construct and apply the simplest plausible model of tumor growth and progression. Simulations using this simple model illustrate the importance of stochastic events early in tumorigenesis, highlight the dominance of exponential growth over linear growth and differentiation, and explain the clonal substructure of tumors. Copyright © 2015 Elsevier Ltd. All rights reserved.

Landscape genetics of leaf-toed geckos in the tropical dry forest of northern Mexico.

PubMed

Blair, Christopher; Jiménez Arcos, Victor H; Mendez de la Cruz, Fausto R; Murphy, Robert W

2013-01-01

Habitat fragmentation due to both natural and anthropogenic forces continues to threaten the evolution and maintenance of biological diversity. This is of particular concern in tropical regions that are experiencing elevated rates of habitat loss. Although less well-studied than tropical rain forests, tropical dry forests (TDF) contain an enormous diversity of species and continue to be threatened by anthropogenic activities including grazing and agriculture. However, little is known about the processes that shape genetic connectivity in species inhabiting TDF ecosystems. We adopt a landscape genetic approach to understanding functional connectivity for leaf-toed geckos (Phyllodactylus tuberculosus) at multiple sites near the northernmost limit of this ecosystem at Alamos, Sonora, Mexico. Traditional analyses of population genetics are combined with multivariate GIS-based landscape analyses to test hypotheses on the potential drivers of spatial genetic variation. Moderate levels of within-population diversity and substantial levels of population differentiation are revealed by FST and Dest. Analyses using structure suggest the occurrence of from 2 to 9 genetic clusters depending on the model used. Landscape genetic analysis suggests that forest cover, stream connectivity, undisturbed habitat, slope, and minimum temperature of the coldest period explain more genetic variation than do simple Euclidean distances. Additional landscape genetic studies throughout TDF habitat are required to understand species-specific responses to landscape and climate change and to identify common drivers. We urge researchers interested in using multivariate distance methods to test for, and report, significant correlations among predictor matrices that can impact results, particularly when adopting least-cost path approaches. Further investigation into the use of information theoretic approaches for model selection is also warranted.

A Constrained Genetic Algorithm with Adaptively Defined Fitness Function in MRS Quantification

NASA Astrophysics Data System (ADS)

Papakostas, G. A.; Karras, D. A.; Mertzios, B. G.; Graveron-Demilly, D.; van Ormondt, D.

MRS Signal quantification is a rather involved procedure and has attracted the interest of the medical engineering community, regarding the development of computationally efficient methodologies. Significant contributions based on Computational Intelligence tools, such as Neural Networks (NNs), demonstrated a good performance but not without drawbacks already discussed by the authors. On the other hand preliminary application of Genetic Algorithms (GA) has already been reported in the literature by the authors regarding the peak detection problem encountered in MRS quantification using the Voigt line shape model. This paper investigates a novel constrained genetic algorithm involving a generic and adaptively defined fitness function which extends the simple genetic algorithm methodology in case of noisy signals. The applicability of this new algorithm is scrutinized through experimentation in artificial MRS signals interleaved with noise, regarding its signal fitting capabilities. Although extensive experiments with real world MRS signals are necessary, the herein shown performance illustrates the method's potential to be established as a generic MRS metabolites quantification procedure.

A Conceptual Framework for Pharmacodynamic Genome-wide Association Studies in Pharmacogenomics

PubMed Central

Wu, Rongling; Tong, Chunfa; Wang, Zhong; Mauger, David; Tantisira, Kelan; Szefler, Stanley J.; Chinchilli, Vernon M.; Israel, Elliot

2013-01-01

Summary Genome-wide association studies (GWAS) have emerged as a powerful tool to identify loci that affect drug response or susceptibility to adverse drug reactions. However, current GWAS based on a simple analysis of associations between genotype and phenotype ignores the biochemical reactions of drug response, thus limiting the scope of inference about its genetic architecture. To facilitate the inference of GWAS in pharmacogenomics, we sought to undertake the mathematical integration of the pharmacodynamic process of drug reactions through computational models. By estimating and testing the genetic control of pharmacodynamic and pharmacokinetic parameters, this mechanistic approach does not only enhance the biological and clinical relevance of significant genetic associations, but also improve the statistical power and robustness of gene detection. This report discusses the general principle and development of pharmacodynamics-based GWAS, highlights the practical use of this approach in addressing various pharmacogenomic problems, and suggests that this approach will be an important method to study the genetic architecture of drug responses or reactions. PMID:21920452

Adventures in hepatocarcinogenesis.

PubMed

Pitot, Henry C

2007-01-01

Neoplasia is a heritably altered, relatively autonomous growth of tissue. Hepatocarcinogenesis, the pathogenesis of neoplasia in liver, as modeled in the rat exhibits three distinct, quantifiable stages: initiation, promotion, and progression. Simple mutations and/or epigenetic alterations may result in the irreversible stage of initiation. The stage of promotion results from selective enhancement of cell replication and selective inhibition of cellular apoptosis of initiated cells dependent on the genetic and/or epigenetic alterations of the latter. The irreversible stage of progression results from initial karyotypic alterations that evolve into greater degrees of genomic instability. The initial genomic alteration in the transition from promotion to progression may involve primarily epigenetic mechanisms driven by epigenetic and genetic alterations fixed during the stage of promotion.

Development of Genomic Simple Sequence Repeats (SSR) by Enrichment Libraries in Date Palm.

PubMed

Al-Faifi, Sulieman A; Migdadi, Hussein M; Algamdi, Salem S; Khan, Mohammad Altaf; Al-Obeed, Rashid S; Ammar, Megahed H; Jakse, Jerenj

2017-01-01

Development of highly informative markers such as simple sequence repeats (SSR) for cultivar identification and germplasm characterization and management is essential for date palms genetic studies. The present study documents the development of SSR markers and assesses genetic relationships of commonly grown date palm (Phoenix dactylifera L.) cultivars in different geographical regions of Saudi Arabia. A total of 93 novel simple sequence repeat (SSR) markers were screened for their ability to detect polymorphism in date palm. Around 71% of genomic SSRs are dinucleotide, 25% trinucleotide, 3% tetranucleotide, and 1% pentanucleotide motives and show 100% polymorphism. The Unweighted Pair Group Method with Arithmetic Mean (UPGMA) cluster analysis illustrates that cultivars trend to group according to their class of maturity, region of cultivation, and fruit color. Analysis of molecular variations (AMOVA) reveals genetic variation among and within cultivars of 27% and 73%, respectively, according to the geographical distribution of the cultivars. Developed microsatellite markers are of additional value to date palm characterization, tools which can be used by researchers in population genetics, cultivar identification, as well as genetic resource exploration and management. The cultivars tested exhibited a significant amount of genetic diversity and could be suitable for successful breeding programs. Genomic sequences generated from this study are available at the National Center for Biotechnology Information (NCBI), Sequence Read Archive (Accession numbers. LIBGSS_039019).

Population structure in Japanese rice population

PubMed Central

Yamasaki, Masanori; Ideta, Osamu

2013-01-01

It is essential to elucidate genetic diversity and relationships among even related individuals and populations for plant breeding and genetic analysis. Since Japanese rice breeding has improved agronomic traits such as yield and eating quality, modern Japanese rice cultivars originated from narrow genetic resource and closely related. To resolve the population structure and genetic diversity in Japanese rice population, we used a total of 706 alleles detected by 134 simple sequence repeat markers in a total of 114 cultivars composed of 94 improved varieties and 20 landraces, which are representative and important for Japanese rice breeding. The landraces exhibit greater gene diversity than improved lines, suggesting that landraces can provide additional genetic diversity for future breeding. Model-based Bayesian clustering analysis revealed six subgroups and admixture situation in the cultivars, showing good agreement with pedigree information. This method could be superior to phylogenetic method in classifying a related population. The leading Japanese rice cultivar, Koshihikari is unique due to the specific genome constitution. We defined Japanese rice diverse sets that capture the maximum number of alleles for given sample sizes. These sets are useful for a variety of genetic application in Japanese rice cultivars. PMID:23641181

Genetic biasing through cultural transmission: do simple Bayesian models of language evolution generalize?

PubMed

Dediu, Dan

2009-08-07

The recent Bayesian approaches to language evolution and change seem to suggest that genetic biases can impact on the characteristics of language, but, at the same time, that its cultural transmission can partially free it from these same genetic constraints. One of the current debates centres on the striking differences between sampling and a posteriori maximising Bayesian learners, with the first converging on the prior bias while the latter allows a certain freedom to language evolution. The present paper shows that this difference disappears if populations more complex than a single teacher and a single learner are considered, with the resulting behaviours more similar to the sampler. This suggests that generalisations based on the language produced by Bayesian agents in such homogeneous single agent chains are not warranted. It is not clear which of the assumptions in such models are responsible, but these findings seem to support the rising concerns on the validity of the "acquisitionist" assumption, whereby the locus of language change and evolution is taken to be the first language acquirers (children) as opposed to the competent language users (the adults).

Using genetically modified tomato crop plants with purple leaves for absolute weed/crop classification.

PubMed

Lati, Ran N; Filin, Sagi; Aly, Radi; Lande, Tal; Levin, Ilan; Eizenberg, Hanan

2014-07-01

Weed/crop classification is considered the main problem in developing precise weed-management methodologies, because both crops and weeds share similar hues. Great effort has been invested in the development of classification models, most based on expensive sensors and complicated algorithms. However, satisfactory results are not consistently obtained due to imaging conditions in the field. We report on an innovative approach that combines advances in genetic engineering and robust image-processing methods to detect weeds and distinguish them from crop plants by manipulating the crop's leaf color. We demonstrate this on genetically modified tomato (germplasm AN-113) which expresses a purple leaf color. An autonomous weed/crop classification is performed using an invariant-hue transformation that is applied to images acquired by a standard consumer camera (visible wavelength) and handles variations in illumination intensities. The integration of these methodologies is simple and effective, and classification results were accurate and stable under a wide range of imaging conditions. Using this approach, we simplify the most complicated stage in image-based weed/crop classification models. © 2013 Society of Chemical Industry.

Environmental isolation explains Iberian genetic diversity in the highly homozygous model grass Brachypodium distachyon.

PubMed

Marques, Isabel; Shiposha, Valeriia; López-Alvarez, Diana; Manzaneda, Antonio J; Hernandez, Pilar; Olonova, Marina; Catalán, Pilar

2017-06-15

Brachypodium distachyon (Poaceae), an annual Mediterranean Aluminum (Al)-sensitive grass, is currently being used as a model species to provide new information on cereals and biofuel crops. The plant has a short life cycle and one of the smallest genomes in the grasses being well suited to experimental manipulation. Its genome has been fully sequenced and several genomic resources are being developed to elucidate key traits and gene functions. A reliable germplasm collection that reflects the natural diversity of this species is therefore needed for all these genomic resources. However, despite being a model plant, we still know very little about its genetic diversity. As a first step to overcome this gap, we used nuclear Simple Sequence Repeats (nSSR) to study the patterns of genetic diversity and population structure of B. distachyon in 14 populations sampled across the Iberian Peninsula (Spain), one of its best known areas. We found very low levels of genetic diversity, allelic number and heterozygosity in B. distachyon, congruent with a highly selfing system. Our results indicate the existence of at least three genetic clusters providing additional evidence for the existence of a significant genetic structure in the Iberian Peninsula and supporting this geographical area as an important genetic reservoir. Several hotspots of genetic diversity were detected and populations growing on basic soils were significantly more diverse than those growing in acidic soils. A partial Mantel test confirmed a statistically significant Isolation-By-Distance (IBD) among all studied populations, as well as a statistically significant Isolation-By-Environment (IBE) revealing the presence of environmental-driven isolation as one explanation for the genetic patterns found in the Iberian Peninsula. The finding of higher genetic diversity in eastern Iberian populations occurring in basic soils suggests that these populations can be better adapted than those occurring in western areas of the Iberian Peninsula where the soils are more acidic and accumulate toxic Al ions. This suggests that the western Iberian acidic soils might prevent the establishment of Al-sensitive B. distachyon populations, potentially causing the existence of more genetically depauperated individuals.

Preliminary Groundwater Simulations To Compare Different Reconstruction Methods of 3-d Alluvial Heterogeneity

NASA Astrophysics Data System (ADS)

Teles, V.; de Marsily, G.; Delay, F.; Perrier, E.

Alluvial floodplains are extremely heterogeneous aquifers, whose three-dimensional structures are quite difficult to model. In general, when representing such structures, the medium heterogeneity is modeled with classical geostatistical or Boolean meth- ods. Another approach, still in its infancy, is called the genetic method because it simulates the generation of the medium by reproducing sedimentary processes. We developed a new genetic model to obtain a realistic three-dimensional image of allu- vial media. It does not simulate the hydrodynamics of sedimentation but uses semi- empirical and statistical rules to roughly reproduce fluvial deposition and erosion. The main processes, either at the stream scale or at the plain scale, are modeled by simple rules applied to "sediment" entities or to conceptual "erosion" entities. The model was applied to a several kilometer long portion of the Aube River floodplain (France) and reproduced the deposition and erosion cycles that occurred during the inferred climate periods (15 000 BP to present). A three-dimensional image of the aquifer was gener- ated, by extrapolating the two-dimensional information collected on a cross-section of the floodplain. Unlike geostatistical methods, this extrapolation does not use a statis- tical spatial analysis of the data, but a genetic analysis, which leads to a more realistic structure. Groundwater flow and transport simulations in the alluvium were carried out with a three-dimensional flow code or simulator (MODFLOW), using different rep- resentations of the alluvial reservoir of the Aube River floodplain: first an equivalent homogeneous medium, and then different heterogeneous media built either with the traditional geostatistical approach simulating the permeability distribution, or with the new genetic model presented here simulating sediment facies. In the latter case, each deposited entity of a given lithology was assigned a constant hydraulic conductivity value. Results of these models have been compared to assess the value of the genetic approach and will be presented.

GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures.

PubMed

Urbanowicz, Ryan J; Kiralis, Jeff; Sinnott-Armstrong, Nicholas A; Heberling, Tamra; Fisher, Jonathan M; Moore, Jason H

2012-10-01

Geneticists who look beyond single locus disease associations require additional strategies for the detection of complex multi-locus effects. Epistasis, a multi-locus masking effect, presents a particular challenge, and has been the target of bioinformatic development. Thorough evaluation of new algorithms calls for simulation studies in which known disease models are sought. To date, the best methods for generating simulated multi-locus epistatic models rely on genetic algorithms. However, such methods are computationally expensive, difficult to adapt to multiple objectives, and unlikely to yield models with a precise form of epistasis which we refer to as pure and strict. Purely and strictly epistatic models constitute the worst-case in terms of detecting disease associations, since such associations may only be observed if all n-loci are included in the disease model. This makes them an attractive gold standard for simulation studies considering complex multi-locus effects. We introduce GAMETES, a user-friendly software package and algorithm which generates complex biallelic single nucleotide polymorphism (SNP) disease models for simulation studies. GAMETES rapidly and precisely generates random, pure, strict n-locus models with specified genetic constraints. These constraints include heritability, minor allele frequencies of the SNPs, and population prevalence. GAMETES also includes a simple dataset simulation strategy which may be utilized to rapidly generate an archive of simulated datasets for given genetic models. We highlight the utility and limitations of GAMETES with an example simulation study using MDR, an algorithm designed to detect epistasis. GAMETES is a fast, flexible, and precise tool for generating complex n-locus models with random architectures. While GAMETES has a limited ability to generate models with higher heritabilities, it is proficient at generating the lower heritability models typically used in simulation studies evaluating new algorithms. In addition, the GAMETES modeling strategy may be flexibly combined with any dataset simulation strategy. Beyond dataset simulation, GAMETES could be employed to pursue theoretical characterization of genetic models and epistasis.

A simple bias correction in linear regression for quantitative trait association under two-tail extreme selection.

PubMed

Kwan, Johnny S H; Kung, Annie W C; Sham, Pak C

2011-09-01

Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias.

Association mapping unveils favorable alleles for grain iron and zinc concentrations in lentil (Lens culinaris subsp. culinaris)

PubMed Central

Singh, Akanksha; Sharma, Vinay; Dikshit, Harsh Kumar; Aski, Muraleedhar; Kumar, Harish; Thirunavukkarasu, Nepolean; Patil, Basavanagouda S.; Kumar, Shiv; Sarker, Ashutosh

2017-01-01

Lentil is a major cool-season grain legume grown in South Asia, West Asia, and North Africa. Populations in developing countries of these regions have micronutrient deficiencies; therefore, breeding programs should focus more on improving the micronutrient content of food. In the present study, a set of 96 diverse germplasm lines were evaluated at three different locations in India to examine the variation in iron (Fe) and zinc (Zn) concentration and identify simple sequence repeat (SSR) markers that associate with the genetic variation. The genetic variation among genotypes of the association mapping (AM) panel was characterized using a genetic distance-based and a general model-based clustering method. The model-based analysis identified six subpopulations, which satisfactorily explained the genetic structure of the AM panel. AM analysis identified three SSRs (PBALC 13, PBALC 206, and GLLC 563) associated with grain Fe concentration explaining 9% to 11% of phenotypic variation and four SSRs (PBALC 353, SSR 317–1, PLC 62, and PBALC 217) were associated with grain Zn concentration explaining 14%, to 21% of phenotypic variation. These identified SSRs exhibited consistent performance across locations. These candidate SSRs can be used in marker-assisted genetic improvement for developing Fe and Zn fortified lentil varieties. Favorable alleles and promising genotypes identified in this study can be utilized for lentil biofortification. PMID:29161321

[The mechanism of root hair development and molecular regulation in plants].

PubMed

Wang, Yue-Ping; Li, Ying-Hui; Guan, Rong-Xia; Liu, Zhang-Xiong; Chen, Xiong-Ting; Chang, Ru-Zhen; Qiu, Li-Juan

2007-04-01

The formation of the root epidermis in Arabidopsis thaliana provides a simple model to study mechanisms underlying patterning in plants. Root hair increases the root surface area and effectively increases the root diameter, so root hair is thought to aid plants in nutrient uptake, anchorage and microbe interactions. The determination of root hair development has two types, lateral inhibition with feedback and position-dependent pattern of cell differentiation. The initiation and development of root hair in Arabidopsis provide a simple and efficacious model for the study of cell fate determination in plants. Molecular genetic studies identify a suite of putative transcription factors which regulate the epidermal cell pattern. The homeodomain protein GLABRA2 (GL2), R2R3 MYB-type transcription factor WEREWOLF (WER) and WD-repeat protein TRANSPARENTT TESTA GLABRA (TTG) are required for specification of non-hair cell type. The CAPRICE (CPC) and TRYPTICHON (TRY) are involved in specifying the hair cell fate.

Distinguishing genetics and eugenics on the basis of fairness.

PubMed Central

Ledley, F D

1994-01-01

There is concern that human applications of modern genetic technologies may lead inexorably to eugenic abuse. To prevent such abuse, it is essential to have clear, formal principles as well as algorithms for distinguishing genetics from eugenics. This work identifies essential distinctions between eugenics and genetics in the implied nature of the social contract and the importance ascribed to individual welfare relative to society. Rawls's construction of 'justice as fairness' is used as a model for how a formal systems of ethics can be used to proscribe eugenic practices. Rawls's synthesis can be applied to this problem if it is assumed that in the original condition all individuals are ignorant of their genetic constitution and unwilling to consent to social structures which may constrain their own potential. The principles of fairness applied to genetics requires that genetic interventions be directed at extending individual liberties and be applied to the greatest benefit of individuals with the least advantages. These principles are incompatible with negative eugenics which would further penalize those with genetic disadvantage. These principles limit positive eugenics to those practices which are designed to provide absolute benefit to those individuals with least advantage, are acceptable to its subjects, and further a system of basic equal liberties. This analysis also illustrates how simple deviations from first principles in Rawls's formulation could countenance eugenic applications of genetic technologies. PMID:7996561

Genetic and environmental influences on last-year major depression in adulthood: a highly heritable stable liability but strong environmental effects on 1-year prevalence.

PubMed

Kendler, K S; Gardner, C O

2017-07-01

This study seeks to clarify the contribution of temporally stable and occasion-specific genetic and environmental influences on risk for major depression (MD). Our sample was 2153 members of female-female twin pairs from the Virginia Twin Registry. We examined four personal interview waves conducted over an 8-year period with MD in the last year defined by DSM-IV criteria. We fitted a structural equation model to the data using classic Mx. The model included genetic and environmental risk factors for a latent, stable vulnerability to MD and for episodes in each of the four waves. The best-fit model was simple and included genetic and unique environmental influences on the latent liability to MD and unique wave-specific environmental effects. The path from latent liability to MD in the last year was constant over time, moderate in magnitude (+0.65) and weaker than the impact of occasion-specific environmental effects (+0.76). Heritability of the latent stable liability to MD was much higher (78%) than that estimated for last-year MD (32%). Of the total unique environmental influences on MD, 13% reflected enduring consequences of earlier environmental insults, 17% diagnostic error and 70% wave-specific short-lived environmental stressors. Both genetic influences on MD and MD heritability are stable over middle adulthood. However, the largest influence on last-year MD is short-lived environmental effects. As predicted by genetic theory, the heritability of MD is increased substantially by measurement at multiple time points largely through the reduction of the effects of measurement error and short-term environmental risk factors.

A Population Genetic Signal of Polygenic Adaptation

PubMed Central

Berg, Jeremy J.; Coop, Graham

2014-01-01

Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed knowledge about the specific loci underlying polygenic traits has begun to emerge from genome-wide association studies (GWAS). Here we combine this knowledge from GWAS with robust population genetic modeling to identify traits that may have been influenced by local adaptation. We exploit the fact that GWAS provide an estimate of the additive effect size of many loci to estimate the mean additive genetic value for a given phenotype across many populations as simple weighted sums of allele frequencies. We use a general model of neutral genetic value drift for an arbitrary number of populations with an arbitrary relatedness structure. Based on this model, we develop methods for detecting unusually strong correlations between genetic values and specific environmental variables, as well as a generalization of comparisons to test for over-dispersion of genetic values among populations. Finally we lay out a framework to identify the individual populations or groups of populations that contribute to the signal of overdispersion. These tests have considerably greater power than their single locus equivalents due to the fact that they look for positive covariance between like effect alleles, and also significantly outperform methods that do not account for population structure. We apply our tests to the Human Genome Diversity Panel (HGDP) dataset using GWAS data for height, skin pigmentation, type 2 diabetes, body mass index, and two inflammatory bowel disease datasets. This analysis uncovers a number of putative signals of local adaptation, and we discuss the biological interpretation and caveats of these results. PMID:25102153

Improving Robot Locomotion Through Learning Methods for Expensive Black-Box Systems

DTIC Science & Technology

2013-11-01

development of a class of “gradient free” optimization techniques; these include local approaches, such as a Nelder- Mead simplex search (c.f. [73]), and global...1Note that this simple method differs from the Nelder Mead constrained nonlinear optimization method [73]. 39 the Non-dominated Sorting Genetic Algorithm...Kober, and Jan Peters. Model-free inverse reinforcement learning. In International Conference on Artificial Intelligence and Statistics, 2011. [12] George

Synthetic Botany.

PubMed

Boehm, Christian R; Pollak, Bernardo; Purswani, Nuri; Patron, Nicola; Haseloff, Jim

2017-07-05

Plants are attractive platforms for synthetic biology and metabolic engineering. Plants' modular and plastic body plans, capacity for photosynthesis, extensive secondary metabolism, and agronomic systems for large-scale production make them ideal targets for genetic reprogramming. However, efforts in this area have been constrained by slow growth, long life cycles, the requirement for specialized facilities, a paucity of efficient tools for genetic manipulation, and the complexity of multicellularity. There is a need for better experimental and theoretical frameworks to understand the way genetic networks, cellular populations, and tissue-wide physical processes interact at different scales. We highlight new approaches to the DNA-based manipulation of plants and the use of advanced quantitative imaging techniques in simple plant models such as Marchantia polymorpha. These offer the prospects of improved understanding of plant dynamics and new approaches to rational engineering of plant traits. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

Sensory Transduction in Caenorhabditis elegans

NASA Astrophysics Data System (ADS)

Brown, Austin L.; Ramot, Daniel; Goodman, Miriam B.

The roundworm Caenorhabditis elegans has a well-defined and comparatively simple repertoire of sensory-guided behaviors, all of which rely on its ability to detect chemical, mechanical or thermal stimuli. In this chapter, we review what is known about the ion channels that mediate sensation in this remarkable model organism. Genetic screens for mutants defective in sensory-guided behaviors have identified genes encoding channel proteins, which are likely transducers of chemical, thermal, and mechanical stimuli. Such classical genetic approaches are now being coupled with molecular genetics and in vivo cellular physiology to elucidate how these channels are activated in specific sensory neurons. The ion channel superfamilies implicated in sensory transduction in C. elegans - CNG, TRP, and DEG/ENaC - are conserved across phyla and also appear to contribute to sensory transduction in other organisms, including vertebrates. What we learn about the role of these ion channels in C. elegans sensation is likely to illuminate analogous processes in other animals, including humans.

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

Szymanski, J. J.; Brumby, Steven P.; Pope, P. A.

Feature extration from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. The tool used is the GENetic Imagery Exploitation (GENIE) software, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniquesmore » to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land-cover features including towns, grasslands, wild fire burn scars, and several types of forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.« less

A climate-associated multispecies cryptic cline in the northwest Atlantic

PubMed Central

DiBacco, Claudio; Lowen, Ben; Beiko, Robert G.; Bentzen, Paul; Brickman, David; Johnson, Catherine; Wang, Zeliang; Wringe, Brendan F.; Bradbury, Ian R.

2018-01-01

The spatial genetic structure of most species in the open marine environment remains largely unresolved. This information gap creates uncertainty in the sustainable management, recovery, and associated resilience of marine communities and our capacity to extrapolate beyond the few species for which such information exists. We document a previously unidentified multispecies biogeographic break aligned with a steep climatic gradient and driven by seasonal temperature minima in the northwest Atlantic. The coherence of this genetic break across our five study species with contrasting life histories suggests a pervasive macroecological phenomenon. The integration of this genetic structure with habitat suitability models and climate forecasts predicts significant variation in northward distributional shifts among populations and availability of suitable habitat in future oceans. The results of our integrated approach provide new perspective on how cryptic intraspecific diversity associated with climatic variation influences species and community response to climate change beyond simple poleward shifts. PMID:29600272

A Hybrid Genetic-Simulated Annealing Algorithm for the Location-Inventory-Routing Problem Considering Returns under E-Supply Chain Environment

PubMed Central

Guo, Hao; Fu, Jing

2013-01-01

Facility location, inventory control, and vehicle routes scheduling are critical and highly related problems in the design of logistics system for e-business. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Many of returned merchandise have no quality defects, which can reenter sales channels just after a simple repackaging process. Focusing on the existing problem in e-commerce logistics system, we formulate a location-inventory-routing problem model with no quality defects returns. To solve this NP-hard problem, an effective hybrid genetic simulated annealing algorithm (HGSAA) is proposed. Results of numerical examples show that HGSAA outperforms GA on computing time, optimal solution, and computing stability. The proposed model is very useful to help managers make the right decisions under e-supply chain environment. PMID:24489489

Engineering a Functional Small RNA Negative Autoregulation Network with Model-Guided Design.

PubMed

Hu, Chelsea Y; Takahashi, Melissa K; Zhang, Yan; Lucks, Julius B

2018-05-22

RNA regulators are powerful components of the synthetic biology toolbox. Here, we expand the repertoire of synthetic gene networks built from these regulators by constructing a transcriptional negative autoregulation (NAR) network out of small RNAs (sRNAs). NAR network motifs are core motifs of natural genetic networks, and are known for reducing network response time and steady state signal. Here we use cell-free transcription-translation (TX-TL) reactions and a computational model to design and prototype sRNA NAR constructs. Using parameter sensitivity analysis, we design a simple set of experiments that allow us to accurately predict NAR function in TX-TL. We transfer successful network designs into Escherichia coli and show that our sRNA transcriptional network reduces both network response time and steady-state gene expression. This work broadens our ability to construct increasingly sophisticated RNA genetic networks with predictable function.

Morphological analysis of Drosophila larval peripheral sensory neuron dendrites and axons using genetic mosaics.

PubMed

Karim, M Rezaul; Moore, Adrian W

2011-11-07

Nervous system development requires the correct specification of neuron position and identity, followed by accurate neuron class-specific dendritic development and axonal wiring. Recently the dendritic arborization (DA) sensory neurons of the Drosophila larval peripheral nervous system (PNS) have become powerful genetic models in which to elucidate both general and class-specific mechanisms of neuron differentiation. There are four main DA neuron classes (I-IV)(1). They are named in order of increasing dendrite arbor complexity, and have class-specific differences in the genetic control of their differentiation(2-10). The DA sensory system is a practical model to investigate the molecular mechanisms behind the control of dendritic morphology(11-13) because: 1) it can take advantage of the powerful genetic tools available in the fruit fly, 2) the DA neuron dendrite arbor spreads out in only 2 dimensions beneath an optically clear larval cuticle making it easy to visualize with high resolution in vivo, 3) the class-specific diversity in dendritic morphology facilitates a comparative analysis to find key elements controlling the formation of simple vs. highly branched dendritic trees, and 4) dendritic arbor stereotypical shapes of different DA neurons facilitate morphometric statistical analyses. DA neuron activity modifies the output of a larval locomotion central pattern generator(14-16). The different DA neuron classes have distinct sensory modalities, and their activation elicits different behavioral responses(14,16-20). Furthermore different classes send axonal projections stereotypically into the Drosophila larval central nervous system in the ventral nerve cord (VNC)(21). These projections terminate with topographic representations of both DA neuron sensory modality and the position in the body wall of the dendritic field(7,22,23). Hence examination of DA axonal projections can be used to elucidate mechanisms underlying topographic mapping(7,22,23), as well as the wiring of a simple circuit modulating larval locomotion(14-17). We present here a practical guide to generate and analyze genetic mosaics(24) marking DA neurons via MARCM (Mosaic Analysis with a Repressible Cell Marker)(1,10,25) and Flp-out(22,26,27) techniques (summarized in Fig. 1).

Model of head-neck joint fast movements in the frontal plane.

PubMed

Pedrocchi, A; Ferrigno, G

2004-06-01

The objective of this work is to develop a model representing the physiological systems driving fast head movements in frontal plane. All the contributions occurring mechanically in the head movement are considered: damping, stiffness, physiological limit of range of motion, gravitational field, and muscular torques due to voluntary activation as well as to stretch reflex depending on fusal afferences. Model parameters are partly derived from the literature, when possible, whereas undetermined block parameters are determined by optimising the model output, fitting to real kinematics data acquired by a motion capture system in specific experimental set-ups. The optimisation for parameter identification is performed by genetic algorithms. Results show that the model represents very well fast head movements in the whole range of inclination in the frontal plane. Such a model could be proposed as a tool for transforming kinematics data on head movements in 'neural equivalent data', especially for assessing head control disease and properly planning the rehabilitation process. In addition, the use of genetic algorithms seems to fit well the problem of parameter identification, allowing for the use of a very simple experimental set-up and granting model robustness.

The Pathogenesis of Nonalcoholic Fatty Liver Disease: Interplay between Diet, Gut Microbiota, and Genetic Background

PubMed Central

Marsh, Sharon; Hu, Junbo; Feng, Wenke

2016-01-01

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in the world, and it comprises a spectrum of hepatic abnormalities from simple hepatic steatosis to steatohepatitis, fibrosis, cirrhosis, and liver cancer. While the pathogenesis of NAFLD remains incompletely understood, a multihit model has been proposed that accommodates causal factors from a variety of sources, including intestinal and adipose proinflammatory stimuli acting on the liver simultaneously. Prior cellular and molecular studies of patient and animal models have characterized several common pathogenic mechanisms of NAFLD, including proinflammation cytokines, lipotoxicity, oxidative stress, and endoplasmic reticulum stress. In recent years, gut microbiota has gained much attention, and dysbiosis is recognized as a crucial factor in NAFLD. Moreover, several genetic variants have been identified through genome-wide association studies, particularly rs738409 (Ile748Met) in PNPLA3 and rs58542926 (Glu167Lys) in TM6SF2, which are critical risk alleles of the disease. Although a high-fat diet and inactive lifestyles are typical risk factors for NAFLD, the interplay between diet, gut microbiota, and genetic background is believed to be more important in the development and progression of NAFLD. This review summarizes the common pathogenic mechanisms, the gut microbiota relevant mechanisms, and the major genetic variants leading to NAFLD and its progression. PMID:27247565

Conceptualizing genetic counseling as psychotherapy in the era of genomic medicine.

PubMed

Austin, Jehannine; Semaka, Alicia; Hadjipavlou, George

2014-12-01

Discussions about genetic contributions to medical illness have become increasingly commonplace. Physicians and other health-care providers in all quarters of medicine, from oncology to psychiatry, routinely field questions about the genetic basis of the medical conditions they treat. Communication about genetic testing and risk also enter into these conversations, as knowledge about genetics is increasingly expected of all medical specialists. Attendant to this evolving medical landscape is some uncertainty regarding the future of the genetic counseling profession, with the potential for both increases and decreases in demand for genetic counselors being possible outcomes. This emerging uncertainty provides the opportunity to explicitly conceptualize the potentially distinct value and contributions of the genetic counselor over and above education about genetics and risk that may be provided by other health professionals. In this paper we suggest conceptualizing genetic counseling as a highly circumscribed form of psychotherapy in which effective communication of genetic information is a central therapeutic goal. While such an approach is by no means new--in 1979 Seymour Kessler explicitly described genetic counseling as a "kind of psychotherapeutic encounter," an "interaction with a psychotherapeutic potential"--we expand on his view, and provide research evidence in support of our position. We review available evidence from process and outcome studies showing that genetic counseling is a therapeutic encounter that cannot be reduced to one where the counselor performs a simple "conduit for information" function, without losing effectiveness. We then discuss potential barriers that may have impeded greater uptake of a psychotherapeutic model of practice, and close by discussing implications for practice.

Conceptualizing genetic counseling as psychotherapy in the era of genomic medicine

PubMed Central

Austin, Jehannine; Semaka, Alicia; Hadjipavlou, George

2014-01-01

Discussions about genetic contributions to medical illness have become increasingly commonplace. Physicians and other health-care providers in all quarters of medicine, from oncology to psychiatry, routinely field questions about the genetic basis of the medical conditions they treat. Communication about genetic testing and risk also enter into these conversations, as knowledge about genetics is increasingly expected of all medical specialists. Attendant to this evolving medical landscape is some uncertainty regarding the future of the genetic counseling profession, with the potential for both increases and decreases in demand for genetic counselors being possible outcomes. This emerging uncertainty provides the opportunity to explicitly conceptualize the potentially distinct value and contributions of the genetic counselor over and above education about genetics and risk that may be provided by other health professionals. In this paper we suggest conceptualizing genetic counseling as a highly circumscribed form of psychotherapy in which effective communication of genetic information is a central therapeutic goal. While such an approach is by no means new—in 1979 Seymour Kessler explicitly described genetic counseling as a “kind of psychotherapeutic encounter,” an “interaction with a psychotherapeutic potential”—we expand on his view, and provide research evidence in support of our position. We review available evidence from process and outcome studies showing that genetic counseling is a therapeutic encounter that cannot be reduced to one where the counselor performs a simple “conduit for information” function, without losing effectiveness. We then discuss potential barriers that may have impeded greater uptake of a psychotherapeutic model of practice, and close by discussing implications for practice. PMID:24841456

Disease induction by human microbial pathogens in plant-model systems: potential, problems and prospects.

PubMed

van Baarlen, Peter; van Belkum, Alex; Thomma, Bart P H J

2007-02-01

Relatively simple eukaryotic model organisms such as the genetic model weed plant Arabidopsis thaliana possess an innate immune system that shares important similarities with its mammalian counterpart. In fact, some human pathogens infect Arabidopsis and cause overt disease with human symptomology. In such cases, decisive elements of the plant's immune system are likely to be targeted by the same microbial factors that are necessary for causing disease in humans. These similarities can be exploited to identify elementary microbial pathogenicity factors and their corresponding targets in a green host. This circumvents important cost aspects that often frustrate studies in humans or animal models and, in addition, results in facile ethical clearance.

Exact solution of a model DNA-inversion genetic switch with orientational control.

PubMed

Visco, Paolo; Allen, Rosalind J; Evans, Martin R

2008-09-12

DNA inversion is an important mechanism by which bacteria and bacteriophage switch reversibly between phenotypic states. In such switches, the orientation of a short DNA element is flipped by a site-specific recombinase enzyme. We propose a simple model for a DNA-inversion switch in which recombinase production is dependent on the switch state (orientational control). Our model is inspired by the fim switch in E. coli. We present an exact analytical solution of the chemical master equation for the model switch, as well as stochastic simulations. Orientational control causes the switch to deviate from Poissonian behavior: the distribution of times in the on state shows a peak and successive flip times are correlated.

Long-Distance Dispersal Shaped Patterns of Human Genetic Diversity in Eurasia.

PubMed

Alves, Isabel; Arenas, Miguel; Currat, Mathias; Sramkova Hanulova, Anna; Sousa, Vitor C; Ray, Nicolas; Excoffier, Laurent

2016-04-01

Most previous attempts at reconstructing the past history of human populations did not explicitly take geography into account or considered very simple scenarios of migration and ignored environmental information. However, it is likely that the last glacial maximum (LGM) affected the demography and the range of many species, including our own. Moreover, long-distance dispersal (LDD) may have been an important component of human migrations, allowing fast colonization of new territories and preserving high levels of genetic diversity. Here, we use a high-quality microsatellite data set genotyped in 22 populations to estimate the posterior probabilities of several scenarios for the settlement of the Old World by modern humans. We considered models ranging from a simple spatial expansion to others including LDD and a LGM-induced range contraction, as well as Neolithic demographic expansions. We find that scenarios with LDD are much better supported by data than models without LDD. Nevertheless, we show evidence that LDD events to empty habitats were strongly prevented during the settlement of Eurasia. This unexpected absence of LDD ahead of the colonization wave front could have been caused by an Allee effect, either due to intrinsic causes such as an inbreeding depression built during the expansion or due to extrinsic causes such as direct competition with archaic humans. Overall, our results suggest only a relatively limited effect of the LGM contraction on current patterns of human diversity. This is in clear contrast with the major role of LDD migrations, which have potentially contributed to the intermingled genetic structure of Eurasian populations. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Neutral null models for diversity in serial transfer evolution experiments.

PubMed

Harpak, Arbel; Sella, Guy

2014-09-01

Evolution experiments with microorganisms coupled with genome-wide sequencing now allow for the systematic study of population genetic processes under a wide range of conditions. In learning about these processes in natural, sexual populations, neutral models that describe the behavior of diversity and divergence summaries have played a pivotal role. It is therefore natural to ask whether neutral models, suitably modified, could be useful in the context of evolution experiments. Here, we introduce coalescent models for polymorphism and divergence under the most common experimental evolution assay, a serial transfer experiment. This relatively simple setting allows us to address several issues that could affect diversity patterns in evolution experiments, whether selection is operating or not: the transient behavior of neutral polymorphism in an experiment beginning from a single clone, the effects of randomness in the timing of cell division and noisiness in population size in the dilution stage. In our analyses and discussion, we emphasize the implications for experiments aimed at measuring diversity patterns and making inferences about population genetic processes based on these measurements. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Assimilating concentration observations for transport and dispersion modeling in a meandering wind field

NASA Astrophysics Data System (ADS)

Haupt, Sue Ellen; Beyer-Lout, Anke; Long, Kerrie J.; Young, George S.

Assimilating concentration data into an atmospheric transport and dispersion model can provide information to improve downwind concentration forecasts. The forecast model is typically a one-way coupled set of equations: the meteorological equations impact the concentration, but the concentration does not generally affect the meteorological field. Thus, indirect methods of using concentration data to influence the meteorological variables are required. The problem studied here involves a simple wind field forcing Gaussian dispersion. Two methods of assimilating concentration data to infer the wind direction are demonstrated. The first method is Lagrangian in nature and treats the puff as an entity using feature extraction coupled with nudging. The second method is an Eulerian field approach akin to traditional variational approaches, but minimizes the error by using a genetic algorithm (GA) to directly optimize the match between observations and predictions. Both methods show success at inferring the wind field. The GA-variational method, however, is more accurate but requires more computational time. Dynamic assimilation of a continuous release modeled by a Gaussian plume is also demonstrated using the genetic algorithm approach.

Identification of important image features for pork and turkey ham classification using colour and wavelet texture features and genetic selection.

PubMed

Jackman, Patrick; Sun, Da-Wen; Allen, Paul; Valous, Nektarios A; Mendoza, Fernando; Ward, Paddy

2010-04-01

A method to discriminate between various grades of pork and turkey ham was developed using colour and wavelet texture features. Image analysis methods originally developed for predicting the palatability of beef were applied to rapidly identify the ham grade. With high quality digital images of 50-94 slices per ham it was possible to identify the greyscale that best expressed the differences between the various ham grades. The best 10 discriminating image features were then found with a genetic algorithm. Using the best 10 image features, simple linear discriminant analysis models produced 100% correct classifications for both pork and turkey on both calibration and validation sets. 2009 Elsevier Ltd. All rights reserved.

Optimization of the ANFIS using a genetic algorithm for physical work rate classification.

PubMed

Habibi, Ehsanollah; Salehi, Mina; Yadegarfar, Ghasem; Taheri, Ali

2018-03-13

Recently, a new method was proposed for physical work rate classification based on an adaptive neuro-fuzzy inference system (ANFIS). This study aims to present a genetic algorithm (GA)-optimized ANFIS model for a highly accurate classification of physical work rate. Thirty healthy men participated in this study. Directly measured heart rate and oxygen consumption of the participants in the laboratory were used for training the ANFIS classifier model in MATLAB version 8.0.0 using a hybrid algorithm. A similar process was done using the GA as an optimization technique. The accuracy, sensitivity and specificity of the ANFIS classifier model were increased successfully. The mean accuracy of the model was increased from 92.95 to 97.92%. Also, the calculated root mean square error of the model was reduced from 5.4186 to 3.1882. The maximum estimation error of the optimized ANFIS during the network testing process was ± 5%. The GA can be effectively used for ANFIS optimization and leads to an accurate classification of physical work rate. In addition to high accuracy, simple implementation and inter-individual variability consideration are two other advantages of the presented model.

The MAM rodent model of schizophrenia

PubMed Central

Lodge, Daniel J.

2013-01-01

Rodent models of human disease are essential to obtain a better understanding of disease pathology, the mechanism of action underlying conventional treatments, as well as for the generation of novel therapeutic approaches. There are a number of rodent models of schizophrenia based on either genetic manipulations, acute or sub-chronic drug administration, or developmental disturbances. The prenatal methylazoxymethanol acetate (MAM) rodent model is a developmental disruption model gaining increased attention because it displays a number of histological, neurophysiological and behavioral deficits analogous to those observed in schizophrenia patients. This unit describes the procedures required to safely induce the MAM phenotype in rats. In addition, we describe a simple behavioral procedure, amphetamine-induced hyper-locomotion, which can be utilized to verify the MAM phenotype. PMID:23559309

Inter-Simple Sequence Repeat Data Reveals High Genetic Diversity in Wild Populations of the Narrowly Distributed Endemic Lilium regale in the Minjiang River Valley of China

PubMed Central

Wu, Zhu-hua; Shi, Jisen; Xi, Meng-li; Jiang, Fu-xing; Deng, Ming-wen; Dayanandan, Selvadurai

2015-01-01

Lilium regale E.H. Wilson is endemic to a narrow geographic area in the Minjiang River valley in southwestern China, and is considered an important germplasm for breeding commercially valuable lily varieties, due to its vigorous growth, resistance to diseases and tolerance for low moisture. We analyzed the genetic diversity of eight populations of L. regale sampled across the entire natural distribution range of the species using Inter-Simple Sequence Repeat markers. The genetic diversity (expected heterozygosity= 0.3356) was higher than those reported for other narrowly distributed endemic plants. The levels of inbreeding (F st = 0.1897) were low, and most of the genetic variability was found to be within (80.91%) than amongpopulations (19.09%). An indirect estimate of historical levels of gene flow (N m =1.0678) indicated high levels of gene flow among populations. The eight analyzed populations clustered into three genetically distinct groups. Based on these results, we recommend conservation of large populations representing these three genetically distinct groups. PMID:25799495

Discovery and mapping of a new expressed sequence tag-single nucleotide polymorphism and simple sequence repeat panel for large-scale genetic studies and breeding of Theobroma cacao L.

PubMed Central

Allegre, Mathilde; Argout, Xavier; Boccara, Michel; Fouet, Olivier; Roguet, Yolande; Bérard, Aurélie; Thévenin, Jean Marc; Chauveau, Aurélie; Rivallan, Ronan; Clement, Didier; Courtois, Brigitte; Gramacho, Karina; Boland-Augé, Anne; Tahi, Mathias; Umaharan, Pathmanathan; Brunel, Dominique; Lanaud, Claire

2012-01-01

Theobroma cacao is an economically important tree of several tropical countries. Its genetic improvement is essential to provide protection against major diseases and improve chocolate quality. We discovered and mapped new expressed sequence tag-single nucleotide polymorphism (EST-SNP) and simple sequence repeat (SSR) markers and constructed a high-density genetic map. By screening 149 650 ESTs, 5246 SNPs were detected in silico, of which 1536 corresponded to genes with a putative function, while 851 had a clear polymorphic pattern across a collection of genetic resources. In addition, 409 new SSR markers were detected on the Criollo genome. Lastly, 681 new EST-SNPs and 163 new SSRs were added to the pre-existing 418 co-dominant markers to construct a large consensus genetic map. This high-density map and the set of new genetic markers identified in this study are a milestone in cocoa genomics and for marker-assisted breeding. The data are available at http://tropgenedb.cirad.fr. PMID:22210604

tropiTree: An NGS-Based EST-SSR Resource for 24 Tropical Tree Species

PubMed Central

Russell, Joanne R.; Hedley, Peter E.; Cardle, Linda; Dancey, Siobhan; Morris, Jenny; Booth, Allan; Odee, David; Mwaura, Lucy; Omondi, William; Angaine, Peter; Machua, Joseph; Muchugi, Alice; Milne, Iain; Kindt, Roeland; Jamnadass, Ramni; Dawson, Ian K.

2014-01-01

The development of genetic tools for non-model organisms has been hampered by cost, but advances in next-generation sequencing (NGS) have created new opportunities. In ecological research, this raises the prospect for developing molecular markers to simultaneously study important genetic processes such as gene flow in multiple non-model plant species within complex natural and anthropogenic landscapes. Here, we report the use of bar-coded multiplexed paired-end Illumina NGS for the de novo development of expressed sequence tag-derived simple sequence repeat (EST-SSR) markers at low cost for a range of 24 tree species. Each chosen tree species is important in complex tropical agroforestry systems where little is currently known about many genetic processes. An average of more than 5,000 EST-SSRs was identified for each of the 24 sequenced species, whereas prior to analysis 20 of the species had fewer than 100 nucleotide sequence citations. To make results available to potential users in a suitable format, we have developed an open-access, interactive online database, tropiTree (http://bioinf.hutton.ac.uk/tropiTree), which has a range of visualisation and search facilities, and which is a model for the efficient presentation and application of NGS data. PMID:25025376

Stochastic noncooperative and cooperative evolutionary game strategies of a population of biological networks under natural selection.

PubMed

Chen, Bor-Sen; Yeh, Chin-Hsun

2017-12-01

We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.

Setaria viridis: A Model for C4 Photosynthesis[C][W

PubMed Central

Brutnell, Thomas P.; Wang, Lin; Swartwood, Kerry; Goldschmidt, Alexander; Jackson, David; Zhu, Xin-Guang; Kellogg, Elizabeth; Van Eck, Joyce

2010-01-01

C4 photosynthesis drives productivity in several major food crops and bioenergy grasses, including maize (Zea mays), sugarcane (Saccharum officinarum), sorghum (Sorghum bicolor), Miscanthus x giganteus, and switchgrass (Panicum virgatum). Gains in productivity associated with C4 photosynthesis include improved water and nitrogen use efficiencies. Thus, engineering C4 traits into C3 crops is an attractive target for crop improvement. However, the lack of a small, rapid cycling genetic model system to study C4 photosynthesis has limited progress in dissecting the regulatory networks underlying the C4 syndrome. Setaria viridis is a member of the Panicoideae clade and is a close relative of several major feed, fuel, and bioenergy grasses. It is a true diploid with a relatively small genome of ~510 Mb. Its short stature, simple growth requirements, and rapid life cycle will greatly facilitate genetic studies of the C4 grasses. Importantly, S. viridis uses an NADP-malic enzyme subtype C4 photosynthetic system to fix carbon and therefore is a potentially powerful model system for dissecting C4 photosynthesis. Here, we summarize some of the recent advances that promise greatly to accelerate the use of S. viridis as a genetic system. These include our recent successful efforts at regenerating plants from seed callus, establishing a transient transformation system, and developing stable transformation. PMID:20693355

Vertebrate sex-determining genes play musical chairs

PubMed Central

Pan, Qiaowei; Anderson, Jennifer; Bertho, Sylvain; Herpin, Amaury; Wilson, Catherine; Postlethwait, John H.; Schartl, Manfred; Guiguen, Yann

2017-01-01

Sexual reproduction is one of the most highly conserved processes in evolution. However, the genetic and cellular mechanisms making the decision of whether the undifferentiated gonad of animal embryos develops either towards male or female are manifold and quite diverse. In vertebrates, sex-determining mechanisms range from environmental to simple or complex genetic mechanisms and different mechanisms have evolved repeatedly and independently. In species with simple genetic sex-determination, master sex-determining genes lying on sex chromosomes drive the gonadal differentiation process by switching on a developmental program, which ultimately leads to testicular or ovarian differentiation. So far, very few sex-determining genes have been identified in vertebrates and apart from mammals and birds, these genes are apparently not conserved over a larger number of related orders, families, genera, or even species. To fill this knowledge gap and to better explore genetic sex-determination, we propose a strategy (RAD-Sex) that makes use of next-generation sequencing technology to identify genetic markers that define sex-specific segments of the male or female genome. PMID:27291506

Genetic diversity studies and identification of SSR markers associated with Fusarium wilt (Fusarium udum) resistance in cultivated pigeonpea (Cajanus cajan).

PubMed

Singh, A K; Rai, V P; Chand, R; Singh, R P; Singh, M N

2013-01-01

Genetic diversity and identification of simple sequence repeat markers correlated with Fusarium wilt resistance was performed in a set of 36 elite cultivated pigeonpea genotypes differing in levels of resistance to Fusarium wilt. Twenty-four polymorphic sequence repeat markers were screened across these genotypes, and amplified a total of 59 alleles with an average high polymorphic information content value of 0.52. Cluster analysis, done by UPGMA and PCA, grouped the 36 pigeonpea genotypes into two main clusters according to their Fusarium wilt reaction. Based on the Kruskal-Wallis ANOVA and simple regression analysis, six simple sequence repeat markers were found to be significantly associated with Fusarium wilt resistance. The phenotypic variation explained by these markers ranged from 23.7 to 56.4%. The present study helps in finding out feasibility of prescreened SSR markers to be used in genetic diversity analysis and their potential association with disease resistance.

Geography and end use drive the diversification of worldwide winter rye populations.

PubMed

Parat, Florence; Schwertfirm, Grit; Rudolph, Ulrike; Miedaner, Thomas; Korzun, Viktor; Bauer, Eva; Schön, Chris-Carolin; Tellier, Aurélien

2016-01-01

To meet the current challenges in human food production, improved understanding of the genetic diversity of crop species that maximizes the selection efficacy in breeding programs is needed. The present study offers new insights into the diversity, genetic structure and demographic history of cultivated rye (Secale cereale L.). We genotyped 620 individuals from 14 global rye populations with a different end use (grain or forage) at 32 genome-wide simple sequence repeat markers. We reveal the relationships among these populations, their sizes and the timing of domestication events using population genetics and model-based inference with approximate Bayesian computation. Our main results demonstrate (i) a high within-population variation and genetic diversity, (ii) an unexpected absence of reduction in diversity with an increasing improvement level and (iii) patterns suggestive of multiple domestication events. We suggest that the main drivers of diversification of winter rye are the end use of rye in two early regions of cultivation: rye forage in the Mediterranean area and grain in northeast Europe. The lower diversity and stronger differentiation of eastern European populations were most likely due to more intensive cultivation and breeding of rye in this region, in contrast to the Mediterranean region where it was considered a secondary crop or even a weed. We discuss the relevance of our results for the management of gene bank resources and the pitfalls of inference methods applied to crop domestication due to violation of model assumptions and model complexity. © 2015 John Wiley & Sons Ltd.

Rooted tRNAomes and evolution of the genetic code

PubMed Central

Pak, Daewoo; Du, Nan; Kim, Yunsoo; Sun, Yanni

2018-01-01

ABSTRACT We advocate for a tRNA- rather than an mRNA-centric model for evolution of the genetic code. The mechanism for evolution of cloverleaf tRNA provides a root sequence for radiation of tRNAs and suggests a simplified understanding of code evolution. To analyze code sectoring, rooted tRNAomes were compared for several archaeal and one bacterial species. Rooting of tRNAome trees reveals conserved structures, indicating how the code was shaped during evolution and suggesting a model for evolution of a LUCA tRNAome tree. We propose the polyglycine hypothesis that the initial product of the genetic code may have been short chain polyglycine to stabilize protocells. In order to describe how anticodons were allotted in evolution, the sectoring-degeneracy hypothesis is proposed. Based on sectoring, a simple stepwise model is developed, in which the code sectors from a 1→4→8→∼16 letter code. At initial stages of code evolution, we posit strong positive selection for wobble base ambiguity, supporting convergence to 4-codon sectors and ∼16 letters. In a later stage, ∼5–6 letters, including stops, were added through innovating at the anticodon wobble position. In archaea and bacteria, tRNA wobble adenine is negatively selected, shrinking the maximum size of the primordial genetic code to 48 anticodons. Because 64 codons are recognized in mRNA, tRNA-mRNA coevolution requires tRNA wobble position ambiguity leading to degeneracy of the code. PMID:29372672

Strategies, models and biomarkers in experimental non-alcoholic fatty liver disease research

PubMed Central

Willebrords, Joost; Pereira, Isabel Veloso Alves; Maes, Michaël; Yanguas, Sara Crespo; Colle, Isabelle; Van Den Bossche, Bert; Da silva, Tereza Cristina; Oliveira, Cláudia P; Andraus, Wellington; Alves, Venâncio Avancini Ferreira; Cogliati, Bruno; Vinken, Mathieu

2015-01-01

Non-alcoholic fatty liver disease encompasses a spectrum of liver diseases, including simple steatosis, steatohepatitis, liver fibrosis and cirrhosis and hepatocellular carcinoma. Non-alcoholic fatty liver disease is currently the most dominant chronic liver disease in Western countries due to the fact that hepatic steatosis is associated with insulin resistance, type 2 diabetes mellitus, obesity, metabolic syndrome and drug-induced injury. A variety of chemicals, mainly drugs, and diets is known to cause hepatic steatosis in humans and rodents. Experimental non-alcoholic fatty liver disease models rely on the application of a diet or the administration of drugs to laboratory animals or the exposure of hepatic cell lines to these drugs. More recently, genetically modified rodents or zebrafish have been introduced as non-alcoholic fatty liver disease models. Considerable interest now lies in the discovery and development of novel non-invasive biomarkers of non-alcoholic fatty liver disease, with specific focus on hepatic steatosis. Experimental diagnostic biomarkers of non-alcoholic fatty liver disease, such as (epi)genetic parameters and ‘-omics’-based read-outs are still in their infancy, but show great promise. . In this paper, the array of tools and models for the study of liver steatosis is discussed. Furthermore, the current state-of-art regarding experimental biomarkers such as epigenetic, genetic, transcriptomic, proteomic and metabonomic biomarkers will be reviewed. PMID:26073454

Oceanography promotes self-recruitment in a planktonic larval disperser.

PubMed

Teske, Peter R; Sandoval-Castillo, Jonathan; van Sebille, Erik; Waters, Jonathan; Beheregaray, Luciano B

2016-09-30

The application of high-resolution genetic data has revealed that oceanographic connectivity in marine species with planktonic larvae can be surprisingly limited, even in the absence of major barriers to dispersal. Australia's southern coast represents a particularly interesting system for studying planktonic larval dispersal, as the hydrodynamic regime of the wide continental shelf has potential to facilitate onshore retention of larvae. We used a seascape genetics approach (the joint analysis of genetic data and oceanographic connectivity simulations) to assess population genetic structure and self-recruitment in a broadcast-spawning marine gastropod that exists as a single meta-population throughout its temperate Australian range. Levels of self-recruitment were surprisingly high, and oceanographic connectivity simulations indicated that this was a result of low-velocity nearshore currents promoting the retention of planktonic larvae in the vicinity of natal sites. Even though the model applied here is comparatively simple and assumes that the dispersal of planktonic larvae is passive, we find that oceanography alone is sufficient to explain the high levels of genetic structure and self-recruitment. Our study contributes to growing evidence that sophisticated larval behaviour is not a prerequisite for larval retention in the nearshore region in planktonic-developing species.

Efficient CRISPR/Cas9-assisted gene targeting enables rapid and precise genetic manipulation of mammalian neural stem cells

PubMed Central

Bressan, Raul Bardini; Dewari, Pooran Singh; Kalantzaki, Maria; Gangoso, Ester; Matjusaitis, Mantas; Garcia-Diaz, Claudia; Blin, Carla; Grant, Vivien; Bulstrode, Harry; Gogolok, Sabine; Skarnes, William C.

2017-01-01

Mammalian neural stem cell (NSC) lines provide a tractable model for discovery across stem cell and developmental biology, regenerative medicine and neuroscience. They can be derived from foetal or adult germinal tissues and continuously propagated in vitro as adherent monolayers. NSCs are clonally expandable, genetically stable, and easily transfectable – experimental attributes compatible with targeted genetic manipulations. However, gene targeting, which is crucial for functional studies of embryonic stem cells, has not been exploited to date in NSC lines. Here, we deploy CRISPR/Cas9 technology to demonstrate a variety of sophisticated genetic modifications via gene targeting in both mouse and human NSC lines, including: (1) efficient targeted transgene insertion at safe harbour loci (Rosa26 and AAVS1); (2) biallelic knockout of neurodevelopmental transcription factor genes; (3) simple knock-in of epitope tags and fluorescent reporters (e.g. Sox2-V5 and Sox2-mCherry); and (4) engineering of glioma mutations (TP53 deletion; H3F3A point mutations). These resources and optimised methods enable facile and scalable genome editing in mammalian NSCs, providing significant new opportunities for functional genetic analysis. PMID:28096221

CRISPR-Cas9: a promising genetic engineering approach in cancer research.

PubMed

Ratan, Zubair Ahmed; Son, Young-Jin; Haidere, Mohammad Faisal; Uddin, Bhuiyan Mohammad Mahtab; Yusuf, Md Abdullah; Zaman, Sojib Bin; Kim, Jong-Hoon; Banu, Laila Anjuman; Cho, Jae Youl

2018-01-01

Bacteria and archaea possess adaptive immunity against foreign genetic materials through clustered regularly interspaced short palindromic repeat (CRISPR) systems. The discovery of this intriguing bacterial system heralded a revolutionary change in the field of medical science. The CRISPR and CRISPR-associated protein 9 (Cas9) based molecular mechanism has been applied to genome editing. This CRISPR-Cas9 technique is now able to mediate precise genetic corrections or disruptions in in vitro and in vivo environments. The accuracy and versatility of CRISPR-Cas have been capitalized upon in biological and medical research and bring new hope to cancer research. Cancer involves complex alterations and multiple mutations, translocations and chromosomal losses and gains. The ability to identify and correct such mutations is an important goal in cancer treatment. In the context of this complex cancer genomic landscape, there is a need for a simple and flexible genetic tool that can easily identify functional cancer driver genes within a comparatively short time. The CRISPR-Cas system shows promising potential for modeling, repairing and correcting genetic events in different types of cancer. This article reviews the concept of CRISPR-Cas, its application and related advantages in oncology.

Genetic value of herd life adjusted for milk production.

PubMed

Allaire, F R; Gibson, J P

1992-05-01

Cow herd life adjusted for lactational milk production was investigated as a genetic trait in the breeding objective. Under a simple model, the relative economic weight of milk to adjusted herd life on a per genetic standard deviation basis was equal to CVY/dCVL where CVY and CVL are the genetic coefficients of variation of milk production and adjusted herd life, respectively, and d is the depreciation per year per cow divided by the total fixed costs per year per cow. The relative economic value of milk to adjusted herd life at the prices and parameters for North America was about 3.2. An increase of 100-kg milk was equivalent to 2.2 mo of adjusted herd life. Three to 7% lower economic gain is expected when only improved milk production is sought compared with a breeding objective that included both production and adjusted herd life for relative value changed +/- 20%. A favorable economic gain to cost ratio probably exists for herd life used as a genetic trait to supplement milk in the breeding objective. Cow survival records are inexpensive, and herd life evaluations from such records may not extend the generation interval when such an evaluation is used in bull sire selection.

GA(M)E-QSAR: a novel, fully automatic genetic-algorithm-(meta)-ensembles approach for binary classification in ligand-based drug design.

PubMed

Pérez-Castillo, Yunierkis; Lazar, Cosmin; Taminau, Jonatan; Froeyen, Mathy; Cabrera-Pérez, Miguel Ángel; Nowé, Ann

2012-09-24

Computer-aided drug design has become an important component of the drug discovery process. Despite the advances in this field, there is not a unique modeling approach that can be successfully applied to solve the whole range of problems faced during QSAR modeling. Feature selection and ensemble modeling are active areas of research in ligand-based drug design. Here we introduce the GA(M)E-QSAR algorithm that combines the search and optimization capabilities of Genetic Algorithms with the simplicity of the Adaboost ensemble-based classification algorithm to solve binary classification problems. We also explore the usefulness of Meta-Ensembles trained with Adaboost and Voting schemes to further improve the accuracy, generalization, and robustness of the optimal Adaboost Single Ensemble derived from the Genetic Algorithm optimization. We evaluated the performance of our algorithm using five data sets from the literature and found that it is capable of yielding similar or better classification results to what has been reported for these data sets with a higher enrichment of active compounds relative to the whole actives subset when only the most active chemicals are considered. More important, we compared our methodology with state of the art feature selection and classification approaches and found that it can provide highly accurate, robust, and generalizable models. In the case of the Adaboost Ensembles derived from the Genetic Algorithm search, the final models are quite simple since they consist of a weighted sum of the output of single feature classifiers. Furthermore, the Adaboost scores can be used as ranking criterion to prioritize chemicals for synthesis and biological evaluation after virtual screening experiments.

From Heuristic to Mathematical Modeling of Drugs Dissolution Profiles: Application of Artificial Neural Networks and Genetic Programming

PubMed Central

Mendyk, Aleksander; Güres, Sinan; Szlęk, Jakub; Wiśniowska, Barbara; Kleinebudde, Peter

2015-01-01

The purpose of this work was to develop a mathematical model of the drug dissolution (Q) from the solid lipid extrudates based on the empirical approach. Artificial neural networks (ANNs) and genetic programming (GP) tools were used. Sensitivity analysis of ANNs provided reduction of the original input vector. GP allowed creation of the mathematical equation in two major approaches: (1) direct modeling of Q versus extrudate diameter (d) and the time variable (t) and (2) indirect modeling through Weibull equation. ANNs provided also information about minimum achievable generalization error and the way to enhance the original dataset used for adjustment of the equations' parameters. Two inputs were found important for the drug dissolution: d and t. The extrudates length (L) was found not important. Both GP modeling approaches allowed creation of relatively simple equations with their predictive performance comparable to the ANNs (root mean squared error (RMSE) from 2.19 to 2.33). The direct mode of GP modeling of Q versus d and t resulted in the most robust model. The idea of how to combine ANNs and GP in order to escape ANNs' black-box drawback without losing their superior predictive performance was demonstrated. Open Source software was used to deliver the state-of-the-art models and modeling strategies. PMID:26101544

Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model

PubMed Central

Nené, Nuno R.; Dunham, Alistair S.; Illingworth, Christopher J. R.

2018-01-01

A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the nondeterministic properties of mutation in a finite population. We propose an alternative approach that acts to correct for this error, and which we denote the delay-deterministic model. Applying our model to a simple evolutionary system, we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model. PMID:29500183

From Heuristic to Mathematical Modeling of Drugs Dissolution Profiles: Application of Artificial Neural Networks and Genetic Programming.

PubMed

Mendyk, Aleksander; Güres, Sinan; Jachowicz, Renata; Szlęk, Jakub; Polak, Sebastian; Wiśniowska, Barbara; Kleinebudde, Peter

2015-01-01

The purpose of this work was to develop a mathematical model of the drug dissolution (Q) from the solid lipid extrudates based on the empirical approach. Artificial neural networks (ANNs) and genetic programming (GP) tools were used. Sensitivity analysis of ANNs provided reduction of the original input vector. GP allowed creation of the mathematical equation in two major approaches: (1) direct modeling of Q versus extrudate diameter (d) and the time variable (t) and (2) indirect modeling through Weibull equation. ANNs provided also information about minimum achievable generalization error and the way to enhance the original dataset used for adjustment of the equations' parameters. Two inputs were found important for the drug dissolution: d and t. The extrudates length (L) was found not important. Both GP modeling approaches allowed creation of relatively simple equations with their predictive performance comparable to the ANNs (root mean squared error (RMSE) from 2.19 to 2.33). The direct mode of GP modeling of Q versus d and t resulted in the most robust model. The idea of how to combine ANNs and GP in order to escape ANNs' black-box drawback without losing their superior predictive performance was demonstrated. Open Source software was used to deliver the state-of-the-art models and modeling strategies.

A genetic-algorithm approach for assessing the liquefaction potential of sandy soils

NASA Astrophysics Data System (ADS)

Sen, G.; Akyol, E.

2010-04-01

The determination of liquefaction potential is required to take into account a large number of parameters, which creates a complex nonlinear structure of the liquefaction phenomenon. The conventional methods rely on simple statistical and empirical relations or charts. However, they cannot characterise these complexities. Genetic algorithms are suited to solve these types of problems. A genetic algorithm-based model has been developed to determine the liquefaction potential by confirming Cone Penetration Test datasets derived from case studies of sandy soils. Software has been developed that uses genetic algorithms for the parameter selection and assessment of liquefaction potential. Then several estimation functions for the assessment of a Liquefaction Index have been generated from the dataset. The generated Liquefaction Index estimation functions were evaluated by assessing the training and test data. The suggested formulation estimates the liquefaction occurrence with significant accuracy. Besides, the parametric study on the liquefaction index curves shows a good relation with the physical behaviour. The total number of misestimated cases was only 7.8% for the proposed method, which is quite low when compared to another commonly used method.

Measuring Visual Literacy Skills on Students’ Concept Understanding of Genetic Transfer Material

NASA Astrophysics Data System (ADS)

Fibriana, F.; Pamelasari, S. D.; Aulia, L. S.

2017-04-01

Visualization is an important skill for all students majoring in natural sciences. Also, the visual literacy skills (VLS) are essential for Microbiology learning. The lecturer can use the external representations (ERs) to visualize the microorganisms and its microenvironment. One of learning materials which are rather difficult to interpret in microbiology is genetic transfer. In this study, we measure the VLS on students’ concept understanding of genetic transfer material using a simple test. The tests were held before and after the lecture on this topic employing a combination of talking drawing with picture and picture model. The results show that in the beginning, students showed their poor visual literacy. After the lecture, students were able to draw their understanding on the genetic transfer in bacteria. Most students’ visual literacy ability improves in the level of acceptable. In conclusion, the students’ ability was improved in the average amount of conceptual knowledge. This result reveals that some students comprehend in the correct level of ability, meaning that they have a high degree of conceptual (propositional) and visual knowledge.

Genetic diversity in the interference selection limit.

PubMed

Good, Benjamin H; Walczak, Aleksandra M; Neher, Richard A; Desai, Michael M

2014-03-01

Pervasive natural selection can strongly influence observed patterns of genetic variation, but these effects remain poorly understood when multiple selected variants segregate in nearby regions of the genome. Classical population genetics fails to account for interference between linked mutations, which grows increasingly severe as the density of selected polymorphisms increases. Here, we describe a simple limit that emerges when interference is common, in which the fitness effects of individual mutations play a relatively minor role. Instead, similar to models of quantitative genetics, molecular evolution is determined by the variance in fitness within the population, defined over an effectively asexual segment of the genome (a "linkage block"). We exploit this insensitivity in a new "coarse-grained" coalescent framework, which approximates the effects of many weakly selected mutations with a smaller number of strongly selected mutations that create the same variance in fitness. This approximation generates accurate and efficient predictions for silent site variability when interference is common. However, these results suggest that there is reduced power to resolve individual selection pressures when interference is sufficiently widespread, since a broad range of parameters possess nearly identical patterns of silent site variability.

Demographic and genetic consequences of disturbed sex determination.

PubMed

Wedekind, Claus

2017-09-19

During sex determination, genetic and/or environmental factors determine the cascade of processes of gonad development. Many organisms, therefore, have a developmental window in which their sex determination can be sensitive to, for example, unusual temperatures or chemical pollutants. Disturbed environments can distort population sex ratios and may even cause sex reversal in species with genetic sex determination. The resulting genotype-phenotype mismatches can have long-lasting effects on population demography and genetics. I review the theoretical and empirical work in this context and explore in a simple population model the role of the fitness v yy of chromosomally aberrant YY genotypes that are a consequence of environmentally induced feminization. Low v yy is mostly beneficial for population growth. During feminization, low v yy reduces the proportion of genetic males and hence accelerates population growth, especially at low rates of feminization and at high fitness costs of the feminization itself (i.e. when feminization would otherwise not affect population dynamics much). When sex reversal ceases, low v yy mitigates the negative effects of feminization and can even prevent population extinction. Little is known about v yy in natural populations. The available models now need to be parametrized in order to better predict the long-term consequences of disturbed sex determination.This article is part of the themed issue 'Adult sex ratios and reproductive decisions: a critical re-examination of sex differences in human and animal societies'. © 2017 The Author(s).

Geographical parthenogenesis and population genetic structure in the alpine species Ranunculus kuepferi (Ranunculaceae).

PubMed

Cosendai, A-C; Wagner, J; Ladinig, U; Rosche, C; Hörandl, E

2013-06-01

Geographical parthenogenesis describes the enigmatic phenomenon that asexual organisms have larger distribution areas than their sexual relatives, especially in previously glaciated areas. Classical models suggest temporary advantages to asexuality in colonization scenarios because of uniparental reproduction and clonality. We analyzed population genetic structure and self-fertility of the plant species Ranunculus kuepferi on 59 populations from the whole distribution area (European Alps, Apennines and Corsica). Amplified fragment length polymorphisms (AFLPs) and five microsatellite loci revealed individual genotypes for all populations and mostly insignificant differences between diploid sexuals and tetraploid apomicts in all measures of genetic diversity. Low frequencies of private AFLP fragments/simple sequence repeat alleles, and character incompatibility analyses suggest that facultative recombination explains best the unexpectedly high genotypic diversity of apomicts. STRUCTURE analyses using AFLPs revealed a higher number of partitions and a stronger geographical subdivision for diploids than for tetraploids, which contradicts expectations of standard gene flow models, but indicates a reduction of genetic structure in asexuals. Apomictic populations exhibited high admixture near the sexual area, but appeared rather uniform in remote areas. Bagging experiments and analyses of pollen tube growth confirmed self-fertility for pollen-dependent apomicts, but self-sterility for diploid sexuals. Facultative apomixis combines advantages of both modes of reproduction: uniparental reproduction allows for rapid colonization of remote areas, whereas facultative sexuality and polyploidy maintains genetic diversity within apomictic populations. The density dependence of outcrossing limits range expansions of sexual populations.

Geographical parthenogenesis and population genetic structure in the alpine species Ranunculus kuepferi (Ranunculaceae)

PubMed Central

Cosendai, A-C; Wagner, J; Ladinig, U; Rosche, C; Hörandl, E

2013-01-01

Geographical parthenogenesis describes the enigmatic phenomenon that asexual organisms have larger distribution areas than their sexual relatives, especially in previously glaciated areas. Classical models suggest temporary advantages to asexuality in colonization scenarios because of uniparental reproduction and clonality. We analyzed population genetic structure and self-fertility of the plant species Ranunculus kuepferi on 59 populations from the whole distribution area (European Alps, Apennines and Corsica). Amplified fragment length polymorphisms (AFLPs) and five microsatellite loci revealed individual genotypes for all populations and mostly insignificant differences between diploid sexuals and tetraploid apomicts in all measures of genetic diversity. Low frequencies of private AFLP fragments/simple sequence repeat alleles, and character incompatibility analyses suggest that facultative recombination explains best the unexpectedly high genotypic diversity of apomicts. STRUCTURE analyses using AFLPs revealed a higher number of partitions and a stronger geographical subdivision for diploids than for tetraploids, which contradicts expectations of standard gene flow models, but indicates a reduction of genetic structure in asexuals. Apomictic populations exhibited high admixture near the sexual area, but appeared rather uniform in remote areas. Bagging experiments and analyses of pollen tube growth confirmed self-fertility for pollen-dependent apomicts, but self-sterility for diploid sexuals. Facultative apomixis combines advantages of both modes of reproduction: uniparental reproduction allows for rapid colonization of remote areas, whereas facultative sexuality and polyploidy maintains genetic diversity within apomictic populations. The density dependence of outcrossing limits range expansions of sexual populations. PMID:23403961

Genome-wide association study of handedness excludes simple genetic models

PubMed Central

Armour, J AL; Davison, A; McManus, I C

2014-01-01

Handedness is a human behavioural phenotype that appears to be congenital, and is often assumed to be inherited, but for which the developmental origin and underlying causation(s) have been elusive. Models of the genetic basis of variation in handedness have been proposed that fit different features of the observed resemblance between relatives, but none has been decisively tested or a corresponding causative locus identified. In this study, we applied data from well-characterised individuals studied at the London Twin Research Unit. Analysis of genome-wide SNP data from 3940 twins failed to identify any locus associated with handedness at a genome-wide level of significance. The most straightforward interpretation of our analyses is that they exclude the simplest formulations of the ‘right-shift' model of Annett and the ‘dextral/chance' model of McManus, although more complex modifications of those models are still compatible with our observations. For polygenic effects, our study is inadequately powered to reliably detect alleles with effect sizes corresponding to an odds ratio of 1.2, but should have good power to detect effects at an odds ratio of 2 or more. PMID:24065183

The production of homozygous tree material

Treesearch

Reinhard F. Stettler; George E. Howe

1966-01-01

Homozygous trees will never be the desired ultimate step in a forest tree improvement program. However, they will serve many purposes in forest genetics research: (1) in the detection of genetic markers; (2) in the isolation of traits under simple genetic control for the study of growth and differentiation phenomena; (3) as a tool as well as reference material in the...

Empirical Bayes Estimation of Semi-parametric Hierarchical Mixture Models for Unbiased Characterization of Polygenic Disease Architectures

PubMed Central

Nishino, Jo; Kochi, Yuta; Shigemizu, Daichi; Kato, Mamoru; Ikari, Katsunori; Ochi, Hidenori; Noma, Hisashi; Matsui, Kota; Morizono, Takashi; Boroevich, Keith A.; Tsunoda, Tatsuhiko; Matsui, Shigeyuki

2018-01-01

Genome-wide association studies (GWAS) suggest that the genetic architecture of complex diseases consists of unexpectedly numerous variants with small effect sizes. However, the polygenic architectures of many diseases have not been well characterized due to lack of simple and fast methods for unbiased estimation of the underlying proportion of disease-associated variants and their effect-size distribution. Applying empirical Bayes estimation of semi-parametric hierarchical mixture models to GWAS summary statistics, we confirmed that schizophrenia was extremely polygenic [~40% of independent genome-wide SNPs are risk variants, most within odds ratio (OR = 1.03)], whereas rheumatoid arthritis was less polygenic (~4 to 8% risk variants, significant portion reaching OR = 1.05 to 1.1). For rheumatoid arthritis, stratified estimations revealed that expression quantitative loci in blood explained large genetic variance, and low- and high-frequency derived alleles were prone to be risk and protective, respectively, suggesting a predominance of deleterious-risk and advantageous-protective mutations. Despite genetic correlation, effect-size distributions for schizophrenia and bipolar disorder differed across allele frequency. These analyses distinguished disease polygenic architectures and provided clues for etiological differences in complex diseases. PMID:29740473

In the swim of things: recent insights to neurogenetic disorders from zebrafish.

PubMed

Kabashi, Edor; Champagne, Nathalie; Brustein, Edna; Drapeau, Pierre

2010-08-01

The advantage of zebrafish as a model to study human pathologies lies in the ease of manipulating gene expression in vivo. Here we focus on recent progress in our understanding of motor neuron diseases and neurodevelopmental disorders and discuss how novel technologies will permit further disease models to be developed. Together these advances set the stage for this simple functional model, with particular advantages for transgenesis, multigenic analyses and chemical biology, to become uniquely suited for advancing the functional genomics of neurological and possibly psychiatric diseases - from understanding the genetics and cell biology of degenerative and developmental disorders to the discovery of therapeutics. Copyright 2010 Elsevier Ltd. All rights reserved.

Development and Interlaboratory Validation of a Simple Screening Method for Genetically Modified Maize Using a ΔΔC(q)-Based Multiplex Real-Time PCR Assay.

PubMed

Noguchi, Akio; Nakamura, Kosuke; Sakata, Kozue; Sato-Fukuda, Nozomi; Ishigaki, Takumi; Mano, Junichi; Takabatake, Reona; Kitta, Kazumi; Teshima, Reiko; Kondo, Kazunari; Nishimaki-Mogami, Tomoko

2016-04-19

A number of genetically modified (GM) maize events have been developed and approved worldwide for commercial cultivation. A screening method is needed to monitor GM maize approved for commercialization in countries that mandate the labeling of foods containing a specified threshold level of GM crops. In Japan, a screening method has been implemented to monitor approved GM maize since 2001. However, the screening method currently used in Japan is time-consuming and requires generation of a calibration curve and experimental conversion factor (C(f)) value. We developed a simple screening method that avoids the need for a calibration curve and C(f) value. In this method, ΔC(q) values between the target sequences and the endogenous gene are calculated using multiplex real-time PCR, and the ΔΔC(q) value between the analytical and control samples is used as the criterion for determining analytical samples in which the GM organism content is below the threshold level for labeling of GM crops. An interlaboratory study indicated that the method is applicable independently with at least two models of PCR instruments used in this study.

Genetic Variation and Association Mapping of Seed-Related Traits in Cultivated Peanut (Arachis hypogaea L.) Using Single-Locus Simple Sequence Repeat Markers.

PubMed

Zhao, Jiaojiao; Huang, Li; Ren, Xiaoping; Pandey, Manish K; Wu, Bei; Chen, Yuning; Zhou, Xiaojing; Chen, Weigang; Xia, Youlin; Li, Zeqing; Luo, Huaiyong; Lei, Yong; Varshney, Rajeev K; Liao, Boshou; Jiang, Huifang

2017-01-01

Cultivated peanut ( Arachis hypogaea L.) is an allotetraploid (AABB, 2 n = 4 x = 40), valued for its edible oil and digestible protein. Seed size and weight are important agronomical traits significantly influence the yield and nutritional composition of peanut. However, the genetic basis of seed-related traits remains ambiguous. Association mapping is a powerful approach for quickly and efficiently exploring the genetic basis of important traits in plants. In this study, a total of 104 peanut accessions were used to identify molecular markers associated with seed-related traits using 554 single-locus simple sequence repeat (SSR) markers. Most of the accessions had no or weak relationship in the peanut panel. The linkage disequilibrium (LD) decayed with the genetic distance of 1cM at the genome level and the LD of B subgenome decayed faster than that of the A subgenome. Large phenotypic variation was observed for four seed-related traits in the association panel. Using mixed linear model with population structure and kinship, a total of 30 significant SSR markers were detected to be associated with four seed-related traits ( P < 1.81 × 10 -3 ) in different environments, which explained 11.22-32.30% of the phenotypic variation for each trait. The marker AHGA44686 was simultaneously and repeatedly associated with seed length and hundred-seed weight in multiple environments with large phenotypic variance (26.23 ∼ 32.30%). The favorable alleles of associated markers for each seed-related trait and the optimal combination of favorable alleles of associated markers were identified to significantly enhance trait performance, revealing a potential of utilization of these associated markers in peanut breeding program.

Expected Shannon Entropy and Shannon Differentiation between Subpopulations for Neutral Genes under the Finite Island Model.

PubMed

Chao, Anne; Jost, Lou; Hsieh, T C; Ma, K H; Sherwin, William B; Rollins, Lee Ann

2015-01-01

Shannon entropy H and related measures are increasingly used in molecular ecology and population genetics because (1) unlike measures based on heterozygosity or allele number, these measures weigh alleles in proportion to their population fraction, thus capturing a previously-ignored aspect of allele frequency distributions that may be important in many applications; (2) these measures connect directly to the rich predictive mathematics of information theory; (3) Shannon entropy is completely additive and has an explicitly hierarchical nature; and (4) Shannon entropy-based differentiation measures obey strong monotonicity properties that heterozygosity-based measures lack. We derive simple new expressions for the expected values of the Shannon entropy of the equilibrium allele distribution at a neutral locus in a single isolated population under two models of mutation: the infinite allele model and the stepwise mutation model. Surprisingly, this complex stochastic system for each model has an entropy expressable as a simple combination of well-known mathematical functions. Moreover, entropy- and heterozygosity-based measures for each model are linked by simple relationships that are shown by simulations to be approximately valid even far from equilibrium. We also identify a bridge between the two models of mutation. We apply our approach to subdivided populations which follow the finite island model, obtaining the Shannon entropy of the equilibrium allele distributions of the subpopulations and of the total population. We also derive the expected mutual information and normalized mutual information ("Shannon differentiation") between subpopulations at equilibrium, and identify the model parameters that determine them. We apply our measures to data from the common starling (Sturnus vulgaris) in Australia. Our measures provide a test for neutrality that is robust to violations of equilibrium assumptions, as verified on real world data from starlings.

Identification of cracks in thick beams with a cracked beam element model

NASA Astrophysics Data System (ADS)

Hou, Chuanchuan; Lu, Yong

2016-12-01

The effect of a crack on the vibration of a beam is a classical problem, and various models have been proposed, ranging from the basic stiffness reduction method to the more sophisticated model involving formulation based on the additional flexibility due to a crack. However, in the damage identification or finite element model updating applications, it is still common practice to employ a simple stiffness reduction factor to represent a crack in the identification process, whereas the use of a more realistic crack model is rather limited. In this paper, the issues with the simple stiffness reduction method, particularly concerning thick beams, are highlighted along with a review of several other crack models. A robust finite element model updating procedure is then presented for the detection of cracks in beams. The description of the crack parameters is based on the cracked beam flexibility formulated by means of the fracture mechanics, and it takes into consideration of shear deformation and coupling between translational and longitudinal vibrations, and thus is particularly suitable for thick beams. The identification procedure employs a global searching technique using Genetic Algorithms, and there is no restriction on the location, severity and the number of cracks to be identified. The procedure is verified to yield satisfactory identification for practically any configurations of cracks in a beam.

Comparison and correlation of Simple Sequence Repeats distribution in genomes of Brucella species

PubMed Central

Kiran, Jangampalli Adi Pradeep; Chakravarthi, Veeraraghavulu Praveen; Kumar, Yellapu Nanda; Rekha, Somesula Swapna; Kruti, Srinivasan Shanthi; Bhaskar, Matcha

2011-01-01

Computational genomics is one of the important tools to understand the distribution of closely related genomes including simple sequence repeats (SSRs) in an organism, which gives valuable information regarding genetic variations. The central objective of the present study was to screen the SSRs distributed in coding and non-coding regions among different human Brucella species which are involved in a range of pathological disorders. Computational analysis of the SSRs in the Brucella indicates few deviations from expected random models. Statistical analysis also reveals that tri-nucleotide SSRs are overrepresented and tetranucleotide SSRs underrepresented in Brucella genomes. From the data, it can be suggested that over expressed tri-nucleotide SSRs in genomic and coding regions might be responsible in the generation of functional variation of proteins expressed which in turn may lead to different pathogenicity, virulence determinants, stress response genes, transcription regulators and host adaptation proteins of Brucella genomes. Abbreviations SSRs - Simple Sequence Repeats, ORFs - Open Reading Frames. PMID:21738309

Filtration Isolation of Nucleic Acids: A Simple and Rapid DNA Extraction Method.

PubMed

McFall, Sally M; Neto, Mário F; Reed, Jennifer L; Wagner, Robin L

2016-08-06

FINA, filtration isolation of nucleic acids, is a novel extraction method which utilizes vertical filtration via a separation membrane and absorbent pad to extract cellular DNA from whole blood in less than 2 min. The blood specimen is treated with detergent, mixed briefly and applied by pipet to the separation membrane. The lysate wicks into the blotting pad due to capillary action, capturing the genomic DNA on the surface of the separation membrane. The extracted DNA is retained on the membrane during a simple wash step wherein PCR inhibitors are wicked into the absorbent blotting pad. The membrane containing the entrapped DNA is then added to the PCR reaction without further purification. This simple method does not require laboratory equipment and can be easily implemented with inexpensive laboratory supplies. Here we describe a protocol for highly sensitive detection and quantitation of HIV-1 proviral DNA from 100 µl whole blood as a model for early infant diagnosis of HIV that could readily be adapted to other genetic targets.

Role of introduction history and landscape in the range expansion of brown trout (Salmo trutta L.) in the Kerguelen Islands.

PubMed

Launey, Sophie; Brunet, Geraldine; Guyomard, René; Davaine, Patrick

2010-01-01

Human-mediated biological invasions constitute interesting case studies to understand evolutionary processes, including the role of founder effects. Population expansion of newly introduced species can be highly dependant on barriers caused by landscape features, but identifying these barriers and their impact on genetic structure is a relatively recent concern in population genetics and ecology. Salmonid populations of the Kerguelen Islands archipelago are a favorable model system to address these questions as these populations are characterized by a simple history of introduction, little or no anthropogenic influence, and demographic monitoring since the first introductions. We analyzed genetic variation at 10 microsatellite loci in 19 populations of brown trout (Salmo trutta L.) in the Courbet Peninsula (Kerguelen Islands), where the species, introduced in 3 rivers only, has colonized the whole water system in 40 years. Despite a limited numbers of introductions, trout populations have maintained a genetic diversity comparable with what is found in hatchery or wild populations in Europe, but they are genetically structured. The main factor explaining the observed patterns of genetic diversity is the history of introductions, with each introduced population acting as a source for colonization of nearby rivers. Correlations between environmental and genetic parameters show that within each "source population" group, landscape characteristics (type of coast, accessibility of river mouth, distances between rivers, river length ...) play a role in shaping directions and rates of migration, and thus the genetic structure of the colonizing populations.

Predictive accuracy of combined genetic and environmental risk scores.

PubMed

Dudbridge, Frank; Pashayan, Nora; Yang, Jian

2018-02-01

The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores. © 2017 WILEY PERIODICALS, INC.

Predictive accuracy of combined genetic and environmental risk scores

PubMed Central

Pashayan, Nora; Yang, Jian

2017-01-01

ABSTRACT The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores. PMID:29178508

A Modified Penalty Parameter Approach for Optimal Estimation of UH with Simultaneous Estimation of Infiltration Parameters

NASA Astrophysics Data System (ADS)

Bhattacharjya, Rajib Kumar

2018-05-01

The unit hydrograph and the infiltration parameters of a watershed can be obtained from observed rainfall-runoff data by using inverse optimization technique. This is a two-stage optimization problem. In the first stage, the infiltration parameters are obtained and the unit hydrograph ordinates are estimated in the second stage. In order to combine this two-stage method into a single stage one, a modified penalty parameter approach is proposed for converting the constrained optimization problem to an unconstrained one. The proposed approach is designed in such a way that the model initially obtains the infiltration parameters and then searches the optimal unit hydrograph ordinates. The optimization model is solved using Genetic Algorithms. A reduction factor is used in the penalty parameter approach so that the obtained optimal infiltration parameters are not destroyed during subsequent generation of genetic algorithms, required for searching optimal unit hydrograph ordinates. The performance of the proposed methodology is evaluated by using two example problems. The evaluation shows that the model is superior, simple in concept and also has the potential for field application.

Comparative artificial neural network and partial least squares models for analysis of Metronidazole, Diloxanide, Spiramycin and Cliquinol in pharmaceutical preparations.

PubMed

Elkhoudary, Mahmoud M; Abdel Salam, Randa A; Hadad, Ghada M

2014-09-15

Metronidazole (MNZ) is a widely used antibacterial and amoebicide drug. Therefore, it is important to develop a rapid and specific analytical method for the determination of MNZ in mixture with Spiramycin (SPY), Diloxanide (DIX) and Cliquinol (CLQ) in pharmaceutical preparations. This work describes simple, sensitive and reliable six multivariate calibration methods, namely linear and nonlinear artificial neural networks preceded by genetic algorithm (GA-ANN) and principle component analysis (PCA-ANN) as well as partial least squares (PLS) either alone or preceded by genetic algorithm (GA-PLS) for UV spectrophotometric determination of MNZ, SPY, DIX and CLQ in pharmaceutical preparations with no interference of pharmaceutical additives. The results manifest the problem of nonlinearity and how models like ANN can handle it. Analytical performance of these methods was statistically validated with respect to linearity, accuracy, precision and specificity. The developed methods indicate the ability of the previously mentioned multivariate calibration models to handle and solve UV spectra of the four components' mixtures using easy and widely used UV spectrophotometer. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparative artificial neural network and partial least squares models for analysis of Metronidazole, Diloxanide, Spiramycin and Cliquinol in pharmaceutical preparations

NASA Astrophysics Data System (ADS)

Elkhoudary, Mahmoud M.; Abdel Salam, Randa A.; Hadad, Ghada M.

2014-09-01

Metronidazole (MNZ) is a widely used antibacterial and amoebicide drug. Therefore, it is important to develop a rapid and specific analytical method for the determination of MNZ in mixture with Spiramycin (SPY), Diloxanide (DIX) and Cliquinol (CLQ) in pharmaceutical preparations. This work describes simple, sensitive and reliable six multivariate calibration methods, namely linear and nonlinear artificial neural networks preceded by genetic algorithm (GA-ANN) and principle component analysis (PCA-ANN) as well as partial least squares (PLS) either alone or preceded by genetic algorithm (GA-PLS) for UV spectrophotometric determination of MNZ, SPY, DIX and CLQ in pharmaceutical preparations with no interference of pharmaceutical additives. The results manifest the problem of nonlinearity and how models like ANN can handle it. Analytical performance of these methods was statistically validated with respect to linearity, accuracy, precision and specificity. The developed methods indicate the ability of the previously mentioned multivariate calibration models to handle and solve UV spectra of the four components’ mixtures using easy and widely used UV spectrophotometer.

Genetic diversity of the Andean tuber-bearing species, oca (Oxalis tuberosa Mol.), investigated by inter-simple sequence repeats.

PubMed

Pissard, A; Ghislain, M; Bertin, P

2006-01-01

The Andean tuber-bearing species, Oxalis tuberosa Mol., is a vegetatively propagated crop cultivated in the uplands of the Andes. Its genetic diversity was investigated in the present study using the inter-simple sequence repeat (ISSR) technique. Thirty-two accessions originating from South America (Argentina, Bolivia, Chile, and Peru) and maintained in vitro were chosen to represent the ecogeographic diversity of its cultivation area. Twenty-two primers were tested and 9 were selected according to fingerprinting quality and reproducibility. Genetic diversity analysis was performed with 90 markers. Jaccard's genetic distance between accessions ranged from 0 to 0.49 with an average of 0.28 +/- 0.08 (mean +/- SD). Dendrogram (UPGMA (unweighted pair-group method with arithmetic averaging)) and factorial correspondence analysis (FCA) showed that the genetic structure was influenced by the collection site. The two most distant clusters contained all of the Peruvian accessions, one from Bolivia, none from Argentina or Chile. Analysis by country revealed that Peru presented the greatest genetic distances from the other countries and possessed the highest intra-country genetic distance (0.30 +/- 0.08). This suggests that the Peruvian oca accessions form a distinct genetic group. The relatively low level of genetic diversity in the oca species may be related to its predominating reproduction strategy, i.e., vegetative propagation. The extent and structure of the genetic diversity of the species detailed here should help the establishment of conservation strategies.

Predicting performance for ecological restoration: A case study using Spartina altemiflora

USGS Publications Warehouse

Travis, S.E.; Grace, J.B.

2010-01-01

The success of population-based ecological restoration relies on the growth and reproductive performance of selected donor materials, whether consisting of whole plants or seed. Accurately predicting performance requires an understanding of a variety of underlying processes, particularly gene flow and selection, which can be measured, at least in part, using surrogates such as neutral marker genetic distances and simple latitudinal effects. Here we apply a structural equation modeling approach to understanding and predicting performance in a widespread salt marsh grass, Spartina alterniflora, commonly used for ecological restoration throughout its native range in North America. We collected source materials from throughout this range, consisting of eight clones each from 23 populations, for transplantation to a common garden site in coastal Louisiana and monitored their performance. We modeled performance as a latent process described by multiple indicator variables (e.g., clone diameter, stem number) and estimated direct and indirect influences of geographic and genetic distances on performance. Genetic distances were determined by comparison of neutral molecular markers with those from a local population at the common garden site. Geographic distance metrics included dispersal distance (the minimum distance over water between donor and experimental sites) and latitude. Model results indicate direct effects of genetic distance and latitude on performance variation among the donor sites. Standardized effect strengths indicate that performance was roughly twice as sensitive to variation in genetic distance as to latitudinal variation. Dispersal distance had an indirect influence on performance through effects on genetic distance, indicating a typical pattern of genetic isolation by distance. Latitude also had an indirect effect on genetic distance through its linear relationship with dispersal distance. Three performance indicators had significant loadings on performance alone (mean clone diameter, mean number of stems, mean number of inflorescences), while the performance indicators mean stem height and mean stem width were also influenced by latitude. We suggest that dispersal distance and latitude should provide an adequate means of predicting performance in future S. alterniflora restorations and propose a maximum sampling distance of 300 km (holding latitude constant) to avoid the sampling of inappropriate ecotypes. ?? 2010 by the Ecological Society of America.

It's not about you: a simple proposition for improving biology education.

PubMed

Wright, Robin

2014-10-01

THE Genetics Society of America's Elizabeth W. Jones Award for Excellence in Education recognizes significant and sustained impact on genetics education. Consistent with her philosophy of linking research and education, the 2014 Awardee Robin Wright includes undergraduate students in all of her research. She seeks to teach how to think like and to actually be a biologist, working in teams and looking at real-world problems. She emphasizes a learner-centered model of classroom work that promotes and enhances lifelong skills, and has transformed biology education at the University of Minnesota through several efforts including developing the interactive, stimulating Foundations of Biology course sequence, encouraging active learning and open-ended research; supporting the construction of Active Learning Classrooms; and establishing Student Learning Outcomes, standards that measure biology education. She serves as founding editor-in-chief of CourseSource, focusing national effort to collect learner-centered, outcomes-based teaching resources in undergraduate biology. Copyright © 2014 by the Genetics Society of America.

Use of Simple Sequence Repeat (SSR) markers for DNA fingerprinting and diversity analysis of sugarcane (Saccharum spp.) cultivars resistant and susceptible to red rot

USDA-ARS?s Scientific Manuscript database

In recent years SSR markers have been used widely for the genetic analysis. The objective of present research was to use SSR markers to develop DNA-based genetic identification and analyze genetic relationship of sugarcane cultivars grown in Pakistan either resistant or susceptible to red rot. Twent...

Grocery Store Genetics: A PCR-Based Genetics Lab that Links Genotype to Phenotype

ERIC Educational Resources Information Center

Briju, Betsy J.; Wyatt, Sarah E.

2015-01-01

Instructors often present Mendelian genetics and molecular biology separately. As a result, students often fail to connect the two topics in a tangible manner. We have adopted a simple experiment to help link these two important topics in a basic biology course, using red and white onions bought from a local grocery store. A lack of red coloration…

Genetic diversity of an Azorean endemic and endangered plant species inferred from inter-simple sequence repeat markers.

PubMed

Lopes, Maria S; Mendonça, Duarte; Bettencourt, Sílvia X; Borba, Ana R; Melo, Catarina; Baptista, Cláudio; da Câmara Machado, Artur

2014-06-26

Knowledge of the levels and distribution of genetic diversity is important for designing conservation strategies for threatened and endangered species so as to guarantee sustainable survival of populations and to preserve their evolutionary potential. Picconia azorica is a valuable Azorean endemic species recently classified as endangered. To contribute with information useful for the establishment of conservation programmes, the genetic variability and differentiation among 230 samples from 11 populations collected in three Azorean islands was accessed with eight inter-simple sequence repeat markers. A total of 64 polymorphic loci were detected. The majority of genetic variability was found within populations and no genetic structure was detected between populations and between islands. Also the coefficient of genetic differentiation and the level of gene flow indicate that geographical distances do not act as barriers for gene flow. In order to ensure the survival of populations in situ and ex situ management practices should be considered, including artificial propagation through the use of plant tissue culture techniques, not only for the restoration of habitat but also for the sustainable use of its valuable wood. Published by Oxford University Press on behalf of the Annals of Botany Company.

Kinetic models of gene expression including non-coding RNAs

NASA Astrophysics Data System (ADS)

Zhdanov, Vladimir P.

2011-03-01

In cells, genes are transcribed into mRNAs, and the latter are translated into proteins. Due to the feedbacks between these processes, the kinetics of gene expression may be complex even in the simplest genetic networks. The corresponding models have already been reviewed in the literature. A new avenue in this field is related to the recognition that the conventional scenario of gene expression is fully applicable only to prokaryotes whose genomes consist of tightly packed protein-coding sequences. In eukaryotic cells, in contrast, such sequences are relatively rare, and the rest of the genome includes numerous transcript units representing non-coding RNAs (ncRNAs). During the past decade, it has become clear that such RNAs play a crucial role in gene expression and accordingly influence a multitude of cellular processes both in the normal state and during diseases. The numerous biological functions of ncRNAs are based primarily on their abilities to silence genes via pairing with a target mRNA and subsequently preventing its translation or facilitating degradation of the mRNA-ncRNA complex. Many other abilities of ncRNAs have been discovered as well. Our review is focused on the available kinetic models describing the mRNA, ncRNA and protein interplay. In particular, we systematically present the simplest models without kinetic feedbacks, models containing feedbacks and predicting bistability and oscillations in simple genetic networks, and models describing the effect of ncRNAs on complex genetic networks. Mathematically, the presentation is based primarily on temporal mean-field kinetic equations. The stochastic and spatio-temporal effects are also briefly discussed.

Religion, fertility and genes: a dual inheritance model

PubMed Central

Rowthorn, Robert

2011-01-01

Religious people nowadays have more children on average than their secular counterparts. This paper uses a simple model to explore the evolutionary implications of this difference. It assumes that fertility is determined entirely by culture, whereas subjective predisposition towards religion is influenced by genetic endowment. People who carry a certain ‘religiosity’ gene are more likely than average to become or remain religious. The paper considers the effect of religious defections and exogamy on the religious and genetic composition of society. Defections reduce the ultimate share of the population with religious allegiance and slow down the spread of the religiosity gene. However, provided the fertility differential persists, and people with a religious allegiance mate mainly with people like themselves, the religiosity gene will eventually predominate despite a high rate of defection. This is an example of ‘cultural hitch-hiking’, whereby a gene spreads because it is able to hitch a ride with a high-fitness cultural practice. The theoretical arguments are supported by numerical simulations. PMID:21227968

Religion, fertility and genes: a dual inheritance model.

PubMed

Rowthorn, Robert

2011-08-22

Religious people nowadays have more children on average than their secular counterparts. This paper uses a simple model to explore the evolutionary implications of this difference. It assumes that fertility is determined entirely by culture, whereas subjective predisposition towards religion is influenced by genetic endowment. People who carry a certain 'religiosity' gene are more likely than average to become or remain religious. The paper considers the effect of religious defections and exogamy on the religious and genetic composition of society. Defections reduce the ultimate share of the population with religious allegiance and slow down the spread of the religiosity gene. However, provided the fertility differential persists, and people with a religious allegiance mate mainly with people like themselves, the religiosity gene will eventually predominate despite a high rate of defection. This is an example of 'cultural hitch-hiking', whereby a gene spreads because it is able to hitch a ride with a high-fitness cultural practice. The theoretical arguments are supported by numerical simulations.

Genomics and the making of yeast biodiversity.

PubMed

Hittinger, Chris Todd; Rokas, Antonis; Bai, Feng-Yan; Boekhout, Teun; Gonçalves, Paula; Jeffries, Thomas W; Kominek, Jacek; Lachance, Marc-André; Libkind, Diego; Rosa, Carlos A; Sampaio, José Paulo; Kurtzman, Cletus P

2015-12-01

Yeasts are unicellular fungi that do not form fruiting bodies. Although the yeast lifestyle has evolved multiple times, most known species belong to the subphylum Saccharomycotina (syn. Hemiascomycota, hereafter yeasts). This diverse group includes the premier eukaryotic model system, Saccharomyces cerevisiae; the common human commensal and opportunistic pathogen, Candida albicans; and over 1000 other known species (with more continuing to be discovered). Yeasts are found in every biome and continent and are more genetically diverse than angiosperms or chordates. Ease of culture, simple life cycles, and small genomes (∼10-20Mbp) have made yeasts exceptional models for molecular genetics, biotechnology, and evolutionary genomics. Here we discuss recent developments in understanding the genomic underpinnings of the making of yeast biodiversity, comparing and contrasting natural and human-associated evolutionary processes. Only a tiny fraction of yeast biodiversity and metabolic capabilities has been tapped by industry and science. Expanding the taxonomic breadth of deep genomic investigations will further illuminate how genome function evolves to encode their diverse metabolisms and ecologies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Whole transcriptome analysis using next-generation sequencing of model species Setaria viridis to support C4 photosynthesis research.

PubMed

Xu, Jiajia; Li, Yuanyuan; Ma, Xiuling; Ding, Jianfeng; Wang, Kai; Wang, Sisi; Tian, Ye; Zhang, Hui; Zhu, Xin-Guang

2013-09-01

Setaria viridis is an emerging model species for genetic studies of C4 photosynthesis. Many basic molecular resources need to be developed to support for this species. In this paper, we performed a comprehensive transcriptome analysis from multiple developmental stages and tissues of S. viridis using next-generation sequencing technologies. Sequencing of the transcriptome from multiple tissues across three developmental stages (seed germination, vegetative growth, and reproduction) yielded a total of 71 million single end 100 bp long reads. Reference-based assembly using Setaria italica genome as a reference generated 42,754 transcripts. De novo assembly generated 60,751 transcripts. In addition, 9,576 and 7,056 potential simple sequence repeats (SSRs) covering S. viridis genome were identified when using the reference based assembled transcripts and the de novo assembled transcripts, respectively. This identified transcripts and SSR provided by this study can be used for both reverse and forward genetic studies based on S. viridis.

Genetic Diversity of Ascaris in China Assessed Using Simple Sequence Repeat Markers.

PubMed

Zhou, Chunhua; Jian, Shaoqing; Peng, Weidong; Li, Min

2018-04-01

The giant roundworm Ascaris infects pigs and people worldwide and causes serious diseases. The taxonomic relationship between Ascaris suum and Ascaris lumbricoides is still unclear. The purpose of the present study was to investigate the genetic diversity and population genetic structure of 258 Ascaris specimens from humans and pigs from 6 sympatric regions in Ascaris -endemic regions of China using existing simple sequence repeat data. The microsatellite markers showed a high level of allelic richness and genetic diversity in the samples. Each of the populations demonstrated excess homozygosity (Ho0). According to a genetic differentiation index (Fst=0.0593), there was a high-level of gene flow in the Ascaris populations. A hierarchical analysis on molecular variance revealed remarkably high levels of variation within the populations. Moreover, a population structure analysis indicated that Ascaris populations fell into 3 main genetic clusters, interpreted as A. suum , A. lumbricoides , and a hybrid of the species. We speculated that humans can be infected with A. lumbricoides , A. suum , and the hybrid, but pigs were mainly infected with A. suum . This study provided new information on the genetic diversity and population structure of Ascaris from human and pigs in China, which can be used for designing Ascaris control strategies. It can also be beneficial to understand the introgression of host affiliation.

Vertebrate sex-determining genes play musical chairs.

PubMed

Pan, Qiaowei; Anderson, Jennifer; Bertho, Sylvain; Herpin, Amaury; Wilson, Catherine; Postlethwait, John H; Schartl, Manfred; Guiguen, Yann

2016-01-01

Sexual reproduction is one of the most highly conserved processes in evolution. However, the genetic and cellular mechanisms making the decision of whether the undifferentiated gonad of animal embryos develops either towards male or female are manifold and quite diverse. In vertebrates, sex-determining mechanisms range from environmental to simple or complex genetic mechanisms and different mechanisms have evolved repeatedly and independently. In species with simple genetic sex-determination, master sex-determining genes lying on sex chromosomes drive the gonadal differentiation process by switching on a developmental program, which ultimately leads to testicular or ovarian differentiation. So far, very few sex-determining genes have been identified in vertebrates and apart from mammals and birds, these genes are apparently not conserved over a larger number of related orders, families, genera, or even species. To fill this knowledge gap and to better explore genetic sex-determination, we propose a strategy (RAD-Sex) that makes use of next-generation sequencing technology to identify genetic markers that define sex-specific segments of the male or female genome. Copyright © 2016 Académie des sciences. All rights reserved.

Analysis on the DNA Fingerprinting of Aspergillus Oryzae Mutant Induced by High Hydrostatic Pressure

NASA Astrophysics Data System (ADS)

Wang, Hua; Zhang, Jian; Yang, Fan; Wang, Kai; Shen, Si-Le; Liu, Bing-Bing; Zou, Bo; Zou, Guang-Tian

2011-01-01

The mutant strains of aspergillus oryzae (HP300a) are screened under 300 MPa for 20 min. Compared with the control strains, the screened mutant strains have unique properties such as genetic stability, rapid growth, lots of spores, and high protease activity. Random amplified polymorphic DNA (RAPD) and inter simple sequence repeats (ISSR) are used to analyze the DNA fingerprinting of HP300a and the control strains. There are 67.9% and 51.3% polymorphic bands obtained by these two markers, respectively, indicating significant genetic variations between HP300a and the control strains. In addition, comparison of HP300a and the control strains, the genetic distances of random sequence and simple sequence repeat of DNA are 0.51 and 0.34, respectively.

PLEMT: A NOVEL PSEUDOLIKELIHOOD BASED EM TEST FOR HOMOGENEITY IN GENERALIZED EXPONENTIAL TILT MIXTURE MODELS.

PubMed

Hong, Chuan; Chen, Yong; Ning, Yang; Wang, Shuang; Wu, Hao; Carroll, Raymond J

2017-01-01

Motivated by analyses of DNA methylation data, we propose a semiparametric mixture model, namely the generalized exponential tilt mixture model, to account for heterogeneity between differentially methylated and non-differentially methylated subjects in the cancer group, and capture the differences in higher order moments (e.g. mean and variance) between subjects in cancer and normal groups. A pairwise pseudolikelihood is constructed to eliminate the unknown nuisance function. To circumvent boundary and non-identifiability problems as in parametric mixture models, we modify the pseudolikelihood by adding a penalty function. In addition, the test with simple asymptotic distribution has computational advantages compared with permutation-based test for high-dimensional genetic or epigenetic data. We propose a pseudolikelihood based expectation-maximization test, and show the proposed test follows a simple chi-squared limiting distribution. Simulation studies show that the proposed test controls Type I errors well and has better power compared to several current tests. In particular, the proposed test outperforms the commonly used tests under all simulation settings considered, especially when there are variance differences between two groups. The proposed test is applied to a real data set to identify differentially methylated sites between ovarian cancer subjects and normal subjects.

Genotyping and Molecular Identification of Date Palm Cultivars Using Inter-Simple Sequence Repeat (ISSR) Markers.

PubMed

Ayesh, Basim M

2017-01-01

Molecular markers are credible for the discrimination of genotypes and estimation of the extent of genetic diversity and relatedness in a set of genotypes. Inter-simple sequence repeat (ISSR) markers rapidly reveal high polymorphic fingerprints and have been used frequently to determine the genetic diversity among date palm cultivars. This chapter describes the application of ISSR markers for genotyping of date palm cultivars. The application involves extraction of genomic DNA from the target cultivars with reliable quality and quantity. Subsequently the extracted DNA serves as a template for amplification of genomic regions flanked by inverted simple sequence repeats using a single primer. The similarity of each pair of samples is measured by calculating the number of mono- and polymorphic bands revealed by gel electrophoresis. Matrices constructed for similarity and genetic distance are used to build a phylogenetic tree and cluster analysis, to determine the molecular relatedness of cultivars. The protocol describes 3 out of 9 tested primers consistently amplified 31 loci in 6 date palm cultivars, with 28 polymorphic loci.

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

Steinhaus, K.A.; Bennett, R.L.; Resta, R.G.

To determine consistency in usage of pedigree symbols by genetics professionals, we reviewed pedigrees printed in 10 human genetic and medical journals and 24 medical genetics textbooks. We found no consistent symbolization for common situations such as pregnancy, spontaneous abortion, death, or test results. Inconsistency in pedigree design can create difficulties in the interpretation of family studies and detract from the pedigree`s basic strength of simple and accurate communication of medical information. We recommend the development of standard pedigree symbols, and their incorporation into genetic publications, professional genetics training programs, pedigree software programs, and genetic board examinations. 5 refs., 11more » figs., 2 tabs.« less

The first genetic map of a synthesized allohexaploid Brassica with A, B and C genomes based on simple sequence repeat markers.

PubMed

Yang, S; Chen, S; Geng, X X; Yan, G; Li, Z Y; Meng, J L; Cowling, W A; Zhou, W J

2016-04-01

We present the first genetic map of an allohexaploid Brassica species, based on segregating microsatellite markers in a doubled haploid mapping population generated from a hybrid between two hexaploid parents. This study reports the first genetic map of trigenomic Brassica. A doubled haploid mapping population consisting of 189 lines was obtained via microspore culture from a hybrid H16-1 derived from a cross between two allohexaploid Brassica lines (7H170-1 and Y54-2). Simple sequence repeat primer pairs specific to the A genome (107), B genome (44) and C genome (109) were used to construct a genetic linkage map of the population. Twenty-seven linkage groups were resolved from 274 polymorphic loci on the A genome (109), B genome (49) and C genome (116) covering a total genetic distance of 3178.8 cM with an average distance between markers of 11.60 cM. This is the first genetic framework map for the artificially synthesized Brassica allohexaploids. The linkage groups represent the expected complement of chromosomes in the A, B and C genomes from the original diploid and tetraploid parents. This framework linkage map will be valuable for QTL analysis and future genetic improvement of a new allohexaploid Brassica species, and in improving our understanding of the genetic control of meiosis in new polyploids.

Estimation of genetic diversity using SSR markers in sunflower

USDA-ARS?s Scientific Manuscript database

Sunflower is a major oilseed crop in central Asia, but little is known of the molecular diversity among collections of sunflower from Pakistan region. This paper described inherent genetic relationships among sunflower collections using Simple Sequence Repeat molecular markers. Results should help...

Genetic Technology: A Proposal for the Development of a Science of the Possible

ERIC Educational Resources Information Center

Hudock, George A.

1974-01-01

Urges that biology teachers include the study of genetic anomolies, some very simple aspects of pedigree analysis, and related problems in order to produce citizens who are aware of the impact of science on their lives. (PEB)

Multi-species genetic connectivity in a terrestrial habitat network.

PubMed

Marrotte, Robby R; Bowman, Jeff; Brown, Michael G C; Cordes, Chad; Morris, Kimberley Y; Prentice, Melanie B; Wilson, Paul J

2017-01-01

Habitat fragmentation reduces genetic connectivity for multiple species, yet conservation efforts tend to rely heavily on single-species connectivity estimates to inform land-use planning. Such conservation activities may benefit from multi-species connectivity estimates, which provide a simple and practical means to mitigate the effects of habitat fragmentation for a larger number of species. To test the validity of a multi-species connectivity model, we used neutral microsatellite genetic datasets of Canada lynx ( Lynx canadensis ), American marten ( Martes americana ), fisher ( Pekania pennanti ), and southern flying squirrel ( Glaucomys volans ) to evaluate multi-species genetic connectivity across Ontario, Canada. We used linear models to compare node-based estimates of genetic connectivity for each species to point-based estimates of landscape connectivity (current density) derived from circuit theory. To our knowledge, we are the first to evaluate current density as a measure of genetic connectivity. Our results depended on landscape context: habitat amount was more important than current density in explaining multi-species genetic connectivity in the northern part of our study area, where habitat was abundant and fragmentation was low. In the south however, where fragmentation was prevalent, genetic connectivity was correlated with current density. Contrary to our expectations however, locations with a high probability of movement as reflected by high current density were negatively associated with gene flow. Subsequent analyses of circuit theory outputs showed that high current density was also associated with high effective resistance, underscoring that the presence of pinch points is not necessarily indicative of gene flow. Overall, our study appears to provide support for the hypothesis that landscape pattern is important when habitat amount is low. We also conclude that while current density is proportional to the probability of movement per unit area, this does not imply increased gene flow, since high current density tends to be a result of neighbouring pixels with high cost of movement (e.g., low habitat amount). In other words, pinch points with high current density appear to constrict gene flow.

Genetic structure and diversity of coffee (Coffea) across Africa and the Indian Ocean islands revealed using microsatellites

PubMed Central

Razafinarivo, Norosoa J.; Guyot, Romain; Davis, Aaron P.; Couturon, Emmanuel; Hamon, Serge; Crouzillat, Dominique; Rigoreau, Michel; Dubreuil-Tranchant, Christine; Poncet, Valerie; De Kochko, Alexandre; Rakotomalala, Jean-Jacques; Hamon, Perla

2013-01-01

Background and Aims The coffee genus (Coffea) comprises 124 species, and is indigenous to the Old World Tropics. Due to its immense economic importance, Coffea has been the focus of numerous genetic diversity studies, but despite this effort it remains insufficiently studied. In this study the genetic diversity and genetic structure of Coffea across Africa and the Indian Ocean islands is investigated. Methods Genetic data were produced using 13 polymorphic nuclear microsatellite markers (simple sequence repeats, SSRs), including seven expressed sequence tag-SSRs, and the data were analysed using model- and non-model-based methods. The study includes a total of 728 individuals from 60 species. Key Results Across Africa and the Indian Ocean islands Coffea comprises a closely related group of species with an overall pattern of genotypes running from west to east. Genetic structure was identified in accordance with pre-determined geographical regions and phylogenetic groups. There is a good relationship between morpho-taxonomic species delimitations and genetic units. Genetic diversity in African and Indian Ocean Coffea is high in terms of number of alleles detected, and Madagascar appears to represent a place of significant diversification in terms of allelic richness and species diversity. Conclusions Cross-species SSR transferability in African and Indian Ocean islands Coffea was very efficient. On the basis of the number of private alleles, diversification in East Africa and the Indian Ocean islands appears to be more recent than in West and West-Central Africa, although this general trend is complicated in Africa by the position of species belonging to lineages connecting the main geographical regions. The general pattern of phylogeography is not in agreement with an overall east to west (Mascarene, Madagascar, East Africa, West Africa) increase in genome size, the high proportion of shared alleles between the four regions or the high numbers of exclusive shared alleles between pairs or triplets of regions. PMID:23275631

Human-facilitated metapopulation dynamics in an emerging pest species, Cimex lectularius

PubMed Central

FOUNTAIN, TOBY; DUVAUX, LUDOVIC; HORSBURGH, GAVIN; REINHARDT, KLAUS; BUTLIN, ROGER K

2014-01-01

The number and demographic history of colonists can have dramatic consequences for the way in which genetic diversity is distributed and maintained in a metapopulation. The bed bug (Cimex lectularius) is a re-emerging pest species whose close association with humans has led to frequent local extinction and colonization, that is, to metapopulation dynamics. Pest control limits the lifespan of subpopulations, causing frequent local extinctions, and human-facilitated dispersal allows the colonization of empty patches. Founder events often result in drastic reductions in diversity and an increased influence of genetic drift. Coupled with restricted migration, this can lead to rapid population differentiation. We therefore predicted strong population structuring. Here, using 21 newly characterized microsatellite markers and approximate Bayesian computation (ABC), we investigate simplified versions of two classical models of metapopulation dynamics, in a coalescent framework, to estimate the number and genetic composition of founders in the common bed bug. We found very limited diversity within infestations but high degrees of structuring across the city of London, with extreme levels of genetic differentiation between infestations (FST = 0.59). ABC results suggest a common origin of all founders of a given subpopulation and that the numbers of colonists were low, implying that even a single mated female is enough to found a new infestation successfully. These patterns of colonization are close to the predictions of the propagule pool model, where all founders originate from the same parental infestation. These results show that aspects of metapopulation dynamics can be captured in simple models and provide insights that are valuable for the future targeted control of bed bug infestations. PMID:24446663

Comparison of Family History and SNPs for Predicting Risk of Complex Disease

PubMed Central

Do, Chuong B.; Hinds, David A.; Francke, Uta; Eriksson, Nicholas

2012-01-01

The clinical utility of family history and genetic tests is generally well understood for simple Mendelian disorders and rare subforms of complex diseases that are directly attributable to highly penetrant genetic variants. However, little is presently known regarding the performance of these methods in situations where disease susceptibility depends on the cumulative contribution of multiple genetic factors of moderate or low penetrance. Using quantitative genetic theory, we develop a model for studying the predictive ability of family history and single nucleotide polymorphism (SNP)–based methods for assessing risk of polygenic disorders. We show that family history is most useful for highly common, heritable conditions (e.g., coronary artery disease), where it explains roughly 20%–30% of disease heritability, on par with the most successful SNP models based on associations discovered to date. In contrast, we find that for diseases of moderate or low frequency (e.g., Crohn disease) family history accounts for less than 4% of disease heritability, substantially lagging behind SNPs in almost all cases. These results indicate that, for a broad range of diseases, already identified SNP associations may be better predictors of risk than their family history–based counterparts, despite the large fraction of missing heritability that remains to be explained. Our model illustrates the difficulty of using either family history or SNPs for standalone disease prediction. On the other hand, we show that, unlike family history, SNP–based tests can reveal extreme likelihood ratios for a relatively large percentage of individuals, thus providing potentially valuable adjunctive evidence in a differential diagnosis. PMID:23071447

Sexual selection and genetic colour polymorphisms in animals.

PubMed

Wellenreuther, Maren; Svensson, Erik I; Hansson, Bengt

2014-11-01

Genetic colour polymorphisms are widespread across animals and often subjected to complex selection regimes. Traditionally, colour morphs were used as simple visual markers to measure allele frequency changes in nature, selection, population divergence and speciation. With advances in sequencing technology and analysis methods, several model systems are emerging where the molecular targets of selection are being described. Here, we discuss recent studies on the genetics of sexually selected colour polymorphisms, aiming at (i) reviewing the evidence of sexual selection on colour polymorphisms, (ii) highlighting the genetic architecture, molecular and developmental basis underlying phenotypic colour diversification and (iii) discuss how the maintenance of such polymorphisms might be facilitated or constrained by these. Studies of the genetic architecture of colour polymorphism point towards the importance of tight clustering of colour loci with other trait loci, such as in the case of inversions and supergene structures. Other interesting findings include linkage between colour loci and mate preferences or sex determination, and the role of introgression and regulatory variation in fuelling polymorphisms. We highlight that more studies are needed that explicitly integrate fitness consequences of sexual selection on colour with the underlying molecular targets of colour to gain insights into the evolutionary consequences of sexual selection on polymorphism maintenance. © 2014 John Wiley & Sons Ltd.

Self-fertilization is the main sexual reproduction mechanism in native wine yeast populations.

PubMed

Cubillos, Francisco A; Vásquez, Claudia; Faugeron, Sylvain; Ganga, Angélica; Martínez, Claudio

2009-01-01

Saccharomyces cerevisiae is a model eukaryotic organism for classical genetics and genomics, and yet its ecology is still largely unknown. In this work, a population genetic analysis was performed on five yeast populations isolated from wine-making areas with different enological practices using simple sequence repeats and restriction fragment length polymorphism of mitochondrial DNA as molecular markers on 292 strains. In accordance with other studies, genome size estimation suggests that native S. cerevisiae strains are mainly homothallic and diploids. Analysis of mtDNA data showed that yeast populations from nonindustrial areas have 40% higher genetic diversity than populations isolated from industrial areas, demonstrating that industrial enological practices are likely to affect native yeast populations negatively by reducing its biodiversity. On the other hand, genetic differentiation analysis based on their microsatellite showed no correlation between genetic and geographic distance and a nonsignificant value when a Mantel test was applied. Finally, in the five populations studied, positive inbreeding (F(is)) values from 0.4 to 0.75, a low but significant level of linkage disequilibrium and a high number of multilocus genotypes were detected. These results strongly advocate that sexual reproduction is frequent enough to erase clonal signature in natural populations and that self-fertilization is the main mating system.

Genetic mapping of sex determination in a wild strawberry, Fragaria virginiana, reveals earliest form of sex chromosome.

PubMed

Spigler, R B; Lewers, K S; Main, D S; Ashman, T-L

2008-12-01

The evolution of separate sexes (dioecy) from hermaphroditism is one of the major evolutionary transitions in plants, and this transition can be accompanied by the development of sex chromosomes. Studies in species with intermediate sexual systems are providing unprecedented insight into the initial stages of sex chromosome evolution. Here, we describe the genetic mechanism of sex determination in the octoploid, subdioecious wild strawberry, Fragaria virginiana Mill., based on a whole-genome simple sequence repeat (SSR)-based genetic map and on mapping sex determination as two qualitative traits, male and female function. The resultant total map length is 2373 cM and includes 212 markers on 42 linkage groups (mean marker spacing: 14 cM). We estimated that approximately 70 and 90% of the total F. virginiana genetic map resides within 10 and 20 cM of a marker on this map, respectively. Both sex expression traits mapped to the same linkage group, separated by approximately 6 cM, along with two SSR markers. Together, our phenotypic and genetic mapping results support a model of gender determination in subdioecious F. virginiana with at least two linked loci (or gene regions) with major effects. Reconstruction of parental genotypes at these loci reveals that both female and hermaphrodite heterogamety exist in this species. Evidence of recombination between the sex-determining loci, an important hallmark of incipient sex chromosomes, suggest that F. virginiana is an example of the youngest sex chromosome in plants and thus a novel model system for the study of sex chromosome evolution.

DPY-17 and MUA-3 Interact for Connective Tissue-Like Tissue Integrity in Caenorhabditis elegans: A Model for Marfan Syndrome.

PubMed

Fotopoulos, Pauline; Kim, Jeongho; Hyun, Moonjung; Qamari, Waiss; Lee, Inhwan; You, Young-Jai

2015-04-27

mua-3 is a Caenorhabditis elegans homolog of the mammalian fibrillin1, a monogenic cause of Marfan syndrome. We identified a new mutation of mua-3 that carries an in-frame deletion of 131 amino acids in the extracellular domain, which allows the mutants to survive in a temperature-dependent manner; at the permissive temperature, the mutants grow normally without obvious phenotypes, but at the nonpermissive temperature, more than 90% die during the L4 molt due to internal organ detachment. Using the temperature-sensitive lethality, we performed unbiased genetic screens to isolate suppressors to find genetic interactors of MUA-3. From two independent screens, we isolated mutations in dpy-17 as a suppressor. RNAi of dpy-17 in mua-3 rescued the lethality, confirming dpy-17 is a suppressor. dpy-17 encodes a collagen known to genetically interact with dpy-31, a BMP-1/Tolloid-like metalloprotease required for TGFβ activation in mammals. Human fibrillin1 mutants fail to sequester TGFβ2 leading to excess TGFβ signaling, which in turn contributes to Marfan syndrome or Marfan-related syndrome. Consistent with that, RNAi of dbl-1, a TGFβ homolog, modestly rescued the lethality of mua-3 mutants, suggesting a potentially conserved interaction between MUA-3 and a TGFβ pathway in C. elegans. Our work provides genetic evidence of the interaction between TGFβ and a fibrillin homolog, and thus provides a simple yet powerful genetic model to study TGFβ function in development of Marfan pathology. Copyright © 2015 Fotopoulos et al.

The structure of genetic and environmental risk factors for phobias in women.

PubMed

Czajkowski, N; Kendler, K S; Tambs, K; Røysamb, E; Reichborn-Kjennerud, T

2011-09-01

To explore the genetic and environmental factors underlying the co-occurrence of lifetime diagnoses of DSM-IV phobia. Female twins (n=1430) from the population-based Norwegian Institute of Public Health Twin Panel were assessed at personal interview for DSM-IV lifetime specific phobia, social phobia and agoraphobia. Comorbidity between the phobias were assessed by odds ratios (ORs) and polychoric correlations and multivariate twin models were fitted in Mx. Phenotypic correlations of lifetime phobia diagnoses ranged from 0.55 (agoraphobia and social phobia, OR 10.95) to 0.06 (animal phobia and social phobia, OR 1.21). In the best fitting twin model, which did not include shared environmental factors, heritability estimates for the phobias ranged from 0.43 to 0.63. Comorbidity between the phobias was accounted for by two common liability factors. The first loaded principally on animal phobia and did not influence the complex phobias (agoraphobia and social phobia). The second liability factor strongly influenced the complex phobias, but also loaded weak to moderate on all the other phobias. Blood phobia was mainly influenced by a specific genetic factor, which accounted for 51% of the total and 81% of the genetic variance. Phobias are highly co-morbid and heritable. Our results suggest that the co-morbidity between phobias is best explained by two distinct liability factors rather than a single factor, as has been assumed in most previous multivariate twin analyses. One of these factors was specific to the simple phobias, while the other was more general. Blood phobia was mainly influenced by disorder specific genetic factors.

The structure of genetic and environmental risk factors for phobias in women

PubMed Central

Czajkowski, N.; Kendler, K. S.; Tambs, K.; Røysamb, E.; Reichborn-Kjennerud, T.

2011-01-01

Background To explore the genetic and environmental factors underlying the co-occurrence of lifetime diagnoses of DSM-IV phobia. Method Female twins (n = 1430) from the population-based Norwegian Institute of Public Health Twin Panel were assessed at personal interview for DSM-IV lifetime specific phobia, social phobia and agoraphobia. Comorbidity between the phobias were assessed by odds ratios (ORs) and polychoric correlations and multivariate twin models were fitted in Mx. Results Phenotypic correlations of lifetime phobia diagnoses ranged from 0.55 (agoraphobia and social phobia, OR 10.95) to 0.06 (animal phobia and social phobia, OR 1.21). In the best fitting twin model, which did not include shared environmental factors, heritability estimates for the phobias ranged from 0.43 to 0.63. Comorbidity between the phobias was accounted for by two common liability factors. The first loaded principally on animal phobia and did not influence the complex phobias (agoraphobia and social phobia). The second liability factor strongly influenced the complex phobias, but also loaded weak to moderate on all the other phobias. Blood phobia was mainly influenced by a specific genetic factor, which accounted for 51% of the total and 81% of the genetic variance. Conclusions Phobias are highly co-morbid and heritable. Our results suggest that the co-morbidity between phobias is best explained by two distinct liability factors rather than a single factor, as has been assumed in most previous multivariate twin analyses. One of these factors was specific to the simple phobias, while the other was more general. Blood phobia was mainly influenced by disorder specific genetic factors. PMID:21211096

Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model.

PubMed

Nené, Nuno R; Dunham, Alistair S; Illingworth, Christopher J R

2018-05-01

A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the nondeterministic properties of mutation in a finite population. We propose an alternative approach that acts to correct for this error, and which we denote the delay-deterministic model. Applying our model to a simple evolutionary system, we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model. Copyright © 2018 Nené et al.

Two-trait-locus linkage analysis: A powerful strategy for mapping complex genetic traits

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

Schork, N.J.; Boehnke, M.; Terwilliger, J.D.

1993-11-01

Nearly all diseases mapped to date follow clear Mendelian, single-locus segregation patterns. In contrast, many common familial diseases such as diabetes, psoriasis, several forms of cancer, and schizophrenia are familial and appear to have a genetic component but do not exhibit simple Mendelian transmission. More complex models are required to explain the genetics of these important diseases. In this paper, the authors explore two-trait-locus, two-marker-locus linkage analysis in which two trait loci are mapped simultaneously to separate genetic markers. The authors compare the utility of this approach to standard one-trait-locus, one-marker-locus linkage analysis with and without allowance for heterogeneity. Themore » authors also compare the utility of the two-trait-locus, two-marker-locus analysis to two-trait-locus, one-marker-locus linkage analysis. For common diseases, pedigrees are often bilineal, with disease genes entering via two or more unrelated pedigree members. Since such pedigrees often are avoided in linkage studies, the authors also investigate the relative information content of unilineal and bilineal pedigrees. For the dominant-or-recessive and threshold models that the authors consider, the authors find that two-trait-locus, two-marker-locus linkage analysis can provide substantially more linkage information, as measured by expected maximum lod score, than standard one-trait-locus, one-marker-locus methods, even allowing for heterogeneity, while, for a dominant-or-dominant generating model, one-locus models that allow for heterogeneity extract essentially as much information as the two-trait-locus methods. For these three models, the authors also find that bilineal pedigrees provide sufficient linkage information to warrant their inclusion in such studies. The authors discuss strategies for assessing the significance of the two linkages assumed in two-trait-locus, two-marker-locus models. 37 refs., 1 fig., 4 tabs.« less

Convergence properties of simple genetic algorithms

NASA Technical Reports Server (NTRS)

Bethke, A. D.; Zeigler, B. P.; Strauss, D. M.

1974-01-01

The essential parameters determining the behaviour of genetic algorithms were investigated. Computer runs were made while systematically varying the parameter values. Results based on the progress curves obtained from these runs are presented along with results based on the variability of the population as the run progresses.

High levels of heterozygosity found for 15 SSR loci in Solanum chacoense

USDA-ARS?s Scientific Manuscript database

Genetic variation is a necessary prerequisite for improving domesticated plants through breeding; without it, breeding progress would be impossible. Genetic variation can be readily ascertained with co-dominant DNA markers, such as simple sequence repeats (SSRs). Twenty-four SSR markers specifically...

Genetic differentiation and geographical relationship of Asian barley landraces using SSRs

USDA-ARS?s Scientific Manuscript database

Genetic diversity in 403 morphologically distinctive landraces of barley (Hordeum vulgare L. subsp. vulgare) originating from seven geographical zones of Asia was studied using simple sequence repeat (SSR) markers. The seven polymorphic SSR markers representing each chromosome chosen for this study ...

Survival of mutations arising during invasions.

PubMed

Miller, Judith R

2010-03-01

When a neutral mutation arises in an invading population, it quickly either dies out or 'surfs', i.e. it comes to occupy almost all the habitat available at its time of origin. Beneficial mutations can also surf, as can deleterious mutations over finite time spans. We develop descriptive statistical models that quantify the relationship between the probability that a mutation will surf and demographic parameters for a cellular automaton model of surfing. We also provide a simple analytic model that performs well at predicting the probability of surfing for neutral and beneficial mutations in one dimension. The results suggest that factors - possibly including even abiotic factors - that promote invasion success may also increase the probability of surfing and associated adaptive genetic change, conditioned on such success.

Privacy and confidentiality measures in genetic testing and counselling: arguing on genetic exceptionalism again?

PubMed

Witt, Magdalena M; Witt, Michał P

2016-11-01

Medical confidentiality in clinical genetics poses an important question about its scope, which would be in line with professional ethics and simple honesty. It is already known that the maintenance of absolute anonymity, bearing in mind the current progress of genetic techniques, is virtually impossible. On the other hand, our insight into the information contained in the human genome is increasing. This mini-review presents the authors' standpoint regarding this complex and difficult issue.

Chromosomes, conflict, and epigenetics: chromosomal speciation revisited.

PubMed

Brown, Judith D; O'Neill, Rachel J

2010-01-01

Since Darwin first noted that the process of speciation was indeed the "mystery of mysteries," scientists have tried to develop testable models for the development of reproductive incompatibilities-the first step in the formation of a new species. Early theorists proposed that chromosome rearrangements were implicated in the process of reproductive isolation; however, the chromosomal speciation model has recently been questioned. In addition, recent data from hybrid model systems indicates that simple epistatic interactions, the Dobzhansky-Muller incompatibilities, are more complex. In fact, incompatibilities are quite broad, including interactions among heterochromatin, small RNAs, and distinct, epigenetically defined genomic regions such as the centromere. In this review, we will examine both classical and current models of chromosomal speciation and describe the "evolving" theory of genetic conflict, epigenetics, and chromosomal speciation.

Mudskippers and Their Genetic Adaptations to an Amphibious Lifestyle

PubMed Central

You, Xinxin; Sun, Min; Li, Jia; Bian, Chao; Chen, Jieming; Yu, Hui; Shi, Qiong

2018-01-01

Simple Summary Mudskippers are an interesting group of goggle-eyed amphibious fish that can live both in water and on land. They are a useful model for obtaining insights into the genetic mechanisms underlying the terrestrial adaptations of amphibious fish. This review summarizes the morphological and physiological modifications of representative mudskippers, and focuses on the recent advancement of genomic studies on their genetic adaptations to the amphibious lifestyle. Abstract Mudskippers are the largest group of amphibious teleost fish that are uniquely adapted to live on mudflats. During their successful transition from aqueous life to terrestrial living, these fish have evolved morphological and physiological modifications of aerial vision and olfaction, higher ammonia tolerance, aerial respiration, improved immunological defense against terrestrial pathogens, and terrestrial locomotion using protruded pectoral fins. Comparative genomic and transcriptomic data have been accumulated and analyzed for understanding molecular mechanisms of the terrestrial adaptations. Our current review provides a general introduction to mudskippers and recent research advances of their genetic adaptations to the amphibious lifestyle, which will be helpful for understanding the evolutionary transition of vertebrates from water to land. Our insights into the genomes and transcriptomes will also support molecular breeding, functional identification, and natural compound screening. PMID:29414871

Genetic Diversity in the Interference Selection Limit

PubMed Central

Good, Benjamin H.; Walczak, Aleksandra M.; Neher, Richard A.; Desai, Michael M.

2014-01-01

Pervasive natural selection can strongly influence observed patterns of genetic variation, but these effects remain poorly understood when multiple selected variants segregate in nearby regions of the genome. Classical population genetics fails to account for interference between linked mutations, which grows increasingly severe as the density of selected polymorphisms increases. Here, we describe a simple limit that emerges when interference is common, in which the fitness effects of individual mutations play a relatively minor role. Instead, similar to models of quantitative genetics, molecular evolution is determined by the variance in fitness within the population, defined over an effectively asexual segment of the genome (a “linkage block”). We exploit this insensitivity in a new “coarse-grained” coalescent framework, which approximates the effects of many weakly selected mutations with a smaller number of strongly selected mutations that create the same variance in fitness. This approximation generates accurate and efficient predictions for silent site variability when interference is common. However, these results suggest that there is reduced power to resolve individual selection pressures when interference is sufficiently widespread, since a broad range of parameters possess nearly identical patterns of silent site variability. PMID:24675740

A Genetic Map Between Gossypium hirsutum and the Brazilian Endemic G. mustelinum and Its Application to QTL Mapping

PubMed Central

Wang, Baohua; Liu, Limei; Zhang, Dong; Zhuang, Zhimin; Guo, Hui; Qiao, Xin; Wei, Lijuan; Rong, Junkang; May, O. Lloyd; Paterson, Andrew H.; Chee, Peng W.

2016-01-01

Among the seven tetraploid cotton species, little is known about transmission genetics and genome organization in Gossypium mustelinum, the species most distant from the source of most cultivated cotton, G. hirsutum. In this research, an F2 population was developed from an interspecific cross between G. hirsutum and G. mustelinum (HM). A genetic linkage map was constructed mainly using simple sequence repeat (SSRs) and restriction fragment length polymorphism (RFLP) DNA markers. The arrangements of most genetic loci along the HM chromosomes were identical to those of other tetraploid cotton species. However, both major and minor structural rearrangements were also observed, for which we propose a parsimony-based model for structural divergence of tetraploid cottons from common ancestors. Sequences of mapped markers were used for alignment with the 26 scaffolds of the G. hirsutum draft genome, and showed high consistency. Quantitative trait locus (QTL) mapping of fiber elongation in advanced backcross populations derived from the same parents demonstrated the value of the HM map. The HM map will serve as a valuable resource for QTL mapping and introgression of G. mustelinum alleles into G. hirsutum, and help clarify evolutionary relationships between the tetraploid cotton genomes. PMID:27172208

The impact of receiving predictive genetic information about Lynch syndrome on individual colonoscopy and smoking behaviors

PubMed Central

Kim, Joanne Soo-Min; Coyte, Peter C.; Cotterchio, Michelle; Keogh, Louise A.; Flander, Louisa B.; Gaff, Clara; Laporte, Audrey

2016-01-01

Background This study investigated whether receiving the results of predictive genetic testing for Lynch syndrome—indicating the presence or absence of an inherited predisposition to various cancers, including colorectal cancer—was associated with change in individual colonoscopy and smoking behaviours, which could prevent colorectal cancer. Methods The study population included individuals with no previous diagnosis of colorectal cancer, whose families had already-identified deleterious mutations in the mismatch repair or EPCAM genes. Hypotheses were generated from a simple health economics model and tested against individual-level panel data from the Australasian Colorectal Cancer Family Registry. Results The empirical analysis revealed evidence consistent with some of the hypotheses, with a higher likelihood of undergoing colonoscopy in those who discovered their genetic predisposition to colorectal cancer and a lower likelihood of quitting smoking in those who discovered their lack thereof. Conclusion Predictive genetic information about Lynch syndrome was associated with change in individual colonoscopy and smoking behaviours but not necessarily in ways to improve population health. Impact The study findings suggest that the impact of personalized medicine on disease prevention is intricate, warranting further analyses to determine the net benefits and costs. PMID:27528600

Determining Phylogenetic Relationships Among Date Palm Cultivars Using Random Amplified Polymorphic DNA (RAPD) and Inter-Simple Sequence Repeat (ISSR) Markers.

PubMed

Haider, Nadia

2017-01-01

Investigation of genetic variation and phylogenetic relationships among date palm (Phoenix dactylifera L.) cultivars is useful for their conservation and genetic improvement. Various molecular markers such as restriction fragment length polymorphisms (RFLPs), simple sequence repeat (SSR), representational difference analysis (RDA), and amplified fragment length polymorphism (AFLP) have been developed to molecularly characterize date palm cultivars. PCR-based markers random amplified polymorphic DNA (RAPD) and inter-simple sequence repeat (ISSR) are powerful tools to determine the relatedness of date palm cultivars that are difficult to distinguish morphologically. In this chapter, the principles, materials, and methods of RAPD and ISSR techniques are presented. Analysis of data generated from these two techniques and the use of these data to reveal phylogenetic relationships among date palm cultivars are also discussed.

Biophysics, environmental stochasticity, and the evolution of thermal safety margins in intertidal limpets.

PubMed

Denny, M W; Dowd, W W

2012-03-15

As the air temperature of the Earth rises, ecological relationships within a community might shift, in part due to differences in the thermal physiology of species. Prediction of these shifts - an urgent task for ecologists - will be complicated if thermal tolerance itself can rapidly evolve. Here, we employ a mechanistic approach to predict the potential for rapid evolution of thermal tolerance in the intertidal limpet Lottia gigantea. Using biophysical principles to predict body temperature as a function of the state of the environment, and an environmental bootstrap procedure to predict how the environment fluctuates through time, we create hypothetical time-series of limpet body temperatures, which are in turn used as a test platform for a mechanistic evolutionary model of thermal tolerance. Our simulations suggest that environmentally driven stochastic variation of L. gigantea body temperature results in rapid evolution of a substantial 'safety margin': the average lethal limit is 5-7°C above the average annual maximum temperature. This predicted safety margin approximately matches that found in nature, and once established is sufficient, in our simulations, to allow some limpet populations to survive a drastic, century-long increase in air temperature. By contrast, in the absence of environmental stochasticity, the safety margin is dramatically reduced. We suggest that the risk of exceeding the safety margin, rather than the absolute value of the safety margin, plays an underappreciated role in the evolution of thermal tolerance. Our predictions are based on a simple, hypothetical, allelic model that connects genetics to thermal physiology. To move beyond this simple model - and thereby potentially to predict differential evolution among populations and among species - will require significant advances in our ability to translate the details of thermal histories into physiological and population-genetic consequences.

Irrigation water allocation optimization using multi-objective evolutionary algorithm (MOEA) - a review

NASA Astrophysics Data System (ADS)

Fanuel, Ibrahim Mwita; Mushi, Allen; Kajunguri, Damian

2018-03-01

This paper analyzes more than 40 papers with a restricted area of application of Multi-Objective Genetic Algorithm, Non-Dominated Sorting Genetic Algorithm-II and Multi-Objective Differential Evolution (MODE) to solve the multi-objective problem in agricultural water management. The paper focused on different application aspects which include water allocation, irrigation planning, crop pattern and allocation of available land. The performance and results of these techniques are discussed. The review finds that there is a potential to use MODE to analyzed the multi-objective problem, the application is more significance due to its advantage of being simple and powerful technique than any Evolutionary Algorithm. The paper concludes with the hopeful new trend of research that demand effective use of MODE; inclusion of benefits derived from farm byproducts and production costs into the model.

Genetic diversity and structure of Phakopsora pachyrhizi infecting soybean in Nigeria

USDA-ARS?s Scientific Manuscript database

The genetic structure of Nigerian field populations of the soybean rust pathogen Phakopsora pachyrhizi was determined using 18 simple sequence repeat markers. A total of 113 fungal isolates was collected by hierarchical sampling infected leaves from soybean fields in three agroecological zones in 2...

Genetic variation assessment of acid lime accessions collected from south of Iran using SSR and ISSR molecular markers.

PubMed

Sharafi, Ata Allah; Abkenar, Asad Asadi; Sharafi, Ali; Masaeli, Mohammad

2016-01-01

Iran has a long history of acid lime cultivation and propagation. In this study, genetic variation in 28 acid lime accessions from five regions of south of Iran, and their relatedness with other 19 citrus cultivars were analyzed using Simple Sequence Repeat (SSR) and Inter-Simple Sequence Repeat (ISSR) molecular markers. Nine primers for SSR and nine ISSR primers were used for allele scoring. In total, 49 SSR and 131 ISSR polymorphic alleles were detected. Cluster analysis of SSR and ISSR data showed that most of the acid lime accessions (19 genotypes) have hybrid origin and genetically distance with nucellar of Mexican lime (9 genotypes). As nucellar of Mexican lime are susceptible to phytoplasma, these acid lime genotypes can be used to evaluate their tolerance against biotic constricts like lime "witches' broom disease".

Genome-wide association studies reveal a simple genetic basis of resistance to naturally coevolving viruses in Drosophila melanogaster.

PubMed

Magwire, Michael M; Fabian, Daniel K; Schweyen, Hannah; Cao, Chuan; Longdon, Ben; Bayer, Florian; Jiggins, Francis M

2012-01-01

Variation in susceptibility to infectious disease often has a substantial genetic component in animal and plant populations. We have used genome-wide association studies (GWAS) in Drosophila melanogaster to identify the genetic basis of variation in susceptibility to viral infection. We found that there is substantially more genetic variation in susceptibility to two viruses that naturally infect D. melanogaster (DCV and DMelSV) than to two viruses isolated from other insects (FHV and DAffSV). Furthermore, this increased variation is caused by a small number of common polymorphisms that have a major effect on resistance and can individually explain up to 47% of the heritability in disease susceptibility. For two of these polymorphisms, it has previously been shown that they have been driven to a high frequency by natural selection. An advantage of GWAS in Drosophila is that the results can be confirmed experimentally. We verified that a gene called pastrel--which was previously not known to have an antiviral function--is associated with DCV-resistance by knocking down its expression by RNAi. Our data suggest that selection for resistance to infectious disease can increase genetic variation by increasing the frequency of major-effect alleles, and this has resulted in a simple genetic basis to variation in virus resistance.

Genetic diversity and origin of weedy rice (Oryza sativa f. spontanea) populations found in North-eastern China revealed by simple sequence repeat (SSR) markers.

PubMed

Cao, Qianjin; Lu, Bao-Rong; Xia, Hui; Rong, Jun; Sala, Francesco; Spada, Alberto; Grassi, Fabrizio

2006-12-01

Weedy rice (Oryza sativa f. spontanea) is one of the most notorious weeds occurring in rice-planting areas worldwide. The objectives of this study are to determine the genetic diversity and differentiation of weedy rice populations from Liaoning Province in North-eastern China and to explore the possible origin of these weedy populations by comparing their genetic relationships with rice varieties (O. sativa) and wild rice (O. rufipogon) from different sources. Simple sequence repeat (SSR) markers were used to estimate the genetic diversity of 30 weedy rice populations from Liaoning, each containing about 30 individuals, selected rice varieties and wild O. rufipogon. Genetic differentiation and the relationships of weedy rice populations were analysed using cluster analysis (UPGMA) and principle component analysis (PCA). The overall genetic diversity of weedy rice populations from Liaoning was relatively high (H(e) = 0.313, I = 0.572), with about 35 % of the genetic variation found among regions. The Liaoning weedy rice populations were closely related to rice varieties from Liaoning and japonica varieties from other regions but distantly related to indica rice varieties and wild O. rufipogon. Weedy rice populations from Liaoning are considerably variable genetically and most probably originated from Liaoning rice varieties by mutation and intervarietal hybrids. Recent changes in farming practices and cultivation methods along with less weed management may have promoted the re-emergence and divergence of weedy rice in North-eastern China.

Rapid contemporary evolution and clonal food web dynamics

PubMed Central

Jones, Laura E.; Becks, Lutz; Ellner, Stephen P.; Hairston, Nelson G.; Yoshida, Takehito; Fussmann, Gregor F.

2009-01-01

Character evolution that affects ecological community interactions often occurs contemporaneously with temporal changes in population size, potentially altering the very nature of those dynamics. Such eco-evolutionary processes may be most readily explored in systems with short generations and simple genetics. Asexual and cyclically parthenogenetic organisms such as microalgae, cladocerans and rotifers, which frequently dominate freshwater plankton communities, meet these requirements. Multiple clonal lines can coexist within each species over extended periods, until either fixation occurs or a sexual phase reshuffles the genetic material. When clones differ in traits affecting interspecific interactions, within-species clonal dynamics can have major effects on the population dynamics. We first consider a simple predator–prey system with two prey genotypes, parametrized with data from a well-studied experimental system, and explore how the extent of differences in defence against predation within the prey population determine dynamic stability versus instability of the system. We then explore how increased potential for evolution affects the community dynamics in a more general community model with multiple predator and multiple prey genotypes. These examples illustrate how microevolutionary ‘details’ that enhance or limit the potential for heritable phenotypic change can have significant effects on contemporaneous community-level dynamics and the persistence and coexistence of species. PMID:19414472

Genetic characterization of guava (psidium guajava l.) Germplasm in the United States using microsatellite markers

USDA-ARS?s Scientific Manuscript database

Genetic diversity of thirty five Psidium guajava accessions maintained at the USDA, National Plants Germplasm System, Hilo, HI, was characterized using 20 simple sequence repeat (SSR) markers. Diversity analysis detected a total of 178 alleles ranging from four to 16. The observed mean heterozygosit...

The AOM/DSS murine model for the study of colon carcinogenesis: From pathways to diagnosis and therapy studies

PubMed Central

Robertis, Mariangela De; Massi, Emanuela; Poeta, Maria Luana; Carotti, Simone; Morini, Sergio; Cecchetelli, Loredana; Signori, Emanuela; Fazio, Vito Michele

2011-01-01

Colorectal cancer (CRC) is a major health problem in industrialized countries. Although inflammation-linked carcinogenesis is a well accepted concept and is often observed within the gastrointestinal tract, the underlying mechanisms remain to be elucidated. Inflammation can indeed provide initiating and promoting stimuli and mediators, generating a tumour-prone microenvironment. Many murine models of sporadic and inflammation-related colon carcinogenesis have been developed in the last decade, including chemically induced CRC models, genetically engineered mouse models, and xenoplants. Among the chemically induced CRC models, the combination of a single hit of azoxymethane (AOM) with 1 week exposure to the inflammatory agent dextran sodium sulphate (DSS) in rodents has proven to dramatically shorten the latency time for induction of CRC and to rapidly recapitulate the aberrant crypt foci–adenoma–carcinoma sequence that occurs in human CRC. Because of its high reproducibility and potency, as well as the simple and affordable mode of application, the AOM/DSS has become an outstanding model for studying colon carcinogenesis and a powerful platform for chemopreventive intervention studies. In this article we highlight the histopathological and molecular features and describe the principal genetic and epigenetic alterations and inflammatory pathways involved in carcinogenesis in AOM/DSS–treated mice; we also present a general overview of recent experimental applications and preclinical testing of novel therapeutics in the AOM/DSS model. PMID:21483655

Development of expressed sequence tag-simple sequence repeat markers for genetic characterization and population structure analysis of Praxelis clematidea (Asteraceae).

PubMed

Wang, Q Z; Huang, M; Downie, S R; Chen, Z X

2016-05-23

Invasive plants tend to spread aggressively in new habitats and an understanding of their genetic diversity and population structure is useful for their management. In this study, expressed sequence tag-simple sequence repeat (EST-SSR) markers were developed for the invasive plant species Praxelis clematidea (Asteraceae) from 5548 Stevia rebaudiana (Asteraceae) expressed sequence tags (ESTs). A total of 133 microsatellite-containing ESTs (2.4%) were identified, of which 56 (42.1%) were hexanucleotide repeat motifs and 50 (37.6%) were trinucleotide repeat motifs. Of the 24 primer pairs designed from these 133 ESTs, 7 (29.2%) resulted in significant polymorphisms. The number of alleles per locus ranged from 5 to 9. The relatively high genetic diversity (H = 0.2667, I = 0.4212, and P = 100%) of P. clematidea was related to high gene flow (Nm = 1.4996) among populations. The coefficient of population differentiation (GST = 0.2500) indicated that most genetic variation occurred within populations. A Mantel test suggested that there was significant correlation between genetic distance and geographical distribution (r = 0.3192, P = 0.012). These results further support the transferability of EST-SSR markers between closely related genera of the same family.

Analysis of genetic diversity and population structure of oil palm (Elaeis guineensis) from China and Malaysia based on species-specific simple sequence repeat markers.

PubMed

Zhou, L X; Xiao, Y; Xia, W; Yang, Y D

2015-12-08

Genetic diversity and patterns of population structure of the 94 oil palm lines were investigated using species-specific simple sequence repeat (SSR) markers. We designed primers for 63 SSR loci based on their flanking sequences and conducted amplification in 94 oil palm DNA samples. The amplification result showed that a relatively high level of genetic diversity was observed between oil palm individuals according a set of 21 polymorphic microsatellite loci. The observed heterozygosity (Ho) was 0.3683 and 0.4035, with an average of 0.3859. The Ho value was a reliable determinant of the discriminatory power of the SSR primer combinations. The principal component analysis and unweighted pair-group method with arithmetic averaging cluster analysis showed the 94 oil palm lines were grouped into one cluster. These results demonstrated that the oil palm in Hainan Province of China and the germplasm introduced from Malaysia may be from the same source. The SSR protocol was effective and reliable for assessing the genetic diversity of oil palm. Knowledge of the genetic diversity and population structure will be crucial for establishing appropriate management stocks for this species.

Evolution of complex dynamics

NASA Astrophysics Data System (ADS)

Wilds, Roy; Kauffman, Stuart A.; Glass, Leon

2008-09-01

We study the evolution of complex dynamics in a model of a genetic regulatory network. The fitness is associated with the topological entropy in a class of piecewise linear equations, and the mutations are associated with changes in the logical structure of the network. We compare hill climbing evolution, in which only mutations that increase the fitness are allowed, with neutral evolution, in which mutations that leave the fitness unchanged are allowed. The simple structure of the fitness landscape enables us to estimate analytically the rates of hill climbing and neutral evolution. In this model, allowing neutral mutations accelerates the rate of evolutionary advancement for low mutation frequencies. These results are applicable to evolution in natural and technological systems.

[Caenorhabditis elegans: a powerful tool for drug discovery].

PubMed

Jia, Xi-Hua; Cao, Cheng

2009-07-01

A simple model organism Caenorhabditis elegans has contributed substantially to the fundamental researches in biology. In an era of functional genomics, nematode worm has been developed into a multi-purpose tool that can be exploited to identify disease-causing or disease-associated genes, validate potential drug targets. This, coupled with its genetic amenability, low cost experimental manipulation and compatibility with high throughput screening in an intact physiological condition, makes the model organism into an effective toolbox for drug discovery. This review shows the unique features of C. elegans, how it can play a valuable role in our understanding of the molecular mechanism of human diseases and finding drug leads in drug development process.

Estimating time since infection in early homogeneous HIV-1 samples using a poisson model

PubMed Central

2010-01-01

Background The occurrence of a genetic bottleneck in HIV sexual or mother-to-infant transmission has been well documented. This results in a majority of new infections being homogeneous, i.e., initiated by a single genetic strain. Early after infection, prior to the onset of the host immune response, the viral population grows exponentially. In this simple setting, an approach for estimating evolutionary and demographic parameters based on comparison of diversity measures is a feasible alternative to the existing Bayesian methods (e.g., BEAST), which are instead based on the simulation of genealogies. Results We have devised a web tool that analyzes genetic diversity in acutely infected HIV-1 patients by comparing it to a model of neutral growth. More specifically, we consider a homogeneous infection (i.e., initiated by a unique genetic strain) prior to the onset of host-induced selection, where we can assume a random accumulation of mutations. Previously, we have shown that such a model successfully describes about 80% of sexual HIV-1 transmissions provided the samples are drawn early enough in the infection. Violation of the model is an indicator of either heterogeneous infections or the initiation of selection. Conclusions When the underlying assumptions of our model (homogeneous infection prior to selection and fast exponential growth) are met, we are under a very particular scenario for which we can use a forward approach (instead of backwards in time as provided by coalescent methods). This allows for more computationally efficient methods to derive the time since the most recent common ancestor. Furthermore, the tool performs statistical tests on the Hamming distance frequency distribution, and outputs summary statistics (mean of the best fitting Poisson distribution, goodness of fit p-value, etc). The tool runs within minutes and can readily accommodate the tens of thousands of sequences generated through new ultradeep pyrosequencing technologies. The tool is available on the LANL website. PMID:20973976

Under the Influence of Genetics: How Transdisciplinarity Leads Us to Rethink Social Pathways to Illness

PubMed Central

Pescosolido, Bernice A.; Perry, Brea L.; Long, J. Scott; Martin, Jack K.; Nurnberger, John I.; Hesselbrock, Victor

2015-01-01

To extend our understanding of how social structures and social processes impact behavior, sociologists have been challenged to incorporate the potential explanatory role of genetics in their models. Here, we draw propositions from three major understandings of illness causation offered by social theory – fundamental causes, social stress processes, and social safety net theories. We tailor hypotheses to the case of alcohol dependence, long considered a multifaceted problem, defying simple explanation and having both biological and social roots. After briefly reviewing current appeals for transdisciplinary research, we describe both sociological and genetic theories, and derive propositions expected under each and under a transdisciplinary theoretical frame. Analyses of a later wave of the preeminent medical science study, the Collaborative Study on the Genetics of Alcoholism (COGA), reveals a complex interplay of how the GABRA2 gene works with and against social structural factors to produce cases meeting DSM/ICD diagnoses. When both genetic and social factors are controlled, virtually equivalent effects of each remain; and, only modest evidence suggests that genetic influence works through social structural conditions and experiences. Further exploratory analyses using multiplicative terms reveal enhanced gene-environment interactions: 1) women are largely unaffected in their risk for alcohol dependence by allele status at this candidate gene; 2) family support attenuates genetic influence; 3) childhood deprivation exacerbates genetic predispositions. We discuss how these findings lead us to consider the essential intradisciplinary tension in sociological theories (i.e., the role of proximal and distal influences in social processes). Overall, our findings point to the promise of theories blending social and genetic influences by focusing directly on dynamic, networked sequences that produce different pathways to health and illness. PMID:19569404

Bet-hedging as a complex interaction among developmental instability, environmental heterogeneity, dispersal, and life-history strategy.

PubMed

Scheiner, Samuel M

2014-02-01

One potential evolutionary response to environmental heterogeneity is the production of randomly variable offspring through developmental instability, a type of bet-hedging. I used an individual-based, genetically explicit model to examine the evolution of developmental instability. The model considered both temporal and spatial heterogeneity alone and in combination, the effect of migration pattern (stepping stone vs. island), and life-history strategy. I confirmed that temporal heterogeneity alone requires a threshold amount of variation to select for a substantial amount of developmental instability. For spatial heterogeneity only, the response to selection on developmental instability depended on the life-history strategy and the form and pattern of dispersal with the greatest response for island migration when selection occurred before dispersal. Both spatial and temporal variation alone select for similar amounts of instability, but in combination resulted in substantially more instability than either alone. Local adaptation traded off against bet-hedging, but not in a simple linear fashion. I found higher-order interactions between life-history patterns, dispersal rates, dispersal patterns, and environmental heterogeneity that are not explainable by simple intuition. We need additional modeling efforts to understand these interactions and empirical tests that explicitly account for all of these factors.

Genetic consequences of cladogenetic vs. anagenetic speciation in endemic plants of oceanic islands

PubMed Central

Takayama, Koji; López-Sepúlveda, Patricio; Greimler, Josef; Crawford, Daniel J.; Peñailillo, Patricio; Baeza, Marcelo; Ruiz, Eduardo; Kohl, Gudrun; Tremetsberger, Karin; Gatica, Alejandro; Letelier, Luis; Novoa, Patricio; Novak, Johannes; Stuessy, Tod F.

2015-01-01

Adaptive radiation is a common mode of speciation among plants endemic to oceanic islands. This pattern is one of cladogenesis, or splitting of the founder population, into diverse lineages in divergent habitats. In contrast, endemic species have also evolved primarily by simple transformations from progenitors in source regions. This is anagenesis, whereby the founding population changes genetically and morphologically over time primarily through mutation and recombination. Gene flow among populations is maintained in a homogeneous environment with no splitting events. Genetic consequences of these modes of speciation have been examined in the Juan Fernández Archipelago, which contains two principal islands of differing geological ages. This article summarizes population genetic results (nearly 4000 analyses) from examination of 15 endemic species, involving 1716 and 1870 individuals in 162 and 163 populations (with amplified fragment length polymorphisms and simple sequence repeats, respectively) in the following genera: Drimys (Winteraceae), Myrceugenia (Myrtaceae), Rhaphithamnus (Verbenaceae), Robinsonia (Asteraceae, Senecioneae) and Erigeron (Asteraceae, Astereae). The results indicate that species originating anagenetically show high levels of genetic variation within the island population and no geographic genetic partitioning. This contrasts with cladogenetic species that show less genetic diversity within and among populations. Species that have been derived anagenetically on the younger island (1–2 Ma) contain less genetic variation than those that have anagenetically speciated on the older island (4 Ma). Genetic distinctness among cladogenetically derived species on the older island is greater than among similarly derived species on the younger island. An important point is that the total genetic variation within each genus analysed is comparable, regardless of whether adaptive divergence occurs. PMID:26311732

Motor and sensory neuropathy due to myelin infolding and paranodal damage in a transgenic mouse model of Charcot–Marie–Tooth disease type 1C

PubMed Central

Lee, Samuel M.; Sha, Di; Mohammed, Anum A.; Asress, Seneshaw; Glass, Jonathan D.; Chin, Lih-Shen; Li, Lian

2013-01-01

Charcot–Marie–Tooth disease type 1C (CMT1C) is a dominantly inherited motor and sensory neuropathy. Despite human genetic evidence linking missense mutations in SIMPLE to CMT1C, the in vivo role of CMT1C-linked SIMPLE mutations remains undetermined. To investigate the molecular mechanism underlying CMT1C pathogenesis, we generated transgenic mice expressing either wild-type or CMT1C-linked W116G human SIMPLE. Mice expressing mutant, but not wild type, SIMPLE develop a late-onset motor and sensory neuropathy that recapitulates key clinical features of CMT1C disease. SIMPLE mutant mice exhibit motor and sensory behavioral impairments accompanied by decreased motor and sensory nerve conduction velocity and reduced compound muscle action potential amplitude. This neuropathy phenotype is associated with focally infolded myelin loops that protrude into the axons at paranodal regions and near Schmidt–Lanterman incisures of peripheral nerves. We find that myelin infolding is often linked to constricted axons with signs of impaired axonal transport and to paranodal defects and abnormal organization of the node of Ranvier. Our findings support that SIMPLE mutation disrupts myelin homeostasis and causes peripheral neuropathy via a combination of toxic gain-of-function and dominant-negative mechanisms. The results from this study suggest that myelin infolding and paranodal damage may represent pathogenic precursors preceding demyelination and axonal degeneration in CMT1C patients. PMID:23359569

Mycobacterium avium restriction fragment length polymorphism-IS IS1245 and the simple double repetitive element polymerase chain reaction typing method to screen genetic diversity in Brazilian strains.

PubMed

Sequeira, Patrícia Carvalho de; Fonseca, Leila de Souza; Silva, Marlei Gomes da; Saad, Maria Helena Féres

2005-11-01

Simple double repetitive element polymerase chain reaction (MaDRE-PCR) and Pvu II-IS1245 restriction fragment length polymorphism (RFLP) typing methods were used to type 41 Mycobacterium avium isolates obtained from 14 AIDS inpatients and 10 environment and animals specimens identified among 53 mycobacteria isolated from 237 food, chicken, and pig. All environmental and animals strains showed orphan patterns by both methods. By MaDRE-PCR four patients, with multiple isolates, showed different patterns, suggesting polyclonal infection that was confirmed by RFLP in two of them. This first evaluation of MaDRE-PCR on Brazilian M. avium strains demonstrated that the method seems to be useful as simple and less expensive typing method for screening genetic diversity in M. avium strains on selected epidemiological studies, although with limitation on analysis identical patterns except for one band.

Direct power comparisons between simple LOD scores and NPL scores for linkage analysis in complex diseases.

PubMed

Abreu, P C; Greenberg, D A; Hodge, S E

1999-09-01

Several methods have been proposed for linkage analysis of complex traits with unknown mode of inheritance. These methods include the LOD score maximized over disease models (MMLS) and the "nonparametric" linkage (NPL) statistic. In previous work, we evaluated the increase of type I error when maximizing over two or more genetic models, and we compared the power of MMLS to detect linkage, in a number of complex modes of inheritance, with analysis assuming the true model. In the present study, we compare MMLS and NPL directly. We simulated 100 data sets with 20 families each, using 26 generating models: (1) 4 intermediate models (penetrance of heterozygote between that of the two homozygotes); (2) 6 two-locus additive models; and (3) 16 two-locus heterogeneity models (admixture alpha = 1.0,.7,.5, and.3; alpha = 1.0 replicates simple Mendelian models). For LOD scores, we assumed dominant and recessive inheritance with 50% penetrance. We took the higher of the two maximum LOD scores and subtracted 0.3 to correct for multiple tests (MMLS-C). We compared expected maximum LOD scores and power, using MMLS-C and NPL as well as the true model. Since NPL uses only the affected family members, we also performed an affecteds-only analysis using MMLS-C. The MMLS-C was both uniformly more powerful than NPL for most cases we examined, except when linkage information was low, and close to the results for the true model under locus heterogeneity. We still found better power for the MMLS-C compared with NPL in affecteds-only analysis. The results show that use of two simple modes of inheritance at a fixed penetrance can have more power than NPL when the trait mode of inheritance is complex and when there is heterogeneity in the data set.

Truss Optimization for a Manned Nuclear Electric Space Vehicle using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Benford, Andrew; Tinker, Michael L.

2004-01-01

The purpose of this paper is to utilize the genetic algorithm (GA) optimization method for structural design of a nuclear propulsion vehicle. Genetic algorithms provide a guided, random search technique that mirrors biological adaptation. To verify the GA capabilities, other traditional optimization methods were used to generate results for comparison to the GA results, first for simple two-dimensional structures, and then for full-scale three-dimensional truss designs.

The potential of genetic algorithms for conceptual design of rotor systems

NASA Technical Reports Server (NTRS)

Crossley, William A.; Wells, Valana L.; Laananen, David H.

1993-01-01

The capabilities of genetic algorithms as a non-calculus based, global search method make them potentially useful in the conceptual design of rotor systems. Coupling reasonably simple analysis tools to the genetic algorithm was accomplished, and the resulting program was used to generate designs for rotor systems to match requirements similar to those of both an existing helicopter and a proposed helicopter design. This provides a comparison with the existing design and also provides insight into the potential of genetic algorithms in design of new rotors.

Drift as a mechanism for cultural change: an example from baby names.

PubMed Central

Hahn, Matthew W; Bentley, R Alexander

2003-01-01

In the social sciences, there is currently no consensus on the mechanism by which cultural elements come and go in human society. For elements that are value-neutral, an appropriate null model may be one of random copying between individuals in the population. We show that the frequency distributions of baby names used in the United States in each decade of the twentieth century, for both males and females, obey a power law that is maintained over 100 years even though the population is growing, names are being introduced and lost every decade and large changes in the frequencies of specific names are common. We show that these distributions are satisfactorily explained by a simple process in which individuals randomly copy names from each other, a process that is analogous to the infinite-allele model of population genetics with random genetic drift. By its simplicity, this model provides a powerful null hypothesis for cultural change. It further explains why a few elements inevitably become highly popular, even if they have no intrinsic superiority over alternatives. Random copying could potentially explain power law distributions in other cultural realms, including the links on the World Wide Web. PMID:12952655

A Data-Driven Approach to Develop Physically Sound Predictors: Application to Depth-Averaged Velocities and Drag Coefficients on Vegetated Flows

NASA Astrophysics Data System (ADS)

Tinoco, R. O.; Goldstein, E. B.; Coco, G.

2016-12-01

We use a machine learning approach to seek accurate, physically sound predictors, to estimate two relevant flow parameters for open-channel vegetated flows: mean velocities and drag coefficients. A genetic programming algorithm is used to find a robust relationship between properties of the vegetation and flow parameters. We use data published from several laboratory experiments covering a broad range of conditions to obtain: a) in the case of mean flow, an equation that matches the accuracy of other predictors from recent literature while showing a less complex structure, and b) for drag coefficients, a predictor that relies on both single element and array parameters. We investigate different criteria for dataset size and data selection to evaluate their impact on the resulting predictor, as well as simple strategies to obtain only dimensionally consistent equations, and avoid the need for dimensional coefficients. The results show that a proper methodology can deliver physically sound models representative of the processes involved, such that genetic programming and machine learning techniques can be used as powerful tools to study complicated phenomena and develop not only purely empirical, but "hybrid" models, coupling results from machine learning methodologies into physics-based models.

Information and redundancy: key concepts in understanding the genetic control of health and intelligence.

PubMed

Morris, J A

1999-08-01

A model is proposed in which information from the environment is analysed by complex biological decision-making systems which are highly redundant. A correct response is intelligent behaviour which preserves health; incorrect responses lead to disease. Mutations in genes which code for the redundant systems will accumulate in the genome and impair decision-making. The number of mutant genes will depend upon a balance between the new mutation rate per generation and systems of elimination based on synergistic interaction in redundant systems. This leads to a polygenic pattern of inheritance for intelligence and the common diseases. The model also gives a simple explanation for some of the hitherto puzzling aspects of work on the genetic basis of intelligence including the recorded rise in IQ this century. There is a prediction that health, intelligence and socio-economic position will be correlated generating a health differential in the social hierarchy. Furthermore, highly competitive societies will place those least able to cope in the harshest environment and this will impair health overall. The model points to a need for population monitoring of somatic mutation in order to preserve the health and intelligence of future generations.

Medaka: a promising model animal for comparative population genomics

PubMed Central

Matsumoto, Yoshifumi; Oota, Hiroki; Asaoka, Yoichi; Nishina, Hiroshi; Watanabe, Koji; Bujnicki, Janusz M; Oda, Shoji; Kawamura, Shoji; Mitani, Hiroshi

2009-01-01

Background Within-species genome diversity has been best studied in humans. The international HapMap project has revealed a tremendous amount of single-nucleotide polymorphisms (SNPs) among humans, many of which show signals of positive selection during human evolution. In most of the cases, however, functional differences between the alleles remain experimentally unverified due to the inherent difficulty of human genetic studies. It would therefore be highly useful to have a vertebrate model with the following characteristics: (1) high within-species genetic diversity, (2) a variety of gene-manipulation protocols already developed, and (3) a completely sequenced genome. Medaka (Oryzias latipes) and its congeneric species, tiny fresh-water teleosts distributed broadly in East and Southeast Asia, meet these criteria. Findings Using Oryzias species from 27 local populations, we conducted a simple screening of nonsynonymous SNPs for 11 genes with apparent orthology between medaka and humans. We found medaka SNPs for which the same sites in human orthologs are known to be highly differentiated among the HapMap populations. Importantly, some of these SNPs show signals of positive selection. Conclusion These results indicate that medaka is a promising model system for comparative population genomics exploring the functional and adaptive significance of allelic differentiations. PMID:19426554

Biophysical model of prokaryotic diversity in geothermal hot springs.

PubMed

Klales, Anna; Duncan, James; Nett, Elizabeth Janus; Kane, Suzanne Amador

2012-02-01

Recent studies of photosynthetic bacteria living in geothermal hot spring environments have revealed surprisingly complex ecosystems with an unexpected level of genetic diversity. One case of particular interest involves the distribution along hot spring thermal gradients of genetically distinct bacterial strains that differ in their preferred temperatures for reproduction and photosynthesis. In such systems, a single variable, temperature, defines the relevant environmental variation. In spite of this, each region along the thermal gradient exhibits multiple strains of photosynthetic bacteria adapted to several distinct thermal optima, rather than a single thermal strain adapted to the local environmental temperature. Here we analyze microbiology data from several ecological studies to show that the thermal distribution data exhibit several universal features independent of location and specific bacterial strain. These include the distribution of optimal temperatures of different thermal strains and the functional dependence of the net population density on temperature. We present a simple population dynamics model of these systems that is highly constrained by biophysical data and by physical features of the environment. This model can explain in detail the observed thermal population distributions, as well as certain features of population dynamics observed in laboratory studies of the same organisms. © 2012 American Physical Society

Direct protein-protein conjugation by genetically introducing bioorthogonal functional groups into proteins.

PubMed

Kim, Sanggil; Ko, Wooseok; Sung, Bong Hyun; Kim, Sun Chang; Lee, Hyun Soo

2016-11-15

Proteins often function as complex structures in conjunction with other proteins. Because these complex structures are essential for sophisticated functions, developing protein-protein conjugates has gained research interest. In this study, site-specific protein-protein conjugation was performed by genetically incorporating an azide-containing amino acid into one protein and a bicyclononyne (BCN)-containing amino acid into the other. Three to four sites in each of the proteins were tested for conjugation efficiency, and three combinations showed excellent conjugation efficiency. The genetic incorporation of unnatural amino acids (UAAs) is technically simple and produces the mutant protein in high yield. In addition, the conjugation reaction can be conducted by simple mixing, and does not require additional reagents or linker molecules. Therefore, this method may prove very useful for generating protein-protein conjugates and protein complexes of biochemical significance. Copyright © 2016. Published by Elsevier Ltd.

Application of Inter-Simple Sequence Repeat Markers in the Analysis of Populations of the Chagas Disease Vector Triatoma infestans (Hemiptera, Reduviidae)

PubMed Central

Pérez de Rosas, Alicia R.; Restelli, María F.; Fernández, Cintia J.; Blariza, María J.; García, Beatriz A.

2017-01-01

Here we apply inter-simple sequence repeat (ISSR) markers to explore the fine-scale genetic structure and dispersal in populations of Triatoma infestans. Five selected primers from 30 primers were used to amplify ISSRs by polymerase chain reaction. A total of 90 polymorphic bands were detected across 134 individuals captured from 11 peridomestic sites from the locality of San Martín (Capayán Department, Catamarca Province, Argentina). Significant levels of genetic differentiation suggest limited gene flow among sampling sites. Spatial autocorrelation analysis confirms that dispersal occurs on the scale of ∼469 m, suggesting that insecticide spraying should be extended at least within a radius of ∼500 m around the infested area. Moreover, Bayesian clustering algorithms indicated genetic exchange among different sites analyzed, supporting the hypothesis of an important role of peridomestic structures in the process of reinfestation. PMID:28115670

A Simple Sequence Repeat- and Single-Nucleotide Polymorphism-Based Genetic Linkage Map of the Brown Planthopper, Nilaparvata lugens

PubMed Central

Jairin, Jirapong; Kobayashi, Tetsuya; Yamagata, Yoshiyuki; Sanada-Morimura, Sachiyo; Mori, Kazuki; Tashiro, Kosuke; Kuhara, Satoru; Kuwazaki, Seigo; Urio, Masahiro; Suetsugu, Yoshitaka; Yamamoto, Kimiko; Matsumura, Masaya; Yasui, Hideshi

2013-01-01

In this study, we developed the first genetic linkage map for the major rice insect pest, the brown planthopper (BPH, Nilaparvata lugens). The linkage map was constructed by integrating linkage data from two backcross populations derived from three inbred BPH strains. The consensus map consists of 474 simple sequence repeats, 43 single-nucleotide polymorphisms, and 1 sequence-tagged site, for a total of 518 markers at 472 unique positions in 17 linkage groups. The linkage groups cover 1093.9 cM, with an average distance of 2.3 cM between loci. The average number of marker loci per linkage group was 27.8. The sex-linkage group was identified by exploiting X-linked and Y-specific markers. Our linkage map and the newly developed markers used to create it constitute an essential resource and a useful framework for future genetic analyses in BPH. PMID:23204257

Genetic diversity studies in pea (Pisum sativum L.) using simple sequence repeat markers.

PubMed

Kumari, P; Basal, N; Singh, A K; Rai, V P; Srivastava, C P; Singh, P K

2013-03-13

The genetic diversity among 28 pea (Pisum sativum L.) genotypes was analyzed using 32 simple sequence repeat markers. A total of 44 polymorphic bands, with an average of 2.1 bands per primer, were obtained. The polymorphism information content ranged from 0.657 to 0.309 with an average of 0.493. The variation in genetic diversity among these cultivars ranged from 0.11 to 0.73. Cluster analysis based on Jaccard's similarity coefficient using the unweighted pair-group method with arithmetic mean (UPGMA) revealed 2 distinct clusters, I and II, comprising 6 and 22 genotypes, respectively. Cluster II was further differentiated into 2 subclusters, IIA and IIB, with 12 and 10 genotypes, respectively. Principal component (PC) analysis revealed results similar to those of UPGMA. The first, second, and third PCs contributed 21.6, 16.1, and 14.0% of the variation, respectively; cumulative variation of the first 3 PCs was 51.7%.

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns

PubMed Central

Cruchet, Steeve; Gustafson, Kyle; Benton, Richard; Floreano, Dario

2015-01-01

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs—locomotor bouts—matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior. PMID:26600381

Combining genetic and physiological data to identify predictors of lifetime reproductive success and the effect of selection on these predictors on underlying fertility traits.

PubMed

Dennis, N A; Stachowicz, K; Visser, B; Hely, F S; Berg, D K; Friggens, N C; Amer, P R; Meier, S; Burke, C R

2018-04-01

Fertility of the dairy cow relies on complex interactions between genetics, physiology, and management. Mathematical modeling can combine a range of information sources to facilitate informed predictions of cow fertility in scenarios that are difficult to evaluate empirically. We have developed a stochastic model that incorporates genetic and physiological data from more than 70 published reports on a wide range of fertility-related traits in dairy cattle. The model simulates pedigree, random mating, genetically correlated traits (in the form of breeding values for traits such as hours in estrus, estrous cycle length, age at puberty, milk yield, and so on), and interacting environmental variables. This model was used to generate a large simulated data set (200,000 cows replicated 100 times) of herd records within a seasonal dairy production system (based on an average New Zealand system). Using these simulated data, we investigated the genetic component of lifetime reproductive success (LRS), which, in reality, would be impractical to assess empirically. We defined LRS as the total number of times, during her lifetime, a cow calved within the first 42 d of the calving season. Sire estimated breeding values for LRS and other traits were calculated using simulated daughter records. Daughter pregnancy rate in the first lactation (PD_1) was the strongest single predictor of a sire's genetic merit for LRS (R 2 = 0.81). A simple predictive model containing PD_1, calving date for the second season and calving rate in the first season provided a good estimate of sire LRS (R 2 = 0.97). Daughters from sires with extremely high (n = 99,995 daughters, sire LRS = +0.70) or low (n = 99,635 daughters, sire LRS = -0.73) LRS estimated breeding values were compared over a single generation. Of the 14 underlying component traits of fertility, 12 were divergent between the 2 lines. This suggests that genetic variation in female fertility has a complex and multifactorial genetic basis. When simulated phenotypes were compared, daughters of the high LRS sires (HiFERT) reached puberty 44.5 d younger and calved ∼14 d younger at each parity than daughters from low LRS sires (LoFERT). Despite having a much lower genetic potential for milk production (-400 L/lactation) than LoFERT cows, HiFERT cows produced 33% more milk over their lifetime due to additional lactations before culling. In summary, this simulation model suggests that LRS contributes substantially to cow productivity, and novel selection criteria would facilitate a more accurate prediction at a younger age. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

The zipper effect: Why different positions along the chromosome suffer different selection pressures

NASA Astrophysics Data System (ADS)

de Oliveira, P. M. C.; Moss de Oliveira, S.

2011-02-01

Variability within diploid sexual populations comes from two ingredients: mutations and recombination (or crossing-over). On average, the first introduces genetic defects in offspring genomes, while the second is a mechanism which tends to eliminate them, continuously “cleaning” the population genetic pool from harmful mutations along the generations. Here, we propose that loci near the chromosome tips are more effectively cleaned by the recombination mechanism than loci near the chromosome centre. This result implies that clusters of neighbouring, orchestrated-functioning genes, supposed to be more robust against the effects of genetic mutations, are more likely found near the chromosome centres, while isolated genes are more likely found near the tips. We confirm the tip-centre asymmetry through a simple computer agent-based model. In order to test this effect in reality, we also analyse as an example the particular case of HOX genes distributed along the 24 human chromosomes and verify that indeed, most HOX genes belong to such clustered networks located near the chromosome centres. Accordingly, isolated HOX genes are located closer to the tips.

Coalescent Times and Patterns of Genetic Diversity in Species with Facultative Sex: Effects of Gene Conversion, Population Structure, and Heterogeneity.

PubMed

Hartfield, Matthew; Wright, Stephen I; Agrawal, Aneil F

2016-01-01

Many diploid organisms undergo facultative sexual reproduction. However, little is currently known concerning the distribution of neutral genetic variation among facultative sexual organisms except in very simple cases. Understanding this distribution is important when making inferences about rates of sexual reproduction, effective population size, and demographic history. Here we extend coalescent theory in diploids with facultative sex to consider gene conversion, selfing, population subdivision, and temporal and spatial heterogeneity in rates of sex. In addition to analytical results for two-sample coalescent times, we outline a coalescent algorithm that accommodates the complexities arising from partial sex; this algorithm can be used to generate multisample coalescent distributions. A key result is that when sex is rare, gene conversion becomes a significant force in reducing diversity within individuals. This can reduce genomic signatures of infrequent sex (i.e., elevated within-individual allelic sequence divergence) or entirely reverse the predicted patterns. These models offer improved methods for assessing null patterns of molecular variation in facultative sexual organisms. Copyright © 2016 by the Genetics Society of America.

Period doubling induced by thermal noise amplification in genetic circuits

PubMed Central

Ruocco, G.; Fratalocchi, A.

2014-01-01

Rhythms of life are dictated by oscillations, which take place in a wide rage of biological scales. In bacteria, for example, oscillations have been proven to control many fundamental processes, ranging from gene expression to cell divisions. In genetic circuits, oscillations originate from elemental block such as autorepressors and toggle switches, which produce robust and noise-free cycles with well defined frequency. In some circumstances, the oscillation period of biological functions may double, thus generating bistable behaviors whose ultimate origin is at the basis of intense investigations. Motivated by brain studies, we here study an “elemental” genetic circuit, where a simple nonlinear process interacts with a noisy environment. In the proposed system, nonlinearity naturally arises from the mechanism of cooperative stability, which regulates the concentration of a protein produced during a transcription process. In this elemental model, bistability results from the coherent amplification of environmental fluctuations due to a stochastic resonance of nonlinear origin. This suggests that the period doubling observed in many biological functions might result from the intrinsic interplay between nonlinearity and thermal noise. PMID:25404210

Period doubling induced by thermal noise amplification in genetic circuits.

PubMed

Ruocco, G; Fratalocchi, A

2014-11-18

Rhythms of life are dictated by oscillations, which take place in a wide rage of biological scales. In bacteria, for example, oscillations have been proven to control many fundamental processes, ranging from gene expression to cell divisions. In genetic circuits, oscillations originate from elemental block such as autorepressors and toggle switches, which produce robust and noise-free cycles with well defined frequency. In some circumstances, the oscillation period of biological functions may double, thus generating bistable behaviors whose ultimate origin is at the basis of intense investigations. Motivated by brain studies, we here study an "elemental" genetic circuit, where a simple nonlinear process interacts with a noisy environment. In the proposed system, nonlinearity naturally arises from the mechanism of cooperative stability, which regulates the concentration of a protein produced during a transcription process. In this elemental model, bistability results from the coherent amplification of environmental fluctuations due to a stochastic resonance of nonlinear origin. This suggests that the period doubling observed in many biological functions might result from the intrinsic interplay between nonlinearity and thermal noise.

Economic and developmental considerations for pharmacogenomic technology.

PubMed

Vernon, John A; Johnson, Scott J; Hughen, W Keener; Trujillo, Antonio

2006-01-01

The pharmaceutical industry's core business is the innovation, development and marketing of new drugs. Pharmacogenetic (PG) testing and technology has the potential to increase a drug's value in many ways. A critical issue for the industry is whether products in development should be teamed with genetic tests that could segment the total population into responders and non-responders. In this paper we use a cost-effectiveness framework to model the strategic decision-making considerations by pharmaceutical manufacturers as they relate to drug development and the new technology of PG (the science of using genetic markers to predict drug response). In a simple, static, one-period model we consider three drug development strategies: a drug is exclusively developed and marketed to patients with a particular genetic marker; no distinguishing among patients based on the expression of a genetic marker is made (traditional approach); and a strategy whereby a drug is marketed to patients both with and without the genetic marker but there is price discrimination between the two subpopulations. We developed three main principles: revenues under a strategy targeting only the responder subpopulation will never generate more revenue than that which could have been obtained under a traditional approach; total revenues under a targeted PG strategy will be less than that under a traditional approach but higher than a naive [corrected] view would believe them to be; and a traditional [corrected] approach will earn the same total revenues as a price discrimination strategy, assuming no intermarket arbitrage. While these principles relate to the singular (and quite narrow) consideration of drug revenues, they may nevertheless partially explain why PG is not being used as widely as was predicted several years ago when the technology first became available, especially in terms of pharmaceutical manufacturer-developed tests.

Predicting human genetic interactions from cancer genome evolution.

PubMed

Lu, Xiaowen; Megchelenbrink, Wout; Notebaart, Richard A; Huynen, Martijn A

2015-01-01

Synthetic Lethal (SL) genetic interactions play a key role in various types of biological research, ranging from understanding genotype-phenotype relationships to identifying drug-targets against cancer. Despite recent advances in empirical measuring SL interactions in human cells, the human genetic interaction map is far from complete. Here, we present a novel approach to predict this map by exploiting patterns in cancer genome evolution. First, we show that empirically determined SL interactions are reflected in various gene presence, absence, and duplication patterns in hundreds of cancer genomes. The most evident pattern that we discovered is that when one member of an SL interaction gene pair is lost, the other gene tends not to be lost, i.e. the absence of co-loss. This observation is in line with expectation, because the loss of an SL interacting pair will be lethal to the cancer cell. SL interactions are also reflected in gene expression profiles, such as an under representation of cases where the genes in an SL pair are both under expressed, and an over representation of cases where one gene of an SL pair is under expressed, while the other one is over expressed. We integrated the various previously unknown cancer genome patterns and the gene expression patterns into a computational model to identify SL pairs. This simple, genome-wide model achieves a high prediction power (AUC = 0.75) for known genetic interactions. It allows us to present for the first time a comprehensive genome-wide list of SL interactions with a high estimated prediction precision, covering up to 591,000 gene pairs. This unique list can potentially be used in various application areas ranging from biotechnology to medical genetics.

Developing metapopulation connectivity criteria from genetic and habitat data to recover the endangered Mexican wolf.

PubMed

Carroll, Carlos; Fredrickson, Richard J; Lacy, Robert C

2014-02-01

Restoring connectivity between fragmented populations is an important tool for alleviating genetic threats to endangered species. Yet recovery plans typically lack quantitative criteria for ensuring such population connectivity. We demonstrate how models that integrate habitat, genetic, and demographic data can be used to develop connectivity criteria for the endangered Mexican wolf (Canis lupus baileyi), which is currently being restored to the wild from a captive population descended from 7 founders. We used population viability analysis that incorporated pedigree data to evaluate the relation between connectivity and persistence for a restored Mexican wolf metapopulation of 3 populations of equal size. Decreasing dispersal rates greatly increased extinction risk for small populations (<150-200), especially as dispersal rates dropped below 0.5 genetically effective migrants per generation. We compared observed migration rates in the Northern Rocky Mountains (NRM) wolf metapopulation to 2 habitat-based effective distance metrics, least-cost and resistance distance. We then used effective distance between potential primary core populations in a restored Mexican wolf metapopulation to evaluate potential dispersal rates. Although potential connectivity was lower in the Mexican wolf versus the NRM wolf metapopulation, a connectivity rate of >0.5 genetically effective migrants per generation may be achievable via natural dispersal under current landscape conditions. When sufficient data are available, these methods allow planners to move beyond general aspirational connectivity goals or rules of thumb to develop objective and measurable connectivity criteria that more effectively support species recovery. The shift from simple connectivity rules of thumb to species-specific analyses parallels the previous shift from general minimum-viable-population thresholds to detailed viability modeling in endangered species recovery planning. © 2013 Society for Conservation Biology.

Narrow Bottlenecks Affect Pea Seedborne Mosaic Virus Populations during Vertical Seed Transmission but not during Leaf Colonization

PubMed Central

Johansen, Elisabeth Ida; Simon, Vincent; Jacquemond, Mireille; Senoussi, Rachid

2014-01-01

The effective size of populations (Ne) determines whether selection or genetic drift is the predominant force shaping their genetic structure and evolution. Populations having high Ne adapt faster, as selection acts more intensely, than populations having low Ne, where random effects of genetic drift dominate. Estimating Ne for various steps of plant virus life cycle has been the focus of several studies in the last decade, but no estimates are available for the vertical transmission of plant viruses, although virus seed transmission is economically significant in at least 18% of plant viruses in at least one plant species. Here we study the co-dynamics of two variants of Pea seedborne mosaic virus (PSbMV) colonizing leaves of pea plants (Pisum sativum L.) during the whole flowering period, and their subsequent transmission to plant progeny through seeds. Whereas classical estimators of Ne could be used for leaf infection at the systemic level, as virus variants were equally competitive, dedicated stochastic models were needed to estimate Ne during vertical transmission. Very little genetic drift was observed during the infection of apical leaves, with Ne values ranging from 59 to 216. In contrast, a very drastic genetic drift was observed during vertical transmission, with an average number of infectious virus particles contributing to the infection of a seedling from an infected mother plant close to one. A simple model of vertical transmission, assuming a cumulative action of virus infectious particles and a virus density threshold required for vertical transmission to occur fitted the experimental data very satisfactorily. This study reveals that vertically-transmitted viruses endure bottlenecks as narrow as those imposed by horizontal transmission. These bottlenecks are likely to slow down virus adaptation and could decrease virus fitness and virulence. PMID:24415934

Simple, Inexpensive, and Rapid Way to Produce Bacillus subtilis Spores for the Guthrie Bioassay

PubMed Central

Franklin, Martha L.; Clark, William A.

1981-01-01

Esculin agar has been found to be a simple, inexpensive, rapid, and reliable means to promote production of spores of inhibitor-sensitive clones of Bacillus subtilis strains ATCC 6051 and 6633 for use in the Guthrie bioassay screening tests for genetic metabolic disorders. Images PMID:6790564

Binary encoding of multiplexed images in mixed noise.

PubMed

Lalush, David S

2008-09-01

Binary coding of multiplexed signals and images has been studied in the context of spectroscopy with models of either purely constant or purely proportional noise, and has been shown to result in improved noise performance under certain conditions. We consider the case of mixed noise in an imaging system consisting of multiple individually-controllable sources (X-ray or near-infrared, for example) shining on a single detector. We develop a mathematical model for the noise in such a system and show that the noise is dependent on the properties of the binary coding matrix and on the average number of sources used for each code. Each binary matrix has a characteristic linear relationship between the ratio of proportional-to-constant noise and the noise level in the decoded image. We introduce a criterion for noise level, which is minimized via a genetic algorithm search. The search procedure results in the discovery of matrices that outperform the Hadamard S-matrices at certain levels of mixed noise. Simulation of a seven-source radiography system demonstrates that the noise model predicts trends and rank order of performance in regions of nonuniform images and in a simple tomosynthesis reconstruction. We conclude that the model developed provides a simple framework for analysis, discovery, and optimization of binary coding patterns used in multiplexed imaging systems.

A null model for microbial diversification

PubMed Central

Straub, Timothy J.

2017-01-01

Whether prokaryotes (Bacteria and Archaea) are naturally organized into phenotypically and genetically cohesive units comparable to animal or plant species remains contested, frustrating attempts to estimate how many such units there might be, or to identify the ecological roles they play. Analyses of gene sequences in various closely related prokaryotic groups reveal that sequence diversity is typically organized into distinct clusters, and processes such as periodic selection and extensive recombination are understood to be drivers of cluster formation (“speciation”). However, observed patterns are rarely compared with those obtainable with simple null models of diversification under stochastic lineage birth and death and random genetic drift. Via a combination of simulations and analyses of core and phylogenetic marker genes, we show that patterns of diversity for the genera Escherichia, Neisseria, and Borrelia are generally indistinguishable from patterns arising under a null model. We suggest that caution should thus be taken in interpreting observed clustering as a result of selective evolutionary forces. Unknown forces do, however, appear to play a role in Helicobacter pylori, and some individual genes in all groups fail to conform to the null model. Taken together, we recommend the presented birth−death model as a null hypothesis in prokaryotic speciation studies. It is only when the real data are statistically different from the expectations under the null model that some speciation process should be invoked. PMID:28630293

Understanding the complexities of Salmonella-host crosstalk as revealed by in vivo model organisms.

PubMed

Verma, Smriti; Srikanth, Chittur V

2015-07-01

Foodborne infections caused by non-typhoidal Salmonellae, such as Salmonella enterica serovar Typhimurium (ST), pose a major challenge in the developed and developing world. With constant rise of drug-resistant strains, understanding the epidemiology, microbiology, pathogenesis and host-pathogen interactions biology is a mandatory requirement to enable health systems to be ready to combat these illnesses. Patient data from hospitals, at least from some parts of the world, have aided in epidemiological understanding of ST-mediated disease. Most of the other aspects connected to Salmonella-host crosstalk have come from model systems that offer convenience, genetic tractability and low maintenance costs that make them extremely valuable tools. Complex model systems such as the bovine model have helped in understanding key virulence factors needed for infection. Simple systems such as fruit flies and Caenorhabditis elegans have aided in identification of novel virulence factors, host pathways and mechanistic details of interactions. Some of the path-breaking concepts of the field have come from mice model of ST colitis, which allows genetic manipulations as well as high degree of similarity to human counterpart. Together, they are invaluable for correlating in vitro findings of ST-induced disease progression in vivo. The current review is a compilation of various advances of ST-host interactions at cellular and molecular levels that has come from investigations involving model organisms. © 2015 International Union of Biochemistry and Molecular Biology.

A Semiparametric Approach for Composite Functional Mapping of Dynamic Quantitative Traits

PubMed Central

Yang, Runqing; Gao, Huijiang; Wang, Xin; Zhang, Ji; Zeng, Zhao-Bang; Wu, Rongling

2007-01-01

Functional mapping has emerged as a powerful tool for mapping quantitative trait loci (QTL) that control developmental patterns of complex dynamic traits. Original functional mapping has been constructed within the context of simple interval mapping, without consideration of separate multiple linked QTL for a dynamic trait. In this article, we present a statistical framework for mapping QTL that affect dynamic traits by capitalizing on the strengths of functional mapping and composite interval mapping. Within this so-called composite functional-mapping framework, functional mapping models the time-dependent genetic effects of a QTL tested within a marker interval using a biologically meaningful parametric function, whereas composite interval mapping models the time-dependent genetic effects of the markers outside the test interval to control the genome background using a flexible nonparametric approach based on Legendre polynomials. Such a semiparametric framework was formulated by a maximum-likelihood model and implemented with the EM algorithm, allowing for the estimation and the test of the mathematical parameters that define the QTL effects and the regression coefficients of the Legendre polynomials that describe the marker effects. Simulation studies were performed to investigate the statistical behavior of composite functional mapping and compare its advantage in separating multiple linked QTL as compared to functional mapping. We used the new mapping approach to analyze a genetic mapping example in rice, leading to the identification of multiple QTL, some of which are linked on the same chromosome, that control the developmental trajectory of leaf age. PMID:17947431

Inference of population splits and mixtures from genome-wide allele frequency data.

PubMed

Pickrell, Joseph K; Pritchard, Jonathan K

2012-01-01

Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In our model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data, we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.com.

Off-Angle Iris Correction Methods

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

Santos-Villalobos, Hector J; Thompson, Joseph T; Karakaya, Mahmut

In many real world iris recognition systems obtaining consistent frontal images is problematic do to inexperienced or uncooperative users, untrained operators, or distracting environments. As a result many collected images are unusable by modern iris matchers. In this chapter we present four methods for correcting off-angle iris images to appear frontal which makes them compatible with existing iris matchers. The methods include an affine correction, a retraced model of the human eye, measured displacements, and a genetic algorithm optimized correction. The affine correction represents a simple way to create an iris image that appears frontal but it does not accountmore » for refractive distortions of the cornea. The other method account for refraction. The retraced model simulates the optical properties of the cornea. The other two methods are data driven. The first uses optical flow to measure the displacements of the iris texture when compared to frontal images of the same subject. The second uses a genetic algorithm to learn a mapping that optimizes the Hamming Distance scores between off-angle and frontal images. In this paper we hypothesize that the biological model presented in our earlier work does not adequately account for all variations in eye anatomy and therefore the two data-driven approaches should yield better performance. Results are presented using the commercial VeriEye matcher that show that the genetic algorithm method clearly improves over prior work and makes iris recognition possible up to 50 degrees off-angle.« less

Applications of a formal approach to decipher discrete genetic networks.

PubMed

Corblin, Fabien; Fanchon, Eric; Trilling, Laurent

2010-07-20

A growing demand for tools to assist the building and analysis of biological networks exists in systems biology. We argue that the use of a formal approach is relevant and applicable to address questions raised by biologists about such networks. The behaviour of these systems being complex, it is essential to exploit efficiently every bit of experimental information. In our approach, both the evolution rules and the partial knowledge about the structure and the behaviour of the network are formalized using a common constraint-based language. In this article our formal and declarative approach is applied to three biological applications. The software environment that we developed allows to specifically address each application through a new class of biologically relevant queries. We show that we can describe easily and in a formal manner the partial knowledge about a genetic network. Moreover we show that this environment, based on a constraint algorithmic approach, offers a wide variety of functionalities, going beyond simple simulations, such as proof of consistency, model revision, prediction of properties, search for minimal models relatively to specified criteria. The formal approach proposed here deeply changes the way to proceed in the exploration of genetic and biochemical networks, first by avoiding the usual trial-and-error procedure, and second by placing the emphasis on sets of solutions, rather than a single solution arbitrarily chosen among many others. Last, the constraint approach promotes an integration of model and experimental data in a single framework.

Survival of mutations arising during invasions

PubMed Central

Miller, Judith R

2010-01-01

When a neutral mutation arises in an invading population, it quickly either dies out or ‘surfs’, i.e. it comes to occupy almost all the habitat available at its time of origin. Beneficial mutations can also surf, as can deleterious mutations over finite time spans. We develop descriptive statistical models that quantify the relationship between the probability that a mutation will surf and demographic parameters for a cellular automaton model of surfing. We also provide a simple analytic model that performs well at predicting the probability of surfing for neutral and beneficial mutations in one dimension. The results suggest that factors – possibly including even abiotic factors – that promote invasion success may also increase the probability of surfing and associated adaptive genetic change, conditioned on such success. PMID:25567912

The genetic architecture of a complex ecological trait: host plant use in the specialist moth, HELIOTHIS SUBFLEXA

USDA-ARS?s Scientific Manuscript database

The study of the genetic basis of ecological adaptation remains in its infancy, and most studies have focused on phenotypically simple traits. Host plant use by herbivorous insects is phenotypically complex. While research has illuminated the evolutionary determinants of host use, knowledge of its...

Loblolly pine SSR markers for shortleaf pine genetics

Treesearch

C. Dana Nelson; Sedley Josserand; Craig S. Echt; Jeff Koppelman

2007-01-01

Simple sequence repeats (SSR) are highly informative DNA-based markers widely used in population genetic and linkage mapping studies. We have been developing PCR primer pairs for amplifying SSR markers for loblolly pine (Pinus taeda L.) using loblolly pine DNA and EST sequence data as starting materials. Fifty primer pairs known to reliably amplify...

Genetic diversity of Danthonia spicata (L.) Beauv. Based on genomic simple sequence repeat markers

USDA-ARS?s Scientific Manuscript database

Danthonia spicata, commonly known as poverty oatgrass, is a perennial bunch-type grass native to North America. D. spicata has dimorphic seed heads; the hypothesis is that terminal seed heads allow some level of outcrossing and axial seed heads are only self-fertilized. However, there is no genetic ...

Genetic noise mechanism for power-law switching in bacterial flagellar motors

NASA Astrophysics Data System (ADS)

Krivonosov, M. I.; Zaburdaev, V.; Denisov, S. V.; Ivanchenko, M. V.

2018-06-01

Switching of the direction of flagella rotations is the key control mechanism governing the chemotactic activity of E. coli and many other bacteria. Power-law distributions of switching times are most peculiar because their emergence cannot be deduced from simple thermodynamic arguments. Recently, it was suggested that by adding finite-time correlations into Gaussian fluctuations regulating the energy height of the barrier between the two rotation states, it is possible to generate switching statistics with an intermediate power-law asymptotics. By using a simple model of a regulatory pathway, we demonstrate that the required amount of correlated ‘noise’ can be produced by finite number fluctuations of reacting protein molecules, a condition common to the intracellular chemistry. The corresponding power-law exponent appears as a tunable characteristic controlled by parameters of the regulatory pathway network such as the equilibrium number of molecules, sensitivities, and the characteristic relaxation time.

Nick-free formation of reciprocal heteroduplexes: a simple solution to the topological problem.

PubMed Central

Wilson, J H

1979-01-01

Because the individual strands of DNA are intertwined, formation of heteroduplex structures between duplexes--as in presumed recombination intermediates--presents a topological puzzle, known as the winding problem. Previous approaches to this problem have assumed that single-strand breaks are required to permit formation of fully coiled heteroduplexes. This paper describes a simple, nick-free solution to the winding problem that satisfies all topological constraints. Homologous duplexes associated by their minor-groove surfaces can switch strand pairing to form reciprocal heteroduplexes that coil together into a compact, four-stranded helix throughout the region of pairing. Model building shows that this fused heteroduplex structure is plausible, being composed entirely of right-handed primary helices with Watson-Crick base pairing throughout. Its simplicity of formation, structural symmetry, and high degree of specificity are suggestive of a natural mechanism for alignment by base pairing between intact homologous duplexes. Implications for genetic recombination are discussed. Images PMID:291028

Non-overlapping Neural Networks in Hydra vulgaris.

PubMed

Dupre, Christophe; Yuste, Rafael

2017-04-24

To understand the emergent properties of neural circuits, it would be ideal to record the activity of every neuron in a behaving animal and decode how it relates to behavior. We have achieved this with the cnidarian Hydra vulgaris, using calcium imaging of genetically engineered animals to measure the activity of essentially all of its neurons. Although the nervous system of Hydra is traditionally described as a simple nerve net, we surprisingly find instead a series of functional networks that are anatomically non-overlapping and are associated with specific behaviors. Three major functional networks extend through the entire animal and are activated selectively during longitudinal contractions, elongations in response to light, and radial contractions, whereas an additional network is located near the hypostome and is active during nodding. These results demonstrate the functional sophistication of apparently simple nerve nets, and the potential of Hydra and other basal metazoans as a model system for neural circuit studies. Published by Elsevier Ltd.

Colorimetric Detection of Plasmodium vivax in Urine Using MSP10 Oligonucleotides and Gold Nanoparticles

PubMed Central

Alnasser, Yossef; Ferradas, Cusi; Clark, Taryn; Calderon, Maritza; Gurbillon, Alejandro; Gamboa, Dionicia; McKakpo, Uri S.; Quakyi, Isabella A.; Bosompem, Kwabena M.; Sullivan, David J.; Vinetz, Joseph M.; Gilman, Robert H.

2016-01-01

Plasmodium vivax is the most prevalent cause of human malaria in the world and can lead to severe disease with high potential for relapse. Its genetic and geographic diversities make it challenging to control. P. vivax is understudied and to achieve control of malaria in endemic areas, a rapid, accurate, and simple diagnostic tool is necessary. In this pilot study, we found that a colorimetric system using AuNPs and MSP10 DNA detection in urine can provide fast, easy, and inexpensive identification of P. vivax. The test exhibited promising sensitivity (84%), high specificity (97%), and only mild cross-reactivity with P. falciparum (21%). It is simple to use, with a visible color change that negates the need for a spectrometer, making it suitable for use in austere conditions. Using urine eliminates the need for finger-prick, increasing both the safety profile and patient acceptance of this model. PMID:27706158

Development of Simple Sequence Repeats (SSR) markers in Setaria italica (Poaceae) and cross-amplification in related species.

PubMed

Lin, Heng-Sheng; Chiang, Chih-Yun; Chang, Song-Bin; Kuoh, Chang-Sheng

2011-01-01

Foxtail millet is one of the world's oldest cultivated crops. It has been adopted as a model organism for providing a deeper understanding of plant biology. In this study, 45 simple sequence repeats (SSR) markers of Setaria italica were developed. These markers showing polymorphism were screened in 223 samples from 12 foxtail millet populations around Taiwan. The most common dinucleotide and trinucleotide repeat motifs are AC/TG (84.21%) and CAT (46.15%). The average number of alleles (N(a)), the average heterozygosities observed (H(o)) and expected (H(e)) are 3.73, 0.714, 0.587, respectively. In addition, 24 SSR markers had shown transferability to six related Poaceae species. These new markers provide tools for examining genetic relatedness among foxtail millet populations and other related species. It is suitable for germplasm management and protection in Poaceae.

Development of Simple Sequence Repeats (SSR) Markers in Setaria italica (Poaceae) and Cross-Amplification in Related Species

PubMed Central

Lin, Heng-Sheng; Chiang, Chih-Yun; Chang, Song-Bin; Kuoh, Chang-Sheng

2011-01-01

Foxtail millet is one of the world’s oldest cultivated crops. It has been adopted as a model organism for providing a deeper understanding of plant biology. In this study, 45 simple sequence repeats (SSR) markers of Setaria italica were developed. These markers showing polymorphism were screened in 223 samples from 12 foxtail millet populations around Taiwan. The most common dinucleotide and trinucleotide repeat motifs are AC/TG (84.21%) and CAT (46.15%). The average number of alleles (Na), the average heterozygosities observed (Ho) and expected (He) are 3.73, 0.714, 0.587, respectively. In addition, 24 SSR markers had shown transferability to six related Poaceae species. These new markers provide tools for examining genetic relatedness among foxtail millet populations and other related species. It is suitable for germplasm management and protection in Poaceae. PMID:22174636

Diversity analysis in Cannabis sativa based on large-scale development of expressed sequence tag-derived simple sequence repeat markers.

PubMed

Gao, Chunsheng; Xin, Pengfei; Cheng, Chaohua; Tang, Qing; Chen, Ping; Wang, Changbiao; Zang, Gonggu; Zhao, Lining

2014-01-01

Cannabis sativa L. is an important economic plant for the production of food, fiber, oils, and intoxicants. However, lack of sufficient simple sequence repeat (SSR) markers has limited the development of cannabis genetic research. Here, large-scale development of expressed sequence tag simple sequence repeat (EST-SSR) markers was performed to obtain more informative genetic markers, and to assess genetic diversity in cannabis (Cannabis sativa L.). Based on the cannabis transcriptome, 4,577 SSRs were identified from 3,624 ESTs. From there, a total of 3,442 complementary primer pairs were designed as SSR markers. Among these markers, trinucleotide repeat motifs (50.99%) were the most abundant, followed by hexanucleotide (25.13%), dinucleotide (16.34%), tetranucloetide (3.8%), and pentanucleotide (3.74%) repeat motifs, respectively. The AAG/CTT trinucleotide repeat (17.96%) was the most abundant motif detected in the SSRs. One hundred and seventeen EST-SSR markers were randomly selected to evaluate primer quality in 24 cannabis varieties. Among these 117 markers, 108 (92.31%) were successfully amplified and 87 (74.36%) were polymorphic. Forty-five polymorphic primer pairs were selected to evaluate genetic diversity and relatedness among the 115 cannabis genotypes. The results showed that 115 varieties could be divided into 4 groups primarily based on geography: Northern China, Europe, Central China, and Southern China. Moreover, the coefficient of similarity when comparing cannabis from Northern China with the European group cannabis was higher than that when comparing with cannabis from the other two groups, owing to a similar climate. This study outlines the first large-scale development of SSR markers for cannabis. These data may serve as a foundation for the development of genetic linkage, quantitative trait loci mapping, and marker-assisted breeding of cannabis.

Diversity Analysis in Cannabis sativa Based on Large-Scale Development of Expressed Sequence Tag-Derived Simple Sequence Repeat Markers

PubMed Central

Cheng, Chaohua; Tang, Qing; Chen, Ping; Wang, Changbiao; Zang, Gonggu; Zhao, Lining

2014-01-01

Cannabis sativa L. is an important economic plant for the production of food, fiber, oils, and intoxicants. However, lack of sufficient simple sequence repeat (SSR) markers has limited the development of cannabis genetic research. Here, large-scale development of expressed sequence tag simple sequence repeat (EST-SSR) markers was performed to obtain more informative genetic markers, and to assess genetic diversity in cannabis (Cannabis sativa L.). Based on the cannabis transcriptome, 4,577 SSRs were identified from 3,624 ESTs. From there, a total of 3,442 complementary primer pairs were designed as SSR markers. Among these markers, trinucleotide repeat motifs (50.99%) were the most abundant, followed by hexanucleotide (25.13%), dinucleotide (16.34%), tetranucloetide (3.8%), and pentanucleotide (3.74%) repeat motifs, respectively. The AAG/CTT trinucleotide repeat (17.96%) was the most abundant motif detected in the SSRs. One hundred and seventeen EST-SSR markers were randomly selected to evaluate primer quality in 24 cannabis varieties. Among these 117 markers, 108 (92.31%) were successfully amplified and 87 (74.36%) were polymorphic. Forty-five polymorphic primer pairs were selected to evaluate genetic diversity and relatedness among the 115 cannabis genotypes. The results showed that 115 varieties could be divided into 4 groups primarily based on geography: Northern China, Europe, Central China, and Southern China. Moreover, the coefficient of similarity when comparing cannabis from Northern China with the European group cannabis was higher than that when comparing with cannabis from the other two groups, owing to a similar climate. This study outlines the first large-scale development of SSR markers for cannabis. These data may serve as a foundation for the development of genetic linkage, quantitative trait loci mapping, and marker-assisted breeding of cannabis. PMID:25329551

Modelling the development and arrangement of the primary vascular structure in plants.

PubMed

Cartenì, Fabrizio; Giannino, Francesco; Schweingruber, Fritz Hans; Mazzoleni, Stefano

2014-09-01

The process of vascular development in plants results in the formation of a specific array of bundles that run throughout the plant in a characteristic spatial arrangement. Although much is known about the genes involved in the specification of procambium, phloem and xylem, the dynamic processes and interactions that define the development of the radial arrangement of such tissues remain elusive. This study presents a spatially explicit reaction-diffusion model defining a set of logical and functional rules to simulate the differentiation of procambium, phloem and xylem and their spatial patterns, starting from a homogeneous group of undifferentiated cells. Simulation results showed that the model is capable of reproducing most vascular patterns observed in plants, from primitive and simple structures made up of a single strand of vascular bundles (protostele), to more complex and evolved structures, with separated vascular bundles arranged in an ordered pattern within the plant section (e.g. eustele). The results presented demonstrate, as a proof of concept, that a common genetic-molecular machinery can be the basis of different spatial patterns of plant vascular development. Moreover, the model has the potential to become a useful tool to test different hypotheses of genetic and molecular interactions involved in the specification of vascular tissues.

RATES OF FITNESS DECLINE AND REBOUND SUGGEST PERVASIVE EPISTASIS

PubMed Central

Perfeito, L; Sousa, A; Bataillon, T; Gordo, I

2014-01-01

Unraveling the factors that determine the rate of adaptation is a major question in evolutionary biology. One key parameter is the effect of a new mutation on fitness, which invariably depends on the environment and genetic background. The fate of a mutation also depends on population size, which determines the amount of drift it will experience. Here, we manipulate both population size and genotype composition and follow adaptation of 23 distinct Escherichia coli genotypes. These have previously accumulated mutations under intense genetic drift and encompass a substantial fitness variation. A simple rule is uncovered: the net fitness change is negatively correlated with the fitness of the genotype in which new mutations appear—a signature of epistasis. We find that Fisher's geometrical model can account for the observed patterns of fitness change and infer the parameters of this model that best fit the data, using Approximate Bayesian Computation. We estimate a genomic mutation rate of 0.01 per generation for fitness altering mutations, albeit with a large confidence interval, a mean fitness effect of mutations of −0.01, and an effective number of traits nine in mutS− E. coli. This framework can be extended to confront a broader range of models with data and test different classes of fitness landscape models. PMID:24372601

Molecular characterization and population structure study of cambuci: strategy for conservation and genetic improvement.

PubMed

Santos, D N; Nunes, C F; Setotaw, T A; Pio, R; Pasqual, M; Cançado, G M A

2016-12-19

Cambuci (Campomanesia phaea) belongs to the Myrtaceae family and is native to the Atlantic Forest of Brazil. It has ecological and social appeal but is exposed to problems associated with environmental degradation and expansion of agricultural activities in the region. Comprehensive studies on this species are rare, making its conservation and genetic improvement difficult. Thus, it is important to develop research activities to understand the current situation of the species as well as to make recommendations for its conservation and use. This study was performed to characterize the cambuci accessions found in the germplasm bank of Coordenadoria de Assistência Técnica Integral using inter-simple sequence repeat markers, with the goal of understanding the plant's population structure. The results showed the existence of some level of genetic diversity among the cambuci accessions that could be exploited for the genetic improvement of the species. Principal coordinate analysis and discriminant analysis clustered the 80 accessions into three groups, whereas Bayesian model-based clustering analysis clustered them into two groups. The formation of two cluster groups and the high membership coefficients within the groups pointed out the importance of further collection to cover more areas and more genetic variability within the species. The study also showed the lack of conservation activities; therefore, more attention from the appropriate organizations is needed to plan and implement natural and ex situ conservation activities.

Development of novel SSR markers for evaluation of genetic diversity and population structure in Tribulus terrestris L. (Zygophyllaceae).

PubMed

Kaur, Kuljit; Sharma, Vikas; Singh, Vijay; Wani, Mohammad Saleem; Gupta, Raghbir Chand

2016-12-01

Tribulus terrestris L., commonly called puncture vine and gokhru, is an important member of Zygophyllaceae. The species is highly important in context to therapeutic uses and provides important active principles responsible for treatment of various diseases and also used as tonic. It is widely distributed in tropical regions of India and the world. However, status of its genetic diversity remained concealed due to lack of research work in this species. In present study, genetic diversity and structure of different populations of T. terrestris from north India was examined at molecular level using newly developed Simple Sequence Repeat (SSR) markers. In total, 20 primers produced 48 alleles in a size range of 100-500 bp with maximum (4) fragments amplified by TTMS-1, TTMS-25 and TTMS-33. Mean Polymorphism Information Content (PIC) and Marker Index (MI) were 0.368 and 1.01, respectively. Dendrogram showed three groups, one of which was purely containing accessions from Rajasthan while other two groups corresponded to Punjab and Haryana regions with intermixing of few other accessions. Analysis of molecular variance partitioned 76 % genetic variance within populations and 24 % among populations. Bayesian model based STRUCTURE analysis detected two genetic stocks for analyzed germplasm and also detected some admixed individuals. Different geographical populations of this species showed high level of genetic diversity. Results of present study can be useful in identifying diverse accessions and management of this plant resource. Moreover, the novel SSR markers developed can be utilized for various genetic analyses in this species in future.

Sequence-Based Prioritization of Nonsynonymous Single-Nucleotide Polymorphisms for the Study of Disease Mutations

PubMed Central

Jiang, Rui ; Yang, Hua ; Zhou, Linqi ; Kuo, C.-C. Jay ; Sun, Fengzhu ; Chen, Ting 

2007-01-01

The increasing demand for the identification of genetic variation responsible for common diseases has translated into a need for sophisticated methods for effectively prioritizing mutations occurring in disease-associated genetic regions. In this article, we prioritize candidate nonsynonymous single-nucleotide polymorphisms (nsSNPs) through a bioinformatics approach that takes advantages of a set of improved numeric features derived from protein-sequence information and a new statistical learning model called “multiple selection rule voting” (MSRV). The sequence-based features can maximize the scope of applications of our approach, and the MSRV model can capture subtle characteristics of individual mutations. Systematic validation of the approach demonstrates that this approach is capable of prioritizing causal mutations for both simple monogenic diseases and complex polygenic diseases. Further studies of familial Alzheimer diseases and diabetes show that the approach can enrich mutations underlying these polygenic diseases among the top of candidate mutations. Application of this approach to unclassified mutations suggests that there are 10 suspicious mutations likely to cause diseases, and there is strong support for this in the literature. PMID:17668383

Kidney organogenesis in the zebrafish: insights into vertebrate nephrogenesis and regeneration

PubMed Central

Gerlach, Gary F.; Wingert, Rebecca A.

2012-01-01

Vertebrates form a progressive series of up to three kidney organs during development—the pronephros, mesonephros, and metanephros. Each kidney derives from the intermediate mesoderm and is comprised of conserved excretory units called nephrons. The zebrafish is a powerful model for vertebrate developmental genetics, and recent studies have illustrated that zebrafish and mammals share numerous similarities in nephron composition and physiology. The zebrafish embryo forms an architecturally simple pronephros that has two nephrons, and these eventually become a scaffold onto which a mesonephros of several hundred nephrons is constructed during larval stages. In adult zebrafish, the mesonephros exhibits ongoing nephrogenesis, generating new nephrons from a local pool of renal progenitors during periods of growth or following kidney injury. The characteristics of the zebrafish pronephros and mesonephros make them genetically tractable kidney systems in which to study the functions of renal genes and address outstanding questions about the mechanisms of nephrogenesis. Here, we provide an overview of the formation and composition of these zebrafish kidney organs, and discuss how various zebrafish mutants, gene knockdowns, and transgenic models have created frameworks in which to further delineate nephrogenesis pathways. PMID:24014448

Cell permeability and nuclear DNA staining by propidium iodide in basidiomycetous yeasts.

PubMed

Zhang, Ning; Fan, Yuxuan; Li, Chen; Wang, Qiming; Leksawasdi, Noppol; Li, Fuli; Wang, Shi'an

2018-05-01

Non-model yeasts within basidiomycetes have considerable importance in agriculture, industry, and environment, but they are not as well studied as ascomycetous yeasts. Serving as a basic technique, nuclear DNA staining is widely used in physiology, ecology, cell biology, and genetics. However, it is unclear whether the classical nuclear DNA staining method for ascomycetous yeasts is applicable to basidiomycetous yeasts. In this study, 5 yeasts ineffectively stained by the classical propidium iodide (PI) staining method were identified from 23 representative basidiomycetous yeasts. Pretreatment of cells using dimethyl sulfoxide (DMSO) or snailase markedly improved cell penetration to PI and thus enabled DNA content determination by flow cytometry on the recalcitrant yeasts. The pretreatments are efficient, simple, and fast, avoiding tedious mutagenesis or genetic engineering used in previous reports. The heterogeneity of cell penetration to PI among basidiomycetous yeasts was attributed to the discrepancy in cell wall polysaccharides instead of capsule or plasma membrane. This study also indicated that care must be taken in attributing PI-negative staining as viable cells when studying non-model microorganisms.

New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times

NASA Astrophysics Data System (ADS)

Kia, Hamidreza; Ghodsypour, Seyed Hassan; Davoudpour, Hamid

2017-09-01

In the literature, the application of multi-objective dynamic scheduling problem and simple priority rules are widely studied. Although these rules are not efficient enough due to simplicity and lack of general insight, composite dispatching rules have a very suitable performance because they result from experiments. In this paper, a dynamic flexible flow line problem with sequence-dependent setup times is studied. The objective of the problem is minimization of mean flow time and mean tardiness. A 0-1 mixed integer model of the problem is formulated. Since the problem is NP-hard, four new composite dispatching rules are proposed to solve it by applying genetic programming framework and choosing proper operators. Furthermore, a discrete-event simulation model is made to examine the performances of scheduling rules considering four new heuristic rules and the six adapted heuristic rules from the literature. It is clear from the experimental results that composite dispatching rules that are formed from genetic programming have a better performance in minimization of mean flow time and mean tardiness than others.

Genetic epidemiology of tooth agenesis in Japan: a population- and family-based study.

PubMed

Machida, J; Nishiyama, T; Kishino, H; Yamaguchi, S; Kimura, M; Shibata, A; Tatematsu, T; Kamamoto, M; Yamamoto, K; Makino, S; Miyachi, H; Shimozato, K; Tokita, Y

2015-08-01

Tooth agenesis is one of the most common congenital anomalies in humans. However, the etiology of tooth agenesis remains largely unclear, as well as evidence base useful for genetic counseling. Therefore, we estimated the prevalence and sibling recurrence risk, and investigated agenetic patterns systematically. Tooth agenesis was classified into two subtypes: hypodontia (one to five missing teeth) and oligodontia (six or more missing teeth). The prevalence of these two subtypes were 6.8% [95% confidence interval (CI): 6.1-7.7%] and 0.1% (95% CI: 0.04-0.3%), respectively, and sibling recurrence risk of these were 24.5% (95% CI: 13.8-38.3%) and 43.8% (95% CI: 26.4-62.3%), respectively. This result suggests that the severe phenotype, oligodontia, might be mostly transmitted in a dominant fashion. Using a simple statistical modeling approach, our data were found to be consistent with a bilateral symmetry model, meaning that there was equal probability of missing teeth from the right and left sides. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Circadian clocks, rhythmic synaptic plasticity and the sleep-wake cycle in zebrafish.

PubMed

Elbaz, Idan; Foulkes, Nicholas S; Gothilf, Yoav; Appelbaum, Lior

2013-01-01

The circadian clock and homeostatic processes are fundamental mechanisms that regulate sleep. Surprisingly, despite decades of research, we still do not know why we sleep. Intriguing hypotheses suggest that sleep regulates synaptic plasticity and consequently has a beneficial role in learning and memory. However, direct evidence is still limited and the molecular regulatory mechanisms remain unclear. The zebrafish provides a powerful vertebrate model system that enables simple genetic manipulation, imaging of neuronal circuits and synapses in living animals, and the monitoring of behavioral performance during day and night. Thus, the zebrafish has become an attractive model to study circadian and homeostatic processes that regulate sleep. Zebrafish clock- and sleep-related genes have been cloned, neuronal circuits that exhibit circadian rhythms of activity and synaptic plasticity have been studied, and rhythmic behavioral outputs have been characterized. Integration of this data could lead to a better understanding of sleep regulation. Here, we review the progress of circadian clock and sleep studies in zebrafish with special emphasis on the genetic and neuroendocrine mechanisms that regulate rhythms of melatonin secretion, structural synaptic plasticity, locomotor activity and sleep.

Growth-rate dependent global effects on gene expression in bacteria

PubMed Central

Klumpp, Stefan; Zhang, Zhongge; Hwa, Terence

2010-01-01

Summary Bacterial gene expression depends not only on specific regulations but also directly on bacterial growth, because important global parameters such as the abundance of RNA polymerases and ribosomes are all growth-rate dependent. Understanding these global effects is necessary for a quantitative understanding of gene regulation and for the robust design of synthetic genetic circuits. The observed growth-rate dependence of constitutive gene expression can be explained by a simple model using the measured growth-rate dependence of the relevant cellular parameters. More complex growth dependences for genetic circuits involving activators, repressors and feedback control were analyzed, and salient features were verified experimentally using synthetic circuits. The results suggest a novel feedback mechanism mediated by general growth-dependent effects and not requiring explicit gene regulation, if the expressed protein affects cell growth. This mechanism can lead to growth bistability and promote the acquisition of important physiological functions such as antibiotic resistance and tolerance (persistence). PMID:20064380

Protists and the Wild, Wild West of Gene Expression: New Frontiers, Lawlessness, and Misfits.

PubMed

Smith, David Roy; Keeling, Patrick J

2016-09-08

The DNA double helix has been called one of life's most elegant structures, largely because of its universality, simplicity, and symmetry. The expression of information encoded within DNA, however, can be far from simple or symmetric and is sometimes surprisingly variable, convoluted, and wantonly inefficient. Although exceptions to the rules exist in certain model systems, the true extent to which life has stretched the limits of gene expression is made clear by nonmodel systems, particularly protists (microbial eukaryotes). The nuclear and organelle genomes of protists are subject to the most tangled forms of gene expression yet identified. The complicated and extravagant picture of the underlying genetics of eukaryotic microbial life changes how we think about the flow of genetic information and the evolutionary processes shaping it. Here, we discuss the origins, diversity, and growing interest in noncanonical protist gene expression and its relationship to genomic architecture.

The existence and abundance of ghost ancestors in biparental populations.

PubMed

Gravel, Simon; Steel, Mike

2015-05-01

In a randomly-mating biparental population of size N there are, with high probability, individuals who are genealogical ancestors of every extant individual within approximately log2(N) generations into the past. We use this result of J. Chang to prove a curious corollary under standard models of recombination: there exist, with high probability, individuals within a constant multiple of log2(N) generations into the past who are simultaneously (i) genealogical ancestors of each of the individuals at the present, and (ii) genetic ancestors to none of the individuals at the present. Such ancestral individuals-ancestors of everyone today that left no genetic trace-represent 'ghost' ancestors in a strong sense. In this short note, we use simple analytical argument and simulations to estimate how many such individuals exist in finite Wright-Fisher populations. Copyright © 2015 Elsevier Inc. All rights reserved.

Neutrality and Robustness in Evo-Devo: Emergence of Lateral Inhibition

PubMed Central

Munteanu, Andreea; Solé, Ricard V.

2008-01-01

Embryonic development is defined by the hierarchical dynamical process that translates genetic information (genotype) into a spatial gene expression pattern (phenotype) providing the positional information for the correct unfolding of the organism. The nature and evolutionary implications of genotype–phenotype mapping still remain key topics in evolutionary developmental biology (evo-devo). We have explored here issues of neutrality, robustness, and diversity in evo-devo by means of a simple model of gene regulatory networks. The small size of the system allowed an exhaustive analysis of the entire fitness landscape and the extent of its neutrality. This analysis shows that evolution leads to a class of robust genetic networks with an expression pattern characteristic of lateral inhibition. This class is a repertoire of distinct implementations of this key developmental process, the diversity of which provides valuable clues about its underlying causal principles. PMID:19023404

Divergent clonal selection dominates medulloblastoma at recurrence

PubMed Central

Morrissy, A. Sorana; Garzia, Livia; Shih, David J. H.; Zuyderduyn, Scott; Huang, Xi; Skowron, Patryk; Remke, Marc; Cavalli, Florence M. G.; Ramaswamy, Vijay; Lindsay, Patricia E.; Jelveh, Salomeh; Donovan, Laura K.; Wang, Xin; Luu, Betty; Zayne, Kory; Li, Yisu; Mayoh, Chelsea; Thiessen, Nina; Mercier, Eloi; Mungall, Karen L.; Ma, Yusanne; Tse, Kane; Zeng, Thomas; Shumansky, Karey; Roth, Andrew J. L.; Shah, Sohrab; Farooq, Hamza; Kijima, Noriyuki; Holgado, Borja L.; Lee, John J. Y.; Matan-Lithwick, Stuart; Liu, Jessica; Mack, Stephen C.; Manno, Alex; Michealraj, K. A.; Nor, Carolina; Peacock, John; Qin, Lei; Reimand, Juri; Rolider, Adi; Thompson, Yuan Y.; Wu, Xiaochong; Pugh, Trevor; Ally, Adrian; Bilenky, Mikhail; Butterfield, Yaron S. N.; Carlsen, Rebecca; Cheng, Young; Chuah, Eric; Corbett, Richard D.; Dhalla, Noreen; He, An; Lee, Darlene; Li, Haiyan I.; Long, William; Mayo, Michael; Plettner, Patrick; Qian, Jenny Q.; Schein, Jacqueline E.; Tam, Angela; Wong, Tina; Birol, Inanc; Zhao, Yongjun; Faria, Claudia C.; Pimentel, José; Nunes, Sofia; Shalaby, Tarek; Grotzer, Michael; Pollack, Ian F.; Hamilton, Ronald L.; Li, Xiao-Nan; Bendel, Anne E.; Fults, Daniel W.; Walter, Andrew W.; Kumabe, Toshihiro; Tominaga, Teiji; Collins, V. Peter; Cho, Yoon-Jae; Hoffman, Caitlin; Lyden, David; Wisoff, Jeffrey H.; Garvin, James H.; Stearns, Duncan S.; Massimi, Luca; Schüller, Ulrich; Sterba, Jaroslav; Zitterbart, Karel; Puget, Stephanie; Ayrault, Olivier; Dunn, Sandra E.; Tirapelli, Daniela P. C.; Carlotti, Carlos G.; Wheeler, Helen; Hallahan, Andrew R.; Ingram, Wendy; MacDonald, Tobey J.; Olson, Jeffrey J.; Van Meir, Erwin G.; Lee, Ji-Yeoun; Wang, Kyu-Chang; Kim, Seung-Ki; Cho, Byung-Kyu; Pietsch, Torsten; Fleischhack, Gudrun; Tippelt, Stephan; Ra, Young Shin; Bailey, Simon; Lindsey, Janet C.; Clifford, Steven C.; Eberhart, Charles G.; Cooper, Michael K.; Packer, Roger J.; Massimino, Maura; Garre, Maria Luisa; Bartels, Ute; Tabori, Uri; Hawkins, Cynthia E.; Dirks, Peter; Bouffet, Eric; Rutka, James T.; Wechsler-Reya, Robert J.; Weiss, William A.; Collier, Lara S.; Dupuy, Adam J.; Korshunov, Andrey; Jones, David T. W.; Kool, Marcel; Northcott, Paul A.; Pfister, Stefan M.; Largaespada, David A.; Mungall, Andrew J.; Moore, Richard A.; Jabado, Nada; Bader, Gary D.; Jones, Steven J. M.; Malkin, David; Marra, Marco A.; Taylor, Michael D.

2016-01-01

The development of targeted anti-cancer therapies through the study of cancer genomes is intended to increase survival rates and decrease treatment-related toxicity. We treated a transposon–driven, functional genomic mouse model of medulloblastoma with ‘humanized’ in vivo therapy (microneurosurgical tumour resection followed by multi-fractionated, image-guided radiotherapy). Genetic events in recurrent murine medulloblastoma exhibit a very poor overlap with those in matched murine diagnostic samples (<5%). Whole-genome sequencing of 33 pairs of human diagnostic and post-therapy medulloblastomas demonstrated substantial genetic divergence of the dominant clone after therapy (<12% diagnostic events were retained at recurrence). In both mice and humans, the dominant clone at recurrence arose through clonal selection of a pre-existing minor clone present at diagnosis. Targeted therapy is unlikely to be effective in the absence of the target, therefore our results offer a simple, proximal, and remediable explanation for the failure of prior clinical trials of targeted therapy. PMID:26760213

Efficient transformation and artificial miRNA gene silencing in Lemna minor

PubMed Central

Cantó-Pastor, Alex; Mollá-Morales, Almudena; Ernst, Evan; Dahl, William; Zhai, Jixian; Yan, Yiheng; Meyers, Blake; Shanklin, John; Martienssen, Robert

2015-01-01

Lack of genetic tools in the Lemnaceae (duckweed) has impeded full implementation of this organism as model for biological research, despite its rapid doubling time, simple architecture and unusual metabolic characteristics. Here we present technologies to facilitate high-throughput genetic studies in duckweed. We developed a fast and efficient method for producing Lemna minor stable transgenic fronds via agrobacterium-mediated transformation and regeneration from tissue culture. Additionally, we engineered an artificial microRNA (amiRNA) gene silencing system. We identified a Lemna gibba endogenous miR166 precursor and used it as a backbone to produce amiRNAs. As a proof of concept we induced the silencing of CH42, a Magnesium Chelatase subunit, using our amiRNA platform. Expression of CH42 in transgenic Lemna minor fronds was significantly reduced, which resulted in reduction of chlorophyll pigmentation. The techniques presented here will enable tackling future challenges in the biology and biotechnology of Lemnaceae. PMID:24989135

On the evolution of primitive genetic codes.

PubMed

Weberndorfer, Günter; Hofacker, Ivo L; Stadler, Peter F

2003-10-01

The primordial genetic code probably has been a drastically simplified ancestor of the canonical code that is used by contemporary cells. In order to understand how the present-day code came about we first need to explain how the language of the building plan can change without destroying the encoded information. In this work we introduce a minimal organism model that is based on biophysically reasonable descriptions of RNA and protein, namely secondary structure folding and knowledge based potentials. The evolution of a population of such organism under competition for a common resource is simulated explicitly at the level of individual replication events. Starting with very simple codes, and hence greatly reduced amino acid alphabets, we observe a diversification of the codes in most simulation runs. The driving force behind this effect is the possibility to produce fitter proteins when the repertoire of amino acids is enlarged.

Ocular surgical models for immune and angiogenic responses

PubMed Central

Inomata, Takenori; Mashaghi, Alireza; Di Zazzo, Antonio; Dana, Reza

2015-01-01

Corneal transplantation serves as a reproducible and simple surgical model to study mechanisms regulating immunity and angiogenesis. The simplicity of the model allows for systematic analysis of different mechanisms involved in immune and angiogenic privilege and their failures. This protocol describes how to induce neovessels and inflammation in an actively regulated avascular and immune-privileged site. This involves placing intra-stromal corneal sutures for two weeks, disrupting the privileges, and performing corneal transplantation subsequently. Privileged and non-privileged recipient responses to donor cornea can be compared to identify key immunological mechanisms that underlie angiogenesis and graft rejection. This protocol can also be adapted to the growing repertoire of genetic models available in the mouse, and is a valuable tool to elucidate molecular mechanisms mediating acceptance or failure of corneal graft. The model could be used to assess the potential of therapeutic molecules to enhance graft survival in vivo. PMID:26550579

In silico method for modelling metabolism and gene product expression at genome scale

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

Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem

2012-07-03

Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome andmore » transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.« less

Genetic Allee effects and their interaction with ecological Allee effects.

PubMed

Wittmann, Meike J; Stuis, Hanna; Metzler, Dirk

2018-01-01

It is now widely accepted that genetic processes such as inbreeding depression and loss of genetic variation can increase the extinction risk of small populations. However, it is generally unclear whether extinction risk from genetic causes gradually increases with decreasing population size or whether there is a sharp transition around a specific threshold population size. In the ecological literature, such threshold phenomena are called 'strong Allee effects' and they can arise for example from mate limitation in small populations. In this study, we aim to (i) develop a meaningful notion of a 'strong genetic Allee effect', (ii) explore whether and under what conditions such an effect can arise from inbreeding depression due to recessive deleterious mutations, and (iii) quantify the interaction of potential genetic Allee effects with the well-known mate-finding Allee effect. We define a strong genetic Allee effect as a genetic process that causes a population's survival probability to be a sigmoid function of its initial size. The inflection point of this function defines the critical population size. To characterize survival-probability curves, we develop and analyse simple stochastic models for the ecology and genetics of small populations. Our results indicate that inbreeding depression can indeed cause a strong genetic Allee effect, but only if individuals carry sufficiently many deleterious mutations (lethal equivalents). Populations suffering from a genetic Allee effect often first grow, then decline as inbreeding depression sets in and then potentially recover as deleterious mutations are purged. Critical population sizes of ecological and genetic Allee effects appear to be often additive, but even superadditive interactions are possible. Many published estimates for the number of lethal equivalents in birds and mammals fall in the parameter range where strong genetic Allee effects are expected. Unfortunately, extinction risk due to genetic Allee effects can easily be underestimated as populations with genetic problems often grow initially, but then crash later. Also interactions between ecological and genetic Allee effects can be strong and should not be neglected when assessing the viability of endangered or introduced populations. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Decoding directional genetic dependencies through orthogonal CRISPR/Cas screens | Office of Cancer Genomics

Cancer.gov

Genetic interaction studies are a powerful approach to identify functional interactions between genes. This approach can reveal networks of regulatory hubs and connect uncharacterized genes to well-studied pathways. However, this approach has previously been limited to simple gene inactivation studies. Here, we present an orthogonal CRISPR/Cas-mediated genetic interaction approach that allows the systematic activation of one gene while simultaneously knocking out a second gene in the same cell.

Aerodynamic Shape Optimization Using A Real-Number-Encoded Genetic Algorithm

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2001-01-01

A new method for aerodynamic shape optimization using a genetic algorithm with real number encoding is presented. The algorithm is used to optimize three different problems, a simple hill climbing problem, a quasi-one-dimensional nozzle problem using an Euler equation solver and a three-dimensional transonic wing problem using a nonlinear potential solver. Results indicate that the genetic algorithm is easy to implement and extremely reliable, being relatively insensitive to design space noise.

Genetic diversity among Puccinia melanocephala isolates from Brazil assessed using simple sequence repeat markers.

PubMed

Peixoto-Junior, R F; Creste, S; Landell, M G A; Nunes, D S; Sanguino, A; Campos, M F; Vencovsky, R; Tambarussi, E V; Figueira, A

2014-09-26

Brown rust (causal agent Puccinia melanocephala) is an important sugarcane disease that is responsible for large losses in yield worldwide. Despite its importance, little is known regarding the genetic diversity of this pathogen in the main Brazilian sugarcane cultivation areas. In this study, we characterized the genetic diversity of 34 P. melanocephala isolates from 4 Brazilian states using loci identified from an enriched simple sequence repeat (SSR) library. The aggressiveness of 3 isolates from major sugarcane cultivation areas was evaluated by inoculating an intermediately resistant and a susceptible cultivar. From the enriched library, 16 SSR-specific primers were developed, which produced scorable alleles. Of these, 4 loci were polymorphic and 12 were monomorphic for all isolates evaluated. The molecular characterization of the 34 isolates of P. melanocephala conducted using 16 SSR loci revealed the existence of low genetic variability among the isolates. The average estimated genetic distance was 0.12. Phenetic analysis based on Nei's genetic distance clustered the isolates into 2 major groups. Groups I and II included 18 and 14 isolates, respectively, and both groups contained isolates from all 4 geographic regions studied. Two isolates did not cluster with these groups. It was not possible to obtain clusters according to location or state of origin. Analysis of disease severity data revealed that the isolates did not show significant differences in aggressiveness between regions.

Selection for sow longevity.

PubMed

Serenius, T; Stalder, K J

2006-04-01

Sow longevity plays an important role in economically efficient piglet production because sow longevity is related to the number of piglets produced during its productive lifetime; however, selection for sow longevity is not commonly practiced in any pig breeding program. There is relatively little scientific literature concerning the genetic parameters (genetic variation and genetic correlations) or methods available for breeding value estimation for effective selection for sow longevity. This paper summarizes the current knowledge about the genetics of sow longevity and discusses the available breeding value estimation methods for sow longevity traits. The studies in the literature clearly indicate that sow longevity is a complex trait, and even the definition of sow longevity is variable depending on the researcher and research objective. In general, the measures and analyses of sow longevity can be divided into 1) continuous traits (e.g., productive lifetime) analyzed with proportional hazard models; and 2) more simple binary traits such as stayability until some predetermined fixed parity. Most studies have concluded that sufficient genetic variation exists for effective selection on sow longevity, and heritability estimates have ranged between 0.02 and 0.25. Moreover, sow longevity has shown to be genetically associated with prolificacy and leg conformation traits. Variable results from previous research have led to a lack of consensus among swine breeders concerning the valid methodology of estimating breeding values for longevity traits. One can not deny the superiority of survival analysis in the modeling approach of longevity data; however, multiple-trait analyses are not possible using currently available survival analysis software. Less sophisticated approaches have the advantage of evaluating multiple traits simultaneously, and thus, can use the genetic associations between sow longevity and other traits. Additional research is needed to identify the most efficient selection methods for sow longevity. Future research needs to concentrate on multiple trait analysis of sow longevity traits. Moreover, because longevity is a fitness trait, the nonadditive genetic effects (e.g., dominance) may play important role in the inheritance of sow longevity. Currently, not a single estimate for dominance variance of sow longevity could be identified from the scientific literature.

Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

PubMed

Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

2017-07-01

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

Using a genetic algorithm to optimize a water-monitoring network for accuracy and cost effectiveness

NASA Astrophysics Data System (ADS)

Julich, R. J.

2004-05-01

The purpose of this project is to determine the optimal spatial distribution of water-monitoring wells to maximize important data collection and to minimize the cost of managing the network. We have employed a genetic algorithm (GA) towards this goal. The GA uses a simple fitness measure with two parts: the first part awards a maximal score to those combinations of hydraulic head observations whose net uncertainty is closest to the value representing all observations present, thereby maximizing accuracy; the second part applies a penalty function to minimize the number of observations, thereby minimizing the overall cost of the monitoring network. We used the linear statistical inference equation to calculate standard deviations on predictions from a numerical model generated for the 501-observation Death Valley Regional Flow System as the basis for our uncertainty calculations. We have organized the results to address the following three questions: 1) what is the optimal design strategy for a genetic algorithm to optimize this problem domain; 2) what is the consistency of solutions over several optimization runs; and 3) how do these results compare to what is known about the conceptual hydrogeology? Our results indicate the genetic algorithms are a more efficient and robust method for solving this class of optimization problems than have been traditional optimization approaches.

On the complex relationship between energy expenditure and longevity: Reconciling the contradictory empirical results with a simple theoretical model.

PubMed

Hou, Chen; Amunugama, Kaushalya

2015-07-01

The relationship between energy expenditure and longevity has been a central theme in aging studies. Empirical studies have yielded controversial results, which cannot be reconciled by existing theories. In this paper, we present a simple theoretical model based on first principles of energy conservation and allometric scaling laws. The model takes into considerations the energy tradeoffs between life history traits and the efficiency of the energy utilization, and offers quantitative and qualitative explanations for a set of seemingly contradictory empirical results. We show that oxidative metabolism can affect cellular damage and longevity in different ways in animals with different life histories and under different experimental conditions. Qualitative data and the linearity between energy expenditure, cellular damage, and lifespan assumed in previous studies are not sufficient to understand the complexity of the relationships. Our model provides a theoretical framework for quantitative analyses and predictions. The model is supported by a variety of empirical studies, including studies on the cellular damage profile during ontogeny; the intra- and inter-specific correlations between body mass, metabolic rate, and lifespan; and the effects on lifespan of (1) diet restriction and genetic modification of growth hormone, (2) the cold and exercise stresses, and (3) manipulations of antioxidant. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Small heat shock proteins mediate cell-autonomous and -nonautonomous protection in a Drosophila model for environmental-stress-induced degeneration.

PubMed

Kawasaki, Fumiko; Koonce, Noelle L; Guo, Linda; Fatima, Shahroz; Qiu, Catherine; Moon, Mackenzie T; Zheng, Yunzhen; Ordway, Richard W

2016-09-01

Cell and tissue degeneration, and the development of degenerative diseases, are influenced by genetic and environmental factors that affect protein misfolding and proteotoxicity. To better understand the role of the environment in degeneration, we developed a genetic model for heat shock (HS)-stress-induced degeneration in Drosophila This model exhibits a unique combination of features that enhance genetic analysis of degeneration and protection mechanisms involving environmental stress. These include cell-type-specific failure of proteostasis and degeneration in response to global stress, cell-nonautonomous interactions within a simple and accessible network of susceptible cell types, and precise temporal control over the induction of degeneration. In wild-type flies, HS stress causes selective loss of the flight ability and degeneration of three susceptible cell types comprising the flight motor: muscle, motor neurons and associated glia. Other motor behaviors persist and, accordingly, the corresponding cell types controlling leg motor function are resistant to degeneration. Flight motor degeneration was preceded by a failure of muscle proteostasis characterized by diffuse ubiquitinated protein aggregates. Moreover, muscle-specific overexpression of a small heat shock protein (HSP), HSP23, promoted proteostasis and protected muscle from HS stress. Notably, neurons and glia were protected as well, indicating that a small HSP can mediate cell-nonautonomous protection. Cell-autonomous protection of muscle was characterized by a distinct distribution of ubiquitinated proteins, including perinuclear localization and clearance of protein aggregates associated with the perinuclear microtubule network. This network was severely disrupted in wild-type preparations prior to degeneration, suggesting that it serves an important role in muscle proteostasis and protection. Finally, studies of resistant leg muscles revealed that they sustain proteostasis and the microtubule cytoskeleton after HS stress. These findings establish a model for genetic analysis of degeneration and protection mechanisms involving contributions of environmental factors, and advance our understanding of the protective functions and therapeutic potential of small HSPs. © 2016. Published by The Company of Biologists Ltd.

Genetic variation of Sargassum horneri populations detected by inter-simple sequence repeats.

PubMed

Ren, J R; Yang, R; He, Y Y; Sun, Q H

2015-01-30

The seaweed Sargassum horneri is an important brown alga in the marine environment, and it is an important raw material in the alginate industry. Unfortunately, the fixed resource that was originally reported is now reduced or disappeared, and increased floating populations have been reported in recent years. We sampled a floating population and 4 fixed cultivated populations of S. horneri along the coast of Zhejiang, China. Inter-simple sequence repeat (ISSR) markers were applied in this research to analyze the genetic variation between floating populations and fixed cultivated populations of S. horneri. In total, 220 loci were amplified with 23 ISSR primers. The percentage of polymorphic loci within each population ranged from 53.64 to 95.45%. The highest diversity was observed in population 3, which was the local species that was suspension cultured in the lab and then fixed cultivated in the Nanji Islands before sampling. The lowest diversity was obtained in the floating population 4. The genetic distances among the 5 S. horneri populations ranged from 0.0819 to 0.2889, and the distance tendency confirmed the genetic diversity. The results suggest that the floating population had the lowest genetic diversity and could not be joined into the cluster branch of the fixed cultivated populations.

An application of traveling salesman problem using the improved genetic algorithm on android google maps

NASA Astrophysics Data System (ADS)

Narwadi, Teguh; Subiyanto

2017-03-01

The Travelling Salesman Problem (TSP) is one of the best known NP-hard problems, which means that no exact algorithm to solve it in polynomial time. This paper present a new variant application genetic algorithm approach with a local search technique has been developed to solve the TSP. For the local search technique, an iterative hill climbing method has been used. The system is implemented on the Android OS because android is now widely used around the world and it is mobile system. It is also integrated with Google API that can to get the geographical location and the distance of the cities, and displays the route. Therefore, we do some experimentation to test the behavior of the application. To test the effectiveness of the application of hybrid genetic algorithm (HGA) is compare with the application of simple GA in 5 sample from the cities in Central Java, Indonesia with different numbers of cities. According to the experiment results obtained that in the average solution HGA shows in 5 tests out of 5 (100%) is better than simple GA. The results have shown that the hybrid genetic algorithm outperforms the genetic algorithm especially in the case with the problem higher complexity.

Cell fate regulation in the shoot meristem.

PubMed

Laux, T; Mayer, K F

1998-04-01

The shoot meristem is a proliferative centre containing pluripotent stem cells that are the ultimate source of all cells and organs continuously added to the growing shoot. The progeny of the stem cells have two developmental options, either to renew the stem cell population or to leave the meristem and to differentiate, possibly according to signals from more mature tissue. The destiny of each cell depends on its position within the dynamic shoot meristem. Genetic data suggest a simple model in which graded positional information is provided by antagonistic gene functions and is interpreted by genes which regulate cell fate.

Protein Structure Prediction with Evolutionary Algorithms

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

Hart, W.E.; Krasnogor, N.; Pelta, D.A.

1999-02-08

Evolutionary algorithms have been successfully applied to a variety of molecular structure prediction problems. In this paper we reconsider the design of genetic algorithms that have been applied to a simple protein structure prediction problem. Our analysis considers the impact of several algorithmic factors for this problem: the confirmational representation, the energy formulation and the way in which infeasible conformations are penalized, Further we empirically evaluated the impact of these factors on a small set of polymer sequences. Our analysis leads to specific recommendations for both GAs as well as other heuristic methods for solving PSP on the HP model.

ISSOL Meeting, Barcelona, Spain, 1993

NASA Technical Reports Server (NTRS)

Ferris, James P. (Editor)

1995-01-01

Topics in a conference on the origins of life and the evolution of the biosphere include the origin of chirality, prebiotic chemistry of small biomolecules, primitive polymer formation, RNA regulation and control. Early origins of life and the ecology of hydrothermal systems such as ocean floor vents and their simple organisms are examined. The process of mineral catalysis in Montmorillonite as a model for early metabolism is used. The origin of the genetic code and the development of branching in molecular structures of amino acids is described. Studies are reported of the effects of meteorite impact on early Earth life.

[MLPA technique--principles and use in practice].

PubMed

Rusu, Cristina; Sireteanu, Adriana; Puiu, Maria; Skrypnyk, Cristina; Tomescu, E; Csep, Katalin; Creţ, Victoria; Barbarii, Ligia

2007-01-01

MLPA (Multiplex Ligation-dependent Probe Amplification) is a recently introduced method, based on PCR principle, useful for the detection of different genetic abnormalities (aneuploidies, gene deletions/duplications, subtelomeric rearrangements, methylation status etc). The technique is simple, reliable and cheap. We present this method to discuss its importance for a modern genetic service and to underline its multiple advantages.

Web-Based Analysis for Student-Generated Complex Genetic Profiles

ERIC Educational Resources Information Center

Kass, David H.; LaRoe, Robert

2007-01-01

A simple, rapid method for generating complex genetic profiles using Alu-based markers was recently developed for students primarily at the undergraduate level to learn more about forensics and paternity analysis. On the basis of the Cold Spring Harbor Allele Server, which provides an excellent tool for analyzing a single Alu variant, we present a…

Genetic variation patterns of American chestnut populations at EST-SSRs

Treesearch

Oliver Gailing; C. Dana Nelson

2017-01-01

The objective of this study is to analyze patterns of genetic variation at genic expressed sequence tag - simple sequence repeats (EST-SSRs) and at chloroplast DNA markers in populations of American chestnut (Castanea dentata Borkh.) to assist in conservation and breeding efforts. Allelic diversity at EST-SSRs decreased significantly from southwest to northeast along...

Use of microsatellite markers in management of conifer forest species

Treesearch

Craig S. Echt

1999-01-01

Within the past ten years a new class of genetic marker1 has risen to prominence as the tool of choice for many geneticists. Microsatellite DNAs, or simple sequence repeats (SSRs), were first characterized as highly informative genetic markers in humans (Weber and May, 1990; Litt and Luty, 1990), and have since been found in practically all...

Genetic diversity and population structure analysis of accessions in the Chinese cowpea [Vigna unguiculata (L.) Walp.] germplasm collection

USDA-ARS?s Scientific Manuscript database

Cowpea (Vigna unguiculata) is an important legume crop with diverse uses. The species is presently a minor crop, and evaluation of its genetic diversity has been very limited. In this study, a total of 200 genic and 100 genomic simple sequence repeat (SSR) markers were developed from cowpea unigene ...

Short-Term Memories in "Drosophila" Are Governed by General and Specific Genetic Systems

ERIC Educational Resources Information Center

Zars, Troy

2010-01-01

In a dynamic environment, there is an adaptive value in the ability of animals to acquire and express memories. That both simple and complex animals can learn is therefore not surprising. How animals have solved this problem genetically and anatomically probably lies somewhere in a range between a single molecular/anatomical mechanism that applies…

Bayesian inference of selection in a heterogeneous environment from genetic time-series data.

PubMed

Gompert, Zachariah

2016-01-01

Evolutionary geneticists have sought to characterize the causes and molecular targets of selection in natural populations for many years. Although this research programme has been somewhat successful, most statistical methods employed were designed to detect consistent, weak to moderate selection. In contrast, phenotypic studies in nature show that selection varies in time and that individual bouts of selection can be strong. Measurements of the genomic consequences of such fluctuating selection could help test and refine hypotheses concerning the causes of ecological specialization and the maintenance of genetic variation in populations. Herein, I proposed a Bayesian nonhomogeneous hidden Markov model to estimate effective population sizes and quantify variable selection in heterogeneous environments from genetic time-series data. The model is described and then evaluated using a series of simulated data, including cases where selection occurs on a trait with a simple or polygenic molecular basis. The proposed method accurately distinguished neutral loci from non-neutral loci under strong selection, but not from those under weak selection. Selection coefficients were accurately estimated when selection was constant or when the fitness values of genotypes varied linearly with the environment, but these estimates were less accurate when fitness was polygenic or the relationship between the environment and the fitness of genotypes was nonlinear. Past studies of temporal evolutionary dynamics in laboratory populations have been remarkably successful. The proposed method makes similar analyses of genetic time-series data from natural populations more feasible and thereby could help answer fundamental questions about the causes and consequences of evolution in the wild. © 2015 John Wiley & Sons Ltd.

Network rewiring dynamics with convergence towards a star network

PubMed Central

Dick, G.; Parry, M.

2016-01-01

Network rewiring as a method for producing a range of structures was first introduced in 1998 by Watts & Strogatz (Nature 393, 440–442. (doi:10.1038/30918)). This approach allowed a transition from regular through small-world to a random network. The subsequent interest in scale-free networks motivated a number of methods for developing rewiring approaches that converged to scale-free networks. This paper presents a rewiring algorithm (RtoS) for undirected, non-degenerate, fixed size networks that transitions from regular, through small-world and scale-free to star-like networks. Applications of the approach to models for the spread of infectious disease and fixation time for a simple genetics model are used to demonstrate the efficacy and application of the approach. PMID:27843396

Network rewiring dynamics with convergence towards a star network.

PubMed

Whigham, P A; Dick, G; Parry, M

2016-10-01

Network rewiring as a method for producing a range of structures was first introduced in 1998 by Watts & Strogatz ( Nature 393 , 440-442. (doi:10.1038/30918)). This approach allowed a transition from regular through small-world to a random network. The subsequent interest in scale-free networks motivated a number of methods for developing rewiring approaches that converged to scale-free networks. This paper presents a rewiring algorithm (RtoS) for undirected, non-degenerate, fixed size networks that transitions from regular, through small-world and scale-free to star-like networks. Applications of the approach to models for the spread of infectious disease and fixation time for a simple genetics model are used to demonstrate the efficacy and application of the approach.

Genetic structure and bio-climatic modeling support allopatric over parapatric speciation along a latitudinal gradient.

PubMed

Rossetto, Maurizio; Allen, Chris B; Thurlby, Katie A G; Weston, Peter H; Milner, Melita L

2012-08-20

Four of the five species of Telopea (Proteaceae) are distributed in a latitudinal replacement pattern on the south-eastern Australian mainland. In similar circumstances, a simple allopatric speciation model that identifies the origins of genetic isolation within temporal geographic separation is considered as the default model. However, secondary contact between differentiated lineages can result in similar distributional patterns to those arising from a process of parapatric speciation (where gene flow between lineages remains uninterrupted during differentiation). Our aim was to use the characteristic distributional patterns in Telopea to test whether it reflected the evolutionary models of allopatric or parapatric speciation. Using a combination of genetic evidence and environmental niche modelling, we focused on three main questions: do currently described geographic borders coincide with genetic and environmental boundaries; are there hybrid zones in areas of secondary contact between closely related species; did species distributions contract during the last glacial maximum resulting in distributional gaps even where overlap and hybridisation currently occur? Total genomic DNA was extracted from 619 individuals sampled from 36 populations representing the four species. Seven nuclear microsatellites (nSSR) and six chloroplast microsatellites (cpSSR) were amplified across all populations. Genetic structure and the signature of admixture in overlap zones was described using the Bayesian clustering methods implemented in STUCTURE and NewHybrids respectively. Relationships between chlorotypes were reconstructed as a median-joining network. Environmental niche models were produced for all species using environmental parameters from both the present day and the last glacial maximum (LGM).The nSSR loci amplified a total of 154 alleles, while data for the cpSSR loci produced a network of six chlorotypes. STRUCTURE revealed an optimum number of five clusters corresponding to the four recognised species with the additional division of T. speciosissima into populations north and south of the Shoalhaven River valley. Unexpectedly, the northern disjunct population of T. oreades grouped with T. mongaensis and was identified as a hybrid swarm by the Bayesian assignment test implemented in NewHybrids. Present day and LGM environmental niche models differed dramatically, suggesting that distributions of all species had repeatedly expanded and contracted in response to Pleistocene climatic oscillations and confirming strongly marked historical distributional gaps among taxes. Genetic structure and bio-climatic modeling results are more consistent with a history of allopatric speciation followed by repeated episodes of secondary contact and localised hybridisation, rather than with parapatric speciation. This study on Telopea shows that the evidence for temporal exclusion of gene flow can be found even outside obvious geographical contexts, and that it is possible to make significant progress towards excluding parapatric speciation as a contributing evolutionary process.

Simple genetic transformation assay for rapid diagnosis of Moraxella osloensis.

PubMed

Juni, E

1974-01-01

A genetic transformation assay for unequivocal identification of strains of Moraxella osloensis is described. In this assay a stable tryptophan auxotroph is transformed to prototrophy by deoxyribonucleic acid (DNA) samples from other strains of M. osloensis but not by DNA samples from unrelated bacteria. The test is simple to perform and definitive results can be obtained in less than 24 h. The procedure, which is suitable for routine diagnosis in a clinical laboratory, involves a rapid method for preparation of crude transforming DNA from small quantities of bacterial cells and permits simultaneous examination of large numbers of isolated cultures. The assay was shown to correctly identify 27 strains previously classified as M. osloensis. Forty-five other gram-negative, oxidase-positive, nonmotile coccobacilli, which might be confused with M. osloensis unless subject to more extensive testing, were shown to be unrelated genetically to M. osloensis. The transformation assay clearly distinguishes M. osloensis from Acinetobacter. Although most strains of M. osloensis are nonfastidious, being able to grow in a mineral medium supplemented with a single organic carbon source, one of the strains tested was only able to grow on fairly complex media and could not be transformed to grow on simple media. Inability to alkalize Simmons citrate agar was shown not to be characteristic of all strains of M. osloensis.

Simple Genetic Transformation Assay for Rapid Diagnosis of Moraxella osloensis

PubMed Central

Juni, Elliot

1974-01-01

A genetic transformation assay for unequivocal identification of strains of Moraxella osloensis is described. In this assay a stable tryptophan auxotroph is transformed to prototrophy by deoxyribonucleic acid (DNA) samples from other strains of M. osloensis but not by DNA samples from unrelated bacteria. The test is simple to perform and definitive results can be obtained in less than 24 h. The procedure, which is suitable for routine diagnosis in a clinical laboratory, involves a rapid method for preparation of crude transforming DNA from small quantities of bacterial cells and permits simultaneous examination of large numbers of isolated cultures. The assay was shown to correctly identify 27 strains previously classified as M. osloensis. Forty-five other gram-negative, oxidase-positive, nonmotile coccobacilli, which might be confused with M. osloensis unless subject to more extensive testing, were shown to be unrelated genetically to M. osloensis. The transformation assay clearly distinguishes M. osloensis from Acinetobacter. Although most strains of M. osloensis are nonfastidious, being able to grow in a mineral medium supplemented with a single organic carbon source, one of the strains tested was only able to grow on fairly complex media and could not be transformed to grow on simple media. Inability to alkalize Simmons citrate agar was shown not to be characteristic of all strains of M. osloensis. Images PMID:4589126

Actuator Placement Via Genetic Algorithm for Aircraft Morphing

NASA Technical Reports Server (NTRS)

Crossley, William A.; Cook, Andrea M.

2001-01-01

This research continued work that began under the support of NASA Grant NAG1-2119. The focus of this effort was to continue investigations of Genetic Algorithm (GA) approaches that could be used to solve an actuator placement problem by treating this as a discrete optimization problem. In these efforts, the actuators are assumed to be "smart" devices that change the aerodynamic shape of an aircraft wing to alter the flow past the wing, and, as a result, provide aerodynamic moments that could provide flight control. The earlier work investigated issued for the problem statement, developed the appropriate actuator modeling, recognized the importance of symmetry for this problem, modified the aerodynamic analysis routine for more efficient use with the genetic algorithm, and began a problem size study to measure the impact of increasing problem complexity. The research discussed in this final summary further investigated the problem statement to provide a "combined moment" problem statement to simultaneously address roll, pitch and yaw. Investigations of problem size using this new problem statement provided insight into performance of the GA as the number of possible actuator locations increased. Where previous investigations utilized a simple wing model to develop the GA approach for actuator placement, this research culminated with application of the GA approach to a high-altitude unmanned aerial vehicle concept to demonstrate that the approach is valid for an aircraft configuration.

Biopreparedness in the Age of Genetically Engineered Pathogens and Open Access Science: An Urgent Need for a Paradigm Shift.

PubMed

MacIntyre, C Raina

2015-09-01

Our systems, thinking, training, legislation, and policies are lagging far behind momentous changes in science, and leaving us vulnerable in biosecurity. Synthetic viruses and genetic engineering of pathogens are a reality, with a rapid acceleration of dual-use science. The public availability of methods for dual-use genetic engineering, coupled with the insider threat, poses an unprecedented risk for biosecurity. Case studies including the 1984 Rajneesh salmonella bioterrorism attack and the controversy over engineered transmissible H5N1 influenza are analyzed. Simple probability analysis shows that the risks of dual-use research are likely to outweigh potential benefits, yet this type of analysis has not been done to date. Many bioterrorism agents may also occur naturally. Distinguishing natural from unnatural epidemics is far more difficult than other types of terrorism. Public health systems do not have mechanisms for routinely considering bioterrorism, and an organizational culture that is reluctant to consider it. A collaborative model for flagging aberrant outbreak patterns and referral from the health to security sectors is proposed. Vulnerabilities in current approaches to biosecurity need to be reviewed and strengthened collaboratively by all stakeholders. New systems, legislation, collaborative operational models, and ways of thinking are required to effectively address the threat to global biosecurity. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

Genetic risk factors for ovarian cancer and their role for endometriosis risk.

PubMed

Burghaus, Stefanie; Fasching, Peter A; Häberle, Lothar; Rübner, Matthias; Büchner, Kathrin; Blum, Simon; Engel, Anne; Ekici, Arif B; Hartmann, Arndt; Hein, Alexander; Beckmann, Matthias W; Renner, Stefan P

2017-04-01

Several genetic variants have been validated as risk factors for ovarian cancer. Endometriosis has also been described as a risk factor for ovarian cancer. Identifying genetic risk factors that are common to the two diseases might help improve our understanding of the molecular pathogenesis potentially linking the two conditions. In a hospital-based case-control analysis, 12 single nucleotide polymorphisms (SNPs), validated by the Ovarian Cancer Association Consortium (OCAC) and the Collaborative Oncological Gene-environment Study (COGS) project, were genotyped using TaqMan® OpenArray™ analysis. The cases consisted of patients with endometriosis, and the controls were healthy individuals without endometriosis. A total of 385 cases and 484 controls were analyzed. Odds ratios and P values were obtained using simple logistic regression models, as well as from multiple logistic regression models with adjustment for clinical predictors. rs11651755 in HNF1B was found to be associated with endometriosis in this case-control study. The OR was 0.66 (95% CI, 0.51 to 0.84) and the P value after correction for multiple testing was 0.01. None of the other genotypes was associated with a risk for endometriosis. As rs11651755 in HNF1B modified both the ovarian cancer risk and also the risk for endometriosis, HNF1B may be causally involved in the pathogenetic pathway leading from endometriosis to ovarian cancer. Copyright © 2017 Elsevier Inc. All rights reserved.

Overgrowth.

PubMed

Verge, Charles F; Mowat, David

2010-06-01

Overgrowth presenting at birth requires blood glucose monitoring while a cause is sought. Among older children presenting with tall stature, common causes such as familial tall stature and simple obesity must be distinguished from rarer endocrine and genetic causes. Several genetic overgrowth syndromes carry increased risk of malignancy and regular screening is recommended. The use of high-dose oestrogen or testosterone in an attempt to limit final stature has limited efficacy and carries a significant risk of side effects. Endocrine and genetic assessment ought to be considered for cases of unexplained overgrowth.

A large-scale survey of genetic copy number variations among Han Chinese residing in Taiwan

PubMed Central

Lin, Chien-Hsing; Li, Ling-Hui; Ho, Sheng-Feng; Chuang, Tzu-Po; Wu, Jer-Yuarn; Chen, Yuan-Tsong; Fann, Cathy SJ

2008-01-01

Background Copy number variations (CNVs) have recently been recognized as important structural variations in the human genome. CNVs can affect gene expression and thus may contribute to phenotypic differences. The copy number inferring tool (CNIT) is an effective hidden Markov model-based algorithm for estimating allele-specific copy number and predicting chromosomal alterations from single nucleotide polymorphism microarrays. The CNIT algorithm, which was constructed using data from 270 HapMap multi-ethnic individuals, was applied to identify CNVs from 300 unrelated Han Chinese individuals in Taiwan. Results Using stringent selection criteria, 230 regions with variable copy numbers were identified in the Han Chinese population; 133 (57.83%) had been reported previously, 64 displayed greater than 1% CNV allele frequency. The average size of the CNV regions was 322 kb (ranging from 1.48 kb to 5.68 Mb) and covered a total of 2.47% of the human genome. A total of 196 of the CNV regions were simple deletions and 27 were simple amplifications. There were 449 genes and 5 microRNAs within these CNV regions; some of these genes are known to be associated with diseases. Conclusion The identified CNVs are characteristic of the Han Chinese population and should be considered when genetic studies are conducted. The CNV distribution in the human genome is still poorly characterized, and there is much diversity among different ethnic populations. PMID:19108714

Biology as population dynamics: heuristics for transmission risk.

PubMed

Keebler, Daniel; Walwyn, David; Welte, Alex

2013-02-01

Population-type models, accounting for phenomena such as population lifetimes, mixing patterns, recruitment patterns, genetic evolution and environmental conditions, can be usefully applied to the biology of HIV infection and viral replication. A simple dynamic model can explore the effect of a vaccine-like stimulus on the mortality and infectiousness, which formally looks like fertility, of invading virions; the mortality of freshly infected cells; and the availability of target cells, all of which impact on the probability of infection. Variations on this model could capture the importance of the timing and duration of different key events in viral transmission, and hence be applied to questions of mucosal immunology. The dynamical insights and assumptions of such models are compatible with the continuum of between- and within-individual risks in sexual violence and may be helpful in making sense of the sparse data available on the association between HIV transmission and sexual violence. © 2012 John Wiley & Sons A/S.

Social dilemmas among supergenes: intragenomic sexual conflict and a selfing solution in Oenothera

PubMed Central

Brown, Sam P.; Levin, Donald A.

2012-01-01

Recombination is a powerful policing mechanism to control intragenomic cheats. The ‘parliament of the genes’ can often rapidly block driving genes from cheating during meiosis. But what if the genome parliament is reduced to only two members, or supergenes? Using a series of simple game-theoretic models inspired by the peculiar genetics of Oenothera sp. we illustrate that a 2 supergene genome (α and β) can produce a number of surprising evolutionary dynamics, including increases in lineage longevity following a transition from sexuality (outcrossing) to asexuality (clonal self-fertilization). We end by interpreting the model in the broader context of the evolution of mutualism, which highlights that greater α, β cooperation in the self-fertilizing model can be viewed as an example of partner fidelity driving multi-lineage cooperation. PMID:22133211

Silicate Inclusions in the Kodaikanal IIE Iron Meteorite

NASA Technical Reports Server (NTRS)

Kurat, G.; Varela, M. E.; Zinner, E.

2005-01-01

Silicate inclusions in iron meteorites display an astonishing chemical and mineralogical variety, ranging from chondritic to highly fractionated, silica- and alkali-rich assemblages. In spite of this, their origin is commonly considered to be a simple one: mixing of silicates, fractionated or unfractionated, with metal. The latter had to be liquid in order to accommodate the former in a pore-free way which all models accomplish by assuming shock melting. II-E iron meteorites are particularly interesting because they contain an exotic zoo of silicate inclusions, including some chemically strongly fractionated ones. They also pose a formidable conundrum: young silicates are enclosed by very old metal. This and many other incompatibilities between models and reality forced the formulation of an alternative genetic model for irons. Here we present preliminary findings in our study of Kodaikanal silicate inclusions.

Epigenetics in Developmental Disorder: ADHD and Endophenotypes

PubMed Central

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

2011-01-01

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

Bacterial Population Genetics in a Forensic Context

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

Velsko, S P

This report addresses the recent Department of Homeland Security (DHS) call for a Phase I study to (1) assess gaps in the forensically relevant knowledge about the population genetics of eight bacterial agents of concern, (2) formulate a technical roadmap to address those gaps, and (3) identify new bioinformatics tools that would be necessary to analyze and interpret population genetic data in a forensic context. The eight organisms that were studied are B. anthracis, Y. pestis, F. tularensis, Brucella spp., E. coli O157/H7, Burkholderia mallei, Burkholderia pseudomallei, and C. botulinum. Our study focused on the use of bacterial population geneticsmore » by forensic investigators to test hypotheses about the possible provenance of an agent that was used in a crime or act of terrorism. Just as human population genetics underpins the calculations of match probabilities for human DNA evidence, bacterial population genetics determines the level of support that microbial DNA evidence provides for or against certain well-defined hypotheses about the origins of an infecting strain. Our key findings are: (1) Bacterial population genetics is critical for answering certain types of questions in a probabilistic manner, akin (but not identical) to 'match probabilities' in DNA forensics. (2) A basic theoretical framework for calculating likelihood ratios or posterior probabilities for forensic hypotheses based on microbial genetic comparisons has been formulated. This 'inference-on-networks' framework has deep but simple connections to the population genetics of mtDNA and Y-STRs in human DNA forensics. (3) The 'phylogeographic' approach to identifying microbial sources is not an adequate basis for understanding bacterial population genetics in a forensic context, and has limited utility, even for generating 'leads' with respect to strain origin. (4) A collection of genotyped isolates obtained opportunistically from international locations augmented by phylogenetic representations of relatedness will not and enzootic outbreaks noted through international outbreak surveillance systems, and 'representative' genetic sequences from each outbreak. (5) Interpretation of genetic comparisons between an attack strain and reference strains requires a model for the network structure of maintenance foci, enzootic outbreaks, and human outbreaks of that disease, coupled with estimates of mutational rate constants. Validation of the model requires a set of sequences from exemplary outbreaks and laboratory data on mutation rates during animal passage. The necessary number of isolates in each validation set is determined by disease transmission network theory, and is based on the 'network diameter' of the outbreak. (6) The 8 bacteria in this study can be classified into 4 categories based on the complexity of the transmission network structure of their natural maintenance foci and their outbreaks, both enzootic and zoonotic. (7) For B. anthracis, Y. pestis, E. coli O157, and Brucella melitensis, and their primary natural animal hosts, most of the fundamental parameters needed for modeling genetic change within natural host or human transmission networks have been determined or can be estimated from existing field and laboratory studies. (8) For Burkholderia mallei, plausible approaches to transmission network models exist, but much of the fundamental parameterization does not. In addition, a validated high-resolution typing system for characterizing genetic change within outbreaks or foci has not yet been demonstrated, although a candidate system exists. (9) For Francisella tularensis, the increased complexity of the transmission network and unresolved questions about maintenance and transmission suggest that it will be more complex and difficult to develop useful models based on currently available data. (10) For Burkholderia pseudomallei and Clostridium botulinum, the transmission and maintenance networks involve complex soil communities and metapopulations about which very little is known. It is not clear that these pathogens can be brought into the inference-on-networks framework without additional conceptual advances. (11) For all 8 bacteria some combination of field studies, computational modeling, and laboratory experiments are needed to provide a useful forensic capability for bacterial genetic inference.« less

Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata.

PubMed

Hill, A A; Crotta, M; Wall, B; Good, L; O'Brien, S J; Guitian, J

2017-03-01

Foodborne infection is a result of exposure to complex, dynamic food systems. The efficiency of foodborne infection is driven by ongoing shifts in genetic machinery. Next-generation sequencing technologies can provide high-fidelity data about the genetics of a pathogen. However, food safety surveillance systems do not currently provide similar high-fidelity epidemiological metadata to associate with genetic data. As a consequence, it is rarely possible to transform genetic data into actionable knowledge that can be used to genuinely inform risk assessment or prevent outbreaks. Big data approaches are touted as a revolution in decision support, and pose a potentially attractive method for closing the gap between the fidelity of genetic and epidemiological metadata for food safety surveillance. We therefore developed a simple food chain model to investigate the potential benefits of combining 'big' data sources, including both genetic and high-fidelity epidemiological metadata. Our results suggest that, as for any surveillance system, the collected data must be relevant and characterize the important dynamics of a system if we are to properly understand risk: this suggests the need to carefully consider data curation, rather than the more ambitious claims of big data proponents that unstructured and unrelated data sources can be combined to generate consistent insight. Of interest is that the biggest influencers of foodborne infection risk were contamination load and processing temperature, not genotype. This suggests that understanding food chain dynamics would probably more effectively generate insight into foodborne risk than prescribing the hazard in ever more detail in terms of genotype.

Mitochondrial genetic codes evolve to match amino acid requirements of proteins.

PubMed

Swire, Jonathan; Judson, Olivia P; Burt, Austin

2005-01-01

Mitochondria often use genetic codes different from the standard genetic code. Now that many mitochondrial genomes have been sequenced, these variant codes provide the first opportunity to examine empirically the processes that produce new genetic codes. The key question is: Are codon reassignments the sole result of mutation and genetic drift? Or are they the result of natural selection? Here we present an analysis of 24 phylogenetically independent codon reassignments in mitochondria. Although the mutation-drift hypothesis can explain reassignments from stop to an amino acid, we found that it cannot explain reassignments from one amino acid to another. In particular--and contrary to the predictions of the mutation-drift hypothesis--the codon involved in such a reassignment was not rare in the ancestral genome. Instead, such reassignments appear to take place while the codon is in use at an appreciable frequency. Moreover, the comparison of inferred amino acid usage in the ancestral genome with the neutral expectation shows that the amino acid gaining the codon was selectively favored over the amino acid losing the codon. These results are consistent with a simple model of weak selection on the amino acid composition of proteins in which codon reassignments are selected because they compensate for multiple slightly deleterious mutations throughout the mitochondrial genome. We propose that the selection pressure is for reduced protein synthesis cost: most reassignments give amino acids that are less expensive to synthesize. Taken together, our results strongly suggest that mitochondrial genetic codes evolve to match the amino acid requirements of proteins.

Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata

PubMed Central

Crotta, M.; Wall, B.; Good, L.; O'Brien, S. J.; Guitian, J.

2017-01-01

Foodborne infection is a result of exposure to complex, dynamic food systems. The efficiency of foodborne infection is driven by ongoing shifts in genetic machinery. Next-generation sequencing technologies can provide high-fidelity data about the genetics of a pathogen. However, food safety surveillance systems do not currently provide similar high-fidelity epidemiological metadata to associate with genetic data. As a consequence, it is rarely possible to transform genetic data into actionable knowledge that can be used to genuinely inform risk assessment or prevent outbreaks. Big data approaches are touted as a revolution in decision support, and pose a potentially attractive method for closing the gap between the fidelity of genetic and epidemiological metadata for food safety surveillance. We therefore developed a simple food chain model to investigate the potential benefits of combining ‘big’ data sources, including both genetic and high-fidelity epidemiological metadata. Our results suggest that, as for any surveillance system, the collected data must be relevant and characterize the important dynamics of a system if we are to properly understand risk: this suggests the need to carefully consider data curation, rather than the more ambitious claims of big data proponents that unstructured and unrelated data sources can be combined to generate consistent insight. Of interest is that the biggest influencers of foodborne infection risk were contamination load and processing temperature, not genotype. This suggests that understanding food chain dynamics would probably more effectively generate insight into foodborne risk than prescribing the hazard in ever more detail in terms of genotype. PMID:28405360

Genetic diversity in Malus ×domestica (Rosaceae) through time in response to domestication.

PubMed

Gross, Briana L; Henk, Adam D; Richards, Christopher M; Fazio, Gennaro; Volk, Gayle M

2014-10-01

• Patterns of genetic diversity in domesticated plants are affected by geographic region of origin and cultivation, intentional artificial selection, and unintentional genetic bottlenecks. While bottlenecks are mainly associated with the initial domestication process, they can also affect diversity during crop improvement. Here, we investigate the impact of the improvement process on the genetic diversity of domesticated apple in comparison with other perennial and annual fruit crops.• Apple cultivars that were developed at various times (ranging from the 13th through the 20th century) and 11 of the 15 apple cultivars that are used for 90% of the apple production in the United States were surveyed for genetic diversity based on either 9 or 19 simple sequence repeats (SSRs). Diversity was compared using standard metrics and model-based approaches based on expected heterozygosity (He) at equilibrium. Improvement bottleneck data for fruit crops were also collected from the literature.• Domesticated apples showed no significant reduction in genetic diversity through time across the last eight centuries. Diversity was generally high, with an average He > 0.7 for apples from all centuries. However, diversity of the apples currently used for the bulk of commercial production was lower.• The improvement bottleneck in domesticated apples appears to be mild or nonexistent, in contrast to improvement bottlenecks in many annual and perennial fruit crops, as documented from the literature survey. The low diversity of the subset of cultivars used for commercial production, however, indicates that an improvement bottleneck may be in progress for this perennial crop. © 2014 Botanical Society of America, Inc.

Genome complexity, robustness and genetic interactions in digital organisms

NASA Astrophysics Data System (ADS)

Lenski, Richard E.; Ofria, Charles; Collier, Travis C.; Adami, Christoph

1999-08-01

Digital organisms are computer programs that self-replicate, mutate and adapt by natural selection. They offer an opportunity to test generalizations about living systems that may extend beyond the organic life that biologists usually study. Here we have generated two classes of digital organism: simple programs selected solely for rapid replication, and complex programs selected to perform mathematical operations that accelerate replication through a set of defined `metabolic' rewards. To examine the differences in their genetic architecture, we introduced millions of single and multiple mutations into each organism and measured the effects on the organism's fitness. The complex organisms are more robust than the simple ones with respect to the average effects of single mutations. Interactions among mutations are common and usually yield higher fitness than predicted from the component mutations assuming multiplicative effects; such interactions are especially important in the complex organisms. Frequent interactions among mutations have also been seen in bacteria, fungi and fruitflies. Our findings support the view that interactions are a general feature of genetic systems.

Genome complexity, robustness and genetic interactions in digital organisms.

PubMed

Lenski, R E; Ofria, C; Collier, T C; Adami, C

1999-08-12

Digital organisms are computer programs that self-replicate, mutate and adapt by natural selection. They offer an opportunity to test generalizations about living systems that may extend beyond the organic life that biologists usually study. Here we have generated two classes of digital organism: simple programs selected solely for rapid replication, and complex programs selected to perform mathematical operations that accelerate replication through a set of defined 'metabolic' rewards. To examine the differences in their genetic architecture, we introduced millions of single and multiple mutations into each organism and measured the effects on the organism's fitness. The complex organisms are more robust than the simple ones with respect to the average effects of single mutations. Interactions among mutations are common and usually yield higher fitness than predicted from the component mutations assuming multiplicative effects; such interactions are especially important in the complex organisms. Frequent interactions among mutations have also been seen in bacteria, fungi and fruitflies. Our findings support the view that interactions are a general feature of genetic systems.

Development of EST-SSR markers for Taxillus nigrans (Loranthaceae) in southwestern China using next-generation sequencing1

PubMed Central

Miao, Ning; Zhang, Lei; Li, Maoping; Fan, Liqiang; Mao, Kangshan

2017-01-01

Premise of the study: We developed transcriptome microsatellite markers (simple sequence repeats) for Taxillus nigrans (Loranthaceae) to survey the genetic diversity and population structure of this species. Methods and Results: We used Illumina HiSeq data to reconstruct the transcriptome of T. nigrans by de novo assembly and used the transcriptome to develop a set of simple sequence repeat markers. Overall, 40 primer pairs were designed and tested; 19 of them amplified successfully and demonstrated polymorphisms. Two loci that detected null alleles were eliminated, and the remaining 17, which were subjected to further analyses, yielded two to 21 alleles per locus. Conclusions: The markers will serve as a basis for studies to assess the extent and pattern of distribution of genetic variation in T. nigrans, and they may also be useful in conservation genetic, ecological, and evolutionary studies of the genus Taxillus, a group of plant species of importance in Chinese traditional medicine. PMID:28924510

Characterization and Amplification of Gene-Based Simple Sequence Repeat (SSR) Markers in Date Palm.

PubMed

Zhao, Yongli; Keremane, Manjunath; Prakash, Channapatna S; He, Guohao

2017-01-01

The paucity of molecular markers limits the application of genetic and genomic research in date palm (Phoenix dactylifera L.). Availability of expressed sequence tag (EST) sequences in date palm may provide a good resource for developing gene-based markers. This study characterizes a substantial fraction of transcriptome sequences containing simple sequence repeats (SSRs) from the EST sequences in date palm. The EST sequences studied are mainly homologous to those of Elaeis guineensis and Musa acuminata. A total of 911 gene-based SSR markers, characterized with functional annotations, have provided a useful basis not only for discovering candidate genes and understanding genetic basis of traits of interest but also for developing genetic and genomic tools for molecular research in date palm, such as diversity study, quantitative trait locus (QTL) mapping, and molecular breeding. The procedures of DNA extraction, polymerase chain reaction (PCR) amplification of these gene-based SSR markers, and gel electrophoresis of PCR products are described in this chapter.

Toward Genomics-Based Breeding in C3 Cool-Season Perennial Grasses.

PubMed

Talukder, Shyamal K; Saha, Malay C

2017-01-01

Most important food and feed crops in the world belong to the C3 grass family. The future of food security is highly reliant on achieving genetic gains of those grasses. Conventional breeding methods have already reached a plateau for improving major crops. Genomics tools and resources have opened an avenue to explore genome-wide variability and make use of the variation for enhancing genetic gains in breeding programs. Major C3 annual cereal breeding programs are well equipped with genomic tools; however, genomic research of C3 cool-season perennial grasses is lagging behind. In this review, we discuss the currently available genomics tools and approaches useful for C3 cool-season perennial grass breeding. Along with a general review, we emphasize the discussion focusing on forage grasses that were considered orphan and have little or no genetic information available. Transcriptome sequencing and genotype-by-sequencing technology for genome-wide marker detection using next-generation sequencing (NGS) are very promising as genomics tools. Most C3 cool-season perennial grass members have no prior genetic information; thus NGS technology will enhance collinear study with other C3 model grasses like Brachypodium and rice. Transcriptomics data can be used for identification of functional genes and molecular markers, i.e., polymorphism markers and simple sequence repeats (SSRs). Genome-wide association study with NGS-based markers will facilitate marker identification for marker-assisted selection. With limited genetic information, genomic selection holds great promise to breeders for attaining maximum genetic gain of the cool-season C3 perennial grasses. Application of all these tools can ensure better genetic gains, reduce length of selection cycles, and facilitate cultivar development to meet the future demand for food and fodder.

Segregation of a QTL cluster for home-cage activity using a new mapping method based on regression analysis of congenic mouse strains

PubMed Central

Kato, S; Ishii, A; Nishi, A; Kuriki, S; Koide, T

2014-01-01

Recent genetic studies have shown that genetic loci with significant effects in whole-genome quantitative trait loci (QTL) analyses were lost or weakened in congenic strains. Characterisation of the genetic basis of this attenuated QTL effect is important to our understanding of the genetic mechanisms of complex traits. We previously found that a consomic strain, B6-Chr6CMSM, which carries chromosome 6 of a wild-derived strain MSM/Ms on the genetic background of C57BL/6J, exhibited lower home-cage activity than C57BL/6J. In the present study, we conducted a composite interval QTL analysis using the F2 mice derived from a cross between C57BL/6J and B6-Chr6CMSM. We found one QTL peak that spans 17.6 Mbp of chromosome 6. A subconsomic strain that covers the entire QTL region also showed lower home-cage activity at the same level as the consomic strain. We developed 15 congenic strains, each of which carries a shorter MSM/Ms-derived chromosomal segment from the subconsomic strain. Given that the results of home-cage activity tests on the congenic strains cannot be explained by a simple single-gene model, we applied regression analysis to segregate the multiple genetic loci. The results revealed three loci (loci 1–3) that have the effect of reducing home-cage activity and one locus (locus 4) that increases activity. We also found that the combination of loci 3 and 4 cancels out the effects of the congenic strains, which indicates the existence of a genetic mechanism related to the loss of QTLs. PMID:24781804

From Mendel's discovery on pea to today's plant genetics and breeding : Commemorating the 150th anniversary of the reading of Mendel's discovery.

PubMed

Smýkal, Petr; K Varshney, Rajeev; K Singh, Vikas; Coyne, Clarice J; Domoney, Claire; Kejnovský, Eduard; Warkentin, Thomas

2016-12-01

This work discusses several selected topics of plant genetics and breeding in relation to the 150th anniversary of the seminal work of Gregor Johann Mendel. In 2015, we celebrated the 150th anniversary of the presentation of the seminal work of Gregor Johann Mendel. While Darwin's theory of evolution was based on differential survival and differential reproductive success, Mendel's theory of heredity relies on equality and stability throughout all stages of the life cycle. Darwin's concepts were continuous variation and "soft" heredity; Mendel espoused discontinuous variation and "hard" heredity. Thus, the combination of Mendelian genetics with Darwin's theory of natural selection was the process that resulted in the modern synthesis of evolutionary biology. Although biology, genetics, and genomics have been revolutionized in recent years, modern genetics will forever rely on simple principles founded on pea breeding using seven single gene characters. Purposeful use of mutants to study gene function is one of the essential tools of modern genetics. Today, over 100 plant species genomes have been sequenced. Mapping populations and their use in segregation of molecular markers and marker-trait association to map and isolate genes, were developed on the basis of Mendel's work. Genome-wide or genomic selection is a recent approach for the development of improved breeding lines. The analysis of complex traits has been enhanced by high-throughput phenotyping and developments in statistical and modeling methods for the analysis of phenotypic data. Introgression of novel alleles from landraces and wild relatives widens genetic diversity and improves traits; transgenic methodologies allow for the introduction of novel genes from diverse sources, and gene editing approaches offer possibilities to manipulate gene in a precise manner.

DNA Mapping Made Simple: An Intellectual Activity about the Genetic Modification of Organisms

ERIC Educational Resources Information Center

Marques, Miguel; Arrabaca, Joao; Chagas, Isabel

2004-01-01

Since the discovery of the DNA double helix (in 1953 by Watson and Crick), technologies have been developed that allow scientists to manipulate the genome of bacteria to produce human hormones, as well as the genome of crop plants to achieve high yield and enhanced flavor. The universality of the genetic code has allowed DNA isolated from a…

Evaluation of genetic diversity amongst Descurainia sophia L. genotypes by inter-simple sequence repeat (ISSR) marker.

PubMed

Saki, Sahar; Bagheri, Hedayat; Deljou, Ali; Zeinalabedini, Mehrshad

2016-01-01

Descurainia sophia is a valuable medicinal plant in family of Brassicaceae. To determine the range of diversity amongst D. sophia in Iran, 32 naturally distributed plants belonging to six natural populations of the Iranian plateau were investigated by inter-simple sequence repeat (ISSR) markers. The average percentage of polymorphism produced by 12 ISSR primers was 86 %. The PIC values for primers ranged from 0.22 to 0.40 and Rp values ranged between 6.5 and 19.9. The relative genetic diversity of the populations was not high (Gst =0.32). However, the value of gene flow revealed by the ISSR marker was high (Nm = 1.03). UPGMA clustering method based on Jaccard similarity coefficient grouped the genotypes into two major clusters. Graph results from Neighbor-Net Network generated after a 1000 bootstrap test using Jaccard coefficient, and STRUCTURE analysis confirmed the UPGMA clustering. The first three PCAs represented 57.31 % of the total variation. The high levels of genetic diversity were observed within populations, which is useful in breeding and conservation programs. ISSR is found to be an eligible marker to study genetic diversity of D. sophia.

Linkage Analysis of a Model Quantitative Trait in Humans: Finger Ridge Count Shows Significant Multivariate Linkage to 5q14.1

PubMed Central

Medland, Sarah E; Loesch, Danuta Z; Mdzewski, Bogdan; Zhu, Gu; Montgomery, Grant W; Martin, Nicholas G

2007-01-01

The finger ridge count (a measure of pattern size) is one of the most heritable complex traits studied in humans and has been considered a model human polygenic trait in quantitative genetic analysis. Here, we report the results of the first genome-wide linkage scan for finger ridge count in a sample of 2,114 offspring from 922 nuclear families. Both univariate linkage to the absolute ridge count (a sum of all the ridge counts on all ten fingers), and multivariate linkage analyses of the counts on individual fingers, were conducted. The multivariate analyses yielded significant linkage to 5q14.1 (Logarithm of odds [LOD] = 3.34, pointwise-empirical p-value = 0.00025) that was predominantly driven by linkage to the ring, index, and middle fingers. The strongest univariate linkage was to 1q42.2 (LOD = 2.04, point-wise p-value = 0.002, genome-wide p-value = 0.29). In summary, the combination of univariate and multivariate results was more informative than simple univariate analyses alone. Patterns of quantitative trait loci factor loadings consistent with developmental fields were observed, and the simple pleiotropic model underlying the absolute ridge count was not sufficient to characterize the interrelationships between the ridge counts of individual fingers. PMID:17907812

DNA biosensors that reason.

PubMed

Sainz de Murieta, Iñaki; Rodríguez-Patón, Alfonso

2012-08-01

Despite the many designs of devices operating with the DNA strand displacement, surprisingly none is explicitly devoted to the implementation of logical deductions. The present article introduces a new model of biosensor device that uses nucleic acid strands to encode simple rules such as "IF DNA_strand(1) is present THEN disease(A)" or "IF DNA_strand(1) AND DNA_strand(2) are present THEN disease(B)". Taking advantage of the strand displacement operation, our model makes these simple rules interact with input signals (either DNA or any type of RNA) to generate an output signal (in the form of nucleotide strands). This output signal represents a diagnosis, which either can be measured using FRET techniques, cascaded as the input of another logical deduction with different rules, or even be a drug that is administered in response to a set of symptoms. The encoding introduces an implicit error cancellation mechanism, which increases the system scalability enabling longer inference cascades with a bounded and controllable signal-noise relation. It also allows the same rule to be used in forward inference or backward inference, providing the option of validly outputting negated propositions (e.g. "diagnosis A excluded"). The models presented in this paper can be used to implement smart logical DNA devices that perform genetic diagnosis in vitro. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Complex Genetic Effects on Early Vegetative Development Shape Resource Allocation Differences Between Arabidopsis lyrata Populations

PubMed Central

Remington, David L.; Leinonen, Päivi H.; Leppälä, Johanna; Savolainen, Outi

2013-01-01

Costs of reproduction due to resource allocation trade-offs have long been recognized as key forces in life history evolution, but little is known about their functional or genetic basis. Arabidopsis lyrata, a perennial relative of the annual model plant A. thaliana with a wide climatic distribution, has populations that are strongly diverged in resource allocation. In this study, we evaluated the genetic and functional basis for variation in resource allocation in a reciprocal transplant experiment, using four A. lyrata populations and F2 progeny from a cross between North Carolina (NC) and Norway parents, which had the most divergent resource allocation patterns. Local alleles at quantitative trait loci (QTL) at a North Carolina field site increased reproductive output while reducing vegetative growth. These QTL had little overlap with flowering date QTL. Structural equation models incorporating QTL genotypes and traits indicated that resource allocation differences result primarily from QTL effects on early vegetative growth patterns, with cascading effects on later vegetative and reproductive development. At a Norway field site, North Carolina alleles at some of the same QTL regions reduced survival and reproductive output components, but these effects were not associated with resource allocation trade-offs in the Norway environment. Our results indicate that resource allocation in perennial plants may involve important adaptive mechanisms largely independent of flowering time. Moreover, the contributions of resource allocation QTL to local adaptation appear to result from their effects on developmental timing and its interaction with environmental constraints, and not from simple models of reproductive costs. PMID:23979581

A New Framework for Adaptive Sampling and Analysis During Long-Term Monitoring and Remedial Action Management

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

Minsker, Barbara

2004-12-01

The Argonne team has gathered available data on monitoring wells and measured hydraulic heads from the Argonne 317/319 site and sent it to UIUC. Xiaodong Li, a research assistant supported by the project, has reviewed the data and has fit initial spatiotemporal statistical models to it. Another research assistant, Yonas Demissie, has completed generation of the artificial data that will be used for model development and testing. In order to generate the artificial data a detailed groundwater flow and contaminant transport model was developed based upon characteristics of the 317/319 site. The model covers a multi-year time horizon that includesmore » both before and after planting of the trees. As described in the proposal, the artificial data is created by adding ''measurement'' error to the ''true'' value from the numerical model. To date, only simple white noise error models have been considered. He is now reviewing the literature and beginning to develop a hierarchical modeling approach for the artificial data. Abhishek Singh, a third research assistant supported by the project, is implementing learning models for learning users preferences in an interactive genetic algorithm for solving the inverse problem. Meghna Babbar, the fourth research assistant supported by the project, has been improving the user interface for the interactive genetic algorithm and preparing a long-term monitoring design problem for testing the approach. Gayathri Gopalakrishnan, the last research assistant who is partially supported by the project, has collected substantial data from the 317/319 phytoremediation site at Argonne and has begun learning approaches for modeling these data.« less

Validity of using ad hoc methods to analyze secondary traits in case-control association studies.

PubMed

Yung, Godwin; Lin, Xihong

2016-12-01

Case-control association studies often collect from their subjects information on secondary phenotypes. Reusing the data and studying the association between genes and secondary phenotypes provide an attractive and cost-effective approach that can lead to discovery of new genetic associations. A number of approaches have been proposed, including simple and computationally efficient ad hoc methods that ignore ascertainment or stratify on case-control status. Justification for these approaches relies on the assumption of no covariates and the correct specification of the primary disease model as a logistic model. Both might not be true in practice, for example, in the presence of population stratification or the primary disease model following a probit model. In this paper, we investigate the validity of ad hoc methods in the presence of covariates and possible disease model misspecification. We show that in taking an ad hoc approach, it may be desirable to include covariates that affect the primary disease in the secondary phenotype model, even though these covariates are not necessarily associated with the secondary phenotype. We also show that when the disease is rare, ad hoc methods can lead to severely biased estimation and inference if the true disease model follows a probit model instead of a logistic model. Our results are justified theoretically and via simulations. Applied to real data analysis of genetic associations with cigarette smoking, ad hoc methods collectively identified as highly significant (P<10-5) single nucleotide polymorphisms from over 10 genes, genes that were identified in previous studies of smoking cessation. © 2016 WILEY PERIODICALS, INC.

Evolution of the archaeal and mammalian information processing systems: towards an archaeal model for human disease.

PubMed

Lyu, Zhe; Whitman, William B

2017-01-01

Current evolutionary models suggest that Eukaryotes originated from within Archaea instead of being a sister lineage. To test this model of ancient evolution, we review recent studies and compare the three major information processing subsystems of replication, transcription and translation in the Archaea and Eukaryotes. Our hypothesis is that if the Eukaryotes arose within the archaeal radiation, their information processing systems will appear to be one of kind and not wholly original. Within the Eukaryotes, the mammalian or human systems are emphasized because of their importance in understanding health. Biochemical as well as genetic studies provide strong evidence for the functional similarity of archaeal homologs to the mammalian information processing system and their dissimilarity to the bacterial systems. In many independent instances, a simple archaeal system is functionally equivalent to more elaborate eukaryotic homologs, suggesting that evolution of complexity is likely an central feature of the eukaryotic information processing system. Because fewer components are often involved, biochemical characterizations of the archaeal systems are often easier to interpret. Similarly, the archaeal cell provides a genetically and metabolically simpler background, enabling convenient studies on the complex information processing system. Therefore, Archaea could serve as a parsimonious and tractable host for studying human diseases that arise in the information processing systems.

Convergence of circuit dysfunction in ASD: a common bridge between diverse genetic and environmental risk factors and common clinical electrophysiology.

PubMed

Port, Russell G; Gandal, Michael J; Roberts, Timothy P L; Siegel, Steven J; Carlson, Gregory C

2014-01-01

Most recent estimates indicate that 1 in 68 children are affected by an autism spectrum disorder (ASD). Though decades of research have uncovered much about these disorders, the pathological mechanism remains unknown. Hampering efforts is the seeming inability to integrate findings over the micro to macro scales of study, from changes in molecular, synaptic and cellular function to large-scale brain dysfunction impacting sensory, communicative, motor and cognitive activity. In this review, we describe how studies focusing on neuronal circuit function provide unique context for identifying common neurobiological disease mechanisms of ASD. We discuss how recent EEG and MEG studies in subjects with ASD have repeatedly shown alterations in ensemble population recordings (both in simple evoked related potential latencies and specific frequency subcomponents). Because these disease-associated electrophysiological abnormalities have been recapitulated in rodent models, studying circuit differences in these models may provide access to abnormal circuit function found in ASD. We then identify emerging in vivo and ex vivo techniques, focusing on how these assays can characterize circuit level dysfunction and determine if these abnormalities underlie abnormal clinical electrophysiology. Such circuit level study in animal models may help us understand how diverse genetic and environmental risks can produce a common set of EEG, MEG and anatomical abnormalities found in ASD.

Evolution of social versus individual learning in a subdivided population revisited: comparative analysis of three coexistence mechanisms using the inclusive-fitness method.

PubMed

Kobayashi, Yutaka; Ohtsuki, Hisashi

2014-03-01

Learning abilities are categorized into social (learning from others) and individual learning (learning on one's own). Despite the typically higher cost of individual learning, there are mechanisms that allow stable coexistence of both learning modes in a single population. In this paper, we investigate by means of mathematical modeling how the effect of spatial structure on evolutionary outcomes of pure social and individual learning strategies depends on the mechanisms for coexistence. We model a spatially structured population based on the infinite-island framework and consider three scenarios that differ in coexistence mechanisms. Using the inclusive-fitness method, we derive the equilibrium frequency of social learners and the genetic load of social learning (defined as average fecundity reduction caused by the presence of social learning) in terms of some summary statistics, such as relatedness, for each of the three scenarios and compare the results. This comparative analysis not only reconciles previous models that made contradictory predictions as to the effect of spatial structure on the equilibrium frequency of social learners but also derives a simple mathematical rule that determines the sign of the genetic load (i.e. whether or not social learning contributes to the mean fecundity of the population). Copyright © 2013 Elsevier Inc. All rights reserved.

Integrating genetic and toxicogenomic information for determining underlying susceptibility to developmental disorders.

PubMed

Robinson, Joshua F; Port, Jesse A; Yu, Xiaozhong; Faustman, Elaine M

2010-10-01

To understand the complex etiology of developmental disorders, an understanding of both genetic and environmental risk factors is needed. Human and rodent genetic studies have identified a multitude of gene candidates for specific developmental disorders such as neural tube defects (NTDs). With the emergence of toxicogenomic-based assessments, scientists now also have the ability to compare and understand the expression of thousands of genes simultaneously across strain, time, and exposure in developmental models. Using a systems-based approach in which we are able to evaluate information from various parts and levels of the developing organism, we propose a framework for integrating genetic information with toxicogenomic-based studies to better understand gene-environmental interactions critical for developmental disorders. This approach has allowed us to characterize candidate genes in the context of variables critical for determining susceptibility such as strain, time, and exposure. Using a combination of toxicogenomic studies and complementary bioinformatic tools, we characterize NTD candidate genes during normal development by function (gene ontology), linked phenotype (disease outcome), location, and expression (temporally and strain-dependent). In addition, we show how environmental exposures (cadmium, methylmercury) can influence expression of these genes in a strain-dependent manner. Using NTDs as an example of developmental disorder, we show how simple integration of genetic information from previous studies into the standard microarray design can enhance analysis of gene-environment interactions to better define environmental exposure-disease pathways in sensitive and resistant mouse strains. © Wiley-Liss, Inc.

Adapting populations in space: clonal interference and genetic diversity

NASA Astrophysics Data System (ADS)

Weissman, Daniel; Barton, Nick

Most species inhabit ranges much larger than the scales over which individuals interact. How does this spatial structure interact with adaptive evolution? We consider a simple model of a spatially-extended, adapting population and show that, while clonal interference severely limits the adaptation of purely asexual populations, even rare recombination is enough to allow adaptation at rates approaching those of well-mixed populations. We also find that the genetic hitchhiking produced by the adaptive alleles sweeping through the population has strange effects on the patterns of genetic diversity. In large spatial ranges, even low rates of adaptation cause all individuals in the population to rapidly trace their ancestry back to individuals living in a small region in the center of the range. The probability of fixation of an allele is thus strongly dependent on the allele's spatial location, with alleles from the center favored. Surprisingly, these effects are seen genome-wide (instead of being localized to the regions of the genome undergoing the sweeps). The spatial concentration of ancestry produces a power-law dependence of relatedness on distance, so that even individuals sampled far apart are likely to be fairly closely related, masking the underlying spatial structure.

Diversity and genetic stability in banana genotypes in a breeding program using inter simple sequence repeats (ISSR) markers.

PubMed

Silva, A V C; Nascimento, A L S; Vitória, M F; Rabbani, A R C; Soares, A N R; Lédo, A S

2017-02-23

Banana (Musa spp) is a fruit species frequently cultivated and consumed worldwide. Molecular markers are important for estimating genetic diversity in germplasm and between genotypes in breeding programs. The objective of this study was to analyze the genetic diversity of 21 banana genotypes (FHIA 23, PA42-44, Maçã, Pacovan Ken, Bucaneiro, YB42-47, Grand Naine, Tropical, FHIA 18, PA94-01, YB42-17, Enxerto, Japira, Pacovã, Prata-Anã, Maravilha, PV79-34, Caipira, Princesa, Garantida, and Thap Maeo), by using inter-simple sequence repeat (ISSR) markers. Material was generated from the banana breeding program of Embrapa Cassava & Fruits and evaluated at Embrapa Coastal Tablelands. The 12 primers used in this study generated 97.5% polymorphism. Four clusters were identified among the different genotypes studied, and the sum of the first two principal components was 48.91%. From the Unweighted Pair Group Method using Arithmetic averages (UPGMA) dendrogram, it was possible to identify two main clusters and subclusters. Two genotypes (Garantida and Thap Maeo) remained isolated from the others, both in the UPGMA clustering and in the principal cordinate analysis (PCoA). Using ISSR markers, we could analyze the genetic diversity of the studied material and state that these markers were efficient at detecting sufficient polymorphism to estimate the genetic variability in banana genotypes.

[Age structure and genetic diversity of Homatula pycnolepis in the Nujiang River basin].

PubMed

Yue, Xing-Jian; Liu, Shao-Ping; Liu, Ming-Dian; Duan, Xin-Bin; Wang, Deng-Qiang; Chen, Da-Qing

2013-08-01

This study examined the age structure of the Loach, Homatula pycnolepis through the otolith growth rings in 204 individual specimens collected from the Xiaomengtong River of the Nujiang River (Salween River) basin in April, 2008. There were only two different age classes, 1 and 2 years of age-no 3 year olds were detected. The age structure of H. pycnolepis was simple. The complete mitochondrial DNA cytochrome b gene sequences (1140) of 80 individuals from 4 populations collected in the Nujiang River drainage were sequenced and a total of 44 variable sites were found among 4 different haplotypes. The global haplotype diversity (Hd) and nucleotide diversity (Pi) were calculated at 0.7595, 0.0151 respectively, and 0, 0 in each population, indicating a consistent lack of genetic diversity in each small population. There was obvious geographic structure in both the Nujiang River basin (NJB) group, and the Nanding River (NDR) group. The genetic distance between NJB and NDR was calculated at 0.0356, suggesting that genetic divergence resulted from long-term isolation of individual population. Such a simple age structure and a lack of genetic diversity in H. pycnolepis may potentially be due to small populations and locale fishing pressures. Accordingly, the results of this study prompt us to recommend that the NJB, NDR and Lancang River populations should be protected as three different evolutionary significant units or separated management units.

A Simple Genetic Incompatibility Causes Hybrid Male Sterility in Mimulus

PubMed Central

Sweigart, Andrea L.; Fishman, Lila; Willis, John H.

2006-01-01

Much evidence has shown that postzygotic reproductive isolation (hybrid inviability or sterility) evolves by the accumulation of interlocus incompatibilities between diverging populations. Although in theory only a single pair of incompatible loci is needed to isolate species, empirical work in Drosophila has revealed that hybrid fertility problems often are highly polygenic and complex. In this article we investigate the genetic basis of hybrid sterility between two closely related species of monkeyflower, Mimulus guttatus and M. nasutus. In striking contrast to Drosophila systems, we demonstrate that nearly complete hybrid male sterility in Mimulus results from a simple genetic incompatibility between a single pair of heterospecific loci. We have genetically mapped this sterility effect: the M. guttatus allele at the hybrid male sterility 1 (hms1) locus acts dominantly in combination with recessive M. nasutus alleles at the hybrid male sterility 2 (hms2) locus to cause nearly complete hybrid male sterility. In a preliminary screen to find additional small-effect male sterility factors, we identified one additional locus that also contributes to some of the variation in hybrid male fertility. Interestingly, hms1 and hms2 also cause a significant reduction in hybrid female fertility, suggesting that sex-specific hybrid defects might share a common genetic basis. This possibility is supported by our discovery that recombination is reduced dramatically in a cross involving a parent with the hms1–hms2 incompatibility. PMID:16415357

A simple genetic incompatibility causes hybrid male sterility in mimulus.

PubMed

Sweigart, Andrea L; Fishman, Lila; Willis, John H

2006-04-01

Much evidence has shown that postzygotic reproductive isolation (hybrid inviability or sterility) evolves by the accumulation of interlocus incompatibilities between diverging populations. Although in theory only a single pair of incompatible loci is needed to isolate species, empirical work in Drosophila has revealed that hybrid fertility problems often are highly polygenic and complex. In this article we investigate the genetic basis of hybrid sterility between two closely related species of monkeyflower, Mimulus guttatus and M. nasutus. In striking contrast to Drosophila systems, we demonstrate that nearly complete hybrid male sterility in Mimulus results from a simple genetic incompatibility between a single pair of heterospecific loci. We have genetically mapped this sterility effect: the M. guttatus allele at the hybrid male sterility 1 (hms1) locus acts dominantly in combination with recessive M. nasutus alleles at the hybrid male sterility 2 (hms2) locus to cause nearly complete hybrid male sterility. In a preliminary screen to find additional small-effect male sterility factors, we identified one additional locus that also contributes to some of the variation in hybrid male fertility. Interestingly, hms1 and hms2 also cause a significant reduction in hybrid female fertility, suggesting that sex-specific hybrid defects might share a common genetic basis. This possibility is supported by our discovery that recombination is reduced dramatically in a cross involving a parent with the hms1-hms2 incompatibility.

Genetic diversity and gene differentiation among ten species of Zingiberaceae from Eastern India.

PubMed

Mohanty, Sujata; Panda, Manoj Kumar; Acharya, Laxmikanta; Nayak, Sanghamitra

2014-08-01

In the present study, genetic fingerprints of ten species of Zingiberaceae from eastern India were developed using PCR-based markers. 19 RAPD (Rapid Amplified polymorphic DNA), 8 ISSR (Inter Simple Sequence Repeats) and 8 SSR (Simple Sequence Repeats) primers were used to elucidate genetic diversity important for utilization, management and conservation. These primers produced 789 loci, out of which 773 loci were polymorphic (including 220 unique loci) and 16 monomorphic loci. Highest number of bands amplified (263) in Curcuma caesia whereas lowest (209) in Zingiber cassumunar. Though all the markers discriminated the species effectively, analysis of combined data of all markers resulted in better distinction of individual species. Highest number of loci was amplified with SSR primers with resolving power in a range of 17.4-39. Dendrogram based on three molecular data using unweighted pair group method with arithmetic mean classified all the species into two clusters. Mantle matrix correspondence test revealed high matrix correlation in all the cases. Correlation values for RAPD, ISSR and SSR were 0.797, 0.84 and 0.8, respectively, with combined data. In both the genera wild and cultivated species were completely separated from each other at genomic level. It also revealed distinct genetic identity between species of Curcuma and Zingiber. High genetic diversity documented in the present study provides a baseline data for optimization of conservation and breeding programme of the studied zingiberacious species.

Probing the prodigious strain fringes from Lourdes

NASA Astrophysics Data System (ADS)

Aerden, Domingo G. A. M.; Sayab, Mohammad

2017-12-01

We investigate the kinematics of classic sigmoidal strain fringes from Lourdes (France) and review previous genetic models, strain methods and strain rates for these microstructures. Displacement controlled quartz and calcite fibers within the fringes yield an average strain of 195% with the technique of Ramsay and Huber (1983). This agrees well with strains measured from boudinaged pyrite layers and calcite veins in the same rocks, but conflicts with ca. ∼675% strain in previous analogue models for the studied strain fringes produced by progressive simple shear. We show that the detailed geometry and orientation of fiber patterns are insufficiently explained by simple shear but imply two successive, differently oriented strain fields. Although all strain fringes have the same overall asymmetry, considerable morphological variation resulted from different amounts of rotation of pyrite grains and fringes. Minor rotation led to sharply kinked fibers that record a ca. 70° rotation of the kinematic frame. Larger (up to 145°) rotations, accommodated by antithetic sliding on pyrite-fringe contacts, produced more strongly and smoothly curved fibers. Combined with published Rb-Sr ages for the studied microstructures, our new strain data indicate an average strain rate of 1.41 10-15 s-1 during ca. 37 Myr. continuous growth.

Omics Data Complementarity Underlines Functional Cross-Communication in Yeast.

PubMed

Malod-Dognin, Noël; Pržulj, Nataša

2017-06-10

Mapping the complete functional layout of a cell and understanding the cross-talk between different processes are fundamental challenges. They elude us because of the incompleteness and noisiness of molecular data and because of the computational intractability of finding the exact answer. We perform a simple integration of three types of baker's yeast omics data to elucidate the functional organization and lines of cross-functional communication. We examine protein-protein interaction (PPI), co-expression (COEX) and genetic interaction (GI) data, and explore their relationship with the gold standard of functional organization, the Gene Ontology (GO). We utilize a simple framework that identifies functional cross-communication lines in each of the three data types, in GO, and collectively in the integrated model of the three omics data types; we present each of them in our new Functional Organization Map (FOM) model. We compare the FOMs of the three omics datasets with the FOM of GO and find that GI is in best agreement with GO, followed COEX and PPI. We integrate the three FOMs into a unified FOM and find that it is in better agreement with the FOM of GO than those of any omics dataset alone, demonstrating functional complementarity of different omics data.

Genetic algorithms and genetic programming for multiscale modeling: Applications in materials science and chemistry and advances in scalability

NASA Astrophysics Data System (ADS)

Sastry, Kumara Narasimha

2007-03-01

Effective and efficient rnultiscale modeling is essential to advance both the science and synthesis in a, wide array of fields such as physics, chemistry, materials science; biology, biotechnology and pharmacology. This study investigates the efficacy and potential of rising genetic algorithms for rnultiscale materials modeling and addresses some of the challenges involved in designing competent algorithms that solve hard problems quickly, reliably and accurately. In particular, this thesis demonstrates the use of genetic algorithms (GAs) and genetic programming (GP) in multiscale modeling with the help of two non-trivial case studies in materials science and chemistry. The first case study explores the utility of genetic programming (GP) in multi-timescaling alloy kinetics simulations. In essence, GP is used to bridge molecular dynamics and kinetic Monte Carlo methods to span orders-of-magnitude in simulation time. Specifically, GP is used to regress symbolically an inline barrier function from a limited set of molecular dynamics simulations to enable kinetic Monte Carlo that simulate seconds of real time. Results on a non-trivial example of vacancy-assisted migration on a surface of a face-centered cubic (fcc) Copper-Cobalt (CuxCo 1-x) alloy show that GP predicts all barriers with 0.1% error from calculations for less than 3% of active configurations, independent of type of potentials used to obtain the learning set of barriers via molecular dynamics. The resulting method enables 2--9 orders-of-magnitude increase in real-time dynamics simulations taking 4--7 orders-of-magnitude less CPU time. The second case study presents the application of multiobjective genetic algorithms (MOGAs) in multiscaling quantum chemistry simulations. Specifically, MOGAs are used to bridge high-level quantum chemistry and semiempirical methods to provide accurate representation of complex molecular excited-state and ground-state behavior. Results on ethylene and benzene---two common building blocks in organic chemistry---indicate that MOGAs produce High-quality semiempirical methods that (1) are stable to small perturbations, (2) yield accurate configuration energies on untested and critical excited states, and (3) yield ab initio quality excited-state dynamics. The proposed method enables simulations of more complex systems to realistic, multi-picosecond timescales, well beyond previous attempts or expectation of human experts, and 2--3 orders-of-magnitude reduction in computational cost. While the two applications use simple evolutionary operators, in order to tackle more complex systems, their scalability and limitations have to be investigated. The second part of the thesis addresses some of the challenges involved with a successful design of genetic algorithms and genetic programming for multiscale modeling. The first issue addressed is the scalability of genetic programming, where facetwise models are built to assess the population size required by GP to ensure adequate supply of raw building blocks and also to ensure accurate decision-making between competing building blocks. This study also presents a design of competent genetic programming, where traditional fixed recombination operators are replaced by building and sampling probabilistic models of promising candidate programs. The proposed scalable GP, called extended compact GP (eCGP), combines the ideas from extended compact genetic algorithm (eCGA) and probabilistic incremental program evolution (PIPE) and adaptively identifies, propagates and exchanges important subsolutions of a search problem. Results show that eCGP scales cubically with problem size on both GP-easy and GP-hard problems. Finally, facetwise models are developed to explore limitations of scalability of MOGAs, where the scalability of multiobjective algorithms in reliably maintaining Pareto-optimal solutions is addressed. The results show that even when the building blocks are accurately identified, massive multimodality of the search problems can easily overwhelm the nicher (diversity preserving operator) and lead to exponential scale-up. Facetwise models are developed, which incorporate the combined effects of model accuracy, decision making, and sub-structure supply, as well as the effect of niching on the population sizing, to predict a limit on the growth rate of a maximum number of sub-structures that can compete in the two objectives to circumvent the failure of the niching method. The results show that if the number of competing building blocks between multiple objectives is less than the proposed limit, multiobjective GAs scale-up polynomially with the problem size on boundedly-difficult problems.

A Low-Cost and Simple Genetic Screening for Cystic Fibrosis Provided by the Brazilian Public Health System.

PubMed

Rispoli, Thaiane; Martins de Castro, Simone; Grandi, Tarciana; Prado, Mayara; Filippon, Letícia; Dornelles da Silva, Cláudia Maria; Vargas, José Eduardo; Rossetti, Lucia Maria Rosa

2018-05-03

Cystic fibrosis newborn screening was implemented in Brazil by the Public Health System in 2012. Because of cost, only 1 mutation was tested - p.Phe508del. We developed a robust low-cost genetic test for screening 11 CFTR gene mutations with potential use in developing countries. Copyright © 2018 Elsevier Inc. All rights reserved.

Instantiating the multiple levels of analysis perspective in a program of study on externalizing behavior

PubMed Central

Beauchaine, Theodore P.; Gatzke-Kopp, Lisa M.

2014-01-01

During the last quarter century, developmental psychopathology has become increasingly inclusive and now spans disciplines ranging from psychiatric genetics to primary prevention. As a result, developmental psychopathologists have extended traditional diathesis–stress and transactional models to include causal processes at and across all relevant levels of analysis. Such research is embodied in what is known as the multiple levels of analysis perspective. We describe how multiple levels of analysis research has informed our current thinking about antisocial and borderline personality development among trait impulsive and therefore vulnerable individuals. Our approach extends the multiple levels of analysis perspective beyond simple Biology × Environment interactions by evaluating impulsivity across physiological systems (genetic, autonomic, hormonal, neural), psychological constructs (social, affective, motivational), developmental epochs (preschool, middle childhood, adolescence, adulthood), sexes (male, female), and methods of inquiry (self-report, informant report, treatment outcome, cardiovascular, electrophysiological, neuroimaging). By conducting our research using any and all available methods across these levels of analysis, we have arrived at a developmental model of trait impulsivity that we believe confers a greater understanding of this highly heritable trait and captures at least some heterogeneity in key behavioral outcomes, including delinquency and suicide. PMID:22781868

Predicting organismal vulnerability to climate warming: roles of behaviour, physiology and adaptation.

PubMed

Huey, Raymond B; Kearney, Michael R; Krockenberger, Andrew; Holtum, Joseph A M; Jess, Mellissa; Williams, Stephen E

2012-06-19

A recently developed integrative framework proposes that the vulnerability of a species to environmental change depends on the species' exposure and sensitivity to environmental change, its resilience to perturbations and its potential to adapt to change. These vulnerability criteria require behavioural, physiological and genetic data. With this information in hand, biologists can predict organisms most at risk from environmental change. Biologists and managers can then target organisms and habitats most at risk. Unfortunately, the required data (e.g. optimal physiological temperatures) are rarely available. Here, we evaluate the reliability of potential proxies (e.g. critical temperatures) that are often available for some groups. Several proxies for ectotherms are promising, but analogous ones for endotherms are lacking. We also develop a simple graphical model of how behavioural thermoregulation, acclimation and adaptation may interact to influence vulnerability over time. After considering this model together with the proxies available for physiological sensitivity to climate change, we conclude that ectotherms sharing vulnerability traits seem concentrated in lowland tropical forests. Their vulnerability may be exacerbated by negative biotic interactions. Whether tropical forest (or other) species can adapt to warming environments is unclear, as genetic and selective data are scant. Nevertheless, the prospects for tropical forest ectotherms appear grim.

To test, or not to test: time for a MODY calculator?

PubMed

Njølstad, P R; Molven, A

2012-05-01

To test, or not to test, that is often the question in diabetes genetics. This is why the paper of Shields et al in the current issue of Diabetologia is so warmly welcomed. MODY is the most common form of monogenic diabetes. Nevertheless, the optimal way of identifying MODY families still poses a challenge both for researchers and clinicians. Hattersley's group in Exeter, UK, have developed an easy-to-use MODY prediction model that can help to identify cases appropriate for genetic testing. By answering eight simple questions on the internet ( www.diabetesgenes.org/content/mody-probability-calculator ), the doctor receives a positive predictive value in return: the probability that the patient has MODY. Thus, the classical binary (yes/no) assessment provided by clinical diagnostic criteria has been substituted by a more rational, quantitative estimate. The model appears to discriminate well between MODY and type 1 and type 2 diabetes when diabetes is diagnosed before the age of 35 years. However, the performance of the MODY probability calculator should now be validated in other settings than where it was developed-and, as always, there is room for some improvements and modifications.

[Transcription activator-like effectors(TALEs)based genome engineering].

PubMed

Zhao, Mei-Wei; Duan, Cheng-Li; Liu, Jiang

2013-10-01

Systematic reverse-engineering of functional genome architecture requires precise modifications of gene sequences and transcription levels. The development and application of transcription activator-like effectors(TALEs) has created a wealth of genome engineering possibilities. TALEs are a class of naturally occurring DNA-binding proteins found in the plant pathogen Xanthomonas species. The DNA-binding domain of each TALE typically consists of tandem 34-amino acid repeat modules rearranged according to a simple cipher to target new DNA sequences. Customized TALEs can be used for a wide variety of genome engineering applications, including transcriptional modulation and genome editing. Such "genome engineering" has now been established in human cells and a number of model organisms, thus opening the door to better understanding gene function in model organisms, improving traits in crop plants and treating human genetic disorders.

Variance-based selection may explain general mating patterns in social insects.

PubMed

Rueppell, Olav; Johnson, Nels; Rychtár, Jan

2008-06-23

Female mating frequency is one of the key parameters of social insect evolution. Several hypotheses have been suggested to explain multiple mating and considerable empirical research has led to conflicting results. Building on several earlier analyses, we present a simple general model that links the number of queen matings to variance in colony performance and this variance to average colony fitness. The model predicts selection for multiple mating if the average colony succeeds in a focal task, and selection for single mating if the average colony fails, irrespective of the proximate mechanism that links genetic diversity to colony fitness. Empirical support comes from interspecific comparisons, e.g. between the bee genera Apis and Bombus, and from data on several ant species, but more comprehensive empirical tests are needed.

Cleaning up the mess: cell corpse clearance in Caenorhabditis elegans.

PubMed

Pinto, Sérgio Morgado; Hengartner, Michael Otmar

2012-12-01

Genetic and cell biology studies have led to the identification in Caenorhabditis elegans of a set of evolutionary conserved cellular mechanisms responsible for the clearance of apoptotic cells. Based on the phenotype of cell corpse clearance mutants, corpse clearance can be divided into three distinct, but linked steps: corpse recognition, corpse internalization, and corpse degradation. Work in recent years has led to a better understanding of the molecular pathways that mediate each of these steps. Here, we review recent developments in our understanding of in vivo cell corpse clearance in this simple but most elegant model organism. Copyright © 2012 Elsevier Ltd. All rights reserved.

First known EL5 chondrite - Evidence for dual genetic sequence for enstatite chondrites

NASA Technical Reports Server (NTRS)

Sears, D. W. G.; Weeks, K. S.; Rubin, A. E.

1984-01-01

The compositionally distinct EH and EL groups together with four (3-6) petrologic types which constitute the enstatite chondrites represent increasing degrees of metamorphic alteration. Although bulk composition variations preclude a simple conversion of EH4 into EL6 material, complex models which involve simultaneous bulk composition and petrologic type variations may be implied by other classification schemes in common use. Attention is presently given to the discovery of the first EL5 chondrite, which breaks the EH3,4-EH5-EL6 sequence and indicates that the enstatite chondrites constitute the two discrete, isochemical metamorphic sequences EH3-5 and EL5-6.

CRISPR therapeutic tools for complex genetic disorders and cancer (Review)

PubMed Central

Baliou, Stella; Adamaki, Maria; Kyriakopoulos, Anthony M.; Spandidos, Demetrios A.; Panayiotidis, Mihalis; Christodoulou, Ioannis; Zoumpourlis, Vassilis

2018-01-01

One of the fundamental discoveries in the field of biology is the ability to modulate the genome and to monitor the functional outputs derived from genomic alterations. In order to unravel new therapeutic options, scientists had initially focused on inducing genetic alterations in primary cells, in established cancer cell lines and mouse models using either RNA interference or cDNA overexpression or various programmable nucleases [zinc finger nucleases (ZNF), transcription activator-like effector nucleases (TALEN)]. Even though a huge volume of data was produced, its use was neither cheap nor accurate. Therefore, the clustered regularly interspaced short palindromic repeats (CRISPR) system was evidenced to be the next step in genome engineering tools. CRISPR-associated protein 9 (Cas9)-mediated genetic perturbation is simple, precise and highly efficient, empowering researchers to apply this method to immortalized cancerous cell lines, primary cells derived from mouse and human origins, xenografts, induced pluripotent stem cells, organoid cultures, as well as the generation of genetically engineered animal models. In this review, we assess the development of the CRISPR system and its therapeutic applications to a wide range of complex diseases (particularly distinct tumors), aiming at personalized therapy. Special emphasis is given to organoids and CRISPR screens in the design of innovative therapeutic approaches. Overall, the CRISPR system is regarded as an eminent genome engineering tool in therapeutics. We envision a new era in cancer biology during which the CRISPR-based genome engineering toolbox will serve as the fundamental conduit between the bench and the bedside; nonetheless, certain obstacles need to be addressed, such as the eradication of side-effects, maximization of efficiency, the assurance of delivery and the elimination of immunogenicity. PMID:29901119

Can the experimental evolution programme help us elucidate the genetic basis of adaptation in nature?

PubMed

Bailey, Susan F; Bataillon, Thomas

2016-01-01

There have been a variety of approaches taken to try to characterize and identify the genetic basis of adaptation in nature, spanning theoretical models, experimental evolution studies and direct tests of natural populations. Theoretical models can provide formalized and detailed hypotheses regarding evolutionary processes and patterns, from which experimental evolution studies can then provide important proofs of concepts and characterize what is biologically reasonable. Genetic and genomic data from natural populations then allow for the identification of the particular factors that have and continue to play an important role in shaping adaptive evolution in the natural world. Further to this, experimental evolution studies allow for tests of theories that may be difficult or impossible to test in natural populations for logistical and methodological reasons and can even generate new insights, suggesting further refinement of existing theories. However, as experimental evolution studies often take place in a very particular set of controlled conditions--that is simple environments, a small range of usually asexual species, relatively short timescales--the question remains as to how applicable these experimental results are to natural populations. In this review, we discuss important insights coming from experimental evolution, focusing on four key topics tied to the evolutionary genetics of adaptation, and within those topics, we discuss the extent to which the experimental work compliments and informs natural population studies. We finish by making suggestions for future work in particular a need for natural population genomic time series data, as well as the necessity for studies that combine both experimental evolution and natural population approaches. © 2015 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Structure and function of neonatal social communication in a genetic mouse model of autism.

PubMed

Takahashi, T; Okabe, S; Broin, P Ó; Nishi, A; Ye, K; Beckert, M V; Izumi, T; Machida, A; Kang, G; Abe, S; Pena, J L; Golden, A; Kikusui, T; Hiroi, N

2016-09-01

A critical step toward understanding autism spectrum disorder (ASD) is to identify both genetic and environmental risk factors. A number of rare copy number variants (CNVs) have emerged as robust genetic risk factors for ASD, but not all CNV carriers exhibit ASD and the severity of ASD symptoms varies among CNV carriers. Although evidence exists that various environmental factors modulate symptomatic severity, the precise mechanisms by which these factors determine the ultimate severity of ASD are still poorly understood. Here, using a mouse heterozygous for Tbx1 (a gene encoded in 22q11.2 CNV), we demonstrate that a genetically triggered neonatal phenotype in vocalization generates a negative environmental loop in pup-mother social communication. Wild-type pups used individually diverse sequences of simple and complicated call types, but heterozygous pups used individually invariable call sequences with less complicated call types. When played back, representative wild-type call sequences elicited maternal approach, but heterozygous call sequences were ineffective. When the representative wild-type call sequences were randomized, they were ineffective in eliciting vigorous maternal approach behavior. These data demonstrate that an ASD risk gene alters the neonatal call sequence of its carriers and this pup phenotype in turn diminishes maternal care through atypical social communication. Thus, an ASD risk gene induces, through atypical neonatal call sequences, less than optimal maternal care as a negative neonatal environmental factor.

Structure and function of neonatal social communication in a genetic mouse model of autism

PubMed Central

Takahashi, Tomohisa; Okabe, Shota; Ó Broin, Pilib; Nishi, Akira; Ye, Kenny; Beckert, Michael V.; Izumi, Takeshi; Machida, Akihiro; Kang, Gina; Abe, Seiji; Pena, Jose L.; Golden, Aaron; Kikusui, Takefumi; Hiroi, Noboru

2015-01-01

A critical step toward understanding autism spectrum disorder (ASD) is to identify both genetic and environmental risk factors. A number of rare copy number variants (CNVs) have emerged as robust genetic risk factors for ASD, but not all CNV carriers exhibit ASD and the severity of ASD symptoms varies among CNV carriers. Although evidence exists that various environmental factors modulate symptomatic severity, the precise mechanisms by which these factors determine the ultimate severity of ASD are still poorly understood. Here, using a mouse heterozygous for Tbx1 (a gene encoded in 22q11.2 CNV), we demonstrate that a genetically-triggered neonatal phenotype in vocalization generates a negative environmental loop in pup-mother social communication. Wild-type pups used individually diverse sequences of simple and complicated call types, but heterozygous pups used individually invariable call sequences with less complicated call types. When played back, representative wild-type call sequences elicited maternal approach, but heterozygous call sequences were ineffective. When the representative wild-type call sequences were randomized, they were ineffective in eliciting vigorous maternal approach behavior. These data demonstrate that an ASD risk gene alters the neonatal call sequence of its carriers and this pup phenotype in turn diminishes maternal care through atypical social communication. Thus, an ASD risk gene induces, through atypical neonatal call sequences, less than optimal maternal care as a negative neonatal environmental factor. PMID:26666205

Six quantitative trait loci influence task thresholds for hygienic behaviour in honeybees (Apis mellifera).

PubMed

Oxley, Peter R; Spivak, Marla; Oldroyd, Benjamin P

2010-04-01

Honeybee hygienic behaviour provides colonies with protection from many pathogens and is an important model system of the genetics of a complex behaviour. It is a textbook example of complex behaviour under simple genetic control: hygienic behaviour consists of two components--uncapping a diseased brood cell, followed by removal of the contents--each of which are thought to be modulated independently by a few loci of medium to large effect. A worker's genetic propensity to engage in hygienic tasks affects the intensity of the stimulus required before she initiates the behaviour. Genetic diversity within colonies leads to task specialization among workers, with a minority of workers performing the majority of nest-cleaning tasks. We identify three quantitative trait loci that influence the likelihood that workers will engage in hygienic behaviour and account for up to 30% of the phenotypic variability in hygienic behaviour in our population. Furthermore, we identify two loci that influence the likelihood that a worker will perform uncapping behaviour only, and one locus that influences removal behaviour. We report the first candidate genes associated with engaging in hygienic behaviour, including four genes involved in olfaction, learning and social behaviour, and one gene involved in circadian locomotion. These candidates will allow molecular characterization of this distinctive behavioural mode of disease resistance, as well as providing the opportunity for marker-assisted selection for this commercially significant trait.

A new QTL for resistance to Fusarium ear rot in maize.

PubMed

Li, Zhi-Min; Ding, Jun-Qiang; Wang, Rui-Xia; Chen, Jia-Fa; Sun, Xiao-Dong; Chen, Wei; Song, Wei-Bin; Dong, Hua-Fang; Dai, Xiao-Dong; Xia, Zong-Liang; Wu, Jian-Yu

2011-11-01

Understanding the inheritance of resistance to Fusarium ear rot is a basic prerequisite for an efficient resistance breeding in maize. In this study, 250 recombinant inbred lines (RILs) along with their resistant (BT-1) and susceptible (N6) parents were planted in Zhengzhou with three replications in 2007 and 2008. Each line was artificially inoculated using the nail-punch method. Significant genotypic variation in response to Fusarium ear rot was detected in both years. Based on a genetic map containing 207 polymorphic simple sequence repeat (SSR) markers with average genetic distances of 8.83 cM, the ear rot resistance quantitative trait loci (QTL) were analyzed by composite interval mapping with a mixed model (MCIM) across the environments. In total, four QTL were detected on chromosomes 3, 4, 5, and 6. The resistance allele at each of these four QTL was contributed by resistant parent BT-1, and accounted for 2.5-10.2% of the phenotypic variation. However, no significant epistasis interaction effect was detected after a two-dimensional genome scan. Among the four QTL, one QTL with the largest effect on chromosome 4 (bin 4.06) can be suggested to be a new locus for resistance to Fusarium ear rot, which broadens the genetic base for resistance to the disease and can be used for further genetic improvement in maize-breeding programs.

How Darwinian reductionism refutes genetic determinism.

PubMed

Rosoff, Philip M; Rosenberg, Alex

2006-03-01

Genetic determinism labels the morally problematical claim that some socially significant traits, traits we care about, such as sexual orientation, gender roles, violence, alcoholism, mental illness, intelligence, are largely the results of the operation of genes and not much alterable by environment, learning or other human intervention. Genetic determinism does not require that genes literally fix these socially significant traits, but rather that they constrain them within narrow channels beyond human intervention. In this essay we analyze genetic determinism in light of what is now known about the inborn error of metabolism phenylketonuria (PKU), which has for so long been the poster child 'simple' argument in favor of some form of genetic determinism. We demonstrate that this case proves the exact opposite of what it has been proposed to support and provides a strong refutation of genetic determinism in all its guises.

[Study on the mode of inheritance for familial polycystic ovary syndrome].

PubMed

Mao, W; Li, M; Chen, Y; Lu, C; Wang, Y; Zhang, X; Qiao, J; Wang, A

2001-02-01

To investigate the mode of inheritance of polycystic ovary syndrome(PCOS). The first female relatives with irregular cycle and the first male relatives with premature balding in each nuclear family were designated the affected. Their prevalence rates in families were respectively calculated. Analyses of segregation ratio were carried out among 139 nuclear families with PCOS by the methods of simple segregation and complex segregation of genetic epidemiology, respectively. The prevalence rates of irregular cycle among mothers and sisters with PCOS were 37.4% and 33.1% respectively, and the prevalence rates of premature balding among fathers and brothers of patients were 19.4% and 6.5%, respectively. The simple segregation analysis indicated that the segregation ratio of PCOS trait in siblings was 0.3023, the complex segregation analysis indicated that it fitted in with the inheritance model of co-dominant disorder with full penetrance and sporadic cases. The frequency of homozygote of disease gene in population was 0.046. PCOS presents the mode of co-dominant inheritance with complete penetrance.

A simple method for imaging axonal transport in aging neurons using the adult Drosophila wing.

PubMed

Vagnoni, Alessio; Bullock, Simon L

2016-09-01

There is growing interest in the link between axonal cargo transport and age-associated neuronal dysfunction. The study of axonal transport in neurons of adult animals requires intravital or ex vivo imaging approaches, which are laborious and expensive in vertebrate models. We describe simple, noninvasive procedures for imaging cargo motility within axons using sensory neurons of the translucent Drosophila wing. A key aspect is a method for mounting the intact fly that allows detailed imaging of transport in wing neurons. Coupled with existing genetic tools in Drosophila, this is a tractable system for studying axonal transport over the life span of an animal and thus for characterization of the relationship between cargo dynamics, neuronal aging and disease. Preparation of a sample for imaging takes ∼5 min, with transport typically filmed for 2-3 min per wing. We also document procedures for the quantification of transport parameters from the acquired images and describe how the protocol can be adapted to study other cell biological processes in aging neurons.

Research Techniques Made Simple: Mouse Models of Autoimmune Blistering Diseases.

PubMed

Pollmann, Robert; Eming, Rüdiger

2017-01-01

Autoimmune blistering diseases are examples of autoantibody-mediated, organ-specific autoimmune disorders. Based on a genetic susceptibility, such as a strong HLA-class II association, as yet unknown triggering factors induce the formation of circulating and tissue-bound autoantibodies that are mainly directed against adhesion structures of the skin and mucous membranes. Compared with other autoimmune diseases, especially systemic disorders, the pathogenicity of autoimmune blistering diseases is relatively well described. Several animal models of autoimmune blistering diseases have been established that helped to uncover the immunological and molecular mechanisms underlying the blistering phenotypes. Each in vivo model focuses on specific aspects of the autoimmune cascade, from loss of immunological tolerance on the level of T and B cells to the pathogenic effects of autoantibodies upon binding to their target autoantigen. We discuss current mouse models of autoimmune blistering diseases, including models of pemphigus vulgaris, bullous pemphigoid, epidermolysis bullosa acquisita, and dermatitis herpetiformis. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Genealogical and evolutionary inference with the human Y chromosome.

PubMed

Stumpf, M P; Goldstein, D B

2001-03-02

Population genetics has emerged as a powerful tool for unraveling human history. In addition to the study of mitochondrial and autosomal DNA, attention has recently focused on Y-chromosome variation. Ambiguities and inaccuracies in data analysis, however, pose an important obstacle to further development of the field. Here we review the methods available for genealogical inference using Y-chromosome data. Approaches can be divided into those that do and those that do not use an explicit population model in genealogical inference. We describe the strengths and weaknesses of these model-based and model-free approaches, as well as difficulties associated with the mutation process that affect both methods. In the case of genealogical inference using microsatellite loci, we use coalescent simulations to show that relatively simple generalizations of the mutation process can greatly increase the accuracy of genealogical inference. Because model-free and model-based approaches have different biases and limitations, we conclude that there is considerable benefit in the continued use of both types of approaches.

QSAR modeling of acute toxicity on mammals caused by aromatic compounds: the case study using oral LD50 for rats.

PubMed

Rasulev, Bakhtiyor; Kusić, Hrvoje; Leszczynska, Danuta; Leszczynski, Jerzy; Koprivanac, Natalija

2010-05-01

The goal of the study was to predict toxicity in vivo caused by aromatic compounds structured with a single benzene ring and the presence or absence of different substituent groups such as hydroxyl-, nitro-, amino-, methyl-, methoxy-, etc., by using QSAR/QSPR tools. A Genetic Algorithm and multiple regression analysis were applied to select the descriptors and to generate the correlation models. The most predictive model is shown to be the 3-variable model which also has a good ratio of the number of descriptors and their predictive ability to avoid overfitting. The main contributions to the toxicity were shown to be the polarizability weighted MATS2p and the number of certain groups C-026 descriptors. The GA-MLRA approach showed good results in this study, which allows the building of a simple, interpretable and transparent model that can be used for future studies of predicting toxicity of organic compounds to mammals.

Social dilemmas among supergenes: intragenomic sexual conflict and a selfing solution in Oenothera.

PubMed

Brown, Sam P; Levin, Donald A

2011-12-01

Recombination is a powerful policing mechanism to control intragenomic cheats. The "parliament of the genes" can often rapidly block driving genes from cheating during meiosis. But what if the genome parliament is reduced to only two members, or supergenes? Using a series of simple game-theoretic models inspired by the peculiar genetics of Oenothera sp., we illustrate that a two supergene genome (α and β) can produce a number of surprising evolutionary dynamics, including increases in lineage longevity following a transition from sexuality (outcrossing) to asexuality (clonal self-fertilization). We end by interpreting the model in the broader context of the evolution of mutualism, which highlights that greater α, β cooperation in the self-fertilizing model can be viewed as an example of partner fidelity driving multilineage cooperation. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Heterosis and outbreeding depression: A multi-locus model and an application to salmon production

USGS Publications Warehouse

Emlen, John M.

1991-01-01

Both artificial propagation and efforts to preserve or augment natural populations sometimes involve, wittingly or unwittingly, the mixing of different gene pools. The advantages of such mixing vis-à-vis the alleviation of inbreeding depression are well known. Acknowledged, but less well understood, are the complications posed by outbreeding depression. This paper derives a simple model of outbreeding depression and demonstrates that it is reasonably possible to predict the generation-to-generation fitness course of hybrids derived from parents from different origins. Genetic difference, or distance between parental types, is defined by the drop in fitness experienced by one type reared at the site to which the other is locally adapted. For situations where decisions involving stock mixing must be made in the absence of complete information, a sensitivity analysis-based conflict resolution method (the Good-Bad-Ugly model) is described.

Empty tracks optimization based on Z-Map model

NASA Astrophysics Data System (ADS)

Liu, Le; Yan, Guangrong; Wang, Zaijun; Zang, Genao

2017-12-01

For parts with many features, there are more empty tracks during machining. If these tracks are not optimized, the machining efficiency will be seriously affected. In this paper, the characteristics of the empty tracks are studied in detail. Combining with the existing optimization algorithm, a new tracks optimization method based on Z-Map model is proposed. In this method, the tool tracks are divided into the unit processing section, and then the Z-Map model simulation technique is used to analyze the order constraint between the unit segments. The empty stroke optimization problem is transformed into the TSP with sequential constraints, and then through the genetic algorithm solves the established TSP problem. This kind of optimization method can not only optimize the simple structural parts, but also optimize the complex structural parts, so as to effectively plan the empty tracks and greatly improve the processing efficiency.

Bacteria, Yeast, Worms, and Flies: Exploiting simple model organisms to investigate human mitochondrial diseases

PubMed Central

Rea, Shane L.; Graham, Brett H.; Nakamaru-Ogiso, Eiko; Kar, Adwitiya; Falk, Marni J.

2013-01-01

The extensive conservation of mitochondrial structure, composition, and function across evolution offers a unique opportunity to expand our understanding of human mitochondrial biology and disease. By investigating the biology of much simpler model organisms, it is often possible to answer questions that are unreachable at the clinical level. Here, we review the relative utility of four different model organisms, namely the bacteria Escherichia coli, the yeast Saccharomyces cerevisiae, the nematode Caenorhabditis elegans and the fruit fly Drosophila melanogaster, in studying the role of mitochondrial proteins relevant to human disease. E. coli are single cell, prokaryotic bacteria that have proven to be a useful model system in which to investigate mitochondrial respiratory chain protein structure and function. S. cerevisiae is a single-celled eukaryote that can grow equally well by mitochondrial-dependent respiration or by ethanol fermentation, a property that has proven to be a veritable boon for investigating mitochondrial functionality. C. elegans is a multi-cellular, microscopic worm that is organized into five major tissues and has proven to be a robust model animal for in vitro and in vivo studies of primary respiratory chain dysfunction and its potential therapies in humans. Studied for over a century, D. melanogaster is a classic metazoan model system offering an abundance of genetic tools and reagents that facilitates investigations of mitochondrial biology using both forward and reverse genetics. The respective strengths and limitations of each species relative to mitochondrial studies are explored. In addition, an overview is provided of major discoveries made in mitochondrial biology in each of these four model systems. PMID:20818735

Sensitive detection of proteasomal activation using the Deg-On mammalian synthetic gene circuit.

PubMed

Zhao, Wenting; Bonem, Matthew; McWhite, Claire; Silberg, Jonathan J; Segatori, Laura

2014-04-08

The ubiquitin proteasome system (UPS) has emerged as a drug target for diverse diseases characterized by altered proteostasis, but pharmacological agents that enhance UPS activity have been challenging to establish. Here we report the Deg-On system, a genetic inverter that translates proteasomal degradation of the transcriptional regulator TetR into a fluorescent signal, thereby linking UPS activity to an easily detectable output, which can be tuned using tetracycline. We demonstrate that this circuit responds to modulation of UPS activity in cell culture arising from the inhibitor MG-132 and activator PA28γ. Guided by predictive modelling, we enhanced the circuit's signal sensitivity and dynamic range by introducing a feedback loop that enables self-amplification of TetR. By linking UPS activity to a simple and tunable fluorescence output, these genetic inverters will enable a variety of applications, including screening for UPS activating molecules and selecting for mammalian cells with different levels of proteasome activity.

Studying gene regulation in methanogenic archaea.

PubMed

Rother, Michael; Sattler, Christian; Stock, Tilmann

2011-01-01

Methanogenic archaea are a unique group of strictly anaerobic microorganisms characterized by their ability, and dependence, to convert simple C1 and C2 compounds to methane for growth. The major models for studying the biology of methanogens are members of the Methanococcus and Methanosarcina species. Recent development of sophisticated tools for molecular analysis and for genetic manipulation allows investigating not only their metabolism but also their cell cycle, and their interaction with the environment in great detail. One aspect of such analyses is assessment and dissection of methanoarchaeal gene regulation, for which, at present, only a handful of cases have been investigated thoroughly, partly due to the great methodological effort required. However, it becomes more and more evident that many new regulatory paradigms can be unraveled in this unique archaeal group. Here, we report both molecular and physiological/genetic methods to assess gene regulation in Methanococcus maripaludis and Methanosarcina acetivorans, which should, however, be applicable for other methanogens as well. Copyright © 2011 Elsevier Inc. All rights reserved.

Efficient transformation and artificial miRNA gene silencing in Lemna minor.

PubMed

Cantó-Pastor, A; Mollá-Morales, A; Ernst, E; Dahl, W; Zhai, J; Yan, Y; Meyers, B C; Shanklin, J; Martienssen, R

2015-01-01

Despite rapid doubling time, simple architecture and ease of metabolic labelling, a lack of genetic tools in the Lemnaceae (duckweed) has impeded the full implementation of this organism as a model for biological research. Here, we present technologies to facilitate high-throughput genetic studies in duckweed. We developed a fast and efficient method for producing Lemna minor stable transgenic fronds via Agrobacterium-mediated transformation and regeneration from tissue culture. Additionally, we engineered an artificial microRNA (amiRNA) gene silencing system. We identified a Lemna gibba endogenous miR166 precursor and used it as a backbone to produce amiRNAs. As a proof of concept we induced the silencing of CH42, a magnesium chelatase subunit, using our amiRNA platform. Expression of CH42 in transgenic L. minor fronds was significantly reduced, which resulted in reduction of chlorophyll pigmentation. The techniques presented here will enable tackling future challenges in the biology and biotechnology of Lemnaceae. © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands.

Animal Models of Alcoholic Liver Disease: Pathogenesis and Clinical Relevance

PubMed Central

Gao, Bin; Xu, Ming-Jiang; Bertola, Adeline; Wang, Hua; Zhou, Zhou; Liangpunsakul, Suthat

2017-01-01

Alcoholic liver disease (ALD), a leading cause of chronic liver injury worldwide, comprises a range of disorders including simple steatosis, steatohepatitis, cirrhosis, and hepatocellular carcinoma. Over the last five decades, many animal models for the study of ALD pathogenesis have been developed. Recently, a chronic-plus-binge ethanol feeding model was reported. This model induces significant steatosis, hepatic neutrophil infiltration, and liver injury. A clinically relevant model of high-fat diet feeding plus binge ethanol was also developed, which highlights the risk of excessive binge drinking in obese/overweight individuals. All of these models recapitulate some features of the different stages of ALD and have been widely used by many investigators to study the pathogenesis of ALD and to test for therapeutic drugs/components. However, these models are somewhat variable, depending on mouse genetic background, ethanol dose, and animal facility environment. This review focuses on these models and discusses these variations and some methods to improve the feeding protocol. The pathogenesis, clinical relevance, and translational studies of these models are also discussed. PMID:28411363

On computation of p-values in parametric linkage analysis.

PubMed

Kurbasic, Azra; Hössjer, Ola

2004-01-01

Parametric linkage analysis is usually used to find chromosomal regions linked to a disease (phenotype) that is described with a specific genetic model. This is done by investigating the relations between the disease and genetic markers, that is, well-characterized loci of known position with a clear Mendelian mode of inheritance. Assume we have found an interesting region on a chromosome that we suspect is linked to the disease. Then we want to test the hypothesis of no linkage versus the alternative one of linkage. As a measure we use the maximal lod score Z(max). It is well known that the maximal lod score has asymptotically a (2 ln 10)(-1) x (1/2 chi2(0) + 1/2 chi2(1)) distribution under the null hypothesis of no linkage when only one point (one marker) on the chromosome is studied. In this paper, we show, both by simulations and theoretical arguments, that the null hypothesis distribution of Zmax has no simple form when more than one marker is used (multipoint analysis). In fact, the distribution of Zmax depends on the number of families, their structure, the assumed genetic model, marker denseness, and marker informativity. This means that a constant critical limit of Zmax leads to tests associated with different significance levels. Because of the above-mentioned problems, from the statistical point of view the maximal lod score should be supplemented by a p-value when results are reported. Copyright (c) 2004 S. Karger AG, Basel.

Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies.

PubMed

Song, Minsun; Wheeler, William; Caporaso, Neil E; Landi, Maria Teresa; Chatterjee, Nilanjan

2018-03-01

Genome-wide association studies (GWAS) are now routinely imputed for untyped single nucleotide polymorphisms (SNPs) based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele counts for imputed SNPs as the dosage variable is known to produce valid score test for genetic association. In this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic associations incorporating gene-environment interactions. We focus on case-control association studies where inference for an underlying logistic regression model can be performed using alternative methods that rely on varying degree on an assumption of gene-environment independence in the underlying population. As increasingly large-scale GWAS are being performed through consortia effort where it is preferable to share only summary-level information across studies, we also describe simple mechanisms for implementing score tests based on standard meta-analysis of "one-step" maximum-likelihood estimates across studies. Applications of the methods in simulation studies and a dataset from GWAS of lung cancer illustrate ability of the proposed methods to maintain type-I error rates for the underlying testing procedures. For analysis of imputed SNPs, similar to typed SNPs, the retrospective methods can lead to considerable efficiency gain for modeling of gene-environment interactions under the assumption of gene-environment independence. Methods are made available for public use through CGEN R software package. © 2017 WILEY PERIODICALS, INC.

Genetic Obesity Risk and Attenuation Effect of Physical Fitness in Mexican-Mestizo Population: a Case-Control Study.

PubMed

Costa-Urrutia, Paula; Abud, Carolina; Franco-Trecu, Valentina; Colistro, Valentina; Rodríguez-Arellano, Martha Eunice; Vázquez-Pérez, Joel; Granados, Julio; Seelaender, Marilia

2017-05-01

We analyzed commonly reported European and Asian obesity-related gene variants in a Mexican-Mestizo population through each single nucleotide polymorphism (SNP) and a genetic risk score (GRS) based on 23 selected SNPs. Study subjects were physically active Mexican-Mestizo adults (n  =  608) with body mass index (BMI) values from 18 to 55 kg/m 2 . For each SNP and for the GRS, logistic models were performed to test for simple SNP associations with BMI, fat mass percentage (FMP), waist circumference (WC), and the interaction with VO 2max and muscular endurance (ME). To further understand the SNP or GRS*physical fitness components, generalized linear models were performed. Obesity risk was significantly associated to 6 SNPs (ADRB2 rs1042713, APOB rs512535, PPARA rs1800206, TNFA rs361525, TRHR rs7832552 and rs16892496) after adjustment by gender, age, ancestry, VO 2max , and ME. ME attenuated the influence of APOB rs512535 and TNFA rs361525 on obesity risk in FMP. WC was significantly associated to GRS. Both ME and VO 2max attenuated GRS effect on WC. We report associations for 6 out of 23 SNPs and for the GRS, which confer obesity risk, a novel finding for Mexican-Mestizo physically active population. Also, the importance of including physical fitness components variables in obesity genetic risk studies is highlighted, with special regard to intervention purposes. © 2017 John Wiley & Sons Ltd/University College London.

A discrete model of Drosophila eggshell patterning reveals cell-autonomous and juxtacrine effects.

PubMed

Fauré, Adrien; Vreede, Barbara M I; Sucena, Elio; Chaouiya, Claudine

2014-03-01

The Drosophila eggshell constitutes a remarkable system for the study of epithelial patterning, both experimentally and through computational modeling. Dorsal eggshell appendages arise from specific regions in the anterior follicular epithelium that covers the oocyte: two groups of cells expressing broad (roof cells) bordered by rhomboid expressing cells (floor cells). Despite the large number of genes known to participate in defining these domains and the important modeling efforts put into this developmental system, key patterning events still lack a proper mechanistic understanding and/or genetic basis, and the literature appears to conflict on some crucial points. We tackle these issues with an original, discrete framework that considers single-cell models that are integrated to construct epithelial models. We first build a phenomenological model that reproduces wild type follicular epithelial patterns, confirming EGF and BMP signaling input as sufficient to establish the major features of this patterning system within the anterior domain. Importantly, this simple model predicts an instructive juxtacrine signal linking the roof and floor domains. To explore this prediction, we define a mechanistic model that integrates the combined effects of cellular genetic networks, cell communication and network adjustment through developmental events. Moreover, we focus on the anterior competence region, and postulate that early BMP signaling participates with early EGF signaling in its specification. This model accurately simulates wild type pattern formation and is able to reproduce, with unprecedented level of precision and completeness, various published gain-of-function and loss-of-function experiments, including perturbations of the BMP pathway previously seen as conflicting results. The result is a coherent model built upon rules that may be generalized to other epithelia and developmental systems.

Application of synthetic biology in cyanobacteria and algae

PubMed Central

Wang, Bo; Wang, Jiangxin; Zhang, Weiwen; Meldrum, Deirdre R.

2012-01-01

Cyanobacteria and algae are becoming increasingly attractive cell factories for producing renewable biofuels and chemicals due to their ability to capture solar energy and CO2 and their relatively simple genetic background for genetic manipulation. Increasing research efforts from the synthetic biology approach have been made in recent years to modify cyanobacteria and algae for various biotechnological applications. In this article, we critically review recent progresses in developing genetic tools for characterizing or manipulating cyanobacteria and algae, the applications of genetically modified strains for synthesizing renewable products such as biofuels and chemicals. In addition, the emergent challenges in the development and application of synthetic biology for cyanobacteria and algae are also discussed. PMID:23049529

Genetic diversity of the Arctic fox using SRAP markers.

PubMed

Zhang, M; Bai, X J

2013-12-04

Sequence-related amplified polymorphism (SRAP) is a recently developed molecular marker technique that is stable, simple, reliable, and achieves moderate to high numbers of codominant markers. This study is the first to apply SRAP markers in a mammal, namely the Arctic fox. In order to investigate the genetic diversity of the Arctic fox and to provide a reference for use of its germplasm, we analyzed 7 populations of Arctic fox by SRAP. The genetic similarity coefficient, genetic distance, proportion of polymorphic loci, total genetic diversity (Ht), genetic diversity within populations (Hs), and genetic differentiation (Gst) were calculated using the Popgene software package. The results indicated abundant genetic diversity among the different populations of Arctic fox studied in China. The genetic similarity coefficient ranged from 0.1694 to 0.0417, genetic distance ranged from 0.8442 to 0.9592, and the proportion of polymorphic loci was smallest in the TS group. Genetic diversity ranged from 0.2535 to 0.3791, Ht was 0.3770, Hs was 0.3158, Gst was 0.1624, and gene flow (Nm) was estimated at 2.5790. Thus, a high level of genetic diversity and many genetic relationships were found in the populations of Arctic fox evaluated in this study.

Genetic control of inflorescence architecture in legumes

PubMed Central

Benlloch, Reyes; Berbel, Ana; Ali, Latifeh; Gohari, Gholamreza; Millán, Teresa; Madueño, Francisco

2015-01-01

The architecture of the inflorescence, the shoot system that bears the flowers, is a main component of the huge diversity of forms found in flowering plants. Inflorescence architecture has also a strong impact on the production of fruits and seeds, and on crop management, two highly relevant agronomical traits. Elucidating the genetic networks that control inflorescence development, and how they vary between different species, is essential to understanding the evolution of plant form and to being able to breed key architectural traits in crop species. Inflorescence architecture depends on the identity and activity of the meristems in the inflorescence apex, which determines when flowers are formed, how many are produced and their relative position in the inflorescence axis. Arabidopsis thaliana, where the genetic control of inflorescence development is best known, has a simple inflorescence, where the primary inflorescence meristem directly produces the flowers, which are thus borne in the main inflorescence axis. In contrast, legumes represent a more complex inflorescence type, the compound inflorescence, where flowers are not directly borne in the main inflorescence axis but, instead, they are formed by secondary or higher order inflorescence meristems. Studies in model legumes such as pea (Pisum sativum) or Medicago truncatula have led to a rather good knowledge of the genetic control of the development of the legume compound inflorescence. In addition, the increasing availability of genetic and genomic tools for legumes is allowing to rapidly extending this knowledge to other grain legume crops. This review aims to describe the current knowledge of the genetic network controlling inflorescence development in legumes. It also discusses how the combination of this knowledge with the use of emerging genomic tools and resources may allow rapid advances in the breeding of grain legume crops. PMID:26257753

Construction of a genetic linkage map and analysis of quantitative trait loci associated with the agronomically important traits of Pleurotus eryngii

Treesearch

Chak Han Im; Young-Hoon Park; Kenneth E. Hammel; Bokyung Park; Soon Wook Kwon; Hojin Ryu; Jae-San Ryu

2016-01-01

Breeding new strains with improved traits is a long-standing goal of mushroom breeders that can be expedited by marker-assisted selection (MAS). We constructed a genetic linkage map of Pleurotus eryngii based on segregation analysis of markers in postmeiotic monokaryons from KNR2312. In total, 256 loci comprising 226 simple sequence-repeat (SSR) markers, 2 mating-type...

Genetic Algorithms and Their Application to the Protein Folding Problem

DTIC Science & Technology

1993-12-01

and symbolic methods, random methods such as Monte Carlo simulation and simulated annealing, distance geometry, and molecular dynamics. Many of these...calculated energies with those obtained using the molecular simulation software package called CHARMm. 10 9) Test both the simple and parallel simpie genetic...homology-based, and simplification techniques. 3.21 Molecular Dynamics. Perhaps the most natural approach is to actually simulate the folding process. This

Analysis of genetic relationships and identification of lily cultivars based on inter-simple sequence repeat markers.

PubMed

Cui, G F; Wu, L F; Wang, X N; Jia, W J; Duan, Q; Ma, L L; Jiang, Y L; Wang, J H

2014-07-29

Inter-simple sequence repeat (ISSR) markers were used to discriminate 62 lily cultivars of 5 hybrid series. Eight ISSR primers generated 104 bands in total, which all showed 100% polymorphism, and an average of 13 bands were amplified by each primer. Two software packages, POPGENE 1.32 and NTSYSpc 2.1, were used to analyze the data matrix. Our results showed that the observed number of alleles (NA), effective number of alleles (NE), Nei's genetic diversity (H), and Shannon's information index (I) were 1.9630, 1.4179, 0.2606, and 0.4080, respectively. The highest genetic similarity (0.9601) was observed between the Oriental x Trumpet and Oriental lilies, which indicated that the two hybrids had a close genetic relationship. An unweighted pair-group method with arithmetic means dendrogram showed that the 62 lily cultivars clustered into two discrete groups. The first group included the Oriental and OT cultivars, while the Asiatic, LA, and Longiflorum lilies were placed in the second cluster. The distribution of individuals in the principal component analysis was consistent with the clustering of the dendrogram. Fingerprints of all lily cultivars built from 8 primers could be separated completely. This study confirmed the effect and efficiency of ISSR identification in lily cultivars.

Genetic Diversity of Arabica Coffee (Coffea arabica L.) in Nicaragua as Estimated by Simple Sequence Repeat Markers

PubMed Central

Geleta, Mulatu; Herrera, Isabel; Monzón, Arnulfo; Bryngelsson, Tomas

2012-01-01

Coffea arabica L. (arabica coffee), the only tetraploid species in the genus Coffea, represents the majority of the world's coffee production and has a significant contribution to Nicaragua's economy. The present paper was conducted to determine the genetic diversity of arabica coffee in Nicaragua for its conservation and breeding values. Twenty-six populations that represent eight varieties in Nicaragua were investigated using simple sequence repeat (SSR) markers. A total of 24 alleles were obtained from the 12 loci investigated across 260 individual plants. The total Nei's gene diversity (H T) and the within-population gene diversity (H S) were 0.35 and 0.29, respectively, which is comparable with that previously reported from other countries and regions. Among the varieties, the highest diversity was recorded in the variety Catimor. Analysis of variance (AMOVA) revealed that about 87% of the total genetic variation was found within populations and the remaining 13% differentiate the populations (F ST = 0.13; P < 0.001). The variation among the varieties was also significant. The genetic variation in Nicaraguan coffee is significant enough to be used in the breeding programs, and most of this variation can be conserved through ex situ conservation of a low number of populations from each variety. PMID:22701376

REML/BLUP and sequential path analysis in estimating genotypic values and interrelationships among simple maize grain yield-related traits.

PubMed

Olivoto, T; Nardino, M; Carvalho, I R; Follmann, D N; Ferrari, M; Szareski, V J; de Pelegrin, A J; de Souza, V Q

2017-03-22

Methodologies using restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) in combination with sequential path analysis in maize are still limited in the literature. Therefore, the aims of this study were: i) to use REML/BLUP-based procedures in order to estimate variance components, genetic parameters, and genotypic values of simple maize hybrids, and ii) to fit stepwise regressions considering genotypic values to form a path diagram with multi-order predictors and minimum multicollinearity that explains the relationships of cause and effect among grain yield-related traits. Fifteen commercial simple maize hybrids were evaluated in multi-environment trials in a randomized complete block design with four replications. The environmental variance (78.80%) and genotype-vs-environment variance (20.83%) accounted for more than 99% of the phenotypic variance of grain yield, which difficult the direct selection of breeders for this trait. The sequential path analysis model allowed the selection of traits with high explanatory power and minimum multicollinearity, resulting in models with elevated fit (R 2 > 0.9 and ε < 0.3). The number of kernels per ear (NKE) and thousand-kernel weight (TKW) are the traits with the largest direct effects on grain yield (r = 0.66 and 0.73, respectively). The high accuracy of selection (0.86 and 0.89) associated with the high heritability of the average (0.732 and 0.794) for NKE and TKW, respectively, indicated good reliability and prospects of success in the indirect selection of hybrids with high-yield potential through these traits. The negative direct effect of NKE on TKW (r = -0.856), however, must be considered. The joint use of mixed models and sequential path analysis is effective in the evaluation of maize-breeding trials.

Reflex epileptic mechanisms in humans: Lessons about natural ictogenesis.

PubMed

Wolf, Peter

2017-06-01

The definition of reflex epileptic seizures is that specific seizure types can be triggered by certain sensory or cognitive stimuli. Simple triggers are sensory (most often visual, more rarely tactile or proprioceptive; simple audiogenic triggers in humans are practically nonexistent) and act within seconds, whereas complex triggers like praxis, reading and talking, and music are mostly cognitive and work within minutes. The constant relation between a qualitatively, often even quantitatively, well-defined stimulus and a specific epileptic response provides unique possibilities to investigate seizure generation in natural human epilepsies. For several reflex epileptic mechanisms (REMs), this has been done. Reflex epileptic mechanisms have been reported less often in focal lesional epilepsies than in idiopathic "generalized" epilepsies (IGEs) which are primarily genetically determined. The key syndrome of IGE is juvenile myoclonic epilepsy (JME), where more than half of the patients present reflex epileptic traits (photosensitivity, eye closure sensitivity, praxis induction, and language-induced orofacial reflex myocloni). Findings with multimodal investigations of cerebral function concur to indicate that ictogenic mechanisms in IGEs largely (ab)use preexisting functional anatomic networks (CNS subsystems) normally serving highly complex physiological functions (e.g., deliberate complex actions and linguistic communication) which supports the concept of system epilepsy. Whereas REMs in IGEs, thus, are primarily function-related, in focal epilepsies, they are primarily localization-related. This article is part of a Special Issue entitled "Genetic and Reflex Epilepsies, Audiogenic Seizures and Strains: From Experimental Models to the Clinic". Copyright © 2015 Elsevier Inc. All rights reserved.

Modeling of Non-isothermal Austenite Formation in Spring Steel

NASA Astrophysics Data System (ADS)

Huang, He; Wang, Baoyu; Tang, Xuefeng; Li, Junling

2017-12-01

The austenitization kinetics description of spring steel 60Si2CrA plays an important role in providing guidelines for industrial production. The dilatometric curves of 60Si2CrA steel were measured using a dilatometer DIL805A at heating rates of 0.3 K to 50 K/s (0.3 °C/s to 50 °C/s). Based on the dilatometric curves, a unified kinetics model using the internal state variable (ISV) method was derived to describe the non-isothermal austenitization kinetics of 60Si2CrA, and the abovementioned model models the incubation and transition periods. The material constants in the model were determined using a genetic algorithm-based optimization technique. Additionally, good agreement between predicted and experimental volume fractions of transformed austenite was obtained, indicating that the model is effective for describing the austenitization kinetics of 60Si2CrA steel. Compared with other modeling methods of austenitization kinetics, this model, which uses the ISV method, has some advantages, such as a simple formula and explicit physics meaning, and can be probably used in engineering practice.

Internal combustion engine control for series hybrid electric vehicles by parallel and distributed genetic programming/multiobjective genetic algorithms

NASA Astrophysics Data System (ADS)

Gladwin, D.; Stewart, P.; Stewart, J.

2011-02-01

This article addresses the problem of maintaining a stable rectified DC output from the three-phase AC generator in a series-hybrid vehicle powertrain. The series-hybrid prime power source generally comprises an internal combustion (IC) engine driving a three-phase permanent magnet generator whose output is rectified to DC. A recent development has been to control the engine/generator combination by an electronically actuated throttle. This system can be represented as a nonlinear system with significant time delay. Previously, voltage control of the generator output has been achieved by model predictive methods such as the Smith Predictor. These methods rely on the incorporation of an accurate system model and time delay into the control algorithm, with a consequent increase in computational complexity in the real-time controller, and as a necessity relies to some extent on the accuracy of the models. Two complementary performance objectives exist for the control system. Firstly, to maintain the IC engine at its optimal operating point, and secondly, to supply a stable DC supply to the traction drive inverters. Achievement of these goals minimises the transient energy storage requirements at the DC link, with a consequent reduction in both weight and cost. These objectives imply constant velocity operation of the IC engine under external load disturbances and changes in both operating conditions and vehicle speed set-points. In order to achieve these objectives, and reduce the complexity of implementation, in this article a controller is designed by the use of Genetic Programming methods in the Simulink modelling environment, with the aim of obtaining a relatively simple controller for the time-delay system which does not rely on the implementation of real time system models or time delay approximations in the controller. A methodology is presented to utilise the miriad of existing control blocks in the Simulink libraries to automatically evolve optimal control structures.

Modeling and parameter identification of the simultaneous saccharification-fermentation process for ethanol production.

PubMed

Ochoa, Silvia; Yoo, Ahrim; Repke, Jens-Uwe; Wozny, Günter; Yang, Dae Ryook

2007-01-01

Despite many environmental advantages of using alcohol as a fuel, there are still serious questions about its economical feasibility when compared with oil-based fuels. The bioethanol industry needs to be more competitive, and therefore, all stages of its production process must be simple, inexpensive, efficient, and "easy" to control. In recent years, there have been significant improvements in process design, such as in the purification technologies for ethanol dehydration (molecular sieves, pressure swing adsorption, pervaporation, etc.) and in genetic modifications of microbial strains. However, a lot of research effort is still required in optimization and control, where the first step is the development of suitable models of the process, which can be used as a simulated plant, as a soft sensor or as part of the control algorithm. Thus, toward developing good, reliable, and simple but highly predictive models that can be used in the future for optimization and process control applications, in this paper an unstructured and a cybernetic model are proposed and compared for the simultaneous saccharification-fermentation process (SSF) for the production of ethanol from starch by a recombinant Saccharomyces cerevisiae strain. The cybernetic model proposed is a new one that considers the degradation of starch not only into glucose but also into dextrins (reducing sugars) and takes into account the intracellular reactions occurring inside the cells, giving a more detailed description of the process. Furthermore, an identification procedure based on the Metropolis Monte Carlo optimization method coupled with a sensitivity analysis is proposed for the identification of the model's parameters, employing experimental data reported in the literature.

Conservation of cardiac L-type Ca2+ channels and their regulation in Drosophila: A novel genetically-pliable channelopathic model.

PubMed

Limpitikul, Worawan B; Viswanathan, Meera C; O'Rourke, Brian; Yue, David T; Cammarato, Anthony

2018-04-21

Dysregulation of L-type Ca 2+ channels (LTCCs) underlies numerous cardiac pathologies. Understanding their modulation with high fidelity relies on investigating LTCCs in their native environment with intact interacting proteins. Such studies benefit from genetic manipulation of endogenous channels in cardiomyocytes, which often proves cumbersome in mammalian models. Drosophila melanogaster, however, offers a potentially efficient alternative as it possesses a relatively simple heart, is genetically pliable, and expresses well-conserved genes. Fluorescence in situ hybridization confirmed an abundance of Ca-α1D and Ca-α1T mRNA in fly myocardium, which encode subunits that specify hetero-oligomeric channels homologous to mammalian LTCCs and T-type Ca 2+ channels, respectively. Cardiac-specific knockdown of Ca-α1D via interfering RNA abolished cardiac contraction, suggesting Ca-α1D (i.e. A1D) represents the primary functioning Ca 2+ channel in Drosophila hearts. Moreover, we successfully isolated viable single cardiomyocytes and recorded Ca 2+ currents via patch clamping, a feat never before accomplished with the fly model. The profile of Ca 2+ currents recorded in individual cells when Ca 2+ channels were hypomorphic, absent, or under selective LTCC blockage by nifedipine, additionally confirmed the predominance of A1D current across all activation voltages. T-type current, activated at more negative voltages, was also detected. Lastly, A1D channels displayed Ca 2+ -dependent inactivation, a critical negative feedback mechanism of LTCCs, and the current through them was augmented by forskolin, an activator of the protein kinase A pathway. In sum, the Drosophila heart possesses a conserved compendium of Ca 2+ channels, suggesting that the fly may serve as a robust and effective platform for studying cardiac channelopathies. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Application of optimized parameters SVM based on photoacoustic spectroscopy method in fault diagnosis of power transformer].

PubMed

Zhang, Yu-xin; Cheng, Zhi-feng; Xu, Zheng-ping; Bai, Jing

2015-01-01

In order to solve the problems such as complex operation, consumption for the carrier gas and long test period in traditional power transformer fault diagnosis approach based on dissolved gas analysis (DGA), this paper proposes a new method which is detecting 5 types of characteristic gas content in transformer oil such as CH4, C2H2, C2H4, C2H6 and H2 based on photoacoustic Spectroscopy and C2H2/C2H4, CH4/H2, C2H4/C2H6 three-ratios data are calculated. The support vector machine model was constructed using cross validation method under five support vector machine functions and four kernel functions, heuristic algorithms were used in parameter optimization for penalty factor c and g, which to establish the best SVM model for the highest fault diagnosis accuracy and the fast computing speed. Particles swarm optimization and genetic algorithm two types of heuristic algorithms were comparative studied in this paper for accuracy and speed in optimization. The simulation result shows that SVM model composed of C-SVC, RBF kernel functions and genetic algorithm obtain 97. 5% accuracy in test sample set and 98. 333 3% accuracy in train sample set, and genetic algorithm was about two times faster than particles swarm optimization in computing speed. The methods described in this paper has many advantages such as simple operation, non-contact measurement, no consumption for the carrier gas, long test period, high stability and sensitivity, the result shows that the methods described in this paper can instead of the traditional transformer fault diagnosis by gas chromatography and meets the actual project needs in transformer fault diagnosis.

Macromolecular recognition: Structural aspects of the origin of the genetic system

NASA Technical Reports Server (NTRS)

Rein, Robert; Sokalski, W. Andrzej; Barak, Dov; Luo, Ning; Zielinski, Theresa Julia; Shibata, Masayuki

1991-01-01

Theoretical simulation of prebiotic chemical processes is an invaluable tool for probing the phenomenon of the evolution of life. Using computational and modeling techniques and guided by analogies from present day systems, we seek to understand the emergence of the genetic apparatus, enzymatic catalysis and protein synthesis under prebiotic conditions. Modeling of the ancestral aminoacyl-tRNA-synthetases (aRS) may provide important clues to the emergence of the genetic code and the protein synthetic machinery. The minimal structural requirements for the catalysis of tRNA aminoacylation are being explored. A formation of an aminoacyl adenylate was studied in the framework of ab initio molecular orbital theory. The role of individual residues in the vicinity of the TyrRS active site was examined, and the effect of all possible amino acids substitutions near the active site was examined. A formation of aminoacyl tRNA was studied by the molecular modeling system SYBYL with the high resolution crystallographic structures of the present day tRNA, aRS's complexes. The ultimate goal is to propose a simple RNA segment that is small enough to be build in the primordial chemical environment but maintains the specificity and catalytic activity of the contemporary RNA enzyme. To understand the mechanism of ribozyme catalyzed reactions, ab initio and semi-empirical (ZINDO) programs were used to investigate the reaction path of transphosphorylation. A special emphasis was placed on the possible catalytic and structural roles played by the coordinated magnesium cation. Both the inline and adjacent mechanisms of transphosphorylation were studied. The structural characteristics of the target helices, particularly a possible role for the G-T pair, is also studied by a molecular dynamics (MD) simulation technique.

Mapping Water Stress Incidence and Intensity, Optimal Plant Populations, and Cultivar Duration for African Groundnut Productivity Enhancement.

PubMed

Vadez, Vincent; Halilou, Oumarou; Hissene, Halime M; Sibiry-Traore, Pierre; Sinclair, Thomas R; Soltani, Afshin

2017-01-01

Groundnut production is limited in Sub-Saharan Africa and water deficit or "drought," is often considered as the main yield-limiting factor. However, no comprehensive study has assessed the extent and intensity of "drought"-related yield decreases, nor has it explored avenues to enhance productivity. Hence, crop simulation modeling with SSM (Simple Simulation Modeling) was used to address these issues. To palliate the lack of reliable weather data as input to the model, the validity of weather data generated by Marksim, a weather generator, was tested. Marksim provided good weather representation across a large gradient of rainfall, representative of the region, and although rainfall generated by Marksim was above observations, run-off from Marksim data was also higher, and consequently simulations using observed or Marksim weather agreed closely across this gradient of weather conditions (root mean square of error = 99 g m -2 ; R 2 = 0.81 for pod yield). More importantly, simulation of yield changes upon agronomic or genetic alterations in the model were equally predicted with Marksim weather. A 1° × 1° grid of weather data was generated. "Drought"-related yield reduction were limited to latitudes above 12-13° North in West Central Africa (WCA) and to the Eastern fringes of Tanzania and Mozambique in East South Africa (ESA). Simulation and experimental trials also showed that doubling the sowing density of Spanish cultivars from 20 to 40 plants m -2 would increase yield dramatically in both WCA and ESA. However, increasing density would require growers to invest in more seeds and likely additional labor. If these trade-offs cannot be alleviated, genetic improvement would then need to re-focus on a plant type that is adapted to the current low sowing density, like a runner rather than a bush plant type, which currently receives most of the genetic attention. Genetic improvement targeting "drought" adaptation should also be restricted to areas where water is indeed an issue, i.e., above 12-13°N latitude in WCA and the Eastern fringes of Tanzania and Mozambique.

VTE Risk assessment - a prognostic Model: BATER Cohort Study of young women.

PubMed

Heinemann, Lothar Aj; Dominh, Thai; Assmann, Anita; Schramm, Wolfgang; Schürmann, Rolf; Hilpert, Jan; Spannagl, Michael

2005-04-18

BACKGROUND: Community-based cohort studies are not available that evaluated the predictive power of both clinical and genetic risk factors for venous thromboembolism (VTE). There is, however, clinical need to forecast the likelihood of future occurrence of VTE, at least qualitatively, to support decisions about intensity of diagnostic or preventive measures. MATERIALS AND METHODS: A 10-year observation period of the Bavarian Thromboembolic Risk (BATER) study, a cohort study of 4337 women (18-55 years), was used to develop a predictive model of VTE based on clinical and genetic variables at baseline (1993). The objective was to prepare a probabilistic scheme that discriminates women with virtually no VTE risk from those at higher levels of absolute VTE risk in the foreseeable future. A multivariate analysis determined which variables at baseline were the best predictors of a future VTE event, provided a ranking according to the predictive power, and permitted to design a simple graphic scheme to assess the individual VTE risk using five predictor variables. RESULTS: Thirty-four new confirmed VTEs occurred during the observation period of over 32,000 women-years (WYs). A model was developed mainly based on clinical information (personal history of previous VTE and family history of VTE, age, BMI) and one composite genetic risk markers (combining Factor V Leiden and Prothrombin G20210A Mutation). Four levels of increasing VTE risk were arbitrarily defined to map the prevalence in the study population: No/low risk of VTE (61.3%), moderate risk (21.1%), high risk (6.0%), very high risk of future VTE (0.9%). In 10.6% of the population the risk assessment was not possible due to lacking VTE cases. The average incidence rates for VTE in these four levels were: 4.1, 12.3, 47.2, and 170.5 per 104 WYs for no, moderate, high, and very high risk, respectively. CONCLUSION: Our prognostic tool - containing clinical information (and if available also genetic data) - seems to be worthwhile testing in medical practice in order to confirm or refute the positive findings of this study. Our cohort study will be continued to include more VTE cases and to increase predictive value of the model.

The genetic architecture of ecological adaptation: intraspecific variation in host plant use by the lepidopteran crop pest Chloridea virescens.

PubMed

Oppenheim, Sara J; Gould, Fred; Hopper, Keith R

2018-03-01

Intraspecific variation in ecologically important traits is a cornerstone of Darwin's theory of evolution by natural selection. The evolution and maintenance of this variation depends on genetic architecture, which in turn determines responses to natural selection. Some models suggest that traits with complex architectures are less likely to respond to selection than those with simple architectures, yet rapid divergence has been observed in such traits. The simultaneous evolutionary lability and genetic complexity of host plant use in the Lepidopteran subfamily Heliothinae suggest that architecture may not constrain ecological adaptation in this group. Here we investigate the response of Chloridea virescens, a generalist that feeds on diverse plant species, to selection for performance on a novel host, Physalis angulata (Solanaceae). P. angulata is the preferred host of Chloridea subflexa, a narrow specialist on the genus Physalis. In previous experiments, we found that the performance of C. subflexa on P. angulata depends on many loci of small effect distributed throughout the genome, but whether the same architecture would be involved in the generalist's adoption of P. angulata was unknown. Here we report a rapid response to selection in C. virescens for performance on P. angulata, and establish that the genetic architecture of intraspecific variation is quite similar to that of the interspecific differences in terms of the number, distribution, and effect sizes of the QTL involved. We discuss the impact of genetic architecture on the ability of Heliothine moths to respond to varying ecological selection pressures.

What can microbial genetics teach sociobiology?

PubMed Central

Foster, Kevin R.; Parkinson, Katie; Thompson, Christopher R.L.

2009-01-01

Progress in our understanding of sociobiology has occurred with little knowledge of the genetic mechanisms that underlie social traits. However, several recent studies have described microbial genes that affect social traits, thereby bringing genetics to sociobiology. A key finding is that simple genetic changes can have marked social consequences, and mutations that affect cheating and recognition behaviors have been discovered. The study of these mutants confirms a central theoretical prediction of social evolution: that genetic relatedness promotes cooperation. Microbial genetics also provides an important new perspective: that the genome-to-phenome mapping of social organisms might be organized to constrain the evolution of social cheaters. This constraint can occur both through pleiotropic genes that link cheating to a personal cost and through the existence of phoenix genes, which rescue cooperative systems from selfish and destructive strategies. These new insights show the power of studying microorganisms to improve our understanding of the evolution of cooperation. PMID:17207887

Genetic diversity and relationship of Hedychium from Northeast India as dissected using PCA analysis and hierarchical clustering.

PubMed

Basak, Supriyo; Ramesh, Aadi Moolam; Kesari, Vigya; Parida, Ajay; Mitra, Sudip; Rangan, Latha

2014-12-01

Molecular genetic fingerprints of eleven Hedychium species from Northeast India were developed using PCR based markers. Fifteen inter-simple sequence repeats (ISSRs) and five amplified fragment length polymorphism (AFLP) primers produced 547 polymorphic fragments. Positive correlation (r = 0.46) was observed between the mean genetic similarity and genetic diversity parameters at the inter-species level. AFLP and ISSR markers were able to group the species according to its altitude and intensity of flower aroma. Cophenetic correlation coefficients between the dendrogram and the original similarity matrix were significant for ISSR (r = 0.89) compared to AFLP (r = 0.83) markers. This genetic characterization of Hedychium from Northeast India contributes to the knowledge of genetic structure of the species and can be used to define strategies for their conservation and management.

Resources for Systems Genetics.

PubMed

Williams, Robert W; Williams, Evan G

2017-01-01

A key characteristic of systems genetics is its reliance on populations that vary to a greater or lesser degree in genetic complexity-from highly admixed populations such as the Collaborative Cross and Diversity Outcross to relatively simple crosses such as sets of consomic strains and reduced complexity crosses. This protocol is intended to help investigators make more informed decisions about choices of resources given different types of questions. We consider factors such as costs, availability, and ease of breeding for common scenarios. In general, we recommend using complementary resources and minimizing depth of resampling of any given genome or strain.

Biomek 3000: the workhorse in an automated accredited forensic genetic laboratory.

PubMed

Stangegaard, Michael; Meijer, Per-Johan; Børsting, Claus; Hansen, Anders J; Morling, Niels

2012-10-01

We have implemented and validated automated protocols for a wide range of processes such as sample preparation, PCR setup, and capillary electrophoresis setup using small, simple, and inexpensive automated liquid handlers. The flexibility and ease of programming enable the Biomek 3000 to be used in many parts of the laboratory process in a modern forensic genetics laboratory with low to medium sample throughput. In conclusion, we demonstrated that sample processing for accredited forensic genetic DNA typing can be implemented on small automated liquid handlers, leading to the reduction of manual work as well as increased quality and throughput.

GenoCore: A simple and fast algorithm for core subset selection from large genotype datasets.

PubMed

Jeong, Seongmun; Kim, Jae-Yoon; Jeong, Soon-Chun; Kang, Sung-Taeg; Moon, Jung-Kyung; Kim, Namshin

2017-01-01

Selecting core subsets from plant genotype datasets is important for enhancing cost-effectiveness and to shorten the time required for analyses of genome-wide association studies (GWAS), and genomics-assisted breeding of crop species, etc. Recently, a large number of genetic markers (>100,000 single nucleotide polymorphisms) have been identified from high-density single nucleotide polymorphism (SNP) arrays and next-generation sequencing (NGS) data. However, there is no software available for picking out the efficient and consistent core subset from such a huge dataset. It is necessary to develop software that can extract genetically important samples in a population with coherence. We here present a new program, GenoCore, which can find quickly and efficiently the core subset representing the entire population. We introduce simple measures of coverage and diversity scores, which reflect genotype errors and genetic variations, and can help to select a sample rapidly and accurately for crop genotype dataset. Comparison of our method to other core collection software using example datasets are performed to validate the performance according to genetic distance, diversity, coverage, required system resources, and the number of selected samples. GenoCore selects the smallest, most consistent, and most representative core collection from all samples, using less memory with more efficient scores, and shows greater genetic coverage compared to the other software tested. GenoCore was written in R language, and can be accessed online with an example dataset and test results at https://github.com/lovemun/Genocore.

Genetic Diversity in Various Accessions of Pineapple [Ananas comosus (L.) Merr.] Using ISSR and SSR Markers.

PubMed

Wang, Jian-Sheng; He, Jun-Hu; Chen, Hua-Rui; Chen, Ye-Yuan; Qiao, Fei

2017-12-01

Inter simple sequence repeat (ISSR) and simple sequence repeat (SSR) markers were used to assess the genetic diversity of 36 pineapple accessions that were introduced from 10 countries/regions. Thirteen ISSR primers amplified 96 bands, of which 91 (93.65%) were polymorphic, whereas 20 SSR primers amplified 73 bands, of which 70 (96.50%) were polymorphic. Nei's gene diversity (h = 0.28), Shannon's information index (I = 0.43), and polymorphism information content (PIC = 0.29) generated using the SSR primers were higher than that with ISSR primers (h =  0.23, I = 0.37, PIC = 0.24), thereby suggesting that the SSR system is more efficient than the ISSR system in assessing genetic diversity in various pineapple accessions. Mean genetic similarities were 0.74, 0.61, and 0.69, as determined using ISSR, SSR, and combined ISSR/SSR, respectively. These results suggest that the genetic diversity among pineapple accessions is very high. We clustered the 36 pineapple accessions into three or five groups on the basis of the phylogenetic trees constructed based on the results of ISSR, SSR, and combined ISSR/SSR analyses using the unweighted pair-group with arithmetic averaging (UPGMA) method. The results of principal components analysis (PCA) also supported the UPGMA clustering. These results will be useful not only for the scientific conservation and management of pineapple germplasm but also for the improvement of the current pineapple breeding strategies.

Applying genetic algorithms for calibrating a hexagonal cellular automata model for the simulation of debris flows characterised by strong inertial effects

NASA Astrophysics Data System (ADS)

Iovine, G.; D'Ambrosio, D.; Di Gregorio, S.

2005-03-01

In modelling complex a-centric phenomena which evolve through local interactions within a discrete time-space, cellular automata (CA) represent a valid alternative to standard solution methods based on differential equations. Flow-type phenomena (such as lava flows, pyroclastic flows, earth flows, and debris flows) can be viewed as a-centric dynamical systems, and they can therefore be properly investigated in CA terms. SCIDDICA S 4a is the last release of a two-dimensional hexagonal CA model for simulating debris flows characterised by strong inertial effects. S 4a has been obtained by progressively enriching an initial simplified model, originally derived for simulating very simple cases of slow-moving flow-type landslides. Using an empirical strategy, in S 4a, the inertial character of the flowing mass is translated into CA terms by means of local rules. In particular, in the transition function of the model, the distribution of landslide debris among the cells is obtained through a double cycle of computation. In the first phase, the inertial character of the landslide debris is taken into account by considering indicators of momentum. In the second phase, any remaining debris in the central cell is distributed among the adjacent cells, according to the principle of maximum possible equilibrium. The complexities of the model and of the phenomena to be simulated suggested the need for an automated technique of evaluation for the determination of the best set of global parameters. Accordingly, the model is calibrated using a genetic algorithm and by considering the May 1998 Curti-Sarno (Southern Italy) debris flow. The boundaries of the area affected by the debris flow are simulated well with the model. Errors computed by comparing the simulations with the mapped areal extent of the actual landslide are smaller than those previously obtained without genetic algorithms. As the experiments have been realised in a sequential computing environment, they could be improved by adopting a parallel environment, which allows the performance of a great number of tests in reasonable times.

Social disinhibition is a heritable subphenotype of tics in Tourette syndrome

PubMed Central

Hirschtritt, Matthew E.; Darrow, Sabrina M.; Illmann, Cornelia; Osiecki, Lisa; Grados, Marco; Sandor, Paul; Dion, Yves; King, Robert A.; Pauls, David L.; Budman, Cathy L.; Cath, Danielle C.; Greenberg, Erica; Lyon, Gholson J.; Yu, Dongmei; McGrath, Lauren M.; McMahon, William M.; Lee, Paul C.; Delucchi, Kevin L.; Scharf, Jeremiah M.

2016-01-01

Objective: To identify heritable symptom-based subtypes of Tourette syndrome (TS). Methods: Forty-nine motor and phonic tics were examined in 3,494 individuals (1,191 TS probands and 2,303 first-degree relatives). Item-level exploratory factor and latent class analyses (LCA) were used to identify tic-based subtypes. Heritabilities of the subtypes were estimated, and associations with clinical characteristics were examined. Results: A 6-factor exploratory factor analysis model provided the best fit, which paralleled the somatotopic representation of the basal ganglia, distinguished simple from complex tics, and separated out socially disinhibited and compulsive tics. The 5-class LCA model best distinguished among the following groups: unaffected, simple tics, intermediate tics without social disinhibition, intermediate with social disinhibition, and high rates of all tic types. Across models, a phenotype characterized by high rates of social disinhibition emerged. This phenotype was associated with increased odds of comorbid psychiatric disorders, in particular, obsessive-compulsive disorder and attention-deficit/hyperactivity disorder, earlier age at TS onset, and increased tic severity. The heritability estimate for this phenotype based on the LCA was 0.53 (SE 0.08, p 1.7 × 10−18). Conclusions: Expanding on previous modeling approaches, a series of TS-related phenotypes, including one characterized by high rates of social disinhibition, were identified. These phenotypes were highly heritable and may reflect underlying biological networks more accurately than traditional diagnoses, thus potentially aiding future genetic, imaging, and treatment studies. PMID:27371487

Social disinhibition is a heritable subphenotype of tics in Tourette syndrome.

PubMed

Hirschtritt, Matthew E; Darrow, Sabrina M; Illmann, Cornelia; Osiecki, Lisa; Grados, Marco; Sandor, Paul; Dion, Yves; King, Robert A; Pauls, David L; Budman, Cathy L; Cath, Danielle C; Greenberg, Erica; Lyon, Gholson J; Yu, Dongmei; McGrath, Lauren M; McMahon, William M; Lee, Paul C; Delucchi, Kevin L; Scharf, Jeremiah M; Mathews, Carol A

2016-08-02

To identify heritable symptom-based subtypes of Tourette syndrome (TS). Forty-nine motor and phonic tics were examined in 3,494 individuals (1,191 TS probands and 2,303 first-degree relatives). Item-level exploratory factor and latent class analyses (LCA) were used to identify tic-based subtypes. Heritabilities of the subtypes were estimated, and associations with clinical characteristics were examined. A 6-factor exploratory factor analysis model provided the best fit, which paralleled the somatotopic representation of the basal ganglia, distinguished simple from complex tics, and separated out socially disinhibited and compulsive tics. The 5-class LCA model best distinguished among the following groups: unaffected, simple tics, intermediate tics without social disinhibition, intermediate with social disinhibition, and high rates of all tic types. Across models, a phenotype characterized by high rates of social disinhibition emerged. This phenotype was associated with increased odds of comorbid psychiatric disorders, in particular, obsessive-compulsive disorder and attention-deficit/hyperactivity disorder, earlier age at TS onset, and increased tic severity. The heritability estimate for this phenotype based on the LCA was 0.53 (SE 0.08, p 1.7 × 10(-18)). Expanding on previous modeling approaches, a series of TS-related phenotypes, including one characterized by high rates of social disinhibition, were identified. These phenotypes were highly heritable and may reflect underlying biological networks more accurately than traditional diagnoses, thus potentially aiding future genetic, imaging, and treatment studies. © 2016 American Academy of Neurology.

Modeling Reality - How Computers Mirror Life

NASA Astrophysics Data System (ADS)

Bialynicki-Birula, Iwo; Bialynicka-Birula, Iwona

2005-01-01

The bookModeling Reality covers a wide range of fascinating subjects, accessible to anyone who wants to learn about the use of computer modeling to solve a diverse range of problems, but who does not possess a specialized training in mathematics or computer science. The material presented is pitched at the level of high-school graduates, even though it covers some advanced topics (cellular automata, Shannon's measure of information, deterministic chaos, fractals, game theory, neural networks, genetic algorithms, and Turing machines). These advanced topics are explained in terms of well known simple concepts: Cellular automata - Game of Life, Shannon's formula - Game of twenty questions, Game theory - Television quiz, etc. The book is unique in explaining in a straightforward, yet complete, fashion many important ideas, related to various models of reality and their applications. Twenty-five programs, written especially for this book, are provided on an accompanying CD. They greatly enhance its pedagogical value and make learning of even the more complex topics an enjoyable pleasure.

Genetics Home Reference: glucose-galactose malabsorption

MedlinePlus

... down into glucose and another simple sugar called fructose, and lactose is broken down into glucose and ... infant formulas. However, they are able to digest fructose-based formulas that do not contain glucose or ...

Further evidence for the increased power of LOD scores compared with nonparametric methods.

PubMed

Durner, M; Vieland, V J; Greenberg, D A

1999-01-01

In genetic analysis of diseases in which the underlying model is unknown, "model free" methods-such as affected sib pair (ASP) tests-are often preferred over LOD-score methods, although LOD-score methods under the correct or even approximately correct model are more powerful than ASP tests. However, there might be circumstances in which nonparametric methods will outperform LOD-score methods. Recently, Dizier et al. reported that, in some complex two-locus (2L) models, LOD-score methods with segregation analysis-derived parameters had less power to detect linkage than ASP tests. We investigated whether these particular models, in fact, represent a situation that ASP tests are more powerful than LOD scores. We simulated data according to the parameters specified by Dizier et al. and analyzed the data by using a (a) single locus (SL) LOD-score analysis performed twice, under a simple dominant and a recessive mode of inheritance (MOI), (b) ASP methods, and (c) nonparametric linkage (NPL) analysis. We show that SL analysis performed twice and corrected for the type I-error increase due to multiple testing yields almost as much linkage information as does an analysis under the correct 2L model and is more powerful than either the ASP method or the NPL method. We demonstrate that, even for complex genetic models, the most important condition for linkage analysis is that the assumed MOI at the disease locus being tested is approximately correct, not that the inheritance of the disease per se is correctly specified. In the analysis by Dizier et al., segregation analysis led to estimates of dominance parameters that were grossly misspecified for the locus tested in those models in which ASP tests appeared to be more powerful than LOD-score analyses.

Modeling an Excitable Biosynthetic Tissue with Inherent Variability for Paired Computational-Experimental Studies.

PubMed

Gokhale, Tanmay A; Kim, Jong M; Kirkton, Robert D; Bursac, Nenad; Henriquez, Craig S

2017-01-01

To understand how excitable tissues give rise to arrhythmias, it is crucially necessary to understand the electrical dynamics of cells in the context of their environment. Multicellular monolayer cultures have proven useful for investigating arrhythmias and other conduction anomalies, and because of their relatively simple structure, these constructs lend themselves to paired computational studies that often help elucidate mechanisms of the observed behavior. However, tissue cultures of cardiomyocyte monolayers currently require the use of neonatal cells with ionic properties that change rapidly during development and have thus been poorly characterized and modeled to date. Recently, Kirkton and Bursac demonstrated the ability to create biosynthetic excitable tissues from genetically engineered and immortalized HEK293 cells with well-characterized electrical properties and the ability to propagate action potentials. In this study, we developed and validated a computational model of these excitable HEK293 cells (called "Ex293" cells) using existing electrophysiological data and a genetic search algorithm. In order to reproduce not only the mean but also the variability of experimental observations, we examined what sources of variation were required in the computational model. Random cell-to-cell and inter-monolayer variation in both ionic conductances and tissue conductivity was necessary to explain the experimentally observed variability in action potential shape and macroscopic conduction, and the spatial organization of cell-to-cell conductance variation was found to not impact macroscopic behavior; the resulting model accurately reproduces both normal and drug-modified conduction behavior. The development of a computational Ex293 cell and tissue model provides a novel framework to perform paired computational-experimental studies to study normal and abnormal conduction in multidimensional excitable tissue, and the methodology of modeling variation can be applied to models of any excitable cell.

Convergence of circuit dysfunction in ASD: a common bridge between diverse genetic and environmental risk factors and common clinical electrophysiology

PubMed Central

Port, Russell G.; Gandal, Michael J.; Roberts, Timothy P. L.; Siegel, Steven J.; Carlson, Gregory C.

2014-01-01

Most recent estimates indicate that 1 in 68 children are affected by an autism spectrum disorder (ASD). Though decades of research have uncovered much about these disorders, the pathological mechanism remains unknown. Hampering efforts is the seeming inability to integrate findings over the micro to macro scales of study, from changes in molecular, synaptic and cellular function to large-scale brain dysfunction impacting sensory, communicative, motor and cognitive activity. In this review, we describe how studies focusing on neuronal circuit function provide unique context for identifying common neurobiological disease mechanisms of ASD. We discuss how recent EEG and MEG studies in subjects with ASD have repeatedly shown alterations in ensemble population recordings (both in simple evoked related potential latencies and specific frequency subcomponents). Because these disease-associated electrophysiological abnormalities have been recapitulated in rodent models, studying circuit differences in these models may provide access to abnormal circuit function found in ASD. We then identify emerging in vivo and ex vivo techniques, focusing on how these assays can characterize circuit level dysfunction and determine if these abnormalities underlie abnormal clinical electrophysiology. Such circuit level study in animal models may help us understand how diverse genetic and environmental risks can produce a common set of EEG, MEG and anatomical abnormalities found in ASD. PMID:25538564

Establishment of the mathematical model for diagnosing the engine valve faults by genetic programming

NASA Astrophysics Data System (ADS)

Yang, Wen-Xian

2006-05-01

Available machine fault diagnostic methods show unsatisfactory performances on both on-line and intelligent analyses because their operations involve intensive calculations and are labour intensive. Aiming at improving this situation, this paper describes the development of an intelligent approach by using the Genetic Programming (abbreviated as GP) method. Attributed to the simple calculation of the mathematical model being constructed, different kinds of machine faults may be diagnosed correctly and quickly. Moreover, human input is significantly reduced in the process of fault diagnosis. The effectiveness of the proposed strategy is validated by an illustrative example, in which three kinds of valve states inherent in a six-cylinders/four-stroke cycle diesel engine, i.e. normal condition, valve-tappet clearance and gas leakage faults, are identified. In the example, 22 mathematical functions have been specially designed and 8 easily obtained signal features are used to construct the diagnostic model. Different from existing GPs, the diagnostic tree used in the algorithm is constructed in an intelligent way by applying a power-weight coefficient to each feature. The power-weight coefficients vary adaptively between 0 and 1 during the evolutionary process. Moreover, different evolutionary strategies are employed, respectively for selecting the diagnostic features and functions, so that the mathematical functions are sufficiently utilized and in the meantime, the repeated use of signal features may be fully avoided. The experimental results are illustrated diagrammatically in the following sections.

Endothelial cell expression of haemoglobin α regulates nitric oxide signalling.

PubMed

Straub, Adam C; Lohman, Alexander W; Billaud, Marie; Johnstone, Scott R; Dwyer, Scott T; Lee, Monica Y; Bortz, Pamela Schoppee; Best, Angela K; Columbus, Linda; Gaston, Benjamin; Isakson, Brant E

2012-11-15

Models of unregulated nitric oxide (NO) diffusion do not consistently account for the biochemistry of NO synthase (NOS)-dependent signalling in many cell systems. For example, endothelial NOS controls blood pressure, blood flow and oxygen delivery through its effect on vascular smooth muscle tone, but the regulation of these processes is not adequately explained by simple NO diffusion from endothelium to smooth muscle. Here we report a new model for the regulation of NO signalling by demonstrating that haemoglobin (Hb) α (encoded by the HBA1 and HBA2 genes in humans) is expressed in human and mouse arterial endothelial cells and enriched at the myoendothelial junction, where it regulates the effects of NO on vascular reactivity. Notably, this function is unique to Hb α and is abrogated by its genetic depletion. Mechanistically, endothelial Hb α haem iron in the Fe(3+) state permits NO signalling, and this signalling is shut off when Hb α is reduced to the Fe(2+) state by endothelial cytochrome b5 reductase 3 (CYB5R3, also known as diaphorase 1). Genetic and pharmacological inhibition of CYB5R3 increases NO bioactivity in small arteries. These data reveal a new mechanism by which the regulation of the intracellular Hb α oxidation state controls NOS signalling in non-erythroid cells. This model may be relevant to haem-containing globins in a broad range of NOS-containing somatic cells.

NemaFlex: a microfluidics-based technology for standardized measurement of muscular strength of C. elegans.

PubMed

Rahman, Mizanur; Hewitt, Jennifer E; Van-Bussel, Frank; Edwards, Hunter; Blawzdziewicz, Jerzy; Szewczyk, Nathaniel J; Driscoll, Monica; Vanapalli, Siva A

2018-06-12

Muscle strength is a functional measure of quality of life in humans. Declines in muscle strength are manifested in diseases as well as during inactivity, aging, and space travel. With conserved muscle biology, the simple genetic model C. elegans is a high throughput platform in which to identify molecular mechanisms causing muscle strength loss and to develop interventions based on diet, exercise, and drugs. In the clinic, standardized strength measures are essential to quantitate changes in patients; however, analogous standards have not been recapitulated in the C. elegans model since force generation fluctuates based on animal behavior and locomotion. Here, we report a microfluidics-based system for strength measurement that we call 'NemaFlex', based on pillar deflection as the nematode crawls through a forest of pillars. We have optimized the micropillar forest design and identified robust measurement conditions that yield a measure of strength that is independent of behavior and gait. Validation studies using a muscle contracting agent and mutants confirm that NemaFlex can reliably score muscular strength in C. elegans. Additionally, we report a scaling factor to account for animal size that is consistent with a biomechanics model and enables comparative strength studies of mutants. Taken together, our findings anchor NemaFlex for applications in genetic and drug screens, for defining molecular and cellular circuits of neuromuscular function, and for dissection of degenerative processes in disuse, aging, and disease.

Frailty Models for Familial Risk with Application to Breast Cancer.

PubMed

Gorfine, Malka; Hsu, Li; Parmigiani, Giovanni

2013-12-01

In evaluating familial risk for disease we have two main statistical tasks: assessing the probability of carrying an inherited genetic mutation conferring higher risk; and predicting the absolute risk of developing diseases over time, for those individuals whose mutation status is known. Despite substantial progress, much remains unknown about the role of genetic and environmental risk factors, about the sources of variation in risk among families that carry high-risk mutations, and about the sources of familial aggregation beyond major Mendelian effects. These sources of heterogeneity contribute substantial variation in risk across families. In this paper we present simple and efficient methods for accounting for this variation in familial risk assessment. Our methods are based on frailty models. We implemented them in the context of generalizing Mendelian models of cancer risk, and compared our approaches to others that do not consider heterogeneity across families. Our extensive simulation study demonstrates that when predicting the risk of developing a disease over time conditional on carrier status, accounting for heterogeneity results in a substantial improvement in the area under the curve of the receiver operating characteristic. On the other hand, the improvement for carriership probability estimation is more limited. We illustrate the utility of the proposed approach through the analysis of BRCA1 and BRCA2 mutation carriers in the Washington Ashkenazi Kin-Cohort Study of Breast Cancer.

Cross-talk between Rho and Rac GTPases drives deterministic exploration of cellular shape space and morphological heterogeneity.

PubMed

Sailem, Heba; Bousgouni, Vicky; Cooper, Sam; Bakal, Chris

2014-01-22

One goal of cell biology is to understand how cells adopt different shapes in response to varying environmental and cellular conditions. Achieving a comprehensive understanding of the relationship between cell shape and environment requires a systems-level understanding of the signalling networks that respond to external cues and regulate the cytoskeleton. Classical biochemical and genetic approaches have identified thousands of individual components that contribute to cell shape, but it remains difficult to predict how cell shape is generated by the activity of these components using bottom-up approaches because of the complex nature of their interactions in space and time. Here, we describe the regulation of cellular shape by signalling systems using a top-down approach. We first exploit the shape diversity generated by systematic RNAi screening and comprehensively define the shape space a migratory cell explores. We suggest a simple Boolean model involving the activation of Rac and Rho GTPases in two compartments to explain the basis for all cell shapes in the dataset. Critically, we also generate a probabilistic graphical model to show how cells explore this space in a deterministic, rather than a stochastic, fashion. We validate the predictions made by our model using live-cell imaging. Our work explains how cross-talk between Rho and Rac can generate different cell shapes, and thus morphological heterogeneity, in genetically identical populations.

First flights of genetic-algorithm Kitty Hawk

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

Goldberg, D.E.

1994-12-31

The design of complex systems requires an effective methodology of invention. This paper considers the methodology of the Wright brothers in inventing the powered airplane and suggests how successes in the design of genetic algorithms have come at the hands of a Wright-brothers-like approach. Recent reliable subquadratic results in solving hard problems with nontraditional GAs and predictions of the limits of simple GAs are presented as two accomplishments achieved in this manner.

The yeast replicative aging model.

PubMed

He, Chong; Zhou, Chuankai; Kennedy, Brian K

2018-03-08

It has been nearly three decades since the budding yeast Saccharomyces cerevisiae became a significant model organism for aging research and it has emerged as both simple and powerful. The replicative aging assay, which interrogates the number of times a "mother" cell can divide and produce "daughters", has been a stalwart in these studies, and genetic approaches have led to the identification of hundreds of genes impacting lifespan. More recently, cell biological and biochemical approaches have been developed to determine how cellular processes become altered with age. Together, the tools are in place to develop a holistic view of aging in this single-celled organism. Here, we summarize the current state of understanding of yeast replicative aging with a focus on the recent studies that shed new light on how aging pathways interact to modulate lifespan in yeast. Copyright © 2018. Published by Elsevier B.V.