Using probability modelling and genetic parentage assignment to test the role of local mate availability in mating system variation.

PubMed

Blyton, Michaela D J; Banks, Sam C; Peakall, Rod; Lindenmayer, David B

2012-02-01

The formal testing of mating system theories with empirical data is important for evaluating the relative importance of different processes in shaping mating systems in wild populations. Here, we present a generally applicable probability modelling framework to test the role of local mate availability in determining a population's level of genetic monogamy. We provide a significance test for detecting departures in observed mating patterns from model expectations based on mate availability alone, allowing the presence and direction of behavioural effects to be inferred. The assessment of mate availability can be flexible and in this study it was based on population density, sex ratio and spatial arrangement. This approach provides a useful tool for (1) isolating the effect of mate availability in variable mating systems and (2) in combination with genetic parentage analyses, gaining insights into the nature of mating behaviours in elusive species. To illustrate this modelling approach, we have applied it to investigate the variable mating system of the mountain brushtail possum (Trichosurus cunninghami) and compared the model expectations with the outcomes of genetic parentage analysis over an 18-year study. The observed level of monogamy was higher than predicted under the model. Thus, behavioural traits, such as mate guarding or selective mate choice, may increase the population level of monogamy. We show that combining genetic parentage data with probability modelling can facilitate an improved understanding of the complex interactions between behavioural adaptations and demographic dynamics in driving mating system variation. © 2011 Blackwell Publishing Ltd.

Population genetics of Setaria viridis, a new model system.

PubMed

Huang, Pu; Feldman, Maximilian; Schroder, Stephan; Bahri, Bochra A; Diao, Xianmin; Zhi, Hui; Estep, Matt; Baxter, Ivan; Devos, Katrien M; Kellogg, Elizabeth A

2014-10-01

An extensive survey of the standing genetic variation in natural populations is among the priority steps in developing a species into a model system. In recent years, green foxtail (Setaria viridis), along with its domesticated form foxtail millet (S. italica), has rapidly become a promising new model system for C4 grasses and bioenergy crops, due to its rapid life cycle, large amount of seed production and small diploid genome, among other characters. However, remarkably little is known about the genetic diversity in natural populations of this species. In this study, we survey the genetic diversity of a worldwide sample of more than 200 S. viridis accessions, using the genotyping-by-sequencing technique. Two distinct genetic groups in S. viridis and a third group resembling S. italica were identified, with considerable admixture among the three groups. We find the genetic variation of North American S. viridis correlates with both geography and climate and is representative of the total genetic diversity in this species. This pattern may reflect several introduction/dispersal events of S. viridis into North America. We also modelled demographic history and show signal of recent population decline in one subgroup. Finally, we show linkage disequilibrium decay is rapid (<45 kb) in our total sample and slow in genetic subgroups. These results together provide an in-depth understanding of the pattern of genetic diversity of this new model species on a broad geographic scale. They also provide key guidelines for on-going and future work including germplasm preservation, local adaptation, crossing designs and genomewide association studies. © 2014 John Wiley & Sons Ltd.

The "GeneTrustee": a universal identification system that ensures privacy and confidentiality for human genetic databases.

PubMed

Burnett, Leslie; Barlow-Stewart, Kris; Proos, Anné L; Aizenberg, Harry

2003-05-01

This article describes a generic model for access to samples and information in human genetic databases. The model utilises a "GeneTrustee", a third-party intermediary independent of the subjects and of the investigators or database custodians. The GeneTrustee model has been implemented successfully in various community genetics screening programs and has facilitated research access to genetic databases while protecting the privacy and confidentiality of research subjects. The GeneTrustee model could also be applied to various types of non-conventional genetic databases, including neonatal screening Guthrie card collections, and to forensic DNA samples.

Description and Validation of a Dynamical Systems Model of Presynaptic Serotonin Function: Genetic Variation, Brain Activation and Impulsivity

PubMed Central

Stoltenberg, Scott F.; Nag, Parthasarathi

2010-01-01

Despite more than a decade of empirical work on the role of genetic polymorphisms in the serotonin system on behavior, the details across levels of analysis are not well understood. We describe a mathematical model of the genetic control of presynaptic serotonergic function that is based on control theory, implemented using systems of differential equations, and focused on better characterizing pathways from genes to behavior. We present the results of model validation tests that include the comparison of simulation outcomes with empirical data on genetic effects on brain response to affective stimuli and on impulsivity. Patterns of simulated neural firing were consistent with recent findings of additive effects of serotonin transporter and tryptophan hydroxylase-2 polymorphisms on brain activation. In addition, simulated levels of cerebral spinal fluid 5-hydroxyindoleacetic acid (CSF 5-HIAA) were negatively correlated with Barratt Impulsiveness Scale (Version 11) Total scores in college students (r = −.22, p = .002, N = 187), which is consistent with the well-established negative correlation between CSF 5-HIAA and impulsivity. The results of the validation tests suggest that the model captures important aspects of the genetic control of presynaptic serotonergic function and behavior via brain activation. The proposed model can be: (1) extended to include other system components, neurotransmitter systems, behaviors and environmental influences; (2) used to generate testable hypotheses. PMID:20111992

Population genetics of Setaria viridis, a new model system

USDA-ARS?s Scientific Manuscript database

An extensive survey of the standing genetic variation in natural populations is among the priority steps in developing a species into a model system. In recent years, green foxtail (Setaria viridis), along with its domesticated form foxtail millet (S. italica), has rapidly become a promising new mod...

Efficient search, mapping, and optimization of multi-protein genetic systems in diverse bacteria

PubMed Central

Farasat, Iman; Kushwaha, Manish; Collens, Jason; Easterbrook, Michael; Guido, Matthew; Salis, Howard M

2014-01-01

Developing predictive models of multi-protein genetic systems to understand and optimize their behavior remains a combinatorial challenge, particularly when measurement throughput is limited. We developed a computational approach to build predictive models and identify optimal sequences and expression levels, while circumventing combinatorial explosion. Maximally informative genetic system variants were first designed by the RBS Library Calculator, an algorithm to design sequences for efficiently searching a multi-protein expression space across a > 10,000-fold range with tailored search parameters and well-predicted translation rates. We validated the algorithm's predictions by characterizing 646 genetic system variants, encoded in plasmids and genomes, expressed in six gram-positive and gram-negative bacterial hosts. We then combined the search algorithm with system-level kinetic modeling, requiring the construction and characterization of 73 variants to build a sequence-expression-activity map (SEAMAP) for a biosynthesis pathway. Using model predictions, we designed and characterized 47 additional pathway variants to navigate its activity space, find optimal expression regions with desired activity response curves, and relieve rate-limiting steps in metabolism. Creating sequence-expression-activity maps accelerates the optimization of many protein systems and allows previous measurements to quantitatively inform future designs. PMID:24952589

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

PubMed

Sardi, Maria; Gasch, Audrey P

2018-04-11

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

Applied genetic evaluations for production and functional traits in dairy cattle.

PubMed

Mark, T

2004-08-01

The objective of this study was to review the current status of genetic evaluation systems for production and functional traits as practiced in different Interbull member countries and to discuss that status in relation to research results and potential improvements. Thirty-one countries provided information. Substantial variation was evident for number of traits considered per country, trait definition, genetic evaluation procedure within trait, effects included, and how these were treated in genetic evaluation models. All countries lacked genetic evaluations for one or more economically important traits. Improvement in the genetic evaluation models, especially for many functional traits, could be achieved by closing the gaps between research and practice. More detailed and up to date information about national genetic evaluation systems for traits in different countries is available at www.interbull.org. Female fertility and workability traits were considered in many countries and could be next in line for international genetic evaluations.

Alternate Service Delivery Models in Cancer Genetic Counseling: A Mini-Review.

PubMed

Buchanan, Adam Hudson; Rahm, Alanna Kulchak; Williams, Janet L

2016-01-01

Demand for cancer genetic counseling has grown rapidly in recent years as germline genomic information has become increasingly incorporated into cancer care, and the field has entered the public consciousness through high-profile celebrity publications. Increased demand and existing variability in the availability of trained cancer genetics clinicians place a priority on developing and evaluating alternate service delivery models for genetic counseling. This mini-review summarizes the state of science regarding service delivery models, such as telephone counseling, telegenetics, and group counseling. Research on comparative effectiveness of these models in traditional individual, in-person genetic counseling has been promising for improving access to care in a manner acceptable to patients. Yet, it has not fully evaluated the short- and long-term patient- and system-level outcomes that will help answer the question of whether these models achieve the same beneficial psychosocial and behavioral outcomes as traditional cancer genetic counseling. We propose a research agenda focused on comparative effectiveness of available service delivery models and how to match models to patients and practice settings. Only through this rigorous research can clinicians and systems find the optimal balance of clinical quality, ready and secure access to care, and financial sustainability. Such research will be integral to achieving the promise of genomic medicine in oncology.

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

Are genetically robust regulatory networks dynamically different from random ones?

NASA Astrophysics Data System (ADS)

Sevim, Volkan; Rikvold, Per Arne

We study a genetic regulatory network model developed to demonstrate that genetic robustness can evolve through stabilizing selection for optimal phenotypes. We report preliminary results on whether such selection could result in a reorganization of the state space of the system. For the chosen parameters, the evolution moves the system slightly toward the more ordered part of the phase diagram. We also find that strong memory effects cause the Derrida annealed approximation to give erroneous predictions about the model's phase diagram.

Emerging Technologies to Create Inducible and Genetically Defined Porcine Cancer Models.

PubMed

Schook, Lawrence B; Rund, Laurie; Begnini, Karine R; Remião, Mariana H; Seixas, Fabiana K; Collares, Tiago

2016-01-01

There is an emerging need for new animal models that address unmet translational cancer research requirements. Transgenic porcine models provide an exceptional opportunity due to their genetic, anatomic, and physiological similarities with humans. Due to recent advances in the sequencing of domestic animal genomes and the development of new organism cloning technologies, it is now very feasible to utilize pigs as a malleable species, with similar anatomic and physiological features with humans, in which to develop cancer models. In this review, we discuss genetic modification technologies successfully used to produce porcine biomedical models, in particular the Cre-loxP System as well as major advances and perspectives the CRISPR/Cas9 System. Recent advancements in porcine tumor modeling and genome editing will bring porcine models to the forefront of translational cancer research.

Identifying future models for delivering genetic services: a nominal group study in primary care

PubMed Central

Elwyn, Glyn; Edwards, Adrian; Iredale, Rachel; Davies, Peter; Gray, Jonathon

2005-01-01

Background To enable primary care medical practitioners to generate a range of possible service delivery models for genetic counselling services and critically assess their suitability. Methods Modified nominal group technique using in primary care professional development workshops. Results 37 general practitioners in Wales, United Kingdom too part in the nominal group process. The practitioners who attended did not believe current systems were sufficient to meet anticipated demand for genetic services. A wide range of different service models was proposed, although no single option emerged as a clear preference. No argument was put forward for genetic assessment and counselling being central to family practice, neither was there a voice for the view that the family doctor should become skilled at advising patients about predictive genetic testing and be able to counsel patients about the wider implications of genetic testing for patients and their family members, even for areas such as common cancers. Nevertheless, all the preferred models put a high priority on providing the service in the community, and often co-located in primary care, by clinicians who had developed expertise. Conclusion There is a need for a wider debate about how healthcare systems address individual concerns about genetic concerns and risk, especially given the increasing commercial marketing of genetic tests. PMID:15831099

Genetics of SLE: evidence from mouse models.

PubMed

Morel, Laurence

2010-06-01

Great progress has been made in the field of lupus genetics in the past few years, notably with the publication of genome-wide association studies in humans and the identification of susceptibility genes (including Fcgr2b, Ly108, Kallikrein genes and Coronin-1A) in mouse models of spontaneous lupus. This influx of new information has revealed an ever-increasing interdependence between the mouse and human systems for unraveling the genetic basis of lupus susceptibility. Studies in the 1980s and 1990s established that mice prone to spontaneous lupus constitute excellent models of the genetic architecture of human systemic lupus erythematosus (SLE). This notion has been greatly strengthened by the convergence of the functional pathways that are defective in both human and murine lupus. Within these pathways, variants in a number of genes have now been shown to be directly associated with lupus in both species. Consequently, mouse models will continue to serve a pre-eminent role in lupus genetics research, with an increased emphasis on mechanistic and molecular studies of human susceptibility alleles.

The Genomic and Genetic Toolbox of the Teleost Medaka (Oryzias latipes)

PubMed Central

Kirchmaier, Stephan; Naruse, Kiyoshi; Wittbrodt, Joachim; Loosli, Felix

2015-01-01

The Japanese medaka, Oryzias latipes, is a vertebrate teleost model with a long history of genetic research. A number of unique features and established resources distinguish medaka from other vertebrate model systems. A large number of laboratory strains from different locations are available. Due to a high tolerance to inbreeding, many highly inbred strains have been established, thus providing a rich resource for genetic studies. Furthermore, closely related species native to different habitats in Southeast Asia permit comparative evolutionary studies. The transparency of embryos, larvae, and juveniles allows a detailed in vivo analysis of development. New tools to study diverse aspects of medaka biology are constantly being generated. Thus, medaka has become an important vertebrate model organism to study development, behavior, and physiology. In this review, we provide a comprehensive overview of established genetic and molecular-genetic tools that render medaka fish a full-fledged vertebrate system. PMID:25855651

MINIGENOMES, TRANSCRIPTION AND REPLICATION COMPETENT VIRUS-LIKE PARTICLES AND BEYOND: REVERSE GENETICS SYSTEMS FOR FILOVIRUSES AND OTHER NEGATIVE STRANDED HEMORRHAGIC FEVER VIRUSES

PubMed Central

Hoenen, Thomas; Groseth, Allison; de Kok-Mercado, Fabian; Kuhn, Jens H.; Wahl-Jensen, Victoria

2012-01-01

Reverse-genetics systems are powerful tools enabling researchers to study the replication cycle of RNA viruses, including filoviruses and other hemorrhagic fever viruses, as well as to discover new antivirals. They include full-length clone systems as well as a number of life cycle modeling systems. Full-length clone systems allow for the generation of infectious, recombinant viruses, and thus are an important tool for studying the virus replication cycle in its entirety. In contrast, life cycle modeling systems such as minigenome and transcription and replication competent virus-like particle systems can be used to simulate and dissect parts of the virus life cycle outside of containment facilities. Minigenome systems are used to model viral genome replication and transcription, whereas transcription and replication competent virus-like particle systems also model morphogenesis and budding as well as infection of target cells. As such, these modeling systems have tremendous potential to further the discovery and screening of new antivirals targeting hemorrhagic fever viruses. This review provides an overview of currently established reverse genetics systems for hemorrhagic fever-causing negative-sense RNA viruses, with a particular emphasis on filoviruses, and the potential application of these systems for antiviral research. PMID:21699921

Fuzzy Logic, Neural Networks, Genetic Algorithms: Views of Three Artificial Intelligence Concepts Used in Modeling Scientific Systems

ERIC Educational Resources Information Center

Sunal, Cynthia Szymanski; Karr, Charles L.; Sunal, Dennis W.

2003-01-01

Students' conceptions of three major artificial intelligence concepts used in the modeling of systems in science, fuzzy logic, neural networks, and genetic algorithms were investigated before and after a higher education science course. Students initially explored their prior ideas related to the three concepts through active tasks. Then,…

[Advances in understanding Drosophila salivary gland polytene chromosome and its applications in genetics teaching].

PubMed

Li, Gang; Chen, Fan-guo

2015-06-01

Drosophila salivary gland polytene chromosome, one of the three classical chromosomes with remarkable characteristics, has been used as an outstanding model for a variety of genetic studies since 1934. The greatest contribution of this model to genetics has been providing extraordinary angle of view in studying interphase chromosome structure and gene expression regulation. Additionally, it has been extensively used to understand some special genetic phenomena, such as dosage compensation and position-effect variegation. In this paper, we briefly review the advances in the study of Drosophila salivary gland chromosome, and try to systematically and effectively introduce this model system into genetics teaching practice in order to steer and inspire students' interest in genetics.

CRISPR: a Versatile Tool for Both Forward and Reverse Genetics Research

PubMed Central

Gurumurthy, Channabasavaiah B.; Grati, M'hamed; Ohtsuka, Masato; Schilit, Samantha L.P.; Quadros, Rolen M.; Liu, Xue Zhong

2016-01-01

Human genetics research employs the two opposing approaches of forward and reverse genetics. While forward genetics identifies and links a mutation to an observed disease etiology, reverse genetics induces mutations in model organisms to study their role in disease. In most cases, causality for mutations identified by forward genetics is confirmed by reverse genetics through the development of genetically engineered animal models and an assessment of whether the model can recapitulate the disease. While many technological advances have helped improve these approaches, some gaps still remain. CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated) system, which has emerged as a revolutionary genetic engineering tool, holds great promise for closing such gaps. By combining the benefits of forward and reverse genetics, it has dramatically expedited human genetics research. We provide a perspective on the power of CRISPR-based forward and reverse genetics tools in human genetics and discuss its applications using some disease examples. PMID:27384229

Reframed Genome-Scale Metabolic Model to Facilitate Genetic Design and Integration with Expression Data.

PubMed

Gu, Deqing; Jian, Xingxing; Zhang, Cheng; Hua, Qiang

2017-01-01

Genome-scale metabolic network models (GEMs) have played important roles in the design of genetically engineered strains and helped biologists to decipher metabolism. However, due to the complex gene-reaction relationships that exist in model systems, most algorithms have limited capabilities with respect to directly predicting accurate genetic design for metabolic engineering. In particular, methods that predict reaction knockout strategies leading to overproduction are often impractical in terms of gene manipulations. Recently, we proposed a method named logical transformation of model (LTM) to simplify the gene-reaction associations by introducing intermediate pseudo reactions, which makes it possible to generate genetic design. Here, we propose an alternative method to relieve researchers from deciphering complex gene-reactions by adding pseudo gene controlling reactions. In comparison to LTM, this new method introduces fewer pseudo reactions and generates a much smaller model system named as gModel. We showed that gModel allows two seldom reported applications: identification of minimal genomes and design of minimal cell factories within a modified OptKnock framework. In addition, gModel could be used to integrate expression data directly and improve the performance of the E-Fmin method for predicting fluxes. In conclusion, the model transformation procedure will facilitate genetic research based on GEMs, extending their applications.

Physiological significance of ghrelin revealed by studies using genetically engineered mouse models with modifications in the ghrelin system.

PubMed

Ariyasu, Hiroyuki; Akamizu, Takashi

2015-01-01

Ghrelin, an endogenous ligand for the growth hormone (GH) secretagogue receptor (GHS-R or ghrelin receptor), is a 28-amino acid acylated peptide mainly produced in the stomach. The pharmacological administration of ghrelin is known to exert diverse effects, such as stimulating GH secretion, promoting food intake, and increasing adiposity. In recent years, genetically engineered mouse models have provided important insights into the physiology of various hormones. In this review, we discuss current knowledge regarding the physiological significance of ghrelin on the basis of studies using genetically engineered mouse models with modifications in the ghrelin system.

Emerging Technologies to Create Inducible and Genetically Defined Porcine Cancer Models

PubMed Central

Schook, Lawrence B.; Rund, Laurie; Begnini, Karine R.; Remião, Mariana H.; Seixas, Fabiana K.; Collares, Tiago

2016-01-01

There is an emerging need for new animal models that address unmet translational cancer research requirements. Transgenic porcine models provide an exceptional opportunity due to their genetic, anatomic, and physiological similarities with humans. Due to recent advances in the sequencing of domestic animal genomes and the development of new organism cloning technologies, it is now very feasible to utilize pigs as a malleable species, with similar anatomic and physiological features with humans, in which to develop cancer models. In this review, we discuss genetic modification technologies successfully used to produce porcine biomedical models, in particular the Cre-loxP System as well as major advances and perspectives the CRISPR/Cas9 System. Recent advancements in porcine tumor modeling and genome editing will bring porcine models to the forefront of translational cancer research. PMID:26973698

Investigation on application of genetic algorithms to optimal reactive power dispatch of power systems

NASA Astrophysics Data System (ADS)

Wu, Q. H.; Ma, J. T.

1993-09-01

A primary investigation into application of genetic algorithms in optimal reactive power dispatch and voltage control is presented. The application was achieved, based on (the United Kingdom) National Grid 48 bus network model, using a novel genetic search approach. Simulation results, compared with that obtained using nonlinear programming methods, are included to show the potential of applications of the genetic search methodology in power system economical and secure operations.

Generating Systems Biology Markup Language Models from the Synthetic Biology Open Language.

PubMed

Roehner, Nicholas; Zhang, Zhen; Nguyen, Tramy; Myers, Chris J

2015-08-21

In the context of synthetic biology, model generation is the automated process of constructing biochemical models based on genetic designs. This paper discusses the use cases for model generation in genetic design automation (GDA) software tools and introduces the foundational concepts of standards and model annotation that make this process useful. Finally, this paper presents an implementation of model generation in the GDA software tool iBioSim and provides an example of generating a Systems Biology Markup Language (SBML) model from a design of a 4-input AND sensor written in the Synthetic Biology Open Language (SBOL).

Using Genetic Algorithm and MODFLOW to Characterize Aquifer System of Northwest Florida

EPA Science Inventory

By integrating Genetic Algorithm and MODFLOW2005, an optimizing tool is developed to characterize the aquifer system of Region II, Northwest Florida. The history and the newest available observation data of the aquifer system is fitted automatically by using the numerical model c...

Petri net modeling of high-order genetic systems using grammatical evolution.

PubMed

Moore, Jason H; Hahn, Lance W

2003-11-01

Understanding how DNA sequence variations impact human health through a hierarchy of biochemical and physiological systems is expected to improve the diagnosis, prevention, and treatment of common, complex human diseases. We have previously developed a hierarchical dynamic systems approach based on Petri nets for generating biochemical network models that are consistent with genetic models of disease susceptibility. This modeling approach uses an evolutionary computation approach called grammatical evolution as a search strategy for optimal Petri net models. We have previously demonstrated that this approach routinely identifies biochemical network models that are consistent with a variety of genetic models in which disease susceptibility is determined by nonlinear interactions between two DNA sequence variations. In the present study, we evaluate whether the Petri net approach is capable of identifying biochemical networks that are consistent with disease susceptibility due to higher order nonlinear interactions between three DNA sequence variations. The results indicate that our model-building approach is capable of routinely identifying good, but not perfect, Petri net models. Ideas for improving the algorithm for this high-dimensional problem are presented.

Flexible Space-Filling Designs for Complex System Simulations

DTIC Science & Technology

2013-06-01

interior of the experimental region and cannot fit higher-order models. We present a genetic algorithm that constructs space-filling designs with...Computer Experiments, Design of Experiments, Genetic Algorithm , Latin Hypercube, Response Surface Methodology, Nearly Orthogonal 15. NUMBER OF PAGES 147...experimental region and cannot fit higher-order models. We present a genetic algorithm that constructs space-filling designs with minimal correlations

Joint genetic analysis of hippocampal size in mouse and human identifies a novel gene linked to neurodegenerative disease.

PubMed

Ashbrook, David G; Williams, Robert W; Lu, Lu; Stein, Jason L; Hibar, Derrek P; Nichols, Thomas E; Medland, Sarah E; Thompson, Paul M; Hager, Reinmar

2014-10-03

Variation in hippocampal volume has been linked to significant differences in memory, behavior, and cognition among individuals. To identify genetic variants underlying such differences and associated disease phenotypes, multinational consortia such as ENIGMA have used large magnetic resonance imaging (MRI) data sets in human GWAS studies. In addition, mapping studies in mouse model systems have identified genetic variants for brain structure variation with great power. A key challenge is to understand how genetically based differences in brain structure lead to the propensity to develop specific neurological disorders. We combine the largest human GWAS of brain structure with the largest mammalian model system, the BXD recombinant inbred mouse population, to identify novel genetic targets influencing brain structure variation that are linked to increased risk for neurological disorders. We first use a novel cross-species, comparative analysis using mouse and human genetic data to identify a candidate gene, MGST3, associated with adult hippocampus size in both systems. We then establish the coregulation and function of this gene in a comprehensive systems-analysis. We find that MGST3 is associated with hippocampus size and is linked to a group of neurodegenerative disorders, such as Alzheimer's.

Using Genetic Algorithm and MODFLOW to Characterize Aquifer System of Northwest Florida (Published Proceedings)

EPA Science Inventory

By integrating Genetic Algorithm and MODFLOW2005, an optimizing tool is developed to characterize the aquifer system of Region II, Northwest Florida. The history and the newest available observation data of the aquifer system is fitted automatically by using the numerical model c...

Setaria viridis as a Model System to Advance Millet Genetics and Genomics

PubMed Central

Huang, Pu; Shyu, Christine; Coelho, Carla P.; Cao, Yingying; Brutnell, Thomas P.

2016-01-01

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops. PMID:27965689

Setaria viridis as a Model System to Advance Millet Genetics and Genomics.

PubMed

Huang, Pu; Shyu, Christine; Coelho, Carla P; Cao, Yingying; Brutnell, Thomas P

2016-01-01

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools and resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail ( Setaria viridis ) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica . These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops.

Optimality models in the age of experimental evolution and genomics.

PubMed

Bull, J J; Wang, I-N

2010-09-01

Optimality models have been used to predict evolution of many properties of organisms. They typically neglect genetic details, whether by necessity or design. This omission is a common source of criticism, and although this limitation of optimality is widely acknowledged, it has mostly been defended rather than evaluated for its impact. Experimental adaptation of model organisms provides a new arena for testing optimality models and for simultaneously integrating genetics. First, an experimental context with a well-researched organism allows dissection of the evolutionary process to identify causes of model failure--whether the model is wrong about genetics or selection. Second, optimality models provide a meaningful context for the process and mechanics of evolution, and thus may be used to elicit realistic genetic bases of adaptation--an especially useful augmentation to well-researched genetic systems. A few studies of microbes have begun to pioneer this new direction. Incompatibility between the assumed and actual genetics has been demonstrated to be the cause of model failure in some cases. More interestingly, evolution at the phenotypic level has sometimes matched prediction even though the adaptive mutations defy mechanisms established by decades of classic genetic studies. Integration of experimental evolutionary tests with genetics heralds a new wave for optimality models and their extensions that does not merely emphasize the forces driving evolution.

Building a Genome Engineering Toolbox in Non-Model Prokaryotic Microbes

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

Eckert, Carrie A; Freed, Emily; Smolinski, Sharon

The realization of a sustainable bioeconomy requires our ability to understand and engineer complex design principles for the development of platform organisms capable of efficient conversion of cheap and sustainable feedstocks (e.g. sunlight, CO2, non-food biomass) to biofuels and bioproducts at sufficient titers and costs. For model microbes such as E. coli, advances in DNA reading and writing technologies are driving adoption of new paradigms for engineering biological systems. Unfortunately, microbes with properties of interest for the utilization of cheap and renewable feedstocks such as photosynthesis, autotrophic growth, and cellulose degradation have very few, if any, genetic tools for metabolicmore » engineering. Therefore, it is important to begin to develop 'design rules' for building a genetic toolbox for novel microbes. Here, we present an overview of our current understanding of these rules for the genetic manipulation of prokaryotic microbes and available genetic tools to expand our ability to genetically engineer non-model systems.« less

New tools for the analysis of glial cell biology in Drosophila.

PubMed

Awasaki, Takeshi; Lee, Tzumin

2011-09-01

Because of its genetic, molecular, and behavioral tractability, Drosophila has emerged as a powerful model system for studying molecular and cellular mechanisms underlying the development and function of nervous systems. The Drosophila nervous system has fewer neurons and exhibits a lower glia:neuron ratio than is seen in vertebrate nervous systems. Despite the simplicity of the Drosophila nervous system, glial organization in flies is as sophisticated as it is in vertebrates. Furthermore, fly glial cells play vital roles in neural development and behavior. In addition, powerful genetic tools are continuously being created to explore cell function in vivo. In taking advantage of these features, the fly nervous system serves as an excellent model system to study general aspects of glial cell development and function in vivo. In this article, we review and discuss advanced genetic tools that are potentially useful for understanding glial cell biology in Drosophila. Copyright © 2011 Wiley-Liss, Inc.

Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

NASA Astrophysics Data System (ADS)

Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

2009-07-01

Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

Modeling of biological intelligence for SCM system optimization.

PubMed

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

PubMed Central

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

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.

Pleiotropic Models of Polygenic Variation, Stabilizing Selection, and Epistasis

PubMed Central

Gavrilets, S.; de-Jong, G.

1993-01-01

We show that in polymorphic populations many polygenic traits pleiotropically related to fitness are expected to be under apparent ``stabilizing selection'' independently of the real selection acting on the population. This occurs, for example, if the genetic system is at a stable polymorphic equilibrium determined by selection and the nonadditive contributions of the loci to the trait value either are absent, or are random and independent of those to fitness. Stabilizing selection is also observed if the polygenic system is at an equilibrium determined by a balance between selection and mutation (or migration) when both additive and nonadditive contributions of the loci to the trait value are random and independent of those to fitness. We also compare different viability models that can maintain genetic variability at many loci with respect to their ability to account for the strong stabilizing selection on an additive trait. Let V(m) be the genetic variance supplied by mutation (or migration) each generation, V(g) be the genotypic variance maintained in the population, and n be the number of the loci influencing fitness. We demonstrate that in mutation (migration)-selection balance models the strength of apparent stabilizing selection is order V(m)/V(g). In the overdominant model and in the symmetric viability model the strength of apparent stabilizing selection is approximately 1/(2n) that of total selection on the whole phenotype. We show that a selection system that involves pairwise additive by additive epistasis in maintaining variability can lead to a lower genetic load and genetic variance in fitness (approximately 1/(2n) times) than an equivalent selection system that involves overdominance. We show that, in the epistatic model, the apparent stabilizing selection on an additive trait can be as strong as the total selection on the whole phenotype. PMID:8325491

Adaptive process control using fuzzy logic and genetic algorithms

NASA Technical Reports Server (NTRS)

Karr, C. L.

1993-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

Adaptive Process Control with Fuzzy Logic and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Karr, C. L.

1993-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

Genetic algorithms in adaptive fuzzy control

NASA Technical Reports Server (NTRS)

Karr, C. Lucas; Harper, Tony R.

1992-01-01

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.

Setaria viridis as a Model System to Advance Millet Genetics and Genomics

DOE PAGES

Huang, Pu; Shyu, Christine; Coelho, Carla P.; ...

2016-11-28

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Yet despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools andmore » resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops.« less

Setaria viridis as a Model System to Advance Millet Genetics and Genomics

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

Huang, Pu; Shyu, Christine; Coelho, Carla P.

Millet is a common name for a group of polyphyletic, small-seeded cereal crops that include pearl, finger and foxtail millet. Millet species are an important source of calories for many societies, often in developing countries. Compared to major cereal crops such as rice and maize, millets are generally better adapted to dry and hot environments. Yet despite their food security value, the genetic architecture of agronomically important traits in millets, including both morphological traits and climate resilience remains poorly studied. These complex traits have been challenging to dissect in large part because of the lack of sufficient genetic tools andmore » resources. In this article, we review the phylogenetic relationship among various millet species and discuss the value of a genetic model system for millet research. We propose that a broader adoption of green foxtail (Setaria viridis) as a model system for millets could greatly accelerate the pace of gene discovery in the millets, and summarize available and emerging resources in S. viridis and its domesticated relative S. italica. These resources have value in forward genetics, reverse genetics and high throughput phenotyping. We describe methods and strategies to best utilize these resources to facilitate the genetic dissection of complex traits. We envision that coupling cutting-edge technologies and the use of S. viridis for gene discovery will accelerate genetic research in millets in general. This will enable strategies and provide opportunities to increase productivity, especially in the semi-arid tropics of Asia and Africa where millets are staple food crops.« less

Precise Network Modeling of Systems Genetics Data Using the Bayesian Network Webserver.

PubMed

Ziebarth, Jesse D; Cui, Yan

2017-01-01

The Bayesian Network Webserver (BNW, http://compbio.uthsc.edu/BNW ) is an integrated platform for Bayesian network modeling of biological datasets. It provides a web-based network modeling environment that seamlessly integrates advanced algorithms for probabilistic causal modeling and reasoning with Bayesian networks. BNW is designed for precise modeling of relatively small networks that contain less than 20 nodes. The structure learning algorithms used by BNW guarantee the discovery of the best (most probable) network structure given the data. To facilitate network modeling across multiple biological levels, BNW provides a very flexible interface that allows users to assign network nodes into different tiers and define the relationships between and within the tiers. This function is particularly useful for modeling systems genetics datasets that often consist of multiscalar heterogeneous genotype-to-phenotype data. BNW enables users to, within seconds or minutes, go from having a simply formatted input file containing a dataset to using a network model to make predictions about the interactions between variables and the potential effects of experimental interventions. In this chapter, we will introduce the functions of BNW and show how to model systems genetics datasets with BNW.

Fractional dynamics of globally slow transcription and its impact on deterministic genetic oscillation.

PubMed

Wei, Kun; Gao, Shilong; Zhong, Suchuan; Ma, Hong

2012-01-01

In dynamical systems theory, a system which can be described by differential equations is called a continuous dynamical system. In studies on genetic oscillation, most deterministic models at early stage are usually built on ordinary differential equations (ODE). Therefore, gene transcription which is a vital part in genetic oscillation is presupposed to be a continuous dynamical system by default. However, recent studies argued that discontinuous transcription might be more common than continuous transcription. In this paper, by appending the inserted silent interval lying between two neighboring transcriptional events to the end of the preceding event, we established that the running time for an intact transcriptional event increases and gene transcription thus shows slow dynamics. By globally replacing the original time increment for each state increment by a larger one, we introduced fractional differential equations (FDE) to describe such globally slow transcription. The impact of fractionization on genetic oscillation was then studied in two early stage models--the Goodwin oscillator and the Rössler oscillator. By constructing a "dual memory" oscillator--the fractional delay Goodwin oscillator, we suggested that four general requirements for generating genetic oscillation should be revised to be negative feedback, sufficient nonlinearity, sufficient memory and proper balancing of timescale. The numerical study of the fractional Rössler oscillator implied that the globally slow transcription tends to lower the chance of a coupled or more complex nonlinear genetic oscillatory system behaving chaotically.

Advantages of using the CRISPR/Cas9 system of genome editing to investigate male reproductive mechanisms using mouse models.

PubMed

Young, Samantha A M; Aitken, R John; Ikawa, Masahito

2015-01-01

Gene disruption technology has long been beneficial for the study of male reproductive biology. However, because of the time and cost involved, this technology was not a viable method except in specialist laboratories. The advent of the CRISPR/Cas9 system of gene disruption has ushered in a new era of genetic investigation. Now, it is possible to generate gene-disrupted mouse models in very little time and at very little cost. This Highlight article discusses the application of this technology to study the genetics of male fertility and looks at some of the future uses of this system that could be used to reveal the essential and nonessential genetic components of male reproductive mechanisms.

Logistics Distribution Center Location Evaluation Based on Genetic Algorithm and Fuzzy Neural Network

NASA Astrophysics Data System (ADS)

Shao, Yuxiang; Chen, Qing; Wei, Zhenhua

Logistics distribution center location evaluation is a dynamic, fuzzy, open and complicated nonlinear system, which makes it difficult to evaluate the distribution center location by the traditional analysis method. The paper proposes a distribution center location evaluation system which uses the fuzzy neural network combined with the genetic algorithm. In this model, the neural network is adopted to construct the fuzzy system. By using the genetic algorithm, the parameters of the neural network are optimized and trained so as to improve the fuzzy system’s abilities of self-study and self-adaptation. At last, the sampled data are trained and tested by Matlab software. The simulation results indicate that the proposed identification model has very small errors.

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

NASA Astrophysics Data System (ADS)

Liu, Zhijian; Yin, Donghui; Yan, Jun

2017-05-01

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

Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia.

PubMed

Vallat, Laurent; Kemper, Corey A; Jung, Nicolas; Maumy-Bertrand, Myriam; Bertrand, Frédéric; Meyer, Nicolas; Pocheville, Arnaud; Fisher, John W; Gribben, John G; Bahram, Seiamak

2013-01-08

Cellular behavior is sustained by genetic programs that are progressively disrupted in pathological conditions--notably, cancer. High-throughput gene expression profiling has been used to infer statistical models describing these cellular programs, and development is now needed to guide orientated modulation of these systems. Here we develop a regression-based model to reverse-engineer a temporal genetic program, based on relevant patterns of gene expression after cell stimulation. This method integrates the temporal dimension of biological rewiring of genetic programs and enables the prediction of the effect of targeted gene disruption at the system level. We tested the performance accuracy of this model on synthetic data before reverse-engineering the response of primary cancer cells to a proliferative (protumorigenic) stimulation in a multistate leukemia biological model (i.e., chronic lymphocytic leukemia). To validate the ability of our method to predict the effects of gene modulation on the global program, we performed an intervention experiment on a targeted gene. Comparison of the predicted and observed gene expression changes demonstrates the possibility of predicting the effects of a perturbation in a gene regulatory network, a first step toward an orientated intervention in a cancer cell genetic program.

Temperature-dependent behaviours are genetically variable in the nematode Caenorhabditis briggsae.

PubMed

Stegeman, Gregory W; de Mesquita, Matthew Bueno; Ryu, William S; Cutter, Asher D

2013-03-01

Temperature-dependent behaviours in Caenorhabditis elegans, such as thermotaxis and isothermal tracking, are complex behavioural responses that integrate sensation, foraging and learning, and have driven investigations to discover many essential genetic and neural pathways. The ease of manipulation of the Caenorhabditis model system also has encouraged its application to comparative analyses of phenotypic evolution, particularly contrasts of the classic model C. elegans with C. briggsae. And yet few studies have investigated natural genetic variation in behaviour in any nematode. Here we measure thermotaxis and isothermal tracking behaviour in genetically distinct strains of C. briggsae, further motivated by the latitudinal differentiation in C. briggsae that is associated with temperature-dependent fitness differences in this species. We demonstrate that C. briggsae performs thermotaxis and isothermal tracking largely similar to that of C. elegans, with a tendency to prefer its rearing temperature. Comparisons of these behaviours among strains reveal substantial heritable natural variation within each species that corresponds to three general patterns of behavioural response. However, intraspecific genetic differences in thermal behaviour often exceed interspecific differences. These patterns of temperature-dependent behaviour motivate further development of C. briggsae as a model system for dissecting the genetic underpinnings of complex behavioural traits.

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.

Research on optimization of combustion efficiency of thermal power unit based on genetic algorithm

NASA Astrophysics Data System (ADS)

Zhou, Qiongyang

2018-04-01

In order to improve the economic performance and reduce pollutant emissions of thermal power units, the characteristics of neural network in establishing boiler combustion model are analyzed based on the analysis of the main factors affecting boiler efficiency by using orthogonal method. In addition, on the basis of this model, the genetic algorithm is used to find the best control amount of the furnace combustion in a certain working condition. Through the genetic algorithm based on real number encoding and roulette selection is concluded: the best control quantity at a condition of furnace combustion can be combined with the boiler combustion system model for neural network training. The precision of the neural network model is further improved, and the basic work is laid for the research of the whole boiler combustion optimization system.

PERSON-Personalized Expert Recommendation System for Optimized Nutrition.

PubMed

Chen, Chih-Han; Karvela, Maria; Sohbati, Mohammadreza; Shinawatra, Thaksin; Toumazou, Christofer

2018-02-01

The rise of personalized diets is due to the emergence of nutrigenetics and genetic tests services. However, the recommendation system is far from mature to provide personalized food suggestion to consumers for daily usage. The main barrier of connecting genetic information to personalized diets is the complexity of data and the scalability of the applied systems. Aiming to cross such barriers and provide direct applications, a personalized expert recommendation system for optimized nutrition is introduced in this paper, which performs direct to consumer personalized grocery product filtering and recommendation. Deep learning neural network model is applied to achieve automatic product categorization. The ability of scaling with unknown new data is achieved through the generalized representation of word embedding. Furthermore, the categorized products are filtered with a model based on individual genetic data with associated phenotypic information and a case study with databases from three different sources is carried out to confirm the system.

Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer.

PubMed

Castelli, Mauro; Trujillo, Leonardo; Vanneschi, Leonardo

2015-01-01

Energy consumption forecasting (ECF) is an important policy issue in today's economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In particular, we propose a system that finds (quasi-)perfect solutions with high probability and that generates models able to produce near optimal predictions also on unseen data. The framework blends a recently developed version of genetic programming that integrates semantic genetic operators with a local search method. The main idea in combining semantic genetic programming and a local searcher is to couple the exploration ability of the former with the exploitation ability of the latter. Experimental results confirm the suitability of the proposed method in predicting the energy consumption. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that including a local searcher in the geometric semantic genetic programming system can speed up the search process and can result in fitter models that are able to produce an accurate forecasting also on unseen data.

Seteria viridis as a model for pathogen resistance in the Poaceae

USDA-ARS?s Scientific Manuscript database

Seteria viridis is an effective model system for functional genetics in the C4 Poaceae grasses, which include important crops like maize, sorghum, and sugar cane. The small genome size, short stature, rapid life cycle, and the availability of genetic transformation protocols, make Seteria an attract...

Weather prediction using a genetic memory

NASA Technical Reports Server (NTRS)

Rogers, David

1990-01-01

Kanaerva's sparse distributed memory (SDM) is an associative memory model based on the mathematical properties of high dimensional binary address spaces. Holland's genetic algorithms are a search technique for high dimensional spaces inspired by evolutional processes of DNA. Genetic Memory is a hybrid of the above two systems, in which the memory uses a genetic algorithm to dynamically reconfigure its physical storage locations to reflect correlations between the stored addresses and data. This architecture is designed to maximize the ability of the system to scale-up to handle real world problems.

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

NASA Technical Reports Server (NTRS)

Szallasi, Zoltan; Liang, Shoudan

2000-01-01

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

Genetically Engineered Mouse Models for Studying Inflammatory Bowel Disease

PubMed Central

Mizoguchi, Atsushi; Takeuchi, Takahito; Himuro, Hidetomo; Okada, Toshiyuki; Mizoguchi, Emiko

2015-01-01

Inflammatory bowel disease (IBD) is a chronic intestinal inflammatory condition that is mediated by very complex mechanisms controlled by genetic, immune, and environmental factors. More than 74 kinds of genetically engineered mouse strains have been established since 1993 for studying IBD. Although mouse models cannot fully reflect human IBD, they have provided significant contributions for not only understanding the mechanism, but also developing new therapeutic means for IBD. Indeed, 20 kinds of genetically engineered mouse models carry the susceptibility genes identified in human IBD, and the functions of some other IBD susceptibility genes have also been dissected out using mouse models. Cutting-edge technologies such as cell-specific and inducible knockout systems, which were recently employed to mouse IBD models, have further enhanced the ability of investigators to provide important and unexpected rationales for developing new therapeutic strategies for IBD. In this review article, we briefly introduce 74 kinds of genetically engineered mouse models that spontaneously develop intestinal inflammation. PMID:26387641

Mouse Models for Drug Discovery. Can New Tools and Technology Improve Translational Power?

PubMed Central

Zuberi, Aamir; Lutz, Cathleen

2016-01-01

Abstract The use of mouse models in biomedical research and preclinical drug evaluation is on the rise. The advent of new molecular genome-altering technologies such as CRISPR/Cas9 allows for genetic mutations to be introduced into the germ line of a mouse faster and less expensively than previous methods. In addition, the rapid progress in the development and use of somatic transgenesis using viral vectors, as well as manipulations of gene expression with siRNAs and antisense oligonucleotides, allow for even greater exploration into genomics and systems biology. These technological advances come at a time when cost reductions in genome sequencing have led to the identification of pathogenic mutations in patient populations, providing unprecedented opportunities in the use of mice to model human disease. The ease of genetic engineering in mice also offers a potential paradigm shift in resource sharing and the speed by which models are made available in the public domain. Predictively, the knowledge alone that a model can be quickly remade will provide relief to resources encumbered by licensing and Material Transfer Agreements. For decades, mouse strains have provided an exquisite experimental tool to study the pathophysiology of the disease and assess therapeutic options in a genetically defined system. However, a major limitation of the mouse has been the limited genetic diversity associated with common laboratory mice. This has been overcome with the recent development of the Collaborative Cross and Diversity Outbred mice. These strains provide new tools capable of replicating genetic diversity to that approaching the diversity found in human populations. The Collaborative Cross and Diversity Outbred strains thus provide a means to observe and characterize toxicity or efficacy of new therapeutic drugs for a given population. The combination of traditional and contemporary mouse genome editing tools, along with the addition of genetic diversity in new modeling systems, are synergistic and serve to make the mouse a better model for biomedical research, enhancing the potential for preclinical drug discovery and personalized medicine. PMID:28053071

From drug to protein: using yeast genetics for high-throughput target discovery.

PubMed

Armour, Christopher D; Lum, Pek Yee

2005-02-01

The budding yeast Saccharomyces cerevisiae has long been an effective eukaryotic model system for understanding basic cellular processes. The genetic tractability and ease of manipulation in the laboratory make yeast well suited for large-scale chemical and genetic screens. Several recent studies describing the use of yeast genetics for high-throughput drug target identification are discussed in this review.

Nemesis Autonomous Test System

NASA Technical Reports Server (NTRS)

Barltrop, Kevin J.; Lee, Cin-Young; Horvath, Gregory A,; Clement, Bradley J.

2012-01-01

A generalized framework has been developed for systems validation that can be applied to both traditional and autonomous systems. The framework consists of an automated test case generation and execution system called Nemesis that rapidly and thoroughly identifies flaws or vulnerabilities within a system. By applying genetic optimization and goal-seeking algorithms on the test equipment side, a "war game" is conducted between a system and its complementary nemesis. The end result of the war games is a collection of scenarios that reveals any undesirable behaviors of the system under test. The software provides a reusable framework to evolve test scenarios using genetic algorithms using an operation model of the system under test. It can automatically generate and execute test cases that reveal flaws in behaviorally complex systems. Genetic algorithms focus the exploration of tests on the set of test cases that most effectively reveals the flaws and vulnerabilities of the system under test. It leverages advances in state- and model-based engineering, which are essential in defining the behavior of autonomous systems. It also uses goal networks to describe test scenarios.

Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases

PubMed Central

Amos, Christopher I.; Bafna, Vineet; Hauser, Elizabeth R.; Hernandez, Ryan D.; Li, Chun; Liberles, David A.; McAllister, Kimberly; Moore, Jason H.; Paltoo, Dina N.; Papanicolaou, George J.; Peng, Bo; Ritchie, Marylyn D.; Rosenfeld, Gabriel; Witte, John S.

2014-01-01

Genetic simulation programs are used to model data under specified assumptions to facilitate the understanding and study of complex genetic systems. Standardized data sets generated using genetic simulation are essential for the development and application of novel analytical tools in genetic epidemiology studies. With continuing advances in high-throughput genomic technologies and generation and analysis of larger, more complex data sets, there is a need for updating current approaches in genetic simulation modeling. To provide a forum to address current and emerging challenges in this area, the National Cancer Institute (NCI) sponsored a workshop, entitled “Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases” at the National Institutes of Health (NIH) in Bethesda, Maryland on March 11-12, 2014. The goals of the workshop were to: (i) identify opportunities, challenges and resource needs for the development and application of genetic simulation models; (ii) improve the integration of tools for modeling and analysis of simulated data; and (iii) foster collaborations to facilitate development and applications of genetic simulation. During the course of the meeting the group identified challenges and opportunities for the science of simulation, software and methods development, and collaboration. This paper summarizes key discussions at the meeting, and highlights important challenges and opportunities to advance the field of genetic simulation. PMID:25371374

Mathematical modeling of continuous ethanol fermentation in a membrane bioreactor by pervaporation compared to conventional system: Genetic algorithm.

PubMed

Esfahanian, Mehri; Shokuhi Rad, Ali; Khoshhal, Saeed; Najafpour, Ghasem; Asghari, Behnam

2016-07-01

In this paper, genetic algorithm was used to investigate mathematical modeling of ethanol fermentation in a continuous conventional bioreactor (CCBR) and a continuous membrane bioreactor (CMBR) by ethanol permselective polydimethylsiloxane (PDMS) membrane. A lab scale CMBR with medium glucose concentration of 100gL(-1) and Saccharomyces cerevisiae microorganism was designed and fabricated. At dilution rate of 0.14h(-1), maximum specific cell growth rate and productivity of 0.27h(-1) and 6.49gL(-1)h(-1) were respectively found in CMBR. However, at very high dilution rate, the performance of CMBR was quite similar to conventional fermentation on account of insufficient incubation time. In both systems, genetic algorithm modeling of cell growth, ethanol production and glucose concentration were conducted based on Monod and Moser kinetic models during each retention time at unsteady condition. The results showed that Moser kinetic model was more satisfactory and desirable than Monod model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genetic counselling in the era of genomic medicine

PubMed Central

Middleton, Anna

2018-01-01

Abstract Background Genomic technology can now deliver cost effective, targeted diagnosis and treatment for patients. Genetic counselling is a communication process empowering patients and families to make autonomous decisions and effectively use new genetic information. The skills of genetic counselling and expertise of genetic counsellors are integral to the effective implementation of genomic medicine. Sources of data Original papers, reviews, guidelines, policy papers and web-resources. Areas of agreement An international consensus on the definition of genetic counselling. Genetic counselling is necessary for implementation of genomic medicine. Areas of controversy Models of genetic counselling. Growing points Genomic medicine is a growing and strategic priority for many health care systems. Genetic counselling is part of this. Areas timely for developing research An evidence base is necessary, incorporating implementation and outcome research, to enable health care systems, practitioners, patients and families to maximize the utility (medically and psychologically) of the new genomic possibilities. PMID:29617718

Systems Engineering Design Via Experimental Operation Research: Complex Organizational Metric for Programmatic Risk Environments (COMPRE)

NASA Technical Reports Server (NTRS)

Mog, Robert A.

1999-01-01

Unique and innovative graph theory, neural network, organizational modeling, and genetic algorithms are applied to the design and evolution of programmatic and organizational architectures. Graph theory representations of programs and organizations increase modeling capabilities and flexibility, while illuminating preferable programmatic/organizational design features. Treating programs and organizations as neural networks results in better system synthesis, and more robust data modeling. Organizational modeling using covariance structures enhances the determination of organizational risk factors. Genetic algorithms improve programmatic evolution characteristics, while shedding light on rulebase requirements for achieving specified technological readiness levels, given budget and schedule resources. This program of research improves the robustness and verifiability of systems synthesis tools, including the Complex Organizational Metric for Programmatic Risk Environments (COMPRE).

Measurement and modeling of intrinsic transcription terminators

PubMed Central

Cambray, Guillaume; Guimaraes, Joao C.; Mutalik, Vivek K.; Lam, Colin; Mai, Quynh-Anh; Thimmaiah, Tim; Carothers, James M.; Arkin, Adam P.; Endy, Drew

2013-01-01

The reliable forward engineering of genetic systems remains limited by the ad hoc reuse of many types of basic genetic elements. Although a few intrinsic prokaryotic transcription terminators are used routinely, termination efficiencies have not been studied systematically. Here, we developed and validated a genetic architecture that enables reliable measurement of termination efficiencies. We then assembled a collection of 61 natural and synthetic terminators that collectively encode termination efficiencies across an ∼800-fold dynamic range within Escherichia coli. We simulated co-transcriptional RNA folding dynamics to identify competing secondary structures that might interfere with terminator folding kinetics or impact termination activity. We found that structures extending beyond the core terminator stem are likely to increase terminator activity. By excluding terminators encoding such context-confounding elements, we were able to develop a linear sequence-function model that can be used to estimate termination efficiencies (r = 0.9, n = 31) better than models trained on all terminators (r = 0.67, n = 54). The resulting systematically measured collection of terminators should improve the engineering of synthetic genetic systems and also advance quantitative modeling of transcription termination. PMID:23511967

Models of ovarian cancer metastasis: Murine models

PubMed Central

Šale, Sanja; Orsulic, Sandra

2008-01-01

Mice have mainly been used in ovarian cancer research as immunodeficient hosts for cell lines derived from the primary tumors and ascites of ovarian cancer patients. These xenograft models have provided a valuable system for pre-clinical trials, however, the genetic complexity of human tumors has precluded the understanding of key events that drive metastatic dissemination. Recently developed immunocompetent, genetically defined mouse models of epithelial ovarian cancer represent significant improvements in the modeling of metastatic disease. PMID:19337569

Genetic and environmental melanoma models in fish

PubMed Central

Patton, E Elizabeth; Mitchell, David L; Nairn, Rodney S

2010-01-01

Experimental animal models are extremely valuable for the study of human diseases, especially those with underlying genetic components. The exploitation of various animal models, from fruitflies to mice, has led to major advances in our understanding of the etiologies of many diseases, including cancer. Cutaneous malignant melanoma is a form of cancer for which both environmental insult (i.e., UV) and hereditary predisposition are major causative factors. Fish melanoma models have been used in studies of both spontaneous and induced melanoma formation. Genetic hybrids between platyfish and swordtails, different species of the genus Xiphophorus, have been studied since the 1920s to identify genetic determinants of pigmentation and melanoma formation. Recently, transgenesis has been used to develop zebrafish and medaka models for melanoma research. This review will provide a historical perspective on the use of fish models in melanoma research, and an updated summary of current and prospective studies using these unique experimental systems. PMID:20230482

A portable expression resource for engineering cross-species genetic circuits and pathways

PubMed Central

Kushwaha, Manish; Salis, Howard M.

2015-01-01

Genetic circuits and metabolic pathways can be reengineered to allow organisms to process signals and manufacture useful chemicals. However, their functions currently rely on organism-specific regulatory parts, fragmenting synthetic biology and metabolic engineering into host-specific domains. To unify efforts, here we have engineered a cross-species expression resource that enables circuits and pathways to reuse the same genetic parts, while functioning similarly across diverse organisms. Our engineered system combines mixed feedback control loops and cross-species translation signals to autonomously self-regulate expression of an orthogonal polymerase without host-specific promoters, achieving nontoxic and tuneable gene expression in diverse Gram-positive and Gram-negative bacteria. Combining 50 characterized system variants with mechanistic modelling, we show how the cross-species expression resource's dynamics, capacity and toxicity are controlled by the control loops' architecture and feedback strengths. We also demonstrate one application of the resource by reusing the same genetic parts to express a biosynthesis pathway in both model and non-model hosts. PMID:26184393

Genetic algorithm based fuzzy control of spacecraft autonomous rendezvous

NASA Technical Reports Server (NTRS)

Karr, C. L.; Freeman, L. M.; Meredith, D. L.

1990-01-01

The U.S. Bureau of Mines is currently investigating ways to combine the control capabilities of fuzzy logic with the learning capabilities of genetic algorithms. Fuzzy logic allows for the uncertainty inherent in most control problems to be incorporated into conventional expert systems. Although fuzzy logic based expert systems have been used successfully for controlling a number of physical systems, the selection of acceptable fuzzy membership functions has generally been a subjective decision. High performance fuzzy membership functions for a fuzzy logic controller that manipulates a mathematical model simulating the autonomous rendezvous of spacecraft are learned using a genetic algorithm, a search technique based on the mechanics of natural genetics. The membership functions learned by the genetic algorithm provide for a more efficient fuzzy logic controller than membership functions selected by the authors for the rendezvous problem. Thus, genetic algorithms are potentially an effective and structured approach for learning fuzzy membership functions.

Advancing the understanding of autism disease mechanisms through genetics

PubMed Central

de la Torre-Ubieta, Luis; Won, Hyejung; Stein, Jason L; Geschwind, Daniel H

2016-01-01

Progress in understanding the genetic etiology of autism spectrum disorders (ASD) has fueled remarkable advances in our understanding of its potential neurobiological mechanisms. Yet, at the same time, these findings highlight extraordinary causal diversity and complexity at many levels ranging from molecules to circuits and emphasize the gaps in our current knowledge. Here we review current understanding of the genetic architecture of ASD and integrate genetic evidence, neuropathology and studies in model systems with how they inform mechanistic models of ASD pathophysiology. Despite the challenges, these advances provide a solid foundation for the development of rational, targeted molecular therapies. PMID:27050589

Striatal cholinergic dysfunction as a unifying theme in the pathophysiology of dystonia

PubMed Central

Jaunarajs, K.L. Eskow; Bonsi, P.; Chesselet, M.F.; Standaert, D.G.; Pisani, A.

2015-01-01

Dystonia is a movement disorder of both genetic and non-genetic causes, which typically results in twisted posturing due to abnormal muscle contraction. Evidence from dystonia patients and animal models of dystonia indicate a crucial role for the striatal cholinergic system in the pathophysiology of dystonia. In this review, we focus on striatal circuitry and the centrality of the acetylcholine system in the function of the basal ganglia in the control of voluntary movement and ultimately clinical manifestion of movement disorders. We consider the impact of cholinergic interneurons (ChIs) on dopamine-acetylcholine interactions and examine new evidence for impairment of ChIs in dysfunction of the motor systems producing dystonic movements, particularly in animal models. We have observed paradoxical excitation of ChIs in the presence of dopamine D2 receptor agonists and impairment of striatal synaptic plasticity in a mouse model of DYT1 dystonia, which are improved by administration of recently developed M1 receptor antagonists. These findings have been confirmed across multiple animal models of DYT1 dystonia and may represent a common endophenotype by which to investigate dystonia induced by other types of genetic and non-genetic causes and to investigate the potential effectiveness of pharmacotherapeutics and other strategies to improve dystonia. PMID:25697043

Inference of genetic network of Xenopus frog egg: improved genetic algorithm.

PubMed

Wu, Shinq-Jen; Chou, Chia-Hsien; Wu, Cheng-Tao; Lee, Tsu-Tian

2006-01-01

An improved genetic algorithm (IGA) is proposed to achieve S-system gene network modeling of Xenopus frog egg. Via the time-courses training datasets from Michaelis-Menten model, the optimal parameters are learned. The S-system can clearly describe activative and inhibitory interaction between genes as generating and consuming process. We concern the mitotic control in cell-cycle of Xenopus frog egg to realize cyclin-Cdc2 and Cdc25 for MPF activity. The proposed IGA can achieve global search with migration and keep the best chromosome with elitism operation. The generated gene regulatory networks can provide biological researchers for further experiments in Xenopus frog egg cell cycle control.

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

Conditions for success of engineered underdominance gene drive systems.

PubMed

Edgington, Matthew P; Alphey, Luke S

2017-10-07

Engineered underdominance is one of a number of different gene drive strategies that have been proposed for the genetic control of insect vectors of disease. Here we model a two-locus engineered underdominance based gene drive system that is based on the concept of mutually suppressing lethals. In such a system two genetic constructs are introduced, each possessing a lethal element and a suppressor of the lethal at the other locus. Specifically, we formulate and analyse a population genetics model of this system to assess when different combinations of release strategies (i.e. single or multiple releases of both sexes or males only) and genetic systems (i.e. bisex lethal or female-specific lethal elements and different strengths of suppressors) will give population replacement or fail to do so. We anticipate that results presented here will inform the future design of engineered underdominance gene drive systems as well as providing a point of reference regarding release strategies for those looking to test such a system. Our discussion is framed in the context of genetic control of insect vectors of disease. One of several serious threats in this context are Aedes aegypti mosquitoes as they are the primary vectors of dengue viruses. However, results are also applicable to Ae. aegypti as vectors of Zika, yellow fever and chikungunya viruses and also to the control of a number of other insect species and thereby of insect-vectored pathogens. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Illuminating Cancer Systems With Genetically-Engineered Mouse Models and Coupled Luciferase Reporters In Vivo

PubMed Central

Kocher, Brandon; Piwnica-Worms, David

2013-01-01

Bioluminescent imaging (BLI) is a powerful non-invasive tool that has dramatically accelerated the in vivo interrogation of cancer systems and longitudinal analysis of mouse models of cancer over the past decade. Various luciferase enzymes have been genetically engineered into mouse models (GEMMs) of cancer which permit investigation of cellular and molecular events associated with oncogenic transcription, post-transcriptional processing, protein-protein interactions, transformation and oncogene addiction in live cells and animals. Luciferase-coupled GEMMs ultimately serve as a non-invasive, repetitive, longitudinal, and physiological means by which cancer systems and therapeutic responses can be investigated accurately within the autochthonous context of a living animal. PMID:23585416

Evolving Ideas on the Origin and Evolution of Flowers: New Perspectives in the Genomic Era

PubMed Central

Chanderbali, Andre S.; Berger, Brent A.; Howarth, Dianella G.; Soltis, Pamela S.; Soltis, Douglas E.

2016-01-01

The origin of the flower was a key innovation in the history of complex organisms, dramatically altering Earth’s biota. Advances in phylogenetics, developmental genetics, and genomics during the past 25 years have substantially advanced our understanding of the evolution of flowers, yet crucial aspects of floral evolution remain, such as the series of genetic and morphological changes that gave rise to the first flowers; the factors enabling the origin of the pentamerous eudicot flower, which characterizes ∼70% of all extant angiosperm species; and the role of gene and genome duplications in facilitating floral innovations. A key early concept was the ABC model of floral organ specification, developed by Elliott Meyerowitz and Enrico Coen and based on two model systems, Arabidopsis thaliana and Antirrhinum majus. Yet it is now clear that these model systems are highly derived species, whose molecular genetic-developmental organization must be very different from that of ancestral, as well as early, angiosperms. In this article, we will discuss how new research approaches are illuminating the early events in floral evolution and the prospects for further progress. In particular, advancing the next generation of research in floral evolution will require the development of one or more functional model systems from among the basal angiosperms and basal eudicots. More broadly, we urge the development of “model clades” for genomic and evolutionary-developmental analyses, instead of the primary use of single “model organisms.” We predict that new evolutionary models will soon emerge as genetic/genomic models, providing unprecedented new insights into floral evolution. PMID:27053123

Genetic variation in social mammals: the marmot model.

PubMed

Schwartz, O A; Armitage, K B

1980-02-08

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

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

PubMed

Bourret, A; Garant, D

2017-03-01

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

The Genetics of Urinary Tract Infections and the Innate Defense of the Kidney and Urinary tract

PubMed Central

Ambite, Ines; Rydstrom, Gustav; Schwaderer, Andrew L.; Hains, David S.

2015-01-01

The urinary tract is a sterile organ system. Urinary tract infections (UTIs) are common and often serious infections. Research has focused on uropathogen, environment, and host factors leading to UTI pathogenesis. A growing body of evidence exists implicating genetic factors that can contribute to UTI risks. In this review, we highlight genetic variations in aspects of the innate immune system critical to the host response to uropathogens. This overview includes genetic variations in pattern recognition receptor molecules, chemokines/cytokines, and neutrophil activation. We also comprehensively cover murine knockout models of UTI, genetic variations involved in renal scarring as a result of ascending UTIs, and asymptomatic bacteriuria. PMID:27617139

Animal models of neoplastic development.

PubMed

Pitot, H C

2001-01-01

The basic animal model for neoplastic development used by regulatory agencies is the two-year chronic bioassay developed more than 30 years ago and based on the presumed mechanism of action of a few potential chemical carcinogens. Since that time, a variety of other model carcinogenic systems have been developed, usually involving shorter duration, single organ endpoints, multistage models, and those in genetically-engineered mice. The chronic bioassay is still the "gold standard" of regulatory agencies despite a number of deficiencies, while in this country the use of shorter term assays based on single organ endpoints has not been popular. The multistage model of carcinogenesis in mouse epidermis actually preceded the development of the chronic two-year bioassay, but it was not until multistage models in other organ systems were developed that the usefulness of such systems became apparent. Recently, several genetically-engineered mouse lines involving mutations in proto-oncogenes and tumour suppressor genes have been proposed as additional model systems for use in regulatory decisions. It is likely that a combination of several of these model systems may be most useful in both practical and basic applications of cancer prevention and therapy.

A next-generation dual-recombinase system for time and host specific targeting of pancreatic cancer

PubMed Central

Schachtler, Christina; Zukowska, Magdalena; Eser, Stefan; Feyerabend, Thorsten B.; Paul, Mariel C.; Eser, Philipp; Klein, Sabine; Lowy, Andrew M.; Banerjee, Ruby; Yang, Fangtang; Lee, Chang-Lung; Moding, Everett J.; Kirsch, David G.; Scheideler, Angelika; Alessi, Dario R.; Varela, Ignacio; Bradley, Allan; Kind, Alexander; Schnieke, Angelika E.; Rodewald, Hans-Reimer; Rad, Roland; Schmid, Roland M.; Schneider, Günter; Saur, Dieter

2014-01-01

Genetically engineered mouse models (GEMMs) have dramatically improved our understanding of tumor evolution and therapeutic resistance. However, sequential genetic manipulation of gene expression and targeting of the host is almost impossible using conventional Cre-loxP–based models. We have developed an inducible dual-recombinase system by combining flippase-FRT (Flp-FRT) and Cre-loxP recombination technologies to improve GEMMs of pancreatic cancer. This enables investigation of multistep carcinogenesis, genetic manipulation of tumor subpopulations (such as cancer stem cells), selective targeting of the tumor microenvironment and genetic validation of therapeutic targets in autochthonous tumors on a genome-wide scale. As a proof of concept, we performed tumor cell–autonomous and nonautonomous targeting, recapitulated hallmarks of human multistep carcinogenesis, validated genetic therapy by 3-phosphoinositide-dependent protein kinase inactivation as well as cancer cell depletion and show that mast cells in the tumor microenvironment, which had been thought to be key oncogenic players, are dispensable for tumor formation. PMID:25326799

A next-generation dual-recombinase system for time- and host-specific targeting of pancreatic cancer.

PubMed

Schönhuber, Nina; Seidler, Barbara; Schuck, Kathleen; Veltkamp, Christian; Schachtler, Christina; Zukowska, Magdalena; Eser, Stefan; Feyerabend, Thorsten B; Paul, Mariel C; Eser, Philipp; Klein, Sabine; Lowy, Andrew M; Banerjee, Ruby; Yang, Fangtang; Lee, Chang-Lung; Moding, Everett J; Kirsch, David G; Scheideler, Angelika; Alessi, Dario R; Varela, Ignacio; Bradley, Allan; Kind, Alexander; Schnieke, Angelika E; Rodewald, Hans-Reimer; Rad, Roland; Schmid, Roland M; Schneider, Günter; Saur, Dieter

2014-11-01

Genetically engineered mouse models (GEMMs) have dramatically improved our understanding of tumor evolution and therapeutic resistance. However, sequential genetic manipulation of gene expression and targeting of the host is almost impossible using conventional Cre-loxP-based models. We have developed an inducible dual-recombinase system by combining flippase-FRT (Flp-FRT) and Cre-loxP recombination technologies to improve GEMMs of pancreatic cancer. This enables investigation of multistep carcinogenesis, genetic manipulation of tumor subpopulations (such as cancer stem cells), selective targeting of the tumor microenvironment and genetic validation of therapeutic targets in autochthonous tumors on a genome-wide scale. As a proof of concept, we performed tumor cell-autonomous and nonautonomous targeting, recapitulated hallmarks of human multistep carcinogenesis, validated genetic therapy by 3-phosphoinositide-dependent protein kinase inactivation as well as cancer cell depletion and show that mast cells in the tumor microenvironment, which had been thought to be key oncogenic players, are dispensable for tumor formation.

CMCpy: Genetic Code-Message Coevolution Models in Python

PubMed Central

Becich, Peter J.; Stark, Brian P.; Bhat, Harish S.; Ardell, David H.

2013-01-01

Code-message coevolution (CMC) models represent coevolution of a genetic code and a population of protein-coding genes (“messages”). Formally, CMC models are sets of quasispecies coupled together for fitness through a shared genetic code. Although CMC models display plausible explanations for the origin of multiple genetic code traits by natural selection, useful modern implementations of CMC models are not currently available. To meet this need we present CMCpy, an object-oriented Python API and command-line executable front-end that can reproduce all published results of CMC models. CMCpy implements multiple solvers for leading eigenpairs of quasispecies models. We also present novel analytical results that extend and generalize applications of perturbation theory to quasispecies models and pioneer the application of a homotopy method for quasispecies with non-unique maximally fit genotypes. Our results therefore facilitate the computational and analytical study of a variety of evolutionary systems. CMCpy is free open-source software available from http://pypi.python.org/pypi/CMCpy/. PMID:23532367

A Computational Workflow for the Automated Generation of Models of Genetic Designs.

PubMed

Misirli, Göksel; Nguyen, Tramy; McLaughlin, James Alastair; Vaidyanathan, Prashant; Jones, Timothy S; Densmore, Douglas; Myers, Chris; Wipat, Anil

2018-06-05

Computational models are essential to engineer predictable biological systems and to scale up this process for complex systems. Computational modeling often requires expert knowledge and data to build models. Clearly, manual creation of models is not scalable for large designs. Despite several automated model construction approaches, computational methodologies to bridge knowledge in design repositories and the process of creating computational models have still not been established. This paper describes a workflow for automatic generation of computational models of genetic circuits from data stored in design repositories using existing standards. This workflow leverages the software tool SBOLDesigner to build structural models that are then enriched by the Virtual Parts Repository API using Systems Biology Open Language (SBOL) data fetched from the SynBioHub design repository. The iBioSim software tool is then utilized to convert this SBOL description into a computational model encoded using the Systems Biology Markup Language (SBML). Finally, this SBML model can be simulated using a variety of methods. This workflow provides synthetic biologists with easy to use tools to create predictable biological systems, hiding away the complexity of building computational models. This approach can further be incorporated into other computational workflows for design automation.

Genetically engineered mouse models for studying inflammatory bowel disease.

PubMed

Mizoguchi, Atsushi; Takeuchi, Takahito; Himuro, Hidetomo; Okada, Toshiyuki; Mizoguchi, Emiko

2016-01-01

Inflammatory bowel disease (IBD) is a chronic intestinal inflammatory condition that is mediated by very complex mechanisms controlled by genetic, immune, and environmental factors. More than 74 kinds of genetically engineered mouse strains have been established since 1993 for studying IBD. Although mouse models cannot fully reflect human IBD, they have provided significant contributions for not only understanding the mechanism, but also developing new therapeutic means for IBD. Indeed, 20 kinds of genetically engineered mouse models carry the susceptibility genes identified in human IBD, and the functions of some other IBD susceptibility genes have also been dissected out using mouse models. Cutting-edge technologies such as cell-specific and inducible knockout systems, which were recently employed to mouse IBD models, have further enhanced the ability of investigators to provide important and unexpected rationales for developing new therapeutic strategies for IBD. In this review article, we briefly introduce 74 kinds of genetically engineered mouse models that spontaneously develop intestinal inflammation. Copyright © 2015 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Model of continual metabolism species for estimating stability of CELSS and natural ecosystems

NASA Astrophysics Data System (ADS)

Bartsev, S. I.

Estimation of stability range of natural and man-made ecosystems is necessary for effective control of them However traditional ecological models usually underestimate stability of real ecosystems It takes place due to the usage of fixed stoichiometry model of metabolism The objective is in creating theoretical and mathematical models for adequate description of both man-made and natural ecological systems A concept of genetically fixed but metabolically flexible species is considered in the paper According to the concept the total flow of matter through ecological system is supported at almost constant level depending on energy income by flexibility of metabolic organization of genetic species It is shown introducing continual metabolism species extends the range of stability making its estimation more adequate to real ecological systems

Human Inspired Self-developmental Model of Neural Network (HIM): Introducing Content/Form Computing

NASA Astrophysics Data System (ADS)

Krajíček, Jiří

This paper presents cross-disciplinary research between medical/psychological evidence on human abilities and informatics needs to update current models in computer science to support alternative methods for computation and communication. In [10] we have already proposed hypothesis introducing concept of human information model (HIM) as cooperative system. Here we continue on HIM design in detail. In our design, first we introduce Content/Form computing system which is new principle of present methods in evolutionary computing (genetic algorithms, genetic programming). Then we apply this system on HIM (type of artificial neural network) model as basic network self-developmental paradigm. Main inspiration of our natural/human design comes from well known concept of artificial neural networks, medical/psychological evidence and Sheldrake theory of "Nature as Alive" [22].

Simulating Drosophila Genetics with the Computer.

ERIC Educational Resources Information Center

Small, James W., Jr.; Edwards, Kathryn L.

1979-01-01

Presents some techniques developed to help improve student understanding of Mendelian principles through the use of a computer simulation model by the genetic system of the fruit fly. Includes discussion and evaluation of this computer assisted program. (MA)

The Sphagnome Project: enabling ecological and evolutionary insights through a genus-level sequencing project

DOE PAGES

Weston, David J.; Turetsky, Merritt R.; Johnson, Matthew G.; ...

2017-10-27

Considerable progress has been made in ecological and evolutionary genetics with studies demonstrating how genes underlying plant and microbial traits can influence adaptation and even ‘extend’ to influence community structure and ecosystem level processes. The progress in this area is limited to model systems with deep genetic and genomic resources that often have negligible ecological impact or interest. Therefore, important linkages between genetic adaptations and their consequences at organismal and ecological scales are often lacking. We introduce the Sphagnome Project, which incorporates genomics into a long-running history of Sphagnum research that has documented unparalleled contributions to peatland ecology, carbon sequestration,more » biogeochemistry, microbiome research, niche construction, and ecosystem engineering. The Sphagnome Project encompasses a genus-level sequencing effort that represents a new type of model system driven not only by genetic tractability, but by ecologically relevant questions and hypotheses.« less

Evolutionary genetics of plant adaptation.

PubMed

Anderson, Jill T; Willis, John H; Mitchell-Olds, Thomas

2011-07-01

Plants provide unique opportunities to study the mechanistic basis and evolutionary processes of adaptation to diverse environmental conditions. Complementary laboratory and field experiments are important for testing hypotheses reflecting long-term ecological and evolutionary history. For example, these approaches can infer whether local adaptation results from genetic tradeoffs (antagonistic pleiotropy), where native alleles are best adapted to local conditions, or if local adaptation is caused by conditional neutrality at many loci, where alleles show fitness differences in one environment, but not in a contrasting environment. Ecological genetics in natural populations of perennial or outcrossing plants can also differ substantially from model systems. In this review of the evolutionary genetics of plant adaptation, we emphasize the importance of field studies for understanding the evolutionary dynamics of model and nonmodel systems, highlight a key life history trait (flowering time) and discuss emerging conservation issues. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Sphagnome Project: enabling ecological and evolutionary insights through a genus-level sequencing project

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

Weston, David J.; Turetsky, Merritt R.; Johnson, Matthew G.

Considerable progress has been made in ecological and evolutionary genetics with studies demonstrating how genes underlying plant and microbial traits can influence adaptation and even ‘extend’ to influence community structure and ecosystem level processes. The progress in this area is limited to model systems with deep genetic and genomic resources that often have negligible ecological impact or interest. Therefore, important linkages between genetic adaptations and their consequences at organismal and ecological scales are often lacking. We introduce the Sphagnome Project, which incorporates genomics into a long-running history of Sphagnum research that has documented unparalleled contributions to peatland ecology, carbon sequestration,more » biogeochemistry, microbiome research, niche construction, and ecosystem engineering. The Sphagnome Project encompasses a genus-level sequencing effort that represents a new type of model system driven not only by genetic tractability, but by ecologically relevant questions and hypotheses.« less

The Sphagnome Project: enabling ecological and evolutionary insights through a genus-level sequencing project.

PubMed

Weston, David J; Turetsky, Merritt R; Johnson, Matthew G; Granath, Gustaf; Lindo, Zoë; Belyea, Lisa R; Rice, Steven K; Hanson, David T; Engelhardt, Katharina A M; Schmutz, Jeremy; Dorrepaal, Ellen; Euskirchen, Eugénie S; Stenøien, Hans K; Szövényi, Péter; Jackson, Michelle; Piatkowski, Bryan T; Muchero, Wellington; Norby, Richard J; Kostka, Joel E; Glass, Jennifer B; Rydin, Håkan; Limpens, Juul; Tuittila, Eeva-Stiina; Ullrich, Kristian K; Carrell, Alyssa; Benscoter, Brian W; Chen, Jin-Gui; Oke, Tobi A; Nilsson, Mats B; Ranjan, Priya; Jacobson, Daniel; Lilleskov, Erik A; Clymo, R S; Shaw, A Jonathan

2018-01-01

Considerable progress has been made in ecological and evolutionary genetics with studies demonstrating how genes underlying plant and microbial traits can influence adaptation and even 'extend' to influence community structure and ecosystem level processes. Progress in this area is limited to model systems with deep genetic and genomic resources that often have negligible ecological impact or interest. Thus, important linkages between genetic adaptations and their consequences at organismal and ecological scales are often lacking. Here we introduce the Sphagnome Project, which incorporates genomics into a long-running history of Sphagnum research that has documented unparalleled contributions to peatland ecology, carbon sequestration, biogeochemistry, microbiome research, niche construction, and ecosystem engineering. The Sphagnome Project encompasses a genus-level sequencing effort that represents a new type of model system driven not only by genetic tractability, but by ecologically relevant questions and hypotheses. © 2017 UT-Battelle New Phytologist © 2017 New Phytologist Trust.

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.

Integrative systems modeling and multi-objective optimization

EPA Science Inventory

This presentation presents a number of algorithms, tools, and methods for utilizing multi-objective optimization within integrated systems modeling frameworks. We first present innovative methods using a genetic algorithm to optimally calibrate the VELMA and SWAT ecohydrological ...

Brachypodium distachyon as a Genetic Model System.

PubMed

Kellogg, Elizabeth A

2015-01-01

Brachypodium distachyon has emerged as a powerful model system for studying the genetics of flowering plants. Originally chosen for its phylogenetic proximity to the large-genome cereal crops wheat and barley, it is proving to be useful for more than simply providing markers for comparative mapping. Studies in B. distachyon have provided new insight into the structure and physiology of plant cell walls, the development and chemical composition of endosperm, and the genetic basis for cold tolerance. Recent work on auxin transport has uncovered mechanisms that apply to all angiosperms other than Arabidopsis. In addition to the areas in which it is currently used, B. distachyon is uniquely suited for studies of floral development, vein patterning, the controls of the perennial versus annual habit, and genome organization.

Neural-genetic synthesis for state-space controllers based on linear quadratic regulator design for eigenstructure assignment.

PubMed

da Fonseca Neto, João Viana; Abreu, Ivanildo Silva; da Silva, Fábio Nogueira

2010-04-01

Toward the synthesis of state-space controllers, a neural-genetic model based on the linear quadratic regulator design for the eigenstructure assignment of multivariable dynamic systems is presented. The neural-genetic model represents a fusion of a genetic algorithm and a recurrent neural network (RNN) to perform the selection of the weighting matrices and the algebraic Riccati equation solution, respectively. A fourth-order electric circuit model is used to evaluate the convergence of the computational intelligence paradigms and the control design method performance. The genetic search convergence evaluation is performed in terms of the fitness function statistics and the RNN convergence, which is evaluated by landscapes of the energy and norm, as a function of the parameter deviations. The control problem solution is evaluated in the time and frequency domains by the impulse response, singular values, and modal analysis.

An integrated approach to characterize genetic interaction networks in yeast metabolism

PubMed Central

Szappanos, Balázs; Kovács, Károly; Szamecz, Béla; Honti, Frantisek; Costanzo, Michael; Baryshnikova, Anastasia; Gelius-Dietrich, Gabriel; Lercher, Martin J.; Jelasity, Márk; Myers, Chad L.; Andrews, Brenda J.; Boone, Charles; Oliver, Stephen G.; Pál, Csaba; Papp, Balázs

2011-01-01

Intense experimental and theoretical efforts have been made to globally map genetic interactions, yet we still do not understand how gene-gene interactions arise from the operation of biomolecular networks. To bridge the gap between empirical and computational studies, we: i) quantitatively measure genetic interactions between ~185,000 metabolic gene pairs in Saccharomyces cerevisiae, ii) superpose the data on a detailed systems biology model of metabolism, and iii) introduce a machine-learning method to reconcile empirical interaction data with model predictions. We systematically investigate the relative impacts of functional modularity and metabolic flux coupling on the distribution of negative and positive genetic interactions. We also provide a mechanistic explanation for the link between the degree of genetic interaction, pleiotropy, and gene dispensability. Last, we demonstrate the feasibility of automated metabolic model refinement by correcting misannotations in NAD biosynthesis and confirming them by in vivo experiments. PMID:21623372

Mining disease fingerprints from within genetic pathways.

PubMed

Nabhan, Ahmed Ragab; Sarkar, Indra Neil

2012-01-01

Mining biological networks can be an effective means to uncover system level knowledge out of micro level associations, such as encapsulated in genetic pathways. Analysis of human disease genetic pathways can lead to the identification of major mechanisms that may underlie disorders at an abstract functional level. The focus of this study was to develop an approach for structural pattern analysis and classification of genetic pathways of diseases. A probabilistic model was developed to capture characteristic components ('fingerprints') of functionally annotated pathways. A probability estimation procedure of this model searched for fingerprints in each disease pathway while improving probability estimates of model parameters. The approach was evaluated on data from the Kyoto Encyclopedia of Genes and Genomes (consisting of 56 pathways across seven disease categories). Based on the achieved average classification accuracy of up to ~77%, the findings suggest that these fingerprints may be used for classification and discovery of genetic pathways.

Mining Disease Fingerprints From Within Genetic Pathways

PubMed Central

Nabhan, Ahmed Ragab; Sarkar, Indra Neil

2012-01-01

Mining biological networks can be an effective means to uncover system level knowledge out of micro level associations, such as encapsulated in genetic pathways. Analysis of human disease genetic pathways can lead to the identification of major mechanisms that may underlie disorders at an abstract functional level. The focus of this study was to develop an approach for structural pattern analysis and classification of genetic pathways of diseases. A probabilistic model was developed to capture characteristic components (‘fingerprints’) of functionally annotated pathways. A probability estimation procedure of this model searched for fingerprints in each disease pathway while improving probability estimates of model parameters. The approach was evaluated on data from the Kyoto Encyclopedia of Genes and Genomes (consisting of 56 pathways across seven disease categories). Based on the achieved average classification accuracy of up to ∼77%, the findings suggest that these fingerprints may be used for classification and discovery of genetic pathways. PMID:23304411

The zebrafish eye—a paradigm for investigating human ocular genetics

PubMed Central

Richardson, R; Tracey-White, D; Webster, A; Moosajee, M

2017-01-01

Although human epidemiological and genetic studies are essential to elucidate the aetiology of normal and aberrant ocular development, animal models have provided us with an understanding of the pathogenesis of multiple developmental ocular malformations. Zebrafish eye development displays in depth molecular complexity and stringent spatiotemporal regulation that incorporates developmental contributions of the surface ectoderm, neuroectoderm and head mesenchyme, similar to that seen in humans. For this reason, and due to its genetic tractability, external fertilisation, and early optical clarity, the zebrafish has become an invaluable vertebrate system to investigate human ocular development and disease. Recently, zebrafish have been at the leading edge of preclinical therapy development, with their amenability to genetic manipulation facilitating the generation of robust ocular disease models required for large-scale genetic and drug screening programmes. This review presents an overview of human and zebrafish ocular development, genetic methodologies employed for zebrafish mutagenesis, relevant models of ocular disease, and finally therapeutic approaches, which may have translational leads in the future. PMID:27612182

Mouse Models for Drug Discovery. Can New Tools and Technology Improve Translational Power?

PubMed

Zuberi, Aamir; Lutz, Cathleen

2016-12-01

The use of mouse models in biomedical research and preclinical drug evaluation is on the rise. The advent of new molecular genome-altering technologies such as CRISPR/Cas9 allows for genetic mutations to be introduced into the germ line of a mouse faster and less expensively than previous methods. In addition, the rapid progress in the development and use of somatic transgenesis using viral vectors, as well as manipulations of gene expression with siRNAs and antisense oligonucleotides, allow for even greater exploration into genomics and systems biology. These technological advances come at a time when cost reductions in genome sequencing have led to the identification of pathogenic mutations in patient populations, providing unprecedented opportunities in the use of mice to model human disease. The ease of genetic engineering in mice also offers a potential paradigm shift in resource sharing and the speed by which models are made available in the public domain. Predictively, the knowledge alone that a model can be quickly remade will provide relief to resources encumbered by licensing and Material Transfer Agreements. For decades, mouse strains have provided an exquisite experimental tool to study the pathophysiology of the disease and assess therapeutic options in a genetically defined system. However, a major limitation of the mouse has been the limited genetic diversity associated with common laboratory mice. This has been overcome with the recent development of the Collaborative Cross and Diversity Outbred mice. These strains provide new tools capable of replicating genetic diversity to that approaching the diversity found in human populations. The Collaborative Cross and Diversity Outbred strains thus provide a means to observe and characterize toxicity or efficacy of new therapeutic drugs for a given population. The combination of traditional and contemporary mouse genome editing tools, along with the addition of genetic diversity in new modeling systems, are synergistic and serve to make the mouse a better model for biomedical research, enhancing the potential for preclinical drug discovery and personalized medicine. © The Author 2016. Published by Oxford University Press.

Genetic and Genomic Toolbox of Zea mays

PubMed Central

Nannas, Natalie J.; Dawe, R. Kelly

2015-01-01

Maize has a long history of genetic and genomic tool development and is considered one of the most accessible higher plant systems. With a fully sequenced genome, a suite of cytogenetic tools, methods for both forward and reverse genetics, and characterized phenotype markers, maize is amenable to studying questions beyond plant biology. Major discoveries in the areas of transposons, imprinting, and chromosome biology came from work in maize. Moving forward in the post-genomic era, this classic model system will continue to be at the forefront of basic biological study. In this review, we outline the basics of working with maize and describe its rich genetic toolbox. PMID:25740912

Males and Females Contribute Unequally to Offspring Genetic Diversity in the Polygynandrous Mating System of Wild Boar

PubMed Central

Pérez-González, Javier; Costa, Vânia; Santos, Pedro; Slate, Jon; Carranza, Juan; Fernández-Llario, Pedro; Zsolnai, Attila; Monteiro, Nuno M.; Anton, István; Buzgó, József; Varga, Gyula; Beja-Pereira, Albano

2014-01-01

The maintenance of genetic diversity across generations depends on both the number of reproducing males and females. Variance in reproductive success, multiple paternity and litter size can all affect the relative contributions of male and female parents to genetic variation of progeny. The mating system of the wild boar (Sus scrofa) has been described as polygynous, although evidence of multiple paternity in litters has been found. Using 14 microsatellite markers, we evaluated the contribution of males and females to genetic variation in the next generation in independent wild boar populations from the Iberian Peninsula and Hungary. Genetic contributions of males and females were obtained by distinguishing the paternal and maternal genetic component inherited by the progeny. We found that the paternally inherited genetic component of progeny was more diverse than the maternally inherited component. Simulations showed that this finding might be due to a sampling bias. However, after controlling for the bias by fitting both the genetic diversity in the adult population and the number of reproductive individuals in the models, paternally inherited genotypes remained more diverse than those inherited maternally. Our results suggest new insights into how promiscuous mating systems can help maintain genetic variation. PMID:25541986

Modifiers and mechanisms of multi-system polyglutamine neurodegenerative disorders: lessons from fly models.

PubMed

Mallik, Moushami; Lakhotia, Subhash C

2010-12-01

Polyglutamine (polyQ) diseases, resulting from a dynamic expansion of glutamine repeats in a polypeptide, are a class of genetically inherited late onset neurodegenerative disorders which, despite expression of the mutated gene widely in brain and other tissues, affect defined subpopulations of neurons in a disease-specific manner. We briefly review the different polyQ-expansion-induced neurodegenerative disorders and the advantages of modelling them in Drosophila. Studies using the fly models have successfully identified a variety of genetic modifiers and have helped in understanding some of the molecular events that follow expression of the abnormal polyQ proteins. Expression of the mutant polyQ proteins causes, as a consequence of intra-cellular and inter-cellular networking, mis-regulation at multiple steps like transcriptional and posttranscriptional regulations, cell signalling, protein quality control systems (protein folding and degradation networks), axonal transport machinery etc., in the sensitive neurons, resulting ultimately in their death. The diversity of genetic modifiers of polyQ toxicity identified through extensive genetic screens in fly and other models clearly reflects a complex network effect of the presence of the mutated protein. Such network effects pose a major challenge for therapeutic applications.

Systematic documentation and analysis of human genetic variation in hemoglobinopathies using the microattribution approach.

PubMed

Giardine, Belinda; Borg, Joseph; Higgs, Douglas R; Peterson, Kenneth R; Philipsen, Sjaak; Maglott, Donna; Singleton, Belinda K; Anstee, David J; Basak, A Nazli; Clark, Barnaby; Costa, Flavia C; Faustino, Paula; Fedosyuk, Halyna; Felice, Alex E; Francina, Alain; Galanello, Renzo; Gallivan, Monica V E; Georgitsi, Marianthi; Gibbons, Richard J; Giordano, Piero C; Harteveld, Cornelis L; Hoyer, James D; Jarvis, Martin; Joly, Philippe; Kanavakis, Emmanuel; Kollia, Panagoula; Menzel, Stephan; Miller, Webb; Moradkhani, Kamran; Old, John; Papachatzopoulou, Adamantia; Papadakis, Manoussos N; Papadopoulos, Petros; Pavlovic, Sonja; Perseu, Lucia; Radmilovic, Milena; Riemer, Cathy; Satta, Stefania; Schrijver, Iris; Stojiljkovic, Maja; Thein, Swee Lay; Traeger-Synodinos, Jan; Tully, Ray; Wada, Takahito; Waye, John S; Wiemann, Claudia; Zukic, Branka; Chui, David H K; Wajcman, Henri; Hardison, Ross C; Patrinos, George P

2011-03-20

We developed a series of interrelated locus-specific databases to store all published and unpublished genetic variation related to hemoglobinopathies and thalassemia and implemented microattribution to encourage submission of unpublished observations of genetic variation to these public repositories. A total of 1,941 unique genetic variants in 37 genes, encoding globins and other erythroid proteins, are currently documented in these databases, with reciprocal attribution of microcitations to data contributors. Our project provides the first example of implementing microattribution to incentivise submission of all known genetic variation in a defined system. It has demonstrably increased the reporting of human variants, leading to a comprehensive online resource for systematically describing human genetic variation in the globin genes and other genes contributing to hemoglobinopathies and thalassemias. The principles established here will serve as a model for other systems and for the analysis of other common and/or complex human genetic diseases.

FITPOP, a heuristic simulation model of population dynamics and genetics with special reference to fisheries

USGS Publications Warehouse

McKenna, James E.

2000-01-01

Although, perceiving genetic differences and their effects on fish population dynamics is difficult, simulation models offer a means to explore and illustrate these effects. I partitioned the intrinsic rate of increase parameter of a simple logistic-competition model into three components, allowing specification of effects of relative differences in fitness and mortality, as well as finite rate of increase. This model was placed into an interactive, stochastic environment to allow easy manipulation of model parameters (FITPOP). Simulation results illustrated the effects of subtle differences in genetic and population parameters on total population size, overall fitness, and sensitivity of the system to variability. Several consequences of mixing genetically distinct populations were illustrated. For example, behaviors such as depression of population size after initial introgression and extirpation of native stocks due to continuous stocking of genetically inferior fish were reproduced. It also was shown that carrying capacity relative to the amount of stocking had an important influence on population dynamics. Uncertainty associated with parameter estimates reduced confidence in model projections. The FITPOP model provided a simple tool to explore population dynamics, which may assist in formulating management strategies and identifying research needs.

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.

The long-term evolution of multilocus traits under frequency-dependent disruptive selection.

PubMed

van Doorn, G Sander; Dieckmann, Ulf

2006-11-01

Frequency-dependent disruptive selection is widely recognized as an important source of genetic variation. Its evolutionary consequences have been extensively studied using phenotypic evolutionary models, based on quantitative genetics, game theory, or adaptive dynamics. However, the genetic assumptions underlying these approaches are highly idealized and, even worse, predict different consequences of frequency-dependent disruptive selection. Population genetic models, by contrast, enable genotypic evolutionary models, but traditionally assume constant fitness values. Only a minority of these models thus addresses frequency-dependent selection, and only a few of these do so in a multilocus context. An inherent limitation of these remaining studies is that they only investigate the short-term maintenance of genetic variation. Consequently, the long-term evolution of multilocus characters under frequency-dependent disruptive selection remains poorly understood. We aim to bridge this gap between phenotypic and genotypic models by studying a multilocus version of Levene's soft-selection model. Individual-based simulations and deterministic approximations based on adaptive dynamics theory provide insights into the underlying evolutionary dynamics. Our analysis uncovers a general pattern of polymorphism formation and collapse, likely to apply to a wide variety of genetic systems: after convergence to a fitness minimum and the subsequent establishment of genetic polymorphism at multiple loci, genetic variation becomes increasingly concentrated on a few loci, until eventually only a single polymorphic locus remains. This evolutionary process combines features observed in quantitative genetics and adaptive dynamics models, and it can be explained as a consequence of changes in the selection regime that are inherent to frequency-dependent disruptive selection. Our findings demonstrate that the potential of frequency-dependent disruptive selection to maintain polygenic variation is considerably smaller than previously expected.

Polygamy and an absence of fine-scale structure in Dendroctonus ponderosae (Hopk.) (Coleoptera: Curcilionidae) confirmed using molecular markers

PubMed Central

Janes, J K; Roe, A D; Rice, A V; Gorrell, J C; Coltman, D W; Langor, D W; Sperling, F A H

2016-01-01

An understanding of mating systems and fine-scale spatial genetic structure is required to effectively manage forest pest species such as Dendroctonus ponderosae (mountain pine beetle). Here we used genome-wide single-nucleotide polymorphisms to assess the fine-scale genetic structure and mating system of D. ponderosae collected from a single stand in Alberta, Canada. Fine-scale spatial genetic structure was absent within the stand and the majority of genetic variation was best explained at the individual level. Relatedness estimates support previous reports of pre-emergence mating. Parentage assignment tests indicate that a polygamous mating system better explains the relationships among individuals within a gallery than the previously reported female monogamous/male polygynous system. Furthermore, there is some evidence to suggest that females may exploit the galleries of other females, at least under epidemic conditions. Our results suggest that current management models are likely to be effective across large geographic areas based on the absence of fine-scale genetic structure. PMID:26286666

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

PubMed Central

Hill, Kristine; Porco, Silvana; Lobet, Guillaume; Zappala, Susan; Mooney, Sacha; Draye, Xavier; Bennett, Malcolm J.

2013-01-01

Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment. PMID:24143806

An Advanced Preclinical Mouse Model for Acute Myeloid Leukemia Using Patients' Cells of Various Genetic Subgroups and In Vivo Bioluminescence Imaging

PubMed Central

Vick, Binje; Rothenberg, Maja; Sandhöfer, Nadine; Carlet, Michela; Finkenzeller, Cornelia; Krupka, Christina; Grunert, Michaela; Trumpp, Andreas; Corbacioglu, Selim; Ebinger, Martin; André, Maya C.; Hiddemann, Wolfgang; Schneider, Stephanie; Subklewe, Marion; Metzeler, Klaus H.; Spiekermann, Karsten; Jeremias, Irmela

2015-01-01

Acute myeloid leukemia (AML) is a clinically and molecularly heterogeneous disease with poor outcome. Adequate model systems are required for preclinical studies to improve understanding of AML biology and to develop novel, rational treatment approaches. Xenografts in immunodeficient mice allow performing functional studies on patient-derived AML cells. We have established an improved model system that integrates serial retransplantation of patient-derived xenograft (PDX) cells in mice, genetic manipulation by lentiviral transduction, and essential quality controls by immunophenotyping and targeted resequencing of driver genes. 17/29 samples showed primary engraftment, 10/17 samples could be retransplanted and some of them allowed virtually indefinite serial transplantation. 5/6 samples were successfully transduced using lentiviruses. Neither serial transplantation nor genetic engineering markedly altered sample characteristics analyzed. Transgene expression was stable in PDX AML cells. Example given, recombinant luciferase enabled bioluminescence in vivo imaging and highly sensitive and reliable disease monitoring; imaging visualized minimal disease at 1 PDX cell in 10000 mouse bone marrow cells and facilitated quantifying leukemia initiating cells. We conclude that serial expansion, genetic engineering and imaging represent valuable tools to improve the individualized xenograft mouse model of AML. Prospectively, these advancements enable repetitive, clinically relevant studies on AML biology and preclinical treatment trials on genetically defined and heterogeneous subgroups. PMID:25793878

Using Genetic Mouse Models to Gain Insight into Glaucoma: Past Results and Future Possibilities

PubMed Central

Fernandes, Kimberly A.; Harder, Jeffrey M.; Williams, Pete A.; Rausch, Rebecca L.; Kiernan, Amy E.; Nair, K. Saidas; Anderson, Michael G.; John, Simon W.; Howell, Gareth R.; Libby, Richard T.

2015-01-01

While all forms of glaucoma are characterized by a specific pattern of retinal ganglion cell death, they are clinically divided into several distinct subclasses, including normal tension glaucoma, primary open angle glaucoma, congenital glaucoma, and secondary glaucoma. For each type of glaucoma there are likely numerous molecular pathways that control susceptibility to the disease. Given this complexity, a single animal model will never precisely model all aspects of all the different types of human glaucoma. Therefore, multiple animal models have been utilized to study glaucoma but more are needed. Because of the powerful genetic tools available to use in the laboratory mouse, it has proven to be a highly useful mammalian system for studying the pathophysiology of human disease. The similarity between human and mouse eyes coupled with the ability to use a combination of advanced cell biological and genetic tools in mice have led to a large increase in the number of studies using mice to model specific glaucoma phenotypes. Over the last decade, numerous new mouse models and genetic tools have emerged, providing important insight into the cell biology and genetics of glaucoma. In this review, we describe available mouse genetic models that can be used to study glaucoma-relevant disease/pathobiology. Furthermore, we discuss how these models have been used to gain insights into ocular hypertension (a major risk factor for glaucoma) and glaucomatous retinal ganglion cell death. Finally, the potential for developing new mouse models and using advanced genetic tools and resources for studying glaucoma are discussed. PMID:26116903

Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States

NASA Technical Reports Server (NTRS)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter M.; Brenner, Martin J.

2017-01-01

This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12× reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design.

Genetic quality and sexual selection: an integrated framework for good genes and compatible genes.

PubMed

Neff, Bryan D; Pitcher, Trevor E

2005-01-01

Why are females so choosy when it comes to mating? This question has puzzled and marveled evolutionary and behavioral ecologists for decades. In mating systems in which males provide direct benefits to the female or her offspring, such as food or shelter, the answer seems straightforward--females should prefer to mate with males that are able to provide more resources. The answer is less clear in other mating systems in which males provide no resources (other than sperm) to females. Theoretical models that account for the evolution of mate choice in such nonresource-based mating systems require that females obtain a genetic benefit through increased offspring fitness from their choice. Empirical studies of nonresource-based mating systems that are characterized by strong female choice for males with elaborate sexual traits (like the large tail of peacocks) suggest that additive genetic benefits can explain only a small percentage of the variation in fitness. Other research on genetic benefits has examined nonadditive effects as another source of genetic variation in fitness and a potential benefit to female mate choice. In this paper, we review the sexual selection literature on genetic quality to address five objectives. First, we attempt to provide an integrated framework for discussing genetic quality. We propose that the term 'good gene' be used exclusively to refer to additive genetic variation in fitness, 'compatible gene' be used to refer to nonadditive genetic variation in fitness, and 'genetic quality' be defined as the sum of the two effects. Second, we review empirical approaches used to calculate the effect size of genetic quality and discuss these approaches in the context of measuring benefits from good genes, compatible genes and both types of genes. Third, we discuss biological mechanisms for acquiring and promoting offspring genetic quality and categorize these into three stages during breeding: (i) precopulatory (mate choice); (ii) postcopulatory, prefertilization (sperm utilization); and (iii) postcopulatory, postfertilization (differential investment). Fourth, we present a verbal model of the effect of good genes sexual selection and compatible genes sexual selection on population genetic variation in fitness, and discuss the potential trade-offs that might exist between mate choice for good genes and mate choice for compatible genes. Fifth, we discuss some future directions for research on genetic quality and sexual selection.

Closed Loop System Identification with Genetic Algorithms

NASA Technical Reports Server (NTRS)

Whorton, Mark S.

2004-01-01

High performance control design for a flexible space structure is challenging since high fidelity plant models are di.cult to obtain a priori. Uncertainty in the control design models typically require a very robust, low performance control design which must be tuned on-orbit to achieve the required performance. Closed loop system identi.cation is often required to obtain a multivariable open loop plant model based on closed-loop response data. In order to provide an accurate initial plant model to guarantee convergence for standard local optimization methods, this paper presents a global parameter optimization method using genetic algorithms. A minimal representation of the state space dynamics is employed to mitigate the non-uniqueness and over-parameterization of general state space realizations. This control-relevant system identi.cation procedure stresses the joint nature of the system identi.cation and control design problem by seeking to obtain a model that minimizes the di.erence between the predicted and actual closed-loop performance.

Teaching and Learning Activity Sequencing System using Distributed Genetic Algorithms

NASA Astrophysics Data System (ADS)

Matsui, Tatsunori; Ishikawa, Tomotake; Okamoto, Toshio

The purpose of this study is development of a supporting system for teacher's design of lesson plan. Especially design of lesson plan which relates to the new subject "Information Study" is supported. In this study, we developed a system which generates teaching and learning activity sequences by interlinking lesson's activities corresponding to the various conditions according to the user's input. Because user's input is multiple information, there will be caused contradiction which the system should solve. This multiobjective optimization problem is resolved by Distributed Genetic Algorithms, in which some fitness functions are defined with reference models on lesson, thinking and teaching style. From results of various experiments, effectivity and validity of the proposed methods and reference models were verified; on the other hand, some future works on reference models and evaluation functions were also pointed out.

Potential large animal models for gene therapy of human genetic diseases of immune and blood cell systems.

PubMed

Bauer, Thomas R; Adler, Rima L; Hickstein, Dennis D

2009-01-01

Genetic mutations involving the cellular components of the hematopoietic system--red blood cells, white blood cells, and platelets--manifest clinically as anemia, infection, and bleeding. Although gene targeting has recapitulated many of these diseases in mice, these murine homologues are limited as translational models by their small size and brief life span as well as the fact that mutations induced by gene targeting do not always faithfully reflect the clinical manifestations of such mutations in humans. Many of these limitations can be overcome by identifying large animals with genetic diseases of the hematopoietic system corresponding to their human disease counterparts. In this article, we describe human diseases of the cellular components of the hematopoietic system that have counterparts in large animal species, in most cases carrying mutations in the same gene (CD18 in leukocyte adhesion deficiency) or genes in interacting proteins (DNA cross-link repair 1C protein and protein kinase, DNA-activated catalytic polypeptide in radiation-sensitive severe combined immunodeficiency). Furthermore, we describe the potential of these animal models to serve as disease-specific preclinical models for testing the efficacy and safety of clinical interventions such as hematopoietic stem cell transplantation or gene therapy before their use in humans with the corresponding disease.

How Complex, Probable, and Predictable is Genetically Driven Red Queen Chaos?

PubMed

Duarte, Jorge; Rodrigues, Carla; Januário, Cristina; Martins, Nuno; Sardanyés, Josep

2015-12-01

Coevolution between two antagonistic species has been widely studied theoretically for both ecologically- and genetically-driven Red Queen dynamics. A typical outcome of these systems is an oscillatory behavior causing an endless series of one species adaptation and others counter-adaptation. More recently, a mathematical model combining a three-species food chain system with an adaptive dynamics approach revealed genetically driven chaotic Red Queen coevolution. In the present article, we analyze this mathematical model mainly focusing on the impact of species rates of evolution (mutation rates) in the dynamics. Firstly, we analytically proof the boundedness of the trajectories of the chaotic attractor. The complexity of the coupling between the dynamical variables is quantified using observability indices. By using symbolic dynamics theory, we quantify the complexity of genetically driven Red Queen chaos computing the topological entropy of existing one-dimensional iterated maps using Markov partitions. Co-dimensional two bifurcation diagrams are also built from the period ordering of the orbits of the maps. Then, we study the predictability of the Red Queen chaos, found in narrow regions of mutation rates. To extend the previous analyses, we also computed the likeliness of finding chaos in a given region of the parameter space varying other model parameters simultaneously. Such analyses allowed us to compute a mean predictability measure for the system in the explored region of the parameter space. We found that genetically driven Red Queen chaos, although being restricted to small regions of the analyzed parameter space, might be highly unpredictable.

Design and analysis of radiometric instruments using high-level numerical models and genetic algorithms

NASA Astrophysics Data System (ADS)

Sorensen, Ira Joseph

A primary objective of the effort reported here is to develop a radiometric instrument modeling environment to provide complete end-to-end numerical models of radiometric instruments, integrating the optical, electro-thermal, and electronic systems. The modeling environment consists of a Monte Carlo ray-trace (MCRT) model of the optical system coupled to a transient, three-dimensional finite-difference electrothermal model of the detector assembly with an analytic model of the signal-conditioning circuitry. The environment provides a complete simulation of the dynamic optical and electrothermal behavior of the instrument. The modeling environment is used to create an end-to-end model of the CERES scanning radiometer, and its performance is compared to the performance of an operational CERES total channel as a benchmark. A further objective of this effort is to formulate an efficient design environment for radiometric instruments. To this end, the modeling environment is then combined with evolutionary search algorithms known as genetic algorithms (GA's) to develop a methodology for optimal instrument design using high-level radiometric instrument models. GA's are applied to the design of the optical system and detector system separately and to both as an aggregate function with positive results.

Genetics of immune recognition and response in Drosophila host defense.

PubMed

Ligoxygakis, Petros

2013-01-01

Due to the evolutionary conservation of innate immune mechanisms, Drosophila has been extensively used as a model for the dissection in genetic terms of innate host immunity to infection. Genetic screening in fruit flies has set the stage for the pathways and systems required for responding to immune challenge and the dynamics of the progression of bacterial and fungal infection. In addition, fruit flies have been used as infection models to dissect host-pathogen interactions from both sides of this equation. This chapter describes our current understanding of the genetics of the fruit fly immune response and summarizes the most important findings in this area during the past decade. © 2013 Elsevier Inc. All rights reserved.

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

PubMed

Feltus, F Alex

2014-06-01

Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2014-01-01

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

Ontology driven modeling for the knowledge of genetic susceptibility to disease.

PubMed

Lin, Yu; Sakamoto, Norihiro

2009-05-12

For the machine helped exploring the relationships between genetic factors and complex diseases, a well-structured conceptual framework of the background knowledge is needed. However, because of the complexity of determining a genetic susceptibility factor, there is no formalization for the knowledge of genetic susceptibility to disease, which makes the interoperability between systems impossible. Thus, the ontology modeling language OWL was used for formalization in this paper. After introducing the Semantic Web and OWL language propagated by W3C, we applied text mining technology combined with competency questions to specify the classes of the ontology. Then, an N-ary pattern was adopted to describe the relationships among these defined classes. Based on the former work of OGSF-DM (Ontology of Genetic Susceptibility Factors to Diabetes Mellitus), we formalized the definition of "Genetic Susceptibility", "Genetic Susceptibility Factor" and other classes by using OWL-DL modeling language; and a reasoner automatically performed the classification of the class "Genetic Susceptibility Factor". The ontology driven modeling is used for formalization the knowledge of genetic susceptibility to complex diseases. More importantly, when a class has been completely formalized in an ontology, the OWL reasoning can automatically compute the classification of the class, in our case, the class of "Genetic Susceptibility Factors". With more types of genetic susceptibility factors obtained from the laboratory research, our ontologies always needs to be refined, and many new classes must be taken into account to harmonize with the ontologies. Using the ontologies to develop the semantic web needs to be applied in the future.

The emergence of DNA in the RNA world: an in silico simulation study of genetic takeover.

PubMed

Ma, Wentao; Yu, Chunwu; Zhang, Wentao; Wu, Sanmao; Feng, Yu

2015-12-07

It is now popularly accepted that there was an "RNA world" in early evolution of life. This idea has a direct consequence that later on there should have been a takeover of genetic material - RNA by DNA. However, since genetic material carries genetic information, the "source code" of all living activities, it is actually reasonable to question the plausibility of such a "revolutionary" transition. Due to our inability to model relevant "primitive living systems" in reality, it is as yet impossible to explore the plausibility and mechanisms of the "genetic takeover" by experiments. Here we investigated this issue by computer simulation using a Monte-Carlo method. It shows that an RNA-by-DNA genetic takeover may be triggered by the emergence of a nucleotide reductase ribozyme with a moderate activity in a pure RNA system. The transition is unstable and limited in scale (i.e., cannot spread in the population), but can get strengthened and globalized if certain parameters are changed against RNA (i.e., in favor of DNA). In relation to the subsequent evolution, an advanced system with a larger genome, which uses DNA as genetic material and RNA as functional material, is modeled - the system cannot sustain if the nucleotide reductase ribozyme is "turned off" (thus, DNA cannot be synthesized). Moreover, the advanced system cannot sustain if only DNA's stability, template suitability or replication fidelity (any of the three) is turned down to the level of RNA's. Genetic takeover should be plausible. In the RNA world, such a takeover may have been triggered by the emergence of some ribozyme favoring the formation of deoxynucleotides. The transition may initially have been "weak", but could have been reinforced by environmental changes unfavorable to RNA (such as temperature or pH rise), and would have ultimately become irreversible accompanying the genome's enlargement. Several virtues of DNA (versus RNA) - higher stability against hydrolysis, greater suitability as template and higher fidelity in replication, should have, each in its own way, all been significant for the genetic takeover in evolution. This study enhances our understandings of the relationship between information and material in the living world.

Optimisation of assembly scheduling in VCIM systems using genetic algorithm

NASA Astrophysics Data System (ADS)

Dao, Son Duy; Abhary, Kazem; Marian, Romeo

2017-09-01

Assembly plays an important role in any production system as it constitutes a significant portion of the lead time and cost of a product. Virtual computer-integrated manufacturing (VCIM) system is a modern production system being conceptually developed to extend the application of traditional computer-integrated manufacturing (CIM) system to global level. Assembly scheduling in VCIM systems is quite different from one in traditional production systems because of the difference in the working principles of the two systems. In this article, the assembly scheduling problem in VCIM systems is modeled and then an integrated approach based on genetic algorithm (GA) is proposed to search for a global optimised solution to the problem. Because of dynamic nature of the scheduling problem, a novel GA with unique chromosome representation and modified genetic operations is developed herein. Robustness of the proposed approach is verified by a numerical example.

Recent Advances in Algal Genetic Tool Development

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

R. Dahlin, Lukas; T. Guarnieri, Michael

The goal of achieving cost-effective biofuels and bioproducts derived from algal biomass will require improvements along the entire value chain, including identification of robust, high-productivity strains and development of advanced genetic tools. Though there have been modest advances in development of genetic systems for the model alga Chlamydomonas reinhardtii, progress in development of algal genetic tools, especially as applied to non-model algae, has generally lagged behind that of more commonly utilized laboratory and industrial microbes. This is in part due to the complex organellar structure of algae, including robust cell walls and intricate compartmentalization of target loci, as well asmore » prevalent gene silencing mechanisms, which hinder facile utilization of conventional genetic engineering tools and methodologies. However, recent progress in global tool development has opened the door for implementation of strain-engineering strategies in industrially-relevant algal strains. Here, we review recent advances in algal genetic tool development and applications in eukaryotic microalgae.« less

Applications of genetic data to improve management and conservation of river fishes and their habitats

USGS Publications Warehouse

Scribner, Kim T.; Lowe, Winsor H.; Landguth, Erin L.; Luikart, Gordon; Infante, Dana M.; Whelan, Gary; Muhlfeld, Clint C.

2015-01-01

Environmental variation and landscape features affect ecological processes in fluvial systems; however, assessing effects at management-relevant temporal and spatial scales is challenging. Genetic data can be used with landscape models and traditional ecological assessment data to identify biodiversity hotspots, predict ecosystem responses to anthropogenic effects, and detect impairments to underlying processes. We show that by combining taxonomic, demographic, and genetic data of species in complex riverscapes, managers can better understand the spatial and temporal scales over which environmental processes and disturbance influence biodiversity. We describe how population genetic models using empirical or simulated genetic data quantify effects of environmental processes affecting species diversity and distribution. Our summary shows that aquatic assessment initiatives that use standardized data sets to direct management actions can benefit from integration of genetic data to improve the predictability of disturbance–response relationships of river fishes and their habitats over a broad range of spatial and temporal scales.

Recent Advances in Algal Genetic Tool Development

DOE PAGES

R. Dahlin, Lukas; T. Guarnieri, Michael

2016-06-24

The goal of achieving cost-effective biofuels and bioproducts derived from algal biomass will require improvements along the entire value chain, including identification of robust, high-productivity strains and development of advanced genetic tools. Though there have been modest advances in development of genetic systems for the model alga Chlamydomonas reinhardtii, progress in development of algal genetic tools, especially as applied to non-model algae, has generally lagged behind that of more commonly utilized laboratory and industrial microbes. This is in part due to the complex organellar structure of algae, including robust cell walls and intricate compartmentalization of target loci, as well asmore » prevalent gene silencing mechanisms, which hinder facile utilization of conventional genetic engineering tools and methodologies. However, recent progress in global tool development has opened the door for implementation of strain-engineering strategies in industrially-relevant algal strains. Here, we review recent advances in algal genetic tool development and applications in eukaryotic microalgae.« less

"Wrecks of Ancient Life": Genetic Variants Vetted by Natural Selection.

PubMed

Postlethwait, John H

2015-07-01

The Genetics Society of America's George W. Beadle Award honors individuals who have made outstanding contributions to the community of genetics researchers and who exemplify the qualities of its namesake as a respected academic, administrator, and public servant. The 2015 recipient is John Postlethwait. He has made groundbreaking contributions in developing the zebrafish as a molecular genetic model and in understanding the evolution of new gene functions in vertebrates. He built the first zebrafish genetic map and showed that its genome, along with that of distantly related teleost fish, had been duplicated. Postlethwait played an integral role in the zebrafish genome-sequencing project and elucidated the genomic organization of several fish species. Postlethwait is also honored for his active involvement with the zebrafish community, advocacy for zebrafish as a model system, and commitment to driving the field forward. Copyright © 2015 by the Genetics Society of America.

FEMALE AND MALE GENETIC EFFECTS ON OFFSPRING PATERNITY: ADDITIVE GENETIC (CO)VARIANCES IN FEMALE EXTRA-PAIR REPRODUCTION AND MALE PATERNITY SUCCESS IN SONG SPARROWS (MELOSPIZA MELODIA)

PubMed Central

Reid, Jane M; Arcese, Peter; Keller, Lukas F; Losdat, Sylvain

2014-01-01

Ongoing evolution of polyandry, and consequent extra-pair reproduction in socially monogamous systems, is hypothesized to be facilitated by indirect selection stemming from cross-sex genetic covariances with components of male fitness. Specifically, polyandry is hypothesized to create positive genetic covariance with male paternity success due to inevitable assortative reproduction, driving ongoing coevolution. However, it remains unclear whether such covariances could or do emerge within complex polyandrous systems. First, we illustrate that genetic covariances between female extra-pair reproduction and male within-pair paternity success might be constrained in socially monogamous systems where female and male additive genetic effects can have opposing impacts on the paternity of jointly reared offspring. Second, we demonstrate nonzero additive genetic variance in female liability for extra-pair reproduction and male liability for within-pair paternity success, modeled as direct and associative genetic effects on offspring paternity, respectively, in free-living song sparrows (Melospiza melodia). The posterior mean additive genetic covariance between these liabilities was slightly positive, but the credible interval was wide and overlapped zero. Therefore, although substantial total additive genetic variance exists, the hypothesis that ongoing evolution of female extra-pair reproduction is facilitated by genetic covariance with male within-pair paternity success cannot yet be definitively supported or rejected either conceptually or empirically. PMID:24724612

DNA Repair Mechanisms and Their Biological Roles in the Malaria Parasite Plasmodium falciparum

PubMed Central

Lee, Andrew H.; Symington, Lorraine S.

2014-01-01

SUMMARY Research into the complex genetic underpinnings of the malaria parasite Plasmodium falciparum is entering a new era with the arrival of site-specific genome engineering. Previously restricted only to model systems but now expanded to most laboratory organisms, and even to humans for experimental gene therapy studies, this technology allows researchers to rapidly generate previously unattainable genetic modifications. This technological advance is dependent on DNA double-strand break repair (DSBR), specifically homologous recombination in the case of Plasmodium. Our understanding of DSBR in malaria parasites, however, is based largely on assumptions and knowledge taken from other model systems, which do not always hold true in Plasmodium. Here we describe the causes of double-strand breaks, the mechanisms of DSBR, and the differences between model systems and P. falciparum. These mechanisms drive basic parasite functions, such as meiosis, antigen diversification, and copy number variation, and allow the parasite to continually evolve in the contexts of host immune pressure and drug selection. Finally, we discuss the new technologies that leverage DSBR mechanisms to accelerate genetic investigations into this global infectious pathogen. PMID:25184562

The Spring of Systems Biology-Driven Breeding.

PubMed

Lavarenne, Jérémy; Guyomarc'h, Soazig; Sallaud, Christophe; Gantet, Pascal; Lucas, Mikaël

2018-05-12

Genetics and molecular biology have contributed to the development of rationalized plant breeding programs. Recent developments in both high-throughput experimental analyses of biological systems and in silico data processing offer the possibility to address the whole gene regulatory network (GRN) controlling a given trait. GRN models can be applied to identify topological features helping to shortlist potential candidate genes for breeding purposes. Time-series data sets can be used to support dynamic modelling of the network. This will enable a deeper comprehension of network behaviour and the identification of the few elements to be genetically rewired to push the system towards a modified phenotype of interest. This paves the way to design more efficient, systems biology-based breeding strategies. Copyright © 2018 Elsevier Ltd. All rights reserved.

The fabulous destiny of the Drosophila heart.

PubMed

Medioni, Caroline; Sénatore, Sébastien; Salmand, Pierre-Adrien; Lalevée, Nathalie; Perrin, Laurent; Sémériva, Michel

2009-10-01

For the last 15 years the fly cardiovascular system has attracted developmental geneticists for its potential as a model system of organogenesis. Heart development in Drosophila indeed provides a remarkable system for elucidating the basic molecular and cellular mechanisms of morphogenesis and, more recently, for understanding the genetic control of cardiac physiology. The success of these studies can in part be attributed to multidisciplinary approaches, the multiplicity of existing genetic tools, and a detailed knowledge of the system. Striking similarities with vertebrate cardiogenesis have long been stressed, in particular concerning the conservation of key molecular regulators of cardiogenesis and the new data presented here confirm Drosophila cardiogenesis as a model not only for organogenesis but also for the study of molecular mechanisms of human cardiac disease.

Progress and Prospects for Genetic Modification of Nonhuman Primate Models in Biomedical Research

PubMed Central

Chan, Anthony W. S.

2013-01-01

The growing interest of modeling human diseases using genetically modified (transgenic) nonhuman primates (NHPs) is a direct result of NHPs (rhesus macaque, etc.) close relation to humans. NHPs share similar developmental paths with humans in their anatomy, physiology, genetics, and neural functions; and in their cognition, emotion, and social behavior. The NHP model within biomedical research has played an important role in the development of vaccines, assisted reproductive technologies, and new therapies for many diseases. Biomedical research has not been the primary role of NHPs. They have mainly been used for safety evaluation and pharmacokinetics studies, rather than determining therapeutic efficacy. The development of the first transgenic rhesus macaque (2001) revolutionized the role of NHP models in biomedicine. Development of the transgenic NHP model of Huntington's disease (2008), with distinctive clinical features, further suggested the uniqueness of the model system; and the potential role of the NHP model for human genetic disorders. Modeling human genetic diseases using NHPs will continue to thrive because of the latest advances in molecular, genetic, and embryo technologies. NHPs rising role in biomedical research, specifically pre-clinical studies, is foreseeable. The path toward the development of transgenic NHPs and the prospect of transgenic NHPs in their new role in future biomedicine needs to be reviewed. This article will focus on the advancement of transgenic NHPs in the past decade, including transgenic technologies and disease modeling. It will outline new technologies that may have significant impact in future NHP modeling and will conclude with a discussion of the future prospects of the transgenic NHP model. PMID:24174443

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

NASA Astrophysics Data System (ADS)

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

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

Mouse forward genetics in the study of the peripheral nervous system and human peripheral neuropathy

PubMed Central

Douglas, Darlene S.; Popko, Brian

2009-01-01

Forward genetics, the phenotype-driven approach to investigating gene identity and function, has a long history in mouse genetics. Random mutations in the mouse transcend bias about gene function and provide avenues towards unique discoveries. The study of the peripheral nervous system is no exception; from historical strains such as the trembler mouse, which led to the identification of PMP22 as a human disease gene causing multiple forms of peripheral neuropathy, to the more recent identification of the claw paw and sprawling mutations, forward genetics has long been a tool for probing the physiology, pathogenesis, and genetics of the PNS. Even as spontaneous and mutagenized mice continue to enable the identification of novel genes, provide allelic series for detailed functional studies, and generate models useful for clinical research, new methods, such as the piggyBac transposon, are being developed to further harness the power of forward genetics. PMID:18481175

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

Characterization of the basal angiosperm Aristolochia fimbriata: a potential experimental system for genetic studies

PubMed Central

2013-01-01

Background Previous studies in basal angiosperms have provided insight into the diversity within the angiosperm lineage and helped to polarize analyses of flowering plant evolution. However, there is still not an experimental system for genetic studies among basal angiosperms to facilitate comparative studies and functional investigation. It would be desirable to identify a basal angiosperm experimental system that possesses many of the features found in existing plant model systems (e.g., Arabidopsis and Oryza). Results We have considered all basal angiosperm families for general characteristics important for experimental systems, including availability to the scientific community, growth habit, and membership in a large basal angiosperm group that displays a wide spectrum of phenotypic diversity. Most basal angiosperms are woody or aquatic, thus are not well-suited for large scale cultivation, and were excluded. We further investigated members of Aristolochiaceae for ease of culture, life cycle, genome size, and chromosome number. We demonstrated self-compatibility for Aristolochia elegans and A. fimbriata, and transformation with a GFP reporter construct for Saruma henryi and A. fimbriata. Furthermore, A. fimbriata was easily cultivated with a life cycle of just three months, could be regenerated in a tissue culture system, and had one of the smallest genomes among basal angiosperms. An extensive multi-tissue EST dataset was produced for A. fimbriata that includes over 3.8 million 454 sequence reads. Conclusions Aristolochia fimbriata has numerous features that facilitate genetic studies and is suggested as a potential model system for use with a wide variety of technologies. Emerging genetic and genomic tools for A. fimbriata and closely related species can aid the investigation of floral biology, developmental genetics, biochemical pathways important in plant-insect interactions as well as human health, and various other features present in early angiosperms. PMID:23347749

Genetic variants associated with neurodegenerative Alzheimer disease in natural models.

PubMed

Salazar, Claudia; Valdivia, Gonzalo; Ardiles, Álvaro O; Ewer, John; Palacios, Adrián G

2016-02-26

The use of transgenic models for the study of neurodegenerative diseases has made valuable contributions to the field. However, some important limitations, including protein overexpression and general systemic compensation for the missing genes, has caused researchers to seek natural models that show the main biomarkers of neurodegenerative diseases during aging. Here we review some of these models-most of them rodents, focusing especially on the genetic variations in biomarkers for Alzheimer diseases, in order to explain their relationships with variants associated with the occurrence of the disease in humans.

A Systems Genetic Approach to Identify Low Dose Radiation-Induced Lymphoma Susceptibility/DOE2013FinalReport

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

Balmain, Allan; Song, Ihn Young

2013-05-15

The ultimate goal of this project is to identify the combinations of genetic variants that confer an individual's susceptibility to the effects of low dose (0.1 Gy) gamma-radiation, in particular with regard to tumor development. In contrast to the known effects of high dose radiation in cancer induction, the responses to low dose radiation (defined as 0.1 Gy or less) are much less well understood, and have been proposed to involve a protective anti-tumor effect in some in vivo scientific models. These conflicting results confound attempts to develop predictive models of the risk of exposure to low dose radiation, particularlymore » when combined with the strong effects of inherited genetic variants on both radiation effects and cancer susceptibility. We have used a Systems Genetics approach in mice that combines genetic background analysis with responses to low and high dose radiation, in order to develop insights that will allow us to reconcile these disparate observations. Using this comprehensive approach we have analyzed normal tissue gene expression (in this case the skin and thymus), together with the changes that take place in this gene expression architecture a) in response to low or high- dose radiation and b) during tumor development. Additionally, we have demonstrated that using our expression analysis approach in our genetically heterogeneous/defined radiation-induced tumor mouse models can uniquely identify genes and pathways relevant to human T-ALL, and uncover interactions between common genetic variants of genes which may lead to tumor susceptibility.« less

Evolution and development in cave animals: from fish to crustaceans.

PubMed

Protas, Meredith; Jeffery, William R

2012-01-01

Cave animals are excellent models to study the general principles of evolution as well as the mechanisms of adaptation to a novel environment: the perpetual darkness of caves. In this article, two of the major model systems used to study the evolution and development (evo-devo) of cave animals are described: the teleost fish Astyanax mexicanus and the isopod crustacean Asellus aquaticus. The ways in which these animals match the major attributes expected of an evo-devo cave animal model system are described. For both species, we enumerate the regressive and constructive troglomorphic traits that have evolved during their adaptation to cave life, the developmental and genetic basis of these traits, the possible evolutionary forces responsible for them, and potential new areas in which these model systems could be used for further exploration of the evolution of cave animals. Furthermore, we compare the two model cave animals to investigate the mechanisms of troglomorphic evolution. Finally, we propose a few other cave animal systems that would be suitable for development as additional models to obtain a more comprehensive understanding of the developmental and genetic mechanisms involved in troglomorphic evolution.

Genetic Algorithm Tuned Fuzzy Logic for Gliding Return Trajectories

NASA Technical Reports Server (NTRS)

Burchett, Bradley T.

2003-01-01

The problem of designing and flying a trajectory for successful recovery of a reusable launch vehicle is tackled using fuzzy logic control with genetic algorithm optimization. The plant is approximated by a simplified three degree of freedom non-linear model. A baseline trajectory design and guidance algorithm consisting of several Mamdani type fuzzy controllers is tuned using a simple genetic algorithm. Preliminary results show that the performance of the overall system is shown to improve with genetic algorithm tuning.

Peptide neuromodulation in invertebrate model systems

PubMed Central

Taghert, Paul H.; Nitabach, Michael N.

2012-01-01

Neuropeptides modulate neural circuits controlling adaptive animal behaviors and physiological processes, such as feeding/metabolism, reproductive behaviors, circadian rhythms, central pattern generation, and sensorimotor integration. Invertebrate model systems have enabled detailed experimental analysis using combined genetic, behavioral, and physiological approaches. Here we review selected examples of neuropeptide modulation in crustaceans, mollusks, insects, and nematodes, with a particular emphasis on the genetic model organisms Drosophila melanogaster and Caenorhabditis elegans, where remarkable progress has been made. On the basis of this survey, we provide several integrating conceptual principles for understanding how neuropeptides modulate circuit function, and also propose that continued progress in this area requires increased emphasis on the development of richer, more sophisticated behavioral paradigms. PMID:23040808

Revisiting the Association Between Television Viewing in Adolescence and Contact With the Criminal Justice System in Adulthood.

PubMed

Schwartz, Joseph A; Beaver, Kevin M

2016-09-01

A substantial number of previous studies have reported significant associations between television viewing habits and a host of detrimental outcomes including increased contact with the criminal justice system. However, it remains unclear whether the results flowing from this literature are generalizable to other samples and whether previously observed associations are confounded due to uncontrolled genetic influences. The current study addresses these limitations using the National Longitudinal Study of Adolescent to Adult Health (Add Health). The results of the preliminary models, which do not include controls for genetic influences, produced a pattern of results similar to those previously reported in the extant literature. The results of the genetically informed models revealed that the associations between television viewing and antisocial outcomes are not causal, but rather are driven by uncontrolled genetic influences. Further replication is required, but these findings suggest that results drawn from the extant literature may not be trustworthy. © The Author(s) 2015.

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

PubMed Central

Kitchen, James L.; Allaby, Robin G.

2013-01-01

Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to study within systems modeling because their sedentary nature simplifies interactions between individuals and the environment, and many important plant processes such as germination or flowering are dependent on annual cycles which can be disrupted by climate behavior. Sedentism makes plants relevant candidates for spatially explicit modeling that is tied in with dynamical environments. We propose that in order to fully understand the complexities behind plant adaptation, a system that couples aspects from systems biology with population and landscape genetics is required. A suitable system could be represented by spatially explicit individual-based models where the virtual individuals are located within time-variable heterogeneous environments and contain mutable regulatory gene networks. These networks could directly interact with the environment, and should provide a useful approach to studying plant adaptation. PMID:27137364

e-Dairy: a dynamic and stochastic whole-farm model that predicts biophysical and economic performance of grazing dairy systems.

PubMed

Baudracco, J; Lopez-Villalobos, N; Holmes, C W; Comeron, E A; Macdonald, K A; Barry, T N

2013-05-01

A whole-farm, stochastic and dynamic simulation model was developed to predict biophysical and economic performance of grazing dairy systems. Several whole-farm models simulate grazing dairy systems, but most of them work at a herd level. This model, named e-Dairy, differs from the few models that work at an animal level, because it allows stochastic behaviour of the genetic merit of individual cows for several traits, namely, yields of milk, fat and protein, live weight (LW) and body condition score (BCS) within a whole-farm model. This model accounts for genetic differences between cows, is sensitive to genotype × environment interactions at an animal level and allows pasture growth, milk and supplements price to behave stochastically. The model includes an energy-based animal module that predicts intake at grazing, mammary gland functioning and body lipid change. This whole-farm model simulates a 365-day period for individual cows within a herd, with cow parameters randomly generated on the basis of the mean parameter values, defined as input and variance and co-variances from experimental data sets. The main inputs of e-Dairy are farm area, use of land, type of pasture, type of crops, monthly pasture growth rate, supplements offered, nutritional quality of feeds, herd description including herd size, age structure, calving pattern, BCS and LW at calving, probabilities of pregnancy, average genetic merit and economic values for items of income and costs. The model allows to set management policies to define: dry-off cows (ceasing of lactation), target pre- and post-grazing herbage mass and feed supplementation. The main outputs are herbage dry matter intake, annual pasture utilisation, milk yield, changes in BCS and LW, economic farm profit and return on assets. The model showed satisfactory accuracy of prediction when validated against two data sets from farmlet system experiments. Relative prediction errors were <10% for all variables, and concordance correlation coefficients over 0.80 for annual pasture utilisation, yields of milk and milk solids (MS; fat plus protein), and of 0.69 and 0.48 for LW and BCS, respectively. A simulation of two contrasting dairy systems is presented to show the practical use of the model. The model can be used to explore the effects of feeding level and genetic merit and their interactions for grazing dairy systems, evaluating the trade-offs between profit and the associated risk.

A versatile modular vector system for rapid combinatorial mammalian genetics.

PubMed

Albers, Joachim; Danzer, Claudia; Rechsteiner, Markus; Lehmann, Holger; Brandt, Laura P; Hejhal, Tomas; Catalano, Antonella; Busenhart, Philipp; Gonçalves, Ana Filipa; Brandt, Simone; Bode, Peter K; Bode-Lesniewska, Beata; Wild, Peter J; Frew, Ian J

2015-04-01

Here, we describe the multiple lentiviral expression (MuLE) system that allows multiple genetic alterations to be introduced simultaneously into mammalian cells. We created a toolbox of MuLE vectors that constitute a flexible, modular system for the rapid engineering of complex polycistronic lentiviruses, allowing combinatorial gene overexpression, gene knockdown, Cre-mediated gene deletion, or CRISPR/Cas9-mediated (where CRISPR indicates clustered regularly interspaced short palindromic repeats) gene mutation, together with expression of fluorescent or enzymatic reporters for cellular assays and animal imaging. Examples of tumor engineering were used to illustrate the speed and versatility of performing combinatorial genetics using the MuLE system. By transducing cultured primary mouse cells with single MuLE lentiviruses, we engineered tumors containing up to 5 different genetic alterations, identified genetic dependencies of molecularly defined tumors, conducted genetic interaction screens, and induced the simultaneous CRISPR/Cas9-mediated knockout of 3 tumor-suppressor genes. Intramuscular injection of MuLE viruses expressing oncogenic H-RasG12V together with combinations of knockdowns of the tumor suppressors cyclin-dependent kinase inhibitor 2A (Cdkn2a), transformation-related protein 53 (Trp53), and phosphatase and tensin homolog (Pten) allowed the generation of 3 murine sarcoma models, demonstrating that genetically defined autochthonous tumors can be rapidly generated and quantitatively monitored via direct injection of polycistronic MuLE lentiviruses into mouse tissues. Together, our results demonstrate that the MuLE system provides genetic power for the systematic investigation of the molecular mechanisms that underlie human diseases.

Calibration of the computer model describing flows in the water supply system; example of the application of a genetic algorithm

NASA Astrophysics Data System (ADS)

Orłowska-Szostak, Maria; Orłowski, Ryszard

2017-11-01

The paper discusses some relevant aspects of the calibration of a computer model describing flows in the water supply system. The authors described an exemplary water supply system and used it as a practical illustration of calibration. A range of measures was discussed and applied, which improve the convergence and effective use of calculations in the calibration process and also the effect of such calibration which is the validity of the results obtained. Drawing up results of performed measurements, i.e. estimating pipe roughnesses, the authors performed using the genetic algorithm implementation of which is a software developed by Resan Labs company from Brazil.

Studies of threespine stickleback developmental evolution: progress and promise.

PubMed

Cresko, William A; McGuigan, Katrina L; Phillips, Patrick C; Postlethwait, John H

2007-01-01

A promising route for understanding the origin and diversification of organismal form is through studies at the intersection of evolution and development (evo-devo). While much has been learned over the last two decades concerning macroevolutionary patterns of developmental change, a fundamental gap in the evo-devo synthesis is the integration of mathematical population and quantitative genetics with studies of how genetic variation in natural populations affects developmental processes. This micro-evo-devo synthesis requires model organisms with which to ask empirical questions. Threespine stickleback fish (Gasterosteus aculeatus), long a model for studying behavior, ecology and evolution, is emerging as a prominent model micro-evo-devo system. Research on stickleback over the last decade has begun to address the genetic basis of morphological variation and sex determination, and much of this work has important implications for understanding the genetics of speciation. In this paper we review recent threespine stickleback micro-evo-devo results, and outline the resources that have been developed to make this synthesis possible. The prospects for stickleback research to speed the micro-(and macro-) evo-devo syntheses are great, and this workhorse model system is well situated to continue contributing to our understanding of the generation of diversity in organismal form for many more decades.

The GP problem: quantifying gene-to-phenotype relationships.

PubMed

Cooper, Mark; Chapman, Scott C; Podlich, Dean W; Hammer, Graeme L

2002-01-01

In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes.

Modeling Selection and Extinction Mechanisms of Biological Systems

NASA Astrophysics Data System (ADS)

Amirjanov, Adil

In this paper, the behavior of a genetic algorithm is modeled to enhance its applicability as a modeling tool of biological systems. A new description model for selection mechanism is introduced which operates on a portion of individuals of population. The extinction and recolonization mechanism is modeled, and solving the dynamics analytically shows that the genetic drift in the population with extinction/recolonization is doubled. The mathematical analysis of the interaction between selection and extinction/recolonization processes is carried out to assess the dynamics of motion of the macroscopic statistical properties of population. Computer simulations confirm that the theoretical predictions of described models are in good approximations. A mathematical model of GA dynamics was also examined, which describes the anti-predator vigilance in an animal group with respect to a known analytical solution of the problem, and showed a good agreement between them to find the evolutionarily stable strategies.

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

A quantitative test of population genetics using spatiogenetic patterns in bacterial colonies.

PubMed

Korolev, Kirill S; Xavier, João B; Nelson, David R; Foster, Kevin R

2011-10-01

It is widely accepted that population-genetics theory is the cornerstone of evolutionary analyses. Empirical tests of the theory, however, are challenging because of the complex relationships between space, dispersal, and evolution. Critically, we lack quantitative validation of the spatial models of population genetics. Here we combine analytics, on- and off-lattice simulations, and experiments with bacteria to perform quantitative tests of the theory. We study two bacterial species, the gut microbe Escherichia coli and the opportunistic pathogen Pseudomonas aeruginosa, and show that spatiogenetic patterns in colony biofilms of both species are accurately described by an extension of the one-dimensional stepping-stone model. We use one empirical measure, genetic diversity at the colony periphery, to parameterize our models and show that we can then accurately predict another key variable: the degree of short-range cell migration along an edge. Moreover, the model allows us to estimate other key parameters, including effective population size (density) at the expansion frontier. While our experimental system is a simplification of natural microbial community, we argue that it constitutes proof of principle that the spatial models of population genetics can quantitatively capture organismal evolution.

Genetic network inference as a series of discrimination tasks.

PubMed

Kimura, Shuhei; Nakayama, Satoshi; Hatakeyama, Mariko

2009-04-01

Genetic network inference methods based on sets of differential equations generally require a great deal of time, as the equations must be solved many times. To reduce the computational cost, researchers have proposed other methods for inferring genetic networks by solving sets of differential equations only a few times, or even without solving them at all. When we try to obtain reasonable network models using these methods, however, we must estimate the time derivatives of the gene expression levels with great precision. In this study, we propose a new method to overcome the drawbacks of inference methods based on sets of differential equations. Our method infers genetic networks by obtaining classifiers capable of predicting the signs of the derivatives of the gene expression levels. For this purpose, we defined a genetic network inference problem as a series of discrimination tasks, then solved the defined series of discrimination tasks with a linear programming machine. Our experimental results demonstrated that the proposed method is capable of correctly inferring genetic networks, and doing so more than 500 times faster than the other inference methods based on sets of differential equations. Next, we applied our method to actual expression data of the bacterial SOS DNA repair system. And finally, we demonstrated that our approach relates to the inference method based on the S-system model. Though our method provides no estimation of the kinetic parameters, it should be useful for researchers interested only in the network structure of a target system. Supplementary data are available at Bioinformatics online.

The Effects of Predator Evolution and Genetic Variation on Predator-Prey Population-Level Dynamics.

PubMed

Cortez, Michael H; Patel, Swati

2017-07-01

This paper explores how predator evolution and the magnitude of predator genetic variation alter the population-level dynamics of predator-prey systems. We do this by analyzing a general eco-evolutionary predator-prey model using four methods: Method 1 identifies how eco-evolutionary feedbacks alter system stability in the fast and slow evolution limits; Method 2 identifies how the amount of standing predator genetic variation alters system stability; Method 3 identifies how the phase lags in predator-prey cycles depend on the amount of genetic variation; and Method 4 determines conditions for different cycle shapes in the fast and slow evolution limits using geometric singular perturbation theory. With these four methods, we identify the conditions under which predator evolution alters system stability and shapes of predator-prey cycles, and how those effect depend on the amount of genetic variation in the predator population. We discuss the advantages and disadvantages of each method and the relations between the four methods. This work shows how the four methods can be used in tandem to make general predictions about eco-evolutionary dynamics and feedbacks.

Setaria Comes of Age: Meeting Report on the Second International Setaria Genetics Conference

DOE PAGES

Zhu, Chuanmei; Yang, Jiani; Shyu, Christine

2017-09-28

Setaria viridis is an emerging model for cereal and bioenergy grasses because of its short stature, rapid life cycle and expanding genetic and genomic toolkits. Its close phylogenetic relationship with economically important crops such as maize and sorghum positions Setaria as an ideal model system for accelerating discovery and characterization of crop genes that control agronomically important traits. The Second International Setaria Genetics Conference was held on March 6–8, 2017 at the Donald Danforth Plant Science Center, St. Louis, MO, United States to discuss recent technological breakthroughs and research directions in Setaria (presentation abstracts can be downloaded at https://www.brutnelllab.org/setaria). Here,more » we highlight topics presented in the conference including inflorescence architecture, C 4 photosynthesis and abiotic stress. Genetic and genomic toolsets including germplasm, mutant populations, transformation and gene editing technologies are also discussed. Since the last meeting in 2014, the Setaria community has matured greatly in the quality of research being conducted. Outreach and increased communication with maize and other plant communities will allow broader adoption of Setaria as a model system to translate fundamental discovery research to crop improvement.« less

Setaria Comes of Age: Meeting Report on the Second International Setaria Genetics Conference

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

Zhu, Chuanmei; Yang, Jiani; Shyu, Christine

Setaria viridis is an emerging model for cereal and bioenergy grasses because of its short stature, rapid life cycle and expanding genetic and genomic toolkits. Its close phylogenetic relationship with economically important crops such as maize and sorghum positions Setaria as an ideal model system for accelerating discovery and characterization of crop genes that control agronomically important traits. The Second International Setaria Genetics Conference was held on March 6–8, 2017 at the Donald Danforth Plant Science Center, St. Louis, MO, United States to discuss recent technological breakthroughs and research directions in Setaria (presentation abstracts can be downloaded at https://www.brutnelllab.org/setaria). Here,more » we highlight topics presented in the conference including inflorescence architecture, C 4 photosynthesis and abiotic stress. Genetic and genomic toolsets including germplasm, mutant populations, transformation and gene editing technologies are also discussed. Since the last meeting in 2014, the Setaria community has matured greatly in the quality of research being conducted. Outreach and increased communication with maize and other plant communities will allow broader adoption of Setaria as a model system to translate fundamental discovery research to crop improvement.« less

Setaria Comes of Age: Meeting Report on the Second International Setaria Genetics Conference

PubMed Central

Zhu, Chuanmei; Yang, Jiani; Shyu, Christine

2017-01-01

Setaria viridis is an emerging model for cereal and bioenergy grasses because of its short stature, rapid life cycle and expanding genetic and genomic toolkits. Its close phylogenetic relationship with economically important crops such as maize and sorghum positions Setaria as an ideal model system for accelerating discovery and characterization of crop genes that control agronomically important traits. The Second International Setaria Genetics Conference was held on March 6–8, 2017 at the Donald Danforth Plant Science Center, St. Louis, MO, United States to discuss recent technological breakthroughs and research directions in Setaria (presentation abstracts can be downloaded at https://www.brutnelllab.org/setaria). Here, we highlight topics presented in the conference including inflorescence architecture, C4 photosynthesis and abiotic stress. Genetic and genomic toolsets including germplasm, mutant populations, transformation and gene editing technologies are also discussed. Since the last meeting in 2014, the Setaria community has matured greatly in the quality of research being conducted. Outreach and increased communication with maize and other plant communities will allow broader adoption of Setaria as a model system to translate fundamental discovery research to crop improvement. PMID:29033954

T Cell Adaptive Immunity Proceeds through Environment-Induced Adaptation from the Exposure of Cryptic Genetic Variation

PubMed Central

Whitacre, James M.; Lin, Joseph; Harding, Angus

2011-01-01

Evolution is often characterized as a process involving incremental genetic changes that are slowly discovered and fixed in a population through genetic drift and selection. However, a growing body of evidence is finding that changes in the environment frequently induce adaptations that are much too rapid to occur by an incremental genetic search process. Rapid evolution is hypothesized to be facilitated by mutations present within the population that are silent or “cryptic” within the first environment but are co-opted or “exapted” to the new environment, providing a selective advantage once revealed. Although cryptic mutations have recently been shown to facilitate evolution in RNA enzymes, their role in the evolution of complex phenotypes has not been proven. In support of this wider role, this paper describes an unambiguous relationship between cryptic genetic variation and complex phenotypic responses within the immune system. By reviewing the biology of the adaptive immune system through the lens of evolution, we show that T cell adaptive immunity constitutes an exemplary model system where cryptic alleles drive rapid adaptation of complex traits. In naive T cells, normally cryptic differences in T cell receptor reveal diversity in activation responses when the cellular population is presented with a novel environment during infection. We summarize how the adaptive immune response presents a well studied and appropriate experimental system that can be used to confirm and expand upon theoretical evolutionary models describing how seemingly small and innocuous mutations can drive rapid cellular evolution. PMID:22363338

Evaluation of LOINC for Representing Constitutional Cytogenetic Test Result Reports

PubMed Central

Heras, Yan Z.; Mitchell, Joyce A.; Williams, Marc S.; Brothman, Arthur R.; Huff, Stanley M.

2009-01-01

Genetic testing is becoming increasingly important to medical practice. Integrating genetics and genomics data into electronic medical records is crucial in translating genetic discoveries into improved patient care. Information technology, especially Clinical Decision Support Systems, holds great potential to help clinical professionals take full advantage of genomic advances in their daily medical practice. However, issues relating to standard terminology and information models for exchanging genetic testing results remain relatively unexplored. This study evaluates whether the current LOINC standard is adequate to represent constitutional cytogenetic test result reports using sample result reports from ARUP Laboratories. The results demonstrate that current standard terminology is insufficient to support the needs of coding cytogenetic test results. The terminology infrastructure must be developed before clinical information systems will be able to handle the high volumes of genetic data expected in the near future. PMID:20351857

Evaluation of LOINC for representing constitutional cytogenetic test result reports.

PubMed

Heras, Yan Z; Mitchell, Joyce A; Williams, Marc S; Brothman, Arthur R; Huff, Stanley M

2009-11-14

Genetic testing is becoming increasingly important to medical practice. Integrating genetics and genomics data into electronic medical records is crucial in translating genetic discoveries into improved patient care. Information technology, especially Clinical Decision Support Systems, holds great potential to help clinical professionals take full advantage of genomic advances in their daily medical practice. However, issues relating to standard terminology and information models for exchanging genetic testing results remain relatively unexplored. This study evaluates whether the current LOINC standard is adequate to represent constitutional cytogenetic test result reports using sample result reports from ARUP Laboratories. The results demonstrate that current standard terminology is insufficient to support the needs of coding cytogenetic test results. The terminology infrastructure must be developed before clinical information systems will be able to handle the high volumes of genetic data expected in the near future.

Recent advances in genetic modification systems for Actinobacteria.

PubMed

Deng, Yu; Zhang, Xi; Zhang, Xiaojuan

2017-03-01

Actinobacteria are extremely important to human health, agriculture, and forests. Because of the vast differences of the characteristics of Actinobacteria, a lot of genetic tools have been developed for efficiently manipulating the genetics. Although there are a lot of successful examples of engineering Actinobacteria, they are still more difficult to be genetically manipulated than other model microorganisms such as Saccharomyces cerevisiae, Escherichia coli, and Bacillus subtilis etc. due to the diverse genomics and biochemical machinery. Here, we review the methods to introduce heterologous DNA into Actinobacteria and the available genetic modification tools. The trends and problems existing in engineering Actinobacteria are also covered.

Genetic service delivery: infrastructure, assessment and information.

PubMed

Kaye, C I

2012-01-01

Identification of genomic determinants of complex disorders such as cancer, diabetes and cardiovascular disease has prompted public health systems to focus on genetic service delivery for prevention of these disorders, adding to their previous efforts in birth defects prevention and newborn screening. This focus is consistent with previously identified obligations of the public health system as well as the core functions of public health identified by the Institute of Medicine. Models of service delivery include provision of services by the primary care provider in conjunction with subspecialists, provision of services through the medical home with co-management by genetics providers, provision of services in conjunction with disorder-specific treatment centers, and provision of services through a network of genetics clinics linked to medical homes. Whatever the model for provision of genetic services, tools to assist providers include facilities for outreach and telemedicine, information technology, just-in-time management plans, and emergency management tools. Assessment tools to determine which care is best are critical for quality improvement and development of best practices. Because the workforce of genetics providers is not keeping pace with the need for services, an understanding of the factors contributing to this lag is important, as is the development of an improved knowledge base in genomics for primary care providers. Copyright © 2012 S. Karger AG, Basel.

Genome Wide Identification of SARS-CoV Susceptibility Loci Using the Collaborative Cross

PubMed Central

Gralinski, Lisa E.; Ferris, Martin T.; Aylor, David L.; Whitmore, Alan C.; Green, Richard; Frieman, Matthew B.; Deming, Damon; Menachery, Vineet D.; Miller, Darla R.; Buus, Ryan J.; Bell, Timothy A.; Churchill, Gary A.; Threadgill, David W.; Katze, Michael G.; McMillan, Leonard; Valdar, William; Heise, Mark T.; Pardo-Manuel de Villena, Fernando; Baric, Ralph S.

2015-01-01

New systems genetics approaches are needed to rapidly identify host genes and genetic networks that regulate complex disease outcomes. Using genetically diverse animals from incipient lines of the Collaborative Cross mouse panel, we demonstrate a greatly expanded range of phenotypes relative to classical mouse models of SARS-CoV infection including lung pathology, weight loss and viral titer. Genetic mapping revealed several loci contributing to differential disease responses, including an 8.5Mb locus associated with vascular cuffing on chromosome 3 that contained 23 genes and 13 noncoding RNAs. Integrating phenotypic and genetic data narrowed this region to a single gene, Trim55, an E3 ubiquitin ligase with a role in muscle fiber maintenance. Lung pathology and transcriptomic data from mice genetically deficient in Trim55 were used to validate its role in SARS-CoV-induced vascular cuffing and inflammation. These data establish the Collaborative Cross platform as a powerful genetic resource for uncovering genetic contributions of complex traits in microbial disease severity, inflammation and virus replication in models of outbred populations. PMID:26452100

Evolving rule-based systems in two medical domains using genetic programming.

PubMed

Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan; Axer, Hubertus; Bjerregaard, Beth; von Keyserlingk, Diedrich Graf

2004-11-01

To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.

Empathizing, systemizing, and autistic traits: latent structure in individuals with autism, their parents, and general population controls.

PubMed

Grove, Rachel; Baillie, Andrew; Allison, Carrie; Baron-Cohen, Simon; Hoekstra, Rosa A

2013-05-01

The search for genes involved in autism spectrum conditions (ASC) may have been hindered by the assumption that the different symptoms that define the condition can be attributed to the same causal mechanism. Instead the social and nonsocial aspects of ASC may have distinct causes at genetic, cognitive, and neural levels. It has been posited that the core features of ASC can be explained by a deficit in empathizing alongside intact or superior systemizing; the drive to understand and derive rules about a system. First-degree relatives also show some mild manifestations that parallel the defining features of ASC, termed the broader autism phenotype. Factor analyses were conducted to assess whether the latent structure of empathizing, systemizing, and autistic traits differs across samples with a high (individuals on the spectrum), medium (first-degree relatives) or low (general population controls) genetic vulnerability to autism. Results highlighted a two-factor model, confirming an empathizing and a systemizing factor. The relationship between these two factors was significantly stronger in first-degree relatives and the autism group compared with controls. The same model provided the best fit among the three groups, suggesting a similar latent structure irrespective of genetic vulnerability. However, results also suggest that although these traits are relatively independent in the general population, they are substantially correlated in individuals with ASC and their parents. This implies that there is substantially more overlap between systemizing and empathizing among individuals with an increased genetic liability to autism. This has potential implications for the genetic, environmental, and cognitive explanations of autism spectrum conditions. © 2013 American Psychological Association

Genetics on the Fly: A Primer on the Drosophila Model System

PubMed Central

Hales, Karen G.; Korey, Christopher A.; Larracuente, Amanda M.; Roberts, David M.

2015-01-01

Fruit flies of the genus Drosophila have been an attractive and effective genetic model organism since Thomas Hunt Morgan and colleagues made seminal discoveries with them a century ago. Work with Drosophila has enabled dramatic advances in cell and developmental biology, neurobiology and behavior, molecular biology, evolutionary and population genetics, and other fields. With more tissue types and observable behaviors than in other short-generation model organisms, and with vast genome data available for many species within the genus, the fly’s tractable complexity will continue to enable exciting opportunities to explore mechanisms of complex developmental programs, behaviors, and broader evolutionary questions. This primer describes the organism’s natural history, the features of sequenced genomes within the genus, the wide range of available genetic tools and online resources, the types of biological questions Drosophila can help address, and historical milestones. PMID:26564900

Sleep and Development in Genetically Tractable Model Organisms.

PubMed

Kayser, Matthew S; Biron, David

2016-05-01

Sleep is widely recognized as essential, but without a clear singular function. Inadequate sleep impairs cognition, metabolism, immune function, and many other processes. Work in genetic model systems has greatly expanded our understanding of basic sleep neurobiology as well as introduced new concepts for why we sleep. Among these is an idea with its roots in human work nearly 50 years old: sleep in early life is crucial for normal brain maturation. Nearly all known species that sleep do so more while immature, and this increased sleep coincides with a period of exuberant synaptogenesis and massive neural circuit remodeling. Adequate sleep also appears critical for normal neurodevelopmental progression. This article describes recent findings regarding molecular and circuit mechanisms of sleep, with a focus on development and the insights garnered from models amenable to detailed genetic analyses. Copyright © 2016 by the Genetics Society of America.

Short communication: Estimates of genetic parameters for dairy fertility in New Zealand.

PubMed

Amer, P R; Stachowicz, K; Jenkins, G M; Meier, S

2016-10-01

Reproductive performance of dairy cows in a seasonal calving system is especially important as cows are required to achieve a 365-d calving interval. Prior research with a small data set has identified that the genetic evaluation model for fertility could be enhanced by replacing the binary calving rate trait (CR42), which gives the probability of a cow calving within the first 42d since the planned start of calving at second, third, and fourth calving, with a continuous version, calving season day (CSD), including a heifer calving season day trait expressed at first calving, removing milk yield, retaining a probability of mating trait (PM21) which gives the probability of a cow being mated within the first 21d from the planned start of mating, and first lactation body condition score (BCS), and including gestation length (GL). The aim of this study was to estimate genetic parameters for the proposed new model using a larger data set and compare these with parameters used in the current system. Heritability estimates for CSD and PM21 ranged from 0.013 to 0.019 and from 0.031 to 0.058, respectively. For the 2 traits that correspond with the ones used in the current genetic evaluation system (mating trait, PM21 and BCS) genetic correlations were lower in this study compared with previous estimates. Genetic correlations between CSD and PM21 across different parities were also lower than the correlations between CR42 and PM21 reported previously. The genetic correlation between heifer CSD and CSD in first parity was 0.66. Estimates of genetic correlations of BCS with CSD were higher than those with PM21. For GL, direct heritability was estimated to be 0.67, maternal heritability was 0.11, and maternal repeatability was 0.22. Direct GL had moderate to high and favorable genetic correlations with evaluated fertility traits, whereas corresponding residual correlations remain low, which makes GL a useful candidate predictor trait for fertility in a multiple trait evaluation. The superiority of direct GL genetic component over the maternal GL component for predicting fertility was demonstrated. Future work planned in this area includes the implementation and testing of this new model on national fertility data. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Challenges and Advances for Genetic Engineering of Non-model Bacteria and Uses in Consolidated Bioprocessing

PubMed Central

Yan, Qiang; Fong, Stephen S.

2017-01-01

Metabolic diversity in microorganisms can provide the basis for creating novel biochemical products. However, most metabolic engineering projects utilize a handful of established model organisms and thus, a challenge for harnessing the potential of novel microbial functions is the ability to either heterologously express novel genes or directly utilize non-model organisms. Genetic manipulation of non-model microorganisms is still challenging due to organism-specific nuances that hinder universal molecular genetic tools and translatable knowledge of intracellular biochemical pathways and regulatory mechanisms. However, in the past several years, unprecedented progress has been made in synthetic biology, molecular genetics tools development, applications of omics data techniques, and computational tools that can aid in developing non-model hosts in a systematic manner. In this review, we focus on concerns and approaches related to working with non-model microorganisms including developing molecular genetics tools such as shuttle vectors, selectable markers, and expression systems. In addition, we will discuss: (1) current techniques in controlling gene expression (transcriptional/translational level), (2) advances in site-specific genome engineering tools [homologous recombination (HR) and clustered regularly interspaced short palindromic repeats (CRISPR)], and (3) advances in genome-scale metabolic models (GSMMs) in guiding design of non-model species. Application of these principles to metabolic engineering strategies for consolidated bioprocessing (CBP) will be discussed along with some brief comments on foreseeable future prospects. PMID:29123506

A Genetic Animal Model of Alcoholism for Screening Medications to Treat Addiction

PubMed Central

Bell, Richard L.; Hauser, Sheketha; Rodd, Zachary A.; Liang, Tiebing; Sari, Youssef; McClintick, Jeanette; Rahman, Shafiqur; Engleman, Eric A.

2016-01-01

The purpose of this review is to present up-to-date pharmacological, genetic and behavioral findings from the alcohol-preferring P rat and summarize similar past work. Behaviorally, the focus will be on how the P rat meets criteria put forth for a valid animal model of alcoholism with a highlight on its use as an animal model of polysubstance abuse, including alcohol, nicotine and psychostimulants. Pharmacologically and genetically, the focus will be on the neurotransmitter and neuropeptide systems that have received the most attention: cholinergic, dopaminergic, GABAergic, glutamatergic, serotonergic, noradrenergic, corticotrophin releasing hormone, opioid, and neuropeptide Y. Herein we sought to place the P rat’s behavioral and neurochemical phenotypes, and to some extent its genotype, in the context of the clinical literature. After reviewing the findings thus far, this paper discusses future directions for expanding the use of this genetic animal model of alcoholism to identify molecular targets for treating drug addiction in general. PMID:27055615

Ghrelin and eating behavior: evidence and insights from genetically-modified mouse models

PubMed Central

Uchida, Aki; Zigman, Jeffrey M.; Perelló, Mario

2013-01-01

Ghrelin is an octanoylated peptide hormone, produced by endocrine cells of the stomach, which acts in the brain to increase food intake and body weight. Our understanding of the mechanisms underlying ghrelin's effects on eating behaviors has been greatly improved by the generation and study of several genetically manipulated mouse models. These models include mice overexpressing ghrelin and also mice with genetic deletion of ghrelin, the ghrelin receptor [the growth hormone secretagogue receptor (GHSR)] or the enzyme that post-translationally modifies ghrelin [ghrelin O-acyltransferase (GOAT)]. In addition, a GHSR-null mouse model in which GHSR transcription is globally blocked but can be cell-specifically reactivated in a Cre recombinase-mediated fashion has been generated. Here, we summarize findings obtained with these genetically manipulated mice, with the aim to highlight the significance of the ghrelin system in the regulation of both homeostatic and hedonic eating, including that occurring in the setting of chronic psychosocial stress. PMID:23882175

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

Female and male genetic effects on offspring paternity: additive genetic (co)variances in female extra-pair reproduction and male paternity success in song sparrows (Melospiza melodia).

PubMed

Reid, Jane M; Arcese, Peter; Keller, Lukas F; Losdat, Sylvain

2014-08-01

Ongoing evolution of polyandry, and consequent extra-pair reproduction in socially monogamous systems, is hypothesized to be facilitated by indirect selection stemming from cross-sex genetic covariances with components of male fitness. Specifically, polyandry is hypothesized to create positive genetic covariance with male paternity success due to inevitable assortative reproduction, driving ongoing coevolution. However, it remains unclear whether such covariances could or do emerge within complex polyandrous systems. First, we illustrate that genetic covariances between female extra-pair reproduction and male within-pair paternity success might be constrained in socially monogamous systems where female and male additive genetic effects can have opposing impacts on the paternity of jointly reared offspring. Second, we demonstrate nonzero additive genetic variance in female liability for extra-pair reproduction and male liability for within-pair paternity success, modeled as direct and associative genetic effects on offspring paternity, respectively, in free-living song sparrows (Melospiza melodia). The posterior mean additive genetic covariance between these liabilities was slightly positive, but the credible interval was wide and overlapped zero. Therefore, although substantial total additive genetic variance exists, the hypothesis that ongoing evolution of female extra-pair reproduction is facilitated by genetic covariance with male within-pair paternity success cannot yet be definitively supported or rejected either conceptually or empirically. © 2014 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

Breeding objectives for indigenous chicken: model development and application to different production systems.

PubMed

Okeno, Tobias O; Magothe, Thomas M; Kahi, Alexander K; Peters, Kurt J

2013-01-01

A bio-economic model was developed to evaluate the utilisation of indigenous chickens (IC) under different production systems accounting for the risk attitude of the farmers. The model classified the production systems into three categories based on the level of management: free-range system (FRS), where chickens were left to scavenge for feed resources with no supplementation and healthcare; intensive system (IS), where the chickens were permanently confined and supplied with rationed feed and healthcare; and semi-intensive system (SIS), a hybrid of FRS and IS, where the chickens were partially confined, supplemented with rationed feeds, provided with healthcare and allowed to scavenge within the homestead or in runs. The model allows prediction of the live weights and feed intake at different stages in the life cycle of the IC and can compute the profitability of each production system using both traditional and risk-rated profit models. The input parameters used in the model represent a typical IC production system in developing countries but are flexible and therefore can be modified to suit specific situations and simulate profitability and costs of other poultry species production systems. The model has the capability to derive the economic values as changes in the genetic merit of the biological parameter results in marginal changes in profitability and costs of the production systems. The results suggested that utilisation of IC in their current genetic merit and production environment is more profitable under FRS and SIS but not economically viable under IS.

A robust computational technique for model order reduction of two-time-scale discrete systems via genetic algorithms.

PubMed

Alsmadi, Othman M K; Abo-Hammour, Zaer S

2015-01-01

A robust computational technique for model order reduction (MOR) of multi-time-scale discrete systems (single input single output (SISO) and multi-input multioutput (MIMO)) is presented in this paper. This work is motivated by the singular perturbation of multi-time-scale systems where some specific dynamics may not have significant influence on the overall system behavior. The new approach is proposed using genetic algorithms (GA) with the advantage of obtaining a reduced order model, maintaining the exact dominant dynamics in the reduced order, and minimizing the steady state error. The reduction process is performed by obtaining an upper triangular transformed matrix of the system state matrix defined in state space representation along with the elements of B, C, and D matrices. The GA computational procedure is based on maximizing the fitness function corresponding to the response deviation between the full and reduced order models. The proposed computational intelligence MOR method is compared to recently published work on MOR techniques where simulation results show the potential and advantages of the new approach.

The simulation method of chemical composition of vermicular graphite iron on the basis of genetic algorithm

NASA Astrophysics Data System (ADS)

Yusupov, L. R.; Klochkova, K. V.; Simonova, L. A.

2017-09-01

The paper presents a methodology of modeling the chemical composition of the composite material via genetic algorithm for optimization of the manufacturing process of products. The paper presents algorithms of methods based on intelligent system of vermicular graphite iron design

Studying Human Disease Genes in "Caenorhabditis Elegans": A Molecular Genetics Laboratory Project

ERIC Educational Resources Information Center

Cox-Paulson, Elisabeth A.; Grana, Theresa M.; Harris, Michelle A.; Batzli, Janet M.

2012-01-01

Scientists routinely integrate information from various channels to explore topics under study. We designed a 4-wk undergraduate laboratory module that used a multifaceted approach to study a question in molecular genetics. Specifically, students investigated whether "Caenorhabditis elegans" can be a useful model system for studying genes…

Genetic Algorithm Phase Retrieval for the Systematic Image-Based Optical Alignment Testbed

NASA Technical Reports Server (NTRS)

Rakoczy, John; Steincamp, James; Taylor, Jaime

2003-01-01

A reduced surrogate, one point crossover genetic algorithm with random rank-based selection was used successfully to estimate the multiple phases of a segmented optical system modeled on the seven-mirror Systematic Image-Based Optical Alignment testbed located at NASA's Marshall Space Flight Center.

Beyond the Central Dogma: Model-Based Learning of How Genes Determine Phenotypes

PubMed Central

Reinagel, Adam; Bray Speth, Elena

2016-01-01

In an introductory biology course, we implemented a learner-centered, model-based pedagogy that frequently engaged students in building conceptual models to explain how genes determine phenotypes. Model-building tasks were incorporated within case studies and aimed at eliciting students’ understanding of 1) the origin of variation in a population and 2) how genes/alleles determine phenotypes. Guided by theory on hierarchical development of systems-thinking skills, we scaffolded instruction and assessment so that students would first focus on articulating isolated relationships between pairs of molecular genetics structures and then integrate these relationships into an explanatory network. We analyzed models students generated on two exams to assess whether students’ learning of molecular genetics progressed along the theoretical hierarchical sequence of systems-thinking skills acquisition. With repeated practice, peer discussion, and instructor feedback over the course of the semester, students’ models became more accurate, better contextualized, and more meaningful. At the end of the semester, however, more than 25% of students still struggled to describe phenotype as an output of protein function. We therefore recommend that 1) practices like modeling, which require connecting genes to phenotypes; and 2) well-developed case studies highlighting proteins and their functions, take center stage in molecular genetics instruction. PMID:26903496

Sex determination in flowering plants: papaya as a model system.

PubMed

Aryal, Rishi; Ming, Ray

2014-03-01

Unisexuality in flowering plants evolved from a hermaphrodite ancestor. Transition from hermaphrodite to unisexual flowers has occurred multiple times across the different lineages of the angiosperms. Sexuality in plants is regulated by genetic, epigenetic and physiological mechanisms. The most specialized mechanism of sex determination is sex chromosomes. The sex chromosomes ensure the stable segregation of sexual phenotypes by preventing the recombination of sex determining genes. Despite continuous efforts, sex determining genes of dioecious plants have not yet been cloned. Concerted efforts with various model systems are necessary to understand the complex mechanism of sex determination in plants. Papaya (Carica papaya L.) is a tropical fruit tree with three sex forms, male, hermaphrodite, and female. Sexuality in papaya is determined by an XY chromosome system that is in an early evolutionary stage. The male and hermaphrodite of papaya are controlled by two different types of Y chromosomes: Y and Y(h). Large amounts of information in the area of genetics, genomics, and epigenetics of papaya have been accumulated over the last few decades. Relatively short lifecycle, small genome size, and readily available genetic and genomic resources render papaya an excellent model system to study sex determination and sex chromosomes in flowering plants. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Comparing ESC and iPSC-Based Models for Human Genetic Disorders.

PubMed

Halevy, Tomer; Urbach, Achia

2014-10-24

Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs) from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs) from patients' somatic cells, and the new technologies for genome editing of pluripotent stem cells have opened a new window of opportunities in the field of disease modeling, and enabled studying diseases that couldn't be modeled in the past. Importantly, despite the high similarity between ESCs and iPSCs, there are several fundamental differences between these cells, which have important implications regarding disease modeling. In this review we compare ESC-based models to iPSC-based models, and highlight the advantages and disadvantages of each system. We further suggest a roadmap for how to choose the optimal strategy to model each specific disorder.

Standing variation in spatially growing populations

NASA Astrophysics Data System (ADS)

Fusco, Diana; Gralka, Matti; Kayser, Jona; Hallatschek, Oskar

Patterns of genetic diversity not only reflect the evolutionary history of a species but they can also determine the evolutionary response to environmental change. For instance, the standing genetic diversity of a microbial population can be key to rescue in the face of an antibiotic attack. While genetic diversity is in general shaped by both demography and evolution, very little is understood when both factors matter, as e.g. for biofilms with pronounced spatial organization. Here, we quantitatively explore patterns of genetic diversity by using microbial colonies and well-mixed test tube populations as antipodal model systems with extreme and very little spatial structure, respectively. We find that Eden model simulations and KPZ theory can remarkably reproduce the genetic diversity in microbial colonies obtained via population sequencing. The excellent agreement allows to draw conclusions on the resilience of spatially-organized populations and to uncover new strategies to contain antibiotic resistance.

Comparative Analysis of Soft Computing Models in Prediction of Bending Rigidity of Cotton Woven Fabrics

NASA Astrophysics Data System (ADS)

Guruprasad, R.; Behera, B. K.

2015-10-01

Quantitative prediction of fabric mechanical properties is an essential requirement for design engineering of textile and apparel products. In this work, the possibility of prediction of bending rigidity of cotton woven fabrics has been explored with the application of Artificial Neural Network (ANN) and two hybrid methodologies, namely Neuro-genetic modeling and Adaptive Neuro-Fuzzy Inference System (ANFIS) modeling. For this purpose, a set of cotton woven grey fabrics was desized, scoured and relaxed. The fabrics were then conditioned and tested for bending properties. With the database thus created, a neural network model was first developed using back propagation as the learning algorithm. The second model was developed by applying a hybrid learning strategy, in which genetic algorithm was first used as a learning algorithm to optimize the number of neurons and connection weights of the neural network. The Genetic algorithm optimized network structure was further allowed to learn using back propagation algorithm. In the third model, an ANFIS modeling approach was attempted to map the input-output data. The prediction performances of the models were compared and a sensitivity analysis was reported. The results show that the prediction by neuro-genetic and ANFIS models were better in comparison with that of back propagation neural network model.

Approaching Resistance to Targeted Inhibition of PI3K in Breast Cancer

DTIC Science & Technology

2011-10-01

promise, there are concerns that drug resistance may emerge within the cancerous cells, thus limiting clinical efficacy. Using genetically defined human...mechanism of such resistance. Using genetically defined human mammary epithelial cells (HMECs), a model system which has previously been used for PI3K...pathway driven transformation due to its dependence on oncogenic PI3K signaling, we screened for emergence of BEZ235-resistance and identified genetic

Biological engineering applications of feedforward neural networks designed and parameterized by genetic algorithms.

PubMed

Ferentinos, Konstantinos P

2005-09-01

Two neural network (NN) applications in the field of biological engineering are developed, designed and parameterized by an evolutionary method based on the evolutionary process of genetic algorithms. The developed systems are a fault detection NN model and a predictive modeling NN system. An indirect or 'weak specification' representation was used for the encoding of NN topologies and training parameters into genes of the genetic algorithm (GA). Some a priori knowledge of the demands in network topology for specific application cases is required by this approach, so that the infinite search space of the problem is limited to some reasonable degree. Both one-hidden-layer and two-hidden-layer network architectures were explored by the GA. Except for the network architecture, each gene of the GA also encoded the type of activation functions in both hidden and output nodes of the NN and the type of minimization algorithm that was used by the backpropagation algorithm for the training of the NN. Both models achieved satisfactory performance, while the GA system proved to be a powerful tool that can successfully replace the problematic trial-and-error approach that is usually used for these tasks.

Cellular Reprogramming, Genome Editing, and Alternative CRISPR Cas9 Technologies for Precise Gene Therapy of Duchenne Muscular Dystrophy

PubMed Central

Xu, Huaigeng

2017-01-01

In the past decade, the development of two innovative technologies, namely, induced pluripotent stem cells (iPSCs) and the CRISPR Cas9 system, has enabled researchers to model diseases derived from patient cells and precisely edit DNA sequences of interest, respectively. In particular, Duchenne muscular dystrophy (DMD) has been an exemplary monogenic disease model for combining these technologies to demonstrate that genome editing can correct genetic mutations in DMD patient-derived iPSCs. DMD is an X-linked genetic disorder caused by mutations that disrupt the open reading frame of the dystrophin gene, which plays a critical role in stabilizing muscle cells during contraction and relaxation. The CRISPR Cas9 system has been shown to be capable of targeting the dystrophin gene and rescuing its expression in in vitro patient-derived iPSCs and in vivo DMD mouse models. In this review, we highlight recent advances made using the CRISPR Cas9 system to correct genetic mutations and discuss how emerging CRISPR technologies and iPSCs in a combined platform can play a role in bringing a therapy for DMD closer to the clinic. PMID:28607562

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

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

Control of Stochastic Master Equation Models of Genetic Regulatory Networks by Approximating Their Average Behavior

NASA Astrophysics Data System (ADS)

Umut Caglar, Mehmet; Pal, Ranadip

2010-10-01

The central dogma of molecular biology states that ``information cannot be transferred back from protein to either protein or nucleic acid.'' However, this assumption is not exactly correct in most of the cases. There are a lot of feedback loops and interactions between different levels of systems. These types of interactions are hard to analyze due to the lack of data in the cellular level and probabilistic nature of interactions. Probabilistic models like Stochastic Master Equation (SME) or deterministic models like differential equations (DE) can be used to analyze these types of interactions. SME models based on chemical master equation (CME) can provide detailed representation of genetic regulatory system, but their use is restricted by the large data requirements and computational costs of calculations. The differential equations models on the other hand, have low calculation costs and much more adequate to generate control procedures on the system; but they are not adequate to investigate the probabilistic nature of interactions. In this work the success of the mapping between SME and DE is analyzed, and the success of a control policy generated by DE model with respect to SME model is examined. Index Terms--- Stochastic Master Equation models, Differential Equation Models, Control Policy Design, Systems biology

Coexistence of sexual individuals and genetically isolated asexual counterparts in a thrips.

PubMed

Kobayashi, Kazuya; Yoshimura, Jin; Hasegawa, Eisuke

2013-11-21

Sex is a paradoxical phenomenon because it is less efficient compared with asexual reproduction. To resolve this paradox we need a direct comparison between sexual and asexual forms. In many organisms, however, sexual and asexual forms do not occur in the same habitat, or at the same time. In a few cases where sexual and asexual forms are found in a single population, some (though rare) genetic exchange is usually detected between the two forms. When genetic exchange occurs a direct comparison is impossible. Here we investigate a thrips exhibiting both sexual and asexual forms (lineages) that are morphologically indistinguishable. We examine if the two forms are genetically isolated. Phylogeny based on nuclear genes confirms that the sexual and asexual lineages are genetically differentiated. Thus we demonstrate that the current system has certain advantages over existing and previously used model systems in the evolution of sexual reproduction.

Reasoning over genetic variance information in cause-and-effect models of neurodegenerative diseases

PubMed Central

Naz, Mufassra; Kodamullil, Alpha Tom

2016-01-01

The work we present here is based on the recent extension of the syntax of the Biological Expression Language (BEL), which now allows for the representation of genetic variation information in cause-and-effect models. In our article, we describe, how genetic variation information can be used to identify candidate disease mechanisms in diseases with complex aetiology such as Alzheimer’s disease and Parkinson’s disease. In those diseases, we have to assume that many genetic variants contribute moderately to the overall dysregulation that in the case of neurodegenerative diseases has such a long incubation time until the first clinical symptoms are detectable. Owing to the multilevel nature of dysregulation events, systems biomedicine modelling approaches need to combine mechanistic information from various levels, including gene expression, microRNA (miRNA) expression, protein–protein interaction, genetic variation and pathway. OpenBEL, the open source version of BEL, has recently been extended to match this requirement, and we demonstrate in our article, how candidate mechanisms for early dysregulation events in Alzheimer’s disease can be identified based on an integrative mining approach that identifies ‘chains of causation’ that include single nucleotide polymorphism information in BEL models. PMID:26249223

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).

Patterns and Mechanisms of Evolutionary Transitions between Genetic Sex-Determining Systems

PubMed Central

Sander van Doorn, G.

2014-01-01

The diversity and patchy phylogenetic distribution of genetic sex-determining mechanisms observed in some taxa is thought to have arisen by the addition, modification, or replacement of regulators at the upstream end of the sex-determining pathway. Here, I review the various evolutionary forces acting on upstream regulators of sexual development that can cause transitions between sex-determining systems. These include sex-ratio selection and pleiotropic benefits, as well as indirect selection mechanisms involving sex-linked sexually antagonistic loci or recessive deleterious mutations. Most of the current theory concentrates on the population–genetic aspects of sex-determination transitions, using models that do not reflect the developmental mechanisms involved in sex determination. However, the increasing availability of molecular data creates opportunities for the development of mechanistic models that can clarify how selection and developmental architecture interact to direct the evolution of sex-determination genes. PMID:24993578

Genetic Adaptive Control for PZT Actuators

NASA Technical Reports Server (NTRS)

Kim, Jeongwook; Stover, Shelley K.; Madisetti, Vijay K.

1995-01-01

A piezoelectric transducer (PZT) is capable of providing linear motion if controlled correctly and could provide a replacement for traditional heavy and large servo systems using motors. This paper focuses on a genetic model reference adaptive control technique (GMRAC) for a PZT which is moving a mirror where the goal is to keep the mirror velocity constant. Genetic Algorithms (GAs) are an integral part of the GMRAC technique acting as the search engine for an optimal PID controller. Two methods are suggested to control the actuator in this research. The first one is to change the PID parameters and the other is to add an additional reference input in the system. The simulation results of these two methods are compared. Simulated Annealing (SA) is also used to solve the problem. Simulation results of GAs and SA are compared after simulation. GAs show the best result according to the simulation results. The entire model is designed using the Mathworks' Simulink tool.

Two-photon calcium imaging from head-fixed Drosophila during optomotor walking behavior.

PubMed

Seelig, Johannes D; Chiappe, M Eugenia; Lott, Gus K; Dutta, Anirban; Osborne, Jason E; Reiser, Michael B; Jayaraman, Vivek

2010-07-01

Drosophila melanogaster is a model organism rich in genetic tools to manipulate and identify neural circuits involved in specific behaviors. Here we present a technique for two-photon calcium imaging in the central brain of head-fixed Drosophila walking on an air-supported ball. The ball's motion is tracked at high resolution and can be treated as a proxy for the fly's own movements. We used the genetically encoded calcium sensor, GCaMP3.0, to record from important elements of the motion-processing pathway, the horizontal-system lobula plate tangential cells (LPTCs) in the fly optic lobe. We presented motion stimuli to the tethered fly and found that calcium transients in horizontal-system neurons correlated with robust optomotor behavior during walking. Our technique allows both behavior and physiology in identified neurons to be monitored in a genetic model organism with an extensive repertoire of walking behaviors.

A genetic fuzzy system for unstable angina risk assessment.

PubMed

Dong, Wei; Huang, Zhengxing; Ji, Lei; Duan, Huilong

2014-02-18

Unstable Angina (UA) is widely accepted as a critical phase of coronary heart disease with patients exhibiting widely varying risks. Early risk assessment of UA is at the center of the management program, which allows physicians to categorize patients according to the clinical characteristics and stratification of risk and different prognosis. Although many prognostic models have been widely used for UA risk assessment in clinical practice, a number of studies have highlighted possible shortcomings. One serious drawback is that existing models lack the ability to deal with the intrinsic uncertainty about the variables utilized. In order to help physicians refine knowledge for the stratification of UA risk with respect to vagueness in information, this paper develops an intelligent system combining genetic algorithm and fuzzy association rule mining. In detail, it models the input information's vagueness through fuzzy sets, and then applies a genetic fuzzy system on the acquired fuzzy sets to extract the fuzzy rule set for the problem of UA risk assessment. The proposed system is evaluated using a real data-set collected from the cardiology department of a Chinese hospital, which consists of 54 patient cases. 9 numerical patient features and 17 categorical patient features that appear in the data-set are selected in the experiments. The proposed system made the same decisions as the physician in 46 (out of a total of 54) tested cases (85.2%). By comparing the results that are obtained through the proposed system with those resulting from the physician's decision, it has been found that the developed model is highly reflective of reality. The proposed system could be used for educational purposes, and with further improvements, could assist and guide young physicians in their daily work.

Drosophila as a model system to study autophagy.

PubMed

Zirin, Jonathan; Perrimon, Norbert

2010-12-01

Originally identified as a response to starvation in yeast, autophagy is now understood to fulfill a variety of roles in higher eukaryotes, from the maintenance of cellular homeostasis to the cellular response to stress, starvation, and infection. Although genetics and biochemical studies in yeast have identified many components involved in autophagy, the findings that some of the essential components of the yeast pathway are missing in higher organisms underscore the need to study autophagy in more complex systems. This review focuses on the use of the fruitfly, Drosophila melanogaster as a model system for analysis of autophagy. Drosophila is an organism well-suited for genetic analysis and represents an intermediate between yeast and mammals with respect to conservation of the autophagy machinery. Furthermore, the complex biology and physiology of Drosophila presents an opportunity to model human diseases in a tissue specific and analogous context.

Drosophila models of amyotrophic lateral sclerosis with defects in RNA metabolism.

PubMed

Zhang, Ke; Coyne, Alyssa N; Lloyd, Thomas E

2018-05-09

The fruit fly Drosophila Melanogaster has been widely used to study neurodegenerative diseases. The conservation of nervous system biology coupled with the rapid life cycle and powerful genetic tools in the fly have enabled the identification of novel therapeutic targets that have been validated in vertebrate model systems and human patients. A recent example is in the study of the devastating motor neuron degenerative disease amyotrophic lateral sclerosis (ALS). Mutations in genes that regulate RNA metabolism are a major cause of inherited ALS, and functional analysis of these genes in the fly nervous system has shed light on how mutations cause disease. Importantly, unbiased genetic screens have identified key pathways that contribute to ALS pathogenesis such as nucleocytoplasmic transport and stress granule assembly. In this review, we will discuss the utilization of Drosophila models of ALS with defects in RNA metabolism. Copyright © 2018 Elsevier B.V. All rights reserved.

Interactions Between Genetics, Lifestyle, and Environmental Factors for Healthcare.

PubMed

Lin, Yuxin; Chen, Jiajia; Shen, Bairong

2017-01-01

The occurrence and progression of diseases are strongly associated with a combination of genetic, lifestyle, and environmental factors. Understanding the interplay between genetic and nongenetic components provides deep insights into disease pathogenesis and promotes personalized strategies for people healthcare. Recently, the paradigm of systems medicine, which integrates biomedical data and knowledge at multidimensional levels, is considered to be an optimal way for disease management and clinical decision-making in the era of precision medicine. In this chapter, epigenetic-mediated genetics-lifestyle-environment interactions within specific diseases and different ethnic groups are systematically discussed, and data sources, computational models, and translational platforms for systems medicine research are sequentially presented. Moreover, feasible suggestions on precision healthcare and healthy longevity are kindly proposed based on the comprehensive review of current studies.

Improving the efficiency of a user-driven learning system with reconfigurable hardware. Application to DNA splicing.

PubMed

Lemoine, E; Merceron, D; Sallantin, J; Nguifo, E M

1999-01-01

This paper describes a new approach to problem solving by splitting up problem component parts between software and hardware. Our main idea arises from the combination of two previously published works. The first one proposed a conceptual environment of concept modelling in which the machine and the human expert interact. The second one reported an algorithm based on reconfigurable hardware system which outperforms any kind of previously published genetic data base scanning hardware or algorithms. Here we show how efficient the interaction between the machine and the expert is when the concept modelling is based on reconfigurable hardware system. Their cooperation is thus achieved with an real time interaction speed. The designed system has been partially applied to the recognition of primate splice junctions sites in genetic sequences.

Cost-effectiveness analysis of carrier and prenatal genetic testing for X-linked hemophilia.

PubMed

Tsai, Meng-Che; Cheng, Chao-Neng; Wang, Ru-Jay; Chen, Kow-Tong; Kuo, Mei-Chin; Lin, Shio-Jean

2015-08-01

Hemophilia involves a lifelong burden from the perspective of the patient and the entire healthcare system. Advances in genetic testing provide valuable information to hemophilia-affected families for family planning. The aim of this study was to analyze the cost-effectiveness of carrier and prenatal genetic testing in the health-economic framework in Taiwan. A questionnaire was developed to assess the attitudes towards genetic testing for hemophilia. We modeled clinical outcomes of the proposed testing scheme by using the decision tree method. Incremental cost-effectiveness analysis was conducted, based on data from the National Health Insurance (NHI) database and a questionnaire survey. From the NHI database, 1111 hemophilic patients were identified and required an average medical expenditure of approximately New Taiwan (NT) $2.1 million per patient-year in 2009. By using the decision tree model, we estimated that 26 potential carriers need to be tested to prevent one case of hemophilia. At a screening rate of 79%, carrier and prenatal genetic testing would cost NT $85.9 million, which would be offset by an incremental saving of NT $203 million per year by preventing 96 cases of hemophilia. Assuming that the life expectancy for hemophilic patients is 70 years, genetic testing could further save NT $14.2 billion. Higher screening rates would increase the savings for healthcare resources. Carrier and prenatal genetic testing for hemophilia is a cost-effective investment in healthcare allocation. A case management system should be integrated in the current practice to facilitate patient care (e.g., collecting family pedigrees and providing genetic counseling). Copyright © 2013. Published by Elsevier B.V.

Using bioinformatics and systems genetics to dissect HDL-cholesterol genetics in an MRL/MpJ x SM/J intercross.

PubMed

Leduc, Magalie S; Blair, Rachael Hageman; Verdugo, Ricardo A; Tsaih, Shirng-Wern; Walsh, Kenneth; Churchill, Gary A; Paigen, Beverly

2012-06-01

A higher incidence of coronary artery disease is associated with a lower level of HDL-cholesterol. We searched for genetic loci influencing HDL-cholesterol in F2 mice from a cross between MRL/MpJ and SM/J mice. Quantitative trait loci (QTL) mapping revealed one significant HDL QTL (Apoa2 locus), four suggestive QTL on chromosomes 10, 11, 13, and 18 and four additional QTL on chromosomes 1 proximal, 3, 4, and 7 after adjusting HDL for the strong Apoa2 locus. A novel nonsynonymous polymorphism supports Lipg as the QTL gene for the chromosome 18 QTL, and a difference in Abca1 expression in liver tissue supports it as the QTL gene for the chromosome 4 QTL. Using weighted gene co-expression network analysis, we identified a module that after adjustment for Apoa2, correlated with HDL, was genetically determined by a QTL on chromosome 11, and overlapped with the HDL QTL. A combination of bioinformatics tools and systems genetics helped identify several candidate genes for both the chromosome 11 HDL and module QTL based on differential expression between the parental strains, cis regulation of expression, and causality modeling. We conclude that integrating systems genetics to a more-traditional genetics approach improves the power of complex trait gene identification.

Inference of Vohradský's Models of Genetic Networks by Solving Two-Dimensional Function Optimization Problems

PubMed Central

Kimura, Shuhei; Sato, Masanao; Okada-Hatakeyama, Mariko

2013-01-01

The inference of a genetic network is a problem in which mutual interactions among genes are inferred from time-series of gene expression levels. While a number of models have been proposed to describe genetic networks, this study focuses on a mathematical model proposed by Vohradský. Because of its advantageous features, several researchers have proposed the inference methods based on Vohradský's model. When trying to analyze large-scale networks consisting of dozens of genes, however, these methods must solve high-dimensional non-linear function optimization problems. In order to resolve the difficulty of estimating the parameters of the Vohradský's model, this study proposes a new method that defines the problem as several two-dimensional function optimization problems. Through numerical experiments on artificial genetic network inference problems, we showed that, although the computation time of the proposed method is not the shortest, the method has the ability to estimate parameters of Vohradský's models more effectively with sufficiently short computation times. This study then applied the proposed method to an actual inference problem of the bacterial SOS DNA repair system, and succeeded in finding several reasonable regulations. PMID:24386175

Construction of a Recyclable Genetic Marker and Serial Gene Deletions in the Human Pathogenic Mucorales Mucor circinelloides.

PubMed

Garcia, Alexis; Adedoyin, Gloria; Heitman, Joseph; Lee, Soo Chan

2017-07-05

Mucor circinelloides is a human pathogen, biofuel producer, and model system that belongs to a basal fungal lineage; however, the genetics of this fungus are limited. In contrast to ascomycetes and basidiomycetes, basal fungal lineages have been understudied. This may be caused by a lack of attention given to these fungi, as well as limited tools for genetic analysis. Nonetheless, the importance of these fungi as pathogens and model systems has increased. M. circinelloides is one of a few genetically tractable organisms in the basal fungi, but it is far from a robust genetic system when compared to model fungi in the subkingdom Dikarya. One problem is the organism is resistant to drugs utilized to select for dominant markers in other fungal transformation systems. Thus, we developed a blaster recyclable marker system by using the pyrG gene (encoding an orotidine-5'-phosphate decarboxylase, ortholog of URA3 in Saccharomyces cerevisiae ). A 237-bp fragment downstream of the pyrG gene was tandemly incorporated into the upstream region of the gene, resulting in construction of a pyrG-dpl237 marker. To test the functionality of the pyrG-dpl237 marker, we disrupted the carRP gene that is involved in carotenoid synthesis in pyrG - mutant background. The resulting carRP :: pyrG-dpl237 mutants exhibit a white colony phenotype due to lack of carotene, whereas wild type displays yellowish colonies. The pyrG marker was then successfully excised, generating carRP-dpl237 on 5-FOA medium. The mutants became auxotrophic and required uridine for growth. We then disrupted the calcineurin B regulatory subunit cnbR gene in the carRP :: dpl237 strain, generating mutants with the alleles carRP :: dpl237 and cnbR :: pyrG These results demonstrate that the recyclable marker system is fully functional, and therefore the pyrG-dpl237 marker can be used for sequential gene deletions in M. circinelloides . Copyright © 2017 Garcia et al.

Research and application of multi-agent genetic algorithm in tower defense game

NASA Astrophysics Data System (ADS)

Jin, Shaohua

2018-04-01

In this paper, a new multi-agent genetic algorithm based on orthogonal experiment is proposed, which is based on multi-agent system, genetic algorithm and orthogonal experimental design. The design of neighborhood competition operator, orthogonal crossover operator, Son and self-learning operator. The new algorithm is applied to mobile tower defense game, according to the characteristics of the game, the establishment of mathematical models, and finally increases the value of the game's monster.

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

Identifying genetic markers of wheat (Triticum aestivum) associated with flavor preference using a mouse model

USDA-ARS?s Scientific Manuscript database

Whole wheat products provide critical nutrients for human health, though differences in wheat flavor are not well understood. Using the house mouse as a model system, flavor was examined using a two-choice feeding system and the Student’s t statistic. To eliminate the confounding effect of processin...

Oxytocin and socioemotional aging: Current knowledge and future trends

PubMed Central

Ebner, Natalie C.; Maura, Gabriela M.; MacDonald, Kai; Westberg, Lars; Fischer, Håkan

2013-01-01

The oxytocin (OT) system is involved in various aspects of social cognition and prosocial behavior. Specifically, OT has been examined in the context of social memory, emotion recognition, cooperation, trust, empathy, and bonding, and—though evidence is somewhat mixed-intranasal OT appears to benefit aspects of socioemotional functioning. However, most of the extant data on aging and OT is from animal research and human OT research has focused largely on young adults. As such, though we know that various socioemotional capacities change with age, we know little about whether age-related changes in the OT system may underlie age-related differences in socioemotional functioning. In this review, we take a genetic-neuro-behavioral approach and evaluate current evidence on age-related changes in the OT system as well as the putative effects of these alterations on age-related socioemotional functioning. Looking forward, we identify informational gaps and propose an Age-Related Genetic, Neurobiological, Sociobehavioral Model of Oxytocin (AGeNeS-OT model) which may structure and inform investigations into aging-related genetic, neural, and sociocognitive processes related to OT. As an exemplar of the use of the model, we report exploratory data suggesting differences in socioemotional processing associated with genetic variation in the oxytocin receptor gene (OXTR) in samples of young and older adults. Information gained from this arena has translational potential in depression, social stress, and anxiety-all of which have high relevance in aging—and may contribute to reducing social isolation and improving well-being of individuals across the lifespan. PMID:24009568

Studying human disease genes in Caenorhabditis elegans: a molecular genetics laboratory project.

PubMed

Cox-Paulson, Elisabeth A; Grana, Theresa M; Harris, Michelle A; Batzli, Janet M

2012-01-01

Scientists routinely integrate information from various channels to explore topics under study. We designed a 4-wk undergraduate laboratory module that used a multifaceted approach to study a question in molecular genetics. Specifically, students investigated whether Caenorhabditis elegans can be a useful model system for studying genes associated with human disease. In a large-enrollment, sophomore-level laboratory course, groups of three to four students were assigned a gene associated with either breast cancer (brc-1), Wilson disease (cua-1), ovarian dysgenesis (fshr-1), or colon cancer (mlh-1). Students compared observable phenotypes of wild-type C. elegans and C. elegans with a homozygous deletion in the assigned gene. They confirmed the genetic deletion with nested polymerase chain reaction and performed a bioinformatics analysis to predict how the deletion would affect the encoded mRNA and protein. Students also performed RNA interference (RNAi) against their assigned gene and evaluated whether RNAi caused a phenotype similar to that of the genetic deletion. As a capstone activity, students prepared scientific posters in which they presented their data, evaluated whether C. elegans was a useful model system for studying their assigned genes, and proposed future directions. Assessment showed gains in understanding genotype versus phenotype, RNAi, common bioinformatics tools, and the utility of model organisms.

Studying Human Disease Genes in Caenorhabditis elegans: A Molecular Genetics Laboratory Project

PubMed Central

Cox-Paulson, Elisabeth A.; Grana, Theresa M.; Harris, Michelle A.; Batzli, Janet M.

2012-01-01

Scientists routinely integrate information from various channels to explore topics under study. We designed a 4-wk undergraduate laboratory module that used a multifaceted approach to study a question in molecular genetics. Specifically, students investigated whether Caenorhabditis elegans can be a useful model system for studying genes associated with human disease. In a large-enrollment, sophomore-level laboratory course, groups of three to four students were assigned a gene associated with either breast cancer (brc-1), Wilson disease (cua-1), ovarian dysgenesis (fshr-1), or colon cancer (mlh-1). Students compared observable phenotypes of wild-type C. elegans and C. elegans with a homozygous deletion in the assigned gene. They confirmed the genetic deletion with nested polymerase chain reaction and performed a bioinformatics analysis to predict how the deletion would affect the encoded mRNA and protein. Students also performed RNA interference (RNAi) against their assigned gene and evaluated whether RNAi caused a phenotype similar to that of the genetic deletion. As a capstone activity, students prepared scientific posters in which they presented their data, evaluated whether C. elegans was a useful model system for studying their assigned genes, and proposed future directions. Assessment showed gains in understanding genotype versus phenotype, RNAi, common bioinformatics tools, and the utility of model organisms. PMID:22665589

Postzygotic isolation involves strong mitochondrial and sex-specific effects in Tigriopus californicus, a species lacking heteromorphic sex chromosomes.

PubMed

Foley, B R; Rose, C G; Rundle, D E; Leong, W; Edmands, S

2013-11-01

Detailed studies of the genetics of speciation have focused on a few model systems, particularly Drosophila. The copepod Tigriopus californicus offers an alternative that differs from standard animal models in that it lacks heteromorphic chromosomes (instead, sex determination is polygenic) and has reduced opportunities for sexual conflict, because females mate only once. Quantitative trait loci (QTL) mapping was conducted on reciprocal F2 hybrids between two strongly differentiated populations, using a saturated linkage map spanning all 12 autosomes and the mitochondrion. By comparing sexes, a possible sex ratio distorter was found but no sex chromosomes. Although studies of standard models often find an excess of hybrid male sterility factors, we found no QTL for sterility and multiple QTL for hybrid viability (indicated by non-Mendelian adult ratios) and other characters. Viability problems were found to be stronger in males, but the usual explanations for weaker hybrid males (sex chromosomes, sensitivity of spermatogenesis, sexual selection) cannot fully account for these male viability problems. Instead, higher metabolic rates may amplify deleterious effects in males. Although many studies of standard speciation models find the strongest genetic incompatibilities to be nuclear-nuclear (specifically X chromosome-autosome), we found the strongest deleterious interaction in this system was mito-nuclear. Consistent with the snowball theory of incompatibility accumulation, we found that trigenic interactions in this highly divergent cross were substantially more frequent (>6×) than digenic interactions. This alternative system thus allows important comparisons to studies of the genetics of reproductive isolation in more standard model systems.

CRISPR/Cas9 System as a Valuable Genome Editing Tool for Wine Yeasts with Application to Decrease Urea Production

PubMed Central

Vigentini, Ileana; Gebbia, Marinella; Belotti, Alessandra; Foschino, Roberto; Roth, Frederick P.

2017-01-01

An extensive repertoire of molecular tools is available for genetic analysis in laboratory strains of S. cerevisiae. Although this has widely contributed to the interpretation of gene functionality within haploid laboratory isolates, the genetics of metabolism in commercially-relevant polyploid yeast strains is still poorly understood. Genetic engineering in industrial yeasts is undergoing major changes due to Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated protein (Cas) engineering approaches. Here we apply the CRISPR/Cas9 system to two commercial “starter” strains of S. cerevisiae (EC1118, AWRI796), eliminating the CAN1 arginine permease pathway to generate strains with reduced urea production (18.5 and 35.5% for EC1118 and AWRI796, respectively). In a wine-model environment based on two grape musts obtained from Chardonnay and Cabernet Sauvignon cultivars, both S. cerevisiae starter strains and CAN1 mutants completed the must fermentation in 8–12 days. However, recombinant strains carrying the can1 mutation failed to produce urea, suggesting that the genetic modification successfully impaired the arginine metabolism. In conclusion, the reduction of urea production in a wine-model environment confirms that the CRISPR/Cas9 system has been successfully established in S. cerevisiae wine yeasts. PMID:29163459

Ciona as a Simple Chordate Model for Heart Development and Regeneration

PubMed Central

Evans Anderson, Heather; Christiaen, Lionel

2016-01-01

Cardiac cell specification and the genetic determinants that govern this process are highly conserved among Chordates. Recent studies have established the importance of evolutionarily-conserved mechanisms in the study of congenital heart defects and disease, as well as cardiac regeneration. As a basal Chordate, the Ciona model system presents a simple scaffold that recapitulates the basic blueprint of cardiac development in Chordates. Here we will focus on the development and cellular structure of the heart of the ascidian Ciona as compared to other Chordates, principally vertebrates. Comparison of the Ciona model system to heart development in other Chordates presents great potential for dissecting the genetic mechanisms that underlie congenital heart defects and disease at the cellular level and might provide additional insight into potential pathways for therapeutic cardiac regeneration. PMID:27642586

Toward a theory of topopatric speciation: The role of genetic assortative mating

NASA Astrophysics Data System (ADS)

Schneider, David M.; do Carmo, Eduardo; Martins, Ayana B.; de Aguiar, Marcus A. M.

2014-09-01

We discuss a minimalist model of assortative mating for sexually reproducing haploid individuals with two biallelic loci. Assortativeness is introduced in the model by preventing mating between individuals whose alleles differ at both loci. Using methods of dynamical systems and population genetics we provide a full description of the evolution of the system for the case of very large populations. We derive the equations governing the evolution of haplotype frequencies and study the equilibrium solutions, stability, and speed of convergence to equilibrium. We find a constant of motion which allows us to introduce a geometrical construction that makes it straightforward to predict the fate of initial conditions. Finally, we discuss the consequences of this class of assortative mating models, including their possible extensions and implications for sympatric and topopatric speciation.

The zebrafish as a model for complex tissue regeneration

PubMed Central

Gemberling, Matthew; Bailey, Travis J.; Hyde, David R.; Poss, Kenneth D.

2013-01-01

For centuries, philosophers and scientists have been fascinated by the principles and implications of regeneration in lower vertebrate species. Two features have made zebrafish an informative model system for determining mechanisms of regenerative events. First, they are highly regenerative, able to regrow amputated fins, as well as a lesioned brain, retina, spinal cord, heart, and other tissues. Second, they are amenable to both forward and reverse genetic approaches, with a research toolset regularly updated by an expanding community of zebrafish researchers. Zebrafish studies have helped identify new mechanistic underpinnings of regeneration in multiple tissues, and in some cases have served as a guide for contemplating regenerative strategies in mammals. Here, we review the recent history of zebrafish as a genetic model system for understanding how and why tissue regeneration occurs. PMID:23927865

Genetically engineered mouse models shed new light on the pathogenesis of neurofibromatosis type I-related neoplasms of the peripheral nervous system.

PubMed

Brossier, Nicole M; Carroll, Steven L

2012-05-01

Neurofibromatosis type 1 (NF1), the most common genetic disorder affecting the human nervous system, is characterized by the development of multiple benign Schwann cell tumors in skin and large peripheral nerves. These neoplasms, which are termed dermal and plexiform neurofibromas respectively, have distinct clinical courses; of particular note, plexiform, but not dermal, neurofibromas often undergo malignant progression to form malignant peripheral nerve sheath tumors (MPNSTs), the most common malignancy occurring in NF1 patients. In recent years, a number of genetically engineered mouse models have been created to investigate the molecular mechanisms driving the pathogenesis of these tumors. These models have been designed to address key questions including: (1) whether NF1 loss in the Schwann cell lineage is essential for tumorigenesis; (2) what cell type(s) in the Schwann cell lineage gives rise to dermal neurofibromas, plexiform neurofibromas and MPNSTs; (3) how the tumor microenvironment contributes to neoplasia; (4) what additional mutations contribute to neurofibroma-MPNST progression; (5) what role different neurofibromin-regulated Ras proteins play in this process and (6) how dysregulated growth factor signaling facilitates PNS tumorigenesis. In this review, we summarize the major findings from each of these models and their limitations as well as how discrepancies between these models may be reconciled. We also discuss how information gleaned from these models can be synthesized to into a comprehensive model of tumor formation in peripheral nervous system and consider several of the major questions that remain unanswered about this process. Copyright © 2011 Elsevier Inc. All rights reserved.

Maintenance of genetic diversity through plant-herbivore interactions

PubMed Central

Gloss, Andrew D.; Dittrich, Anna C. Nelson; Goldman-Huertas, Benjamin; Whiteman, Noah K.

2013-01-01

Identifying the factors governing the maintenance of genetic variation is a central challenge in evolutionary biology. New genomic data, methods and conceptual advances provide increasing evidence that balancing selection, mediated by antagonistic species interactions, maintains functionally-important genetic variation within species and natural populations. Because diverse interactions between plants and herbivorous insects dominate terrestrial communities, they provide excellent systems to address this hypothesis. Population genomic studies of Arabidopsis thaliana and its relatives suggest spatial variation in herbivory maintains adaptive genetic variation controlling defense phenotypes, both within and among populations. Conversely, inter-species variation in plant defenses promotes adaptive genetic variation in herbivores. Emerging genomic model herbivores of Arabidopsis could illuminate how genetic variation in herbivores and plants interact simultaneously. PMID:23834766

A hybrid genetic algorithm-queuing multi-compartment model for optimizing inpatient bed occupancy and associated costs.

PubMed

Belciug, Smaranda; Gorunescu, Florin

2016-03-01

Explore how efficient intelligent decision support systems, both easily understandable and straightforwardly implemented, can help modern hospital managers to optimize both bed occupancy and utilization costs. This paper proposes a hybrid genetic algorithm-queuing multi-compartment model for the patient flow in hospitals. A finite capacity queuing model with phase-type service distribution is combined with a compartmental model, and an associated cost model is set up. An evolutionary-based approach is used for enhancing the ability to optimize both bed management and associated costs. In addition, a "What-if analysis" shows how changing the model parameters could improve performance while controlling costs. The study uses bed-occupancy data collected at the Department of Geriatric Medicine - St. George's Hospital, London, period 1969-1984, and January 2000. The hybrid model revealed that a bed-occupancy exceeding 91%, implying a patient rejection rate around 1.1%, can be carried out with 159 beds plus 8 unstaffed beds. The same holding and penalty costs, but significantly different bed allocations (156 vs. 184 staffed beds, and 8 vs. 9 unstaffed beds, respectively) will result in significantly different costs (£755 vs. £1172). Moreover, once the arrival rate exceeds 7 patient/day, the costs associated to the finite capacity system become significantly smaller than those associated to an Erlang B queuing model (£134 vs. £947). Encoding the whole information provided by both the queuing system and the cost model through chromosomes, the genetic algorithm represents an efficient tool in optimizing the bed allocation and associated costs. The methodology can be extended to different medical departments with minor modifications in structure and parameterization. Copyright © 2016 Elsevier B.V. All rights reserved.

Caenorhabditis elegans: An Emerging Model in Biomedical and Environmental Toxicology

PubMed Central

Leung, Maxwell C. K.; Williams, Phillip L.; Benedetto, Alexandre; Au, Catherine; Helmcke, Kirsten J.; Aschner, Michael; Meyer, Joel N.

2008-01-01

The nematode Caenorhabditis elegans has emerged as an important animal model in various fields including neurobiology, developmental biology, and genetics. Characteristics of this animal model that have contributed to its success include its genetic manipulability, invariant and fully described developmental program, well-characterized genome, ease of maintenance, short and prolific life cycle, and small body size. These same features have led to an increasing use of C. elegans in toxicology, both for mechanistic studies and high-throughput screening approaches. We describe some of the research that has been carried out in the areas of neurotoxicology, genetic toxicology, and environmental toxicology, as well as high-throughput experiments with C. elegans including genome-wide screening for molecular targets of toxicity and rapid toxicity assessment for new chemicals. We argue for an increased role for C. elegans in complementing other model systems in toxicological research. PMID:18566021

Genetics of common forms of heart failure: challenges and potential solutions.

PubMed

Rau, Christoph D; Lusis, Aldons J; Wang, Yibin

2015-05-01

In contrast to many other human diseases, the use of genome-wide association studies (GWAS) to identify genes for heart failure (HF) has had limited success. We will discuss the underlying challenges as well as potential new approaches to understanding the genetics of common forms of HF. Recent research using intermediate phenotypes, more detailed and quantitative stratification of HF symptoms, founder populations and novel animal models has begun to allow researchers to make headway toward explaining the genetics underlying HF using GWAS techniques. By expanding analyses of HF to improved clinical traits, additional HF classifications and innovative model systems, the intractability of human HF GWAS should be ameliorated significantly.

ptk7 mutant zebrafish models of congenital and idiopathic scoliosis implicate dysregulated Wnt signalling in disease

PubMed Central

Hayes, Madeline; Gao, Xiaochong; Yu, Lisa X; Paria, Nandina; Henkelman, R. Mark; Wise, Carol A.; Ciruna, Brian

2014-01-01

Scoliosis is a complex genetic disorder of the musculoskeletal system, characterized by three-dimensional rotation of the spine. Curvatures caused by malformed vertebrae (congenital scoliosis (CS)) are apparent at birth. Spinal curvatures with no underlying vertebral abnormality (idiopathic scoliosis (IS)) most commonly manifest during adolescence. The genetic and biological mechanisms responsible for IS remain poorly understood due largely to limited experimental models. Here we describe zygotic ptk7 (Zptk7) mutant zebrafish, deficient in a critical regulator of Wnt signalling, as the first genetically defined developmental model of IS. We identify a novel sequence variant within a single IS patient that disrupts PTK7 function, consistent with a role for dysregulated Wnt activity in disease pathogenesis. Furthermore, we demonstrate that embryonic loss-of-gene function in maternal-zygotic ptk7 mutants (MZptk7) leads to vertebral anomalies associated with CS. Our data suggest novel molecular origins of, and genetic links between, congenital and idiopathic forms of disease. PMID:25182715

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

Engineered probiotic Escherichia coli can eliminate and prevent Pseudomonas aeruginosa gut infection in animal models

PubMed Central

Hwang, In Young; Koh, Elvin; Wong, Adison; March, John C.; Bentley, William E.; Lee, Yung Seng; Chang, Matthew Wook

2017-01-01

Bacteria can be genetically engineered to kill specific pathogens or inhibit their virulence. We previously developed a synthetic genetic system that allows a laboratory strain of Escherichia coli to sense and kill Pseudomonas aeruginosa in vitro. Here, we generate a modified version of the system, including a gene encoding an anti-biofilm enzyme, and use the probiotic strain Escherichia coli Nissle 1917 as host. The engineered probiotic shows in vivo prophylactic and therapeutic activity against P. aeruginosa during gut infection in two animal models (Caenorhabditis elegans and mice). These findings support the further development of engineered microorganisms with potential prophylactic and therapeutic activities against gut infections. PMID:28398304

The behavioural and neuropathological impact of intranigral AAV-α-synuclein is exacerbated by systemic infusion of the Parkinson's disease-associated pesticide, rotenone, in rats.

PubMed

Mulcahy, Pádraig; O'Doherty, Aideen; Paucard, Alexia; O'Brien, Timothy; Kirik, Deniz; Dowd, Eilís

2013-04-15

Despite the widely held belief that Parkinson's disease is caused by both underlying genetics and exposure to environmental risk factors, it is still widely modelled in preclinical models using a single genetic or neurotoxic insult. This single-insult approach has resulted in a variety of models that are limited with respect to their aetiological, construct, face and/or predictive validity. Thus, the aim of the current study was to investigate the interplay between genes and the environment as an alternative approach to modelling Parkinson's disease. To do so, rats underwent stereotaxic surgery for unilateral delivery of the Parkinson's disease-associated gene, α-synuclein, into the substantia nigra (using AAV vectors). This was followed 13 weeks later by subcutaneous implantation of an osmotic minipump delivering the Parkinson's disease-associated pesticide, rotenone (2.5mgkg(-1)day(-1) for 4 weeks). The effect of the genetic and environmental insults alone or in combination on lateralised motor performance (Corridor, Stepping and Whisker Tests), nigrostriatal integrity (tyrosine hydroxylase immunohistochemistry) and α-synucleinopathy (α-synuclein immunohistochemistry) was assessed. We found that exposing AAV-α-synuclein-treated rats to rotenone led to a model in which the classical Parkinson's disease triad of progressive motor dysfunction, nigrostriatal neurodegeneration and α-synucleinopathy was evident. However, delivering rotenone systemically was also associated with bilateral motor dysfunction and loss of body weight. Thus, although we have shown that Parkinson's disease can be modelled in experimental animals by combined exposure to both genetic and environmental risk factors, this approach is limited by systemic toxicity of the pesticide rotenone. Direct intracerebral delivery of rotenone may be more useful in longer-term studies as we have previously shown that it overcomes this limitation. Copyright © 2013 Elsevier B.V. All rights reserved.

Hybrid feedforward and feedback controller design for nuclear steam generators over wide range operation using genetic algorithm

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

Zhao, Y.; Edwards, R.M.; Lee, K.Y.

1997-03-01

In this paper, a simplified model with a lower order is first developed for a nuclear steam generator system and verified against some realistic environments. Based on this simplified model, a hybrid multi-input and multi-out (MIMO) control system, consisting of feedforward control (FFC) and feedback control (FBC), is designed for wide range conditions by using the genetic algorithm (GA) technique. The FFC control, obtained by the GA optimization method, injects an a priori command input into the system to achieve an optimal performance for the designed system, while the GA-based FBC control provides the necessary compensation for any disturbances ormore » uncertainties in a real steam generator. The FBC control is an optimal design of a PI-based control system which would be more acceptable for industrial practices and power plant control system upgrades. The designed hybrid MIMO FFC/FBC control system is first applied to the simplified model and then to a more complicated model with a higher order which is used as a substitute of the real system to test the efficacy of the designed control system. Results from computer simulations show that the designed GA-based hybrid MIMO FFC/FBC control can achieve good responses and robust performances. Hence, it can be considered as a viable alternative to the current control system upgrade.« less

Anticipatory dynamics of biological systems: from molecular quantum states to evolution

NASA Astrophysics Data System (ADS)

Igamberdiev, Abir U.

2015-08-01

Living systems possess anticipatory behaviour that is based on the flexibility of internal models generated by the system's embedded description. The idea was suggested by Aristotle and is explicitly introduced to theoretical biology by Rosen. The possibility of holding the embedded internal model is grounded in the principle of stable non-equilibrium (Bauer). From the quantum mechanical view, this principle aims to minimize energy dissipation in expense of long relaxation times. The ideas of stable non-equilibrium were developed by Liberman who viewed living systems as subdivided into the quantum regulator and the molecular computer supporting coherence of the regulator's internal quantum state. The computational power of the cell molecular computer is based on the possibility of molecular rearrangements according to molecular addresses. In evolution, the anticipatory strategies are realized both as a precession of phylogenesis by ontogenesis (Berg) and as the anticipatory search of genetic fixation of adaptive changes that incorporates them into the internal model of genetic system. We discuss how the fundamental ideas of anticipation can be introduced into the basic foundations of theoretical biology.

Genetics in child and adolescent psychiatry: methodological advances and conceptual issues.

PubMed

Hohmann, Sarah; Adamo, Nicoletta; Lahey, Benjamin B; Faraone, Stephen V; Banaschewski, Tobias

2015-06-01

Discovering the genetic basis of early-onset psychiatric disorders has been the aim of intensive research during the last decade. We will first selectively summarize results of genetic research in child and adolescent psychiatry by using examples from different disorders and discuss methodological issues, emerging questions and future directions. In the second part of this review, we will focus on how to link genetic causes of disorders with physiological pathways, discuss the impact of genetic findings on diagnostic systems, prevention and therapeutic interventions. Finally we will highlight some ethical aspects connected to genetic research in child and adolescent psychiatry. Advances in molecular genetic methods have led to insights into the genetic architecture of psychiatric disorders, but not yet provided definite pathways to pathophysiology. If replicated, promising findings from genetic studies might in some cases lead to personalized treatments. On the one hand, knowledge of the genetic basis of disorders may influence diagnostic categories. On the other hand, models also suggest studying the genetic architecture of psychiatric disorders across diagnoses and clinical groups.

Genetic algorithm for neural networks optimization

NASA Astrophysics Data System (ADS)

Setyawati, Bina R.; Creese, Robert C.; Sahirman, Sidharta

2004-11-01

This paper examines the forecasting performance of multi-layer feed forward neural networks in modeling a particular foreign exchange rates, i.e. Japanese Yen/US Dollar. The effects of two learning methods, Back Propagation and Genetic Algorithm, in which the neural network topology and other parameters fixed, were investigated. The early results indicate that the application of this hybrid system seems to be well suited for the forecasting of foreign exchange rates. The Neural Networks and Genetic Algorithm were programmed using MATLAB«.

How Obstacles Perturb Population Fronts and Alter Their Genetic Structure.

PubMed

Möbius, Wolfram; Murray, Andrew W; Nelson, David R

2015-12-01

As populations spread into new territory, environmental heterogeneities can shape the population front and genetic composition. We focus here on the effects of an important building block of heterogeneous environments, isolated obstacles. With a combination of experiments, theory, and simulation, we show how isolated obstacles both create long-lived distortions of the front shape and amplify the effect of genetic drift. A system of bacteriophage T7 spreading on a spatially heterogeneous Escherichia coli lawn serves as an experimental model system to study population expansions. Using an inkjet printer, we create well-defined replicates of the lawn and quantitatively study the population expansion of phage T7. The transient perturbations of the population front found in the experiments are well described by a model in which the front moves with constant speed. Independent of the precise details of the expansion, we show that obstacles create a kink in the front that persists over large distances and is insensitive to the details of the obstacle's shape. The small deviations between experimental findings and the predictions of the constant speed model can be understood with a more general reaction-diffusion model, which reduces to the constant speed model when the obstacle size is large compared to the front width. Using this framework, we demonstrate that frontier genotypes just grazing the side of an isolated obstacle increase in abundance, a phenomenon we call 'geometry-enhanced genetic drift', complementary to the founder effect associated with spatial bottlenecks. Bacterial range expansions around nutrient-poor barriers and stochastic simulations confirm this prediction. The effect of the obstacle on the genealogy of individuals at the front is characterized by simulations and rationalized using the constant speed model. Lastly, we consider the effect of two obstacles on front shape and genetic composition of the population illuminating the effects expected from complex environments with many obstacles.

How Obstacles Perturb Population Fronts and Alter Their Genetic Structure

PubMed Central

Möbius, Wolfram; Murray, Andrew W.; Nelson, David R.

2015-01-01

As populations spread into new territory, environmental heterogeneities can shape the population front and genetic composition. We focus here on the effects of an important building block of heterogeneous environments, isolated obstacles. With a combination of experiments, theory, and simulation, we show how isolated obstacles both create long-lived distortions of the front shape and amplify the effect of genetic drift. A system of bacteriophage T7 spreading on a spatially heterogeneous Escherichia coli lawn serves as an experimental model system to study population expansions. Using an inkjet printer, we create well-defined replicates of the lawn and quantitatively study the population expansion of phage T7. The transient perturbations of the population front found in the experiments are well described by a model in which the front moves with constant speed. Independent of the precise details of the expansion, we show that obstacles create a kink in the front that persists over large distances and is insensitive to the details of the obstacle’s shape. The small deviations between experimental findings and the predictions of the constant speed model can be understood with a more general reaction-diffusion model, which reduces to the constant speed model when the obstacle size is large compared to the front width. Using this framework, we demonstrate that frontier genotypes just grazing the side of an isolated obstacle increase in abundance, a phenomenon we call ‘geometry-enhanced genetic drift’, complementary to the founder effect associated with spatial bottlenecks. Bacterial range expansions around nutrient-poor barriers and stochastic simulations confirm this prediction. The effect of the obstacle on the genealogy of individuals at the front is characterized by simulations and rationalized using the constant speed model. Lastly, we consider the effect of two obstacles on front shape and genetic composition of the population illuminating the effects expected from complex environments with many obstacles. PMID:26696601

Introduction to focus issue: quantitative approaches to genetic networks.

PubMed

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

2013-06-01

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

Introduction to Focus Issue: Quantitative Approaches to Genetic Networks

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

Deadlock-free genetic scheduling algorithm for automated manufacturing systems based on deadlock control policy.

PubMed

Xing, KeYi; Han, LiBin; Zhou, MengChu; Wang, Feng

2012-06-01

Deadlock-free control and scheduling are vital for optimizing the performance of automated manufacturing systems (AMSs) with shared resources and route flexibility. Based on the Petri net models of AMSs, this paper embeds the optimal deadlock avoidance policy into the genetic algorithm and develops a novel deadlock-free genetic scheduling algorithm for AMSs. A possible solution of the scheduling problem is coded as a chromosome representation that is a permutation with repetition of parts. By using the one-step look-ahead method in the optimal deadlock control policy, the feasibility of a chromosome is checked, and infeasible chromosomes are amended into feasible ones, which can be easily decoded into a feasible deadlock-free schedule. The chromosome representation and polynomial complexity of checking and amending procedures together support the cooperative aspect of genetic search for scheduling problems strongly.

Foundations and Emerging Paradigms for Computing in Living Cells.

PubMed

Ma, Kevin C; Perli, Samuel D; Lu, Timothy K

2016-02-27

Genetic circuits, composed of complex networks of interacting molecular machines, enable living systems to sense their dynamic environments, perform computation on the inputs, and formulate appropriate outputs. By rewiring and expanding these circuits with novel parts and modules, synthetic biologists have adapted living systems into vibrant substrates for engineering. Diverse paradigms have emerged for designing, modeling, constructing, and characterizing such artificial genetic systems. In this paper, we first provide an overview of recent advances in the development of genetic parts and highlight key engineering approaches. We then review the assembly of these parts into synthetic circuits from the perspectives of digital and analog logic, systems biology, and metabolic engineering, three areas of particular theoretical and practical interest. Finally, we discuss notable challenges that the field of synthetic biology still faces in achieving reliable and predictable forward-engineering of artificial biological circuits. Copyright © 2016. Published by Elsevier Ltd.

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.

Genetic Tools for the Industrially Promising Methanotroph Methylomicrobium buryatense

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

Puri, AW; Owen, S; Chu, F

2015-02-10

Aerobic methanotrophs oxidize methane at ambient temperatures and pressures and are therefore attractive systems for methane-based bioconversions. In this work, we developed and validated genetic tools for Methylomicrobium buryatense, a haloalkaliphilic gammaproteobacterial (type I) methanotroph. M. buryatense was isolated directly on natural gas and grows robustly in pure culture with a 3-h doubling time, enabling rapid genetic manipulation compared to many other methanotrophic species. As a proof of concept, we used a sucrose counterselection system to eliminate glycogen production in M. buryatense by constructing unmarked deletions in two redundant glycogen synthase genes. We also selected for a more genetically tractablemore » variant strain that can be conjugated with small incompatibility group P (IncP)-based broad-host-range vectors and determined that this capability is due to loss of the native plasmid. These tools make M. buryatense a promising model system for studying aerobic methanotroph physiology and enable metabolic engineering in this bacterium for industrial biocatalysis of methane.« less

Stochastic model simulation using Kronecker product analysis and Zassenhaus formula approximation.

PubMed

Caglar, Mehmet Umut; Pal, Ranadip

2013-01-01

Probabilistic Models are regularly applied in Genetic Regulatory Network modeling to capture the stochastic behavior observed in the generation of biological entities such as mRNA or proteins. Several approaches including Stochastic Master Equations and Probabilistic Boolean Networks have been proposed to model the stochastic behavior in genetic regulatory networks. It is generally accepted that Stochastic Master Equation is a fundamental model that can describe the system being investigated in fine detail, but the application of this model is computationally enormously expensive. On the other hand, Probabilistic Boolean Network captures only the coarse-scale stochastic properties of the system without modeling the detailed interactions. We propose a new approximation of the stochastic master equation model that is able to capture the finer details of the modeled system including bistabilities and oscillatory behavior, and yet has a significantly lower computational complexity. In this new method, we represent the system using tensors and derive an identity to exploit the sparse connectivity of regulatory targets for complexity reduction. The algorithm involves an approximation based on Zassenhaus formula to represent the exponential of a sum of matrices as product of matrices. We derive upper bounds on the expected error of the proposed model distribution as compared to the stochastic master equation model distribution. Simulation results of the application of the model to four different biological benchmark systems illustrate performance comparable to detailed stochastic master equation models but with considerably lower computational complexity. The results also demonstrate the reduced complexity of the new approach as compared to commonly used Stochastic Simulation Algorithm for equivalent accuracy.

Genetic markers of wheat (Triticum aestivum) associated with flavor preference using a mouse (Mus musculus) model

USDA-ARS?s Scientific Manuscript database

Whole wheat products provide critical nutrients for human health, differences in wheat flavor are not well understood. Using the house mouse as a model system, flavor preference and discrimination were examined using a two-choice feeding system and 24-h trials and the Student’s t statistic. To elimi...

Inverse problem studies of biochemical systems with structure identification of S-systems by embedding training functions in a genetic algorithm.

PubMed

Sarode, Ketan Dinkar; Kumar, V Ravi; Kulkarni, B D

2016-05-01

An efficient inverse problem approach for parameter estimation, state and structure identification from dynamic data by embedding training functions in a genetic algorithm methodology (ETFGA) is proposed for nonlinear dynamical biosystems using S-system canonical models. Use of multiple shooting and decomposition approach as training functions has been shown for handling of noisy datasets and computational efficiency in studying the inverse problem. The advantages of the methodology are brought out systematically by studying it for three biochemical model systems of interest. By studying a small-scale gene regulatory system described by a S-system model, the first example demonstrates the use of ETFGA for the multifold aims of the inverse problem. The estimation of a large number of parameters with simultaneous state and network identification is shown by training a generalized S-system canonical model with noisy datasets. The results of this study bring out the superior performance of ETFGA on comparison with other metaheuristic approaches. The second example studies the regulation of cAMP oscillations in Dictyostelium cells now assuming limited availability of noisy data. Here, flexibility of the approach to incorporate partial system information in the identification process is shown and its effect on accuracy and predictive ability of the estimated model are studied. The third example studies the phenomenological toy model of the regulation of circadian oscillations in Drosophila that follows rate laws different from S-system power-law. For the limited noisy data, using a priori information about properties of the system, we could estimate an alternate S-system model that showed robust oscillatory behavior with predictive abilities. Copyright © 2016 Elsevier Inc. All rights reserved.

Life-history and habitat features influence the within-river genetic structure of Atlantic salmon.

PubMed

Vähä, Juha-Pekka; Erkinaro, Jaakko; Niemelä, Eero; Primmer, Craig R

2007-07-01

Defining populations and identifying ecological and life-history characteristics affecting genetic structure is important for understanding species biology and hence, for managing threatened or endangered species or populations. In this study, populations of the world's largest indigenous Atlantic salmon (Salmo salar) stock were first inferred using model-based clustering methods, following which life-history and habitat variables best predicting the genetic diversity of populations were identified. This study revealed that natal homing of Atlantic salmon within the Teno River system is accurate at least to the tributary level. Generally, defining populations by main tributaries was observed to be a reasonable approach in this large river system, whereas in the mainstem of the river, the number of inferred populations was fewer than the number of distinct sampling sites. Mainstem and headwater populations were genetically more diverse and less diverged, while each tributary fostered a distinct population with high genetic differentiation and lower genetic diversity. Population structure and variation in genetic diversity among populations were poorly explained by geographical distance. In contrast, age-structure, as estimated by the proportion of multisea-winter spawners, was the most predictive variable in explaining the variation in the genetic diversity of the populations. This observation, being in agreement with theoretical predictions, emphasizes the essence of large multisea-winter females in maintaining the genetic diversity of populations. In addition, the unique genetic diversity of populations, as estimated by private allele richness, was affected by the ease of accessibility of a site, with more difficult to access sites having lower unique genetic diversity. Our results show that despite this species' high capacity for migration, tributaries foster relatively closed populations with little gene flow which will be important to consider when developing management strategies for the system.

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

PubMed Central

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

2006-01-01

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

Advanced technologies for genetically manipulating the silkworm Bombyx mori, a model Lepidopteran insect

PubMed Central

Xu, Hanfu; O'Brochta, David A.

2015-01-01

Genetic technologies based on transposon-mediated transgenesis along with several recently developed genome-editing technologies have become the preferred methods of choice for genetically manipulating many organisms. The silkworm, Bombyx mori, is a Lepidopteran insect of great economic importance because of its use in silk production and because it is a valuable model insect that has greatly enhanced our understanding of the biology of insects, including many agricultural pests. In the past 10 years, great advances have been achieved in the development of genetic technologies in B. mori, including transposon-based technologies that rely on piggyBac-mediated transgenesis and genome-editing technologies that rely on protein- or RNA-guided modification of chromosomes. The successful development and application of these technologies has not only facilitated a better understanding of B. mori and its use as a silk production system, but also provided valuable experiences that have contributed to the development of similar technologies in non-model insects. This review summarizes the technologies currently available for use in B. mori, their application to the study of gene function and their use in genetically modifying B. mori for biotechnology applications. The challenges, solutions and future prospects associated with the development and application of genetic technologies in B. mori are also discussed. PMID:26108630

Gene silencing in non-model insects: Overcoming hurdles using symbiotic bacteria for trauma-free sustainable delivery of RNA interference: Sustained RNA interference in insects mediated by symbiotic bacteria: Applications as a genetic tool and as a biocide.

PubMed

Whitten, Miranda; Dyson, Paul

2017-03-01

Insight into animal biology and development provided by classical genetic analysis of the model organism Drosophila melanogaster was an incentive to develop advanced genetic tools for this insect. But genetic systems for the over one million other known insect species are largely undeveloped. With increasing information about insect genomes resulting from next generation sequencing, RNA interference is now the method of choice for reverse genetics, although it is constrained by the means of delivery of interfering RNA. A recent advance to ensure sustained delivery with minimal experimental intervention or trauma to the insect is to exploit commensal bacteria for symbiont-mediated RNA interference. This technology not only offers an efficient means for RNA interference in insects in laboratory conditions, but also has potential for use in the control of human disease vectors, agricultural pests and pathogens of beneficial insects. © 2017 WILEY Periodicals, Inc.

Advergence in Müllerian mimicry: the case of the poison dart frogs of Northern Peru revisited

PubMed Central

Chouteau, Mathieu; Summers, Kyle; Morales, Victor; Angers, Bernard

2011-01-01

Whether the evolution of similar aposematic signals in different unpalatable species (i.e. Müllerian mimicry) is because of phenotypic convergence or advergence continues to puzzle scientists. The poison dart frog Ranitomeya imitator provides a rare example in support of the hypothesis of advergence: this species was believed to mimic numerous distinct model species because of high phenotypic variability and low genetic divergence among populations. In this study, we test the evidence in support of advergence using a population genetic framework in two localities where R. imitator is sympatric with different model species, Ranitomeya ventrimaculata and Ranitomeya variabilis. Genetic analyses revealed incomplete sorting of mitochondrial haplotypes between the two model species. These two species are also less genetically differentiated than R. imitator populations on the basis of both mitochondrial and nuclear DNA comparisons. The genetic similarity between the model species suggests that they have either diverged more recently than R. imitator populations or that they are still connected by gene flow and were misidentified as different species. An analysis of phenotypic variability indicates that the model species are as variable as R. imitator. These results do not support the hypothesis of advergence by R. imitator. Although we cannot rule out phenotypic advergence in the evolution of Müllerian mimicry, this study reopens the discussion regarding the direction of the evolution of mimicry in the R. imitator system. PMID:21411452

Networking in autism: leveraging genetic, biomarker and model system findings in the search for new treatments.

PubMed

Veenstra-VanderWeele, Jeremy; Blakely, Randy D

2012-01-01

Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder affecting approximately 1% of children. ASD is defined by core symptoms in two domains: negative symptoms of impairment in social and communication function, and positive symptoms of restricted and repetitive behaviors. Available treatments are inadequate for treating both core symptoms and associated conditions. Twin studies indicate that ASD susceptibility has a large heritable component. Genetic studies have identified promising leads, with converging insights emerging from single-gene disorders that bear ASD features, with particular interest in mammalian target of rapamycin (mTOR)-linked synaptic plasticity mechanisms. Mouse models of these disorders are revealing not only opportunities to model behavioral perturbations across species, but also evidence of postnatal rescue of brain and behavioral phenotypes. An intense search for ASD biomarkers has consistently pointed to elevated platelet serotonin (5-HT) levels and a surge in brain growth in the first 2 years of life. Following a review of the diversity of ASD phenotypes and its genetic origins and biomarkers, we discuss opportunities for translation of these findings into novel ASD treatments, focusing on mTor- and 5-HT-signaling pathways, and their possible intersection. Paralleling the progress made in understanding the root causes of rare genetic syndromes that affect cognitive development, we anticipate progress in models systems using bona fide ASD-associated molecular changes that have the potential to accelerate the development of ASD diagnostics and therapeutics.

Networking in Autism: Leveraging Genetic, Biomarker and Model System Findings in the Search for New Treatments

PubMed Central

Veenstra-VanderWeele, Jeremy; Blakely, Randy D

2012-01-01

Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder affecting approximately 1% of children. ASD is defined by core symptoms in two domains: negative symptoms of impairment in social and communication function, and positive symptoms of restricted and repetitive behaviors. Available treatments are inadequate for treating both core symptoms and associated conditions. Twin studies indicate that ASD susceptibility has a large heritable component. Genetic studies have identified promising leads, with converging insights emerging from single-gene disorders that bear ASD features, with particular interest in mammalian target of rapamycin (mTOR)-linked synaptic plasticity mechanisms. Mouse models of these disorders are revealing not only opportunities to model behavioral perturbations across species, but also evidence of postnatal rescue of brain and behavioral phenotypes. An intense search for ASD biomarkers has consistently pointed to elevated platelet serotonin (5-HT) levels and a surge in brain growth in the first 2 years of life. Following a review of the diversity of ASD phenotypes and its genetic origins and biomarkers, we discuss opportunities for translation of these findings into novel ASD treatments, focusing on mTor- and 5-HT-signaling pathways, and their possible intersection. Paralleling the progress made in understanding the root causes of rare genetic syndromes that affect cognitive development, we anticipate progress in models systems using bona fide ASD-associated molecular changes that have the potential to accelerate the development of ASD diagnostics and therapeutics. PMID:21937981

Sleep and Development in Genetically Tractable Model Organisms

PubMed Central

Kayser, Matthew S.; Biron, David

2016-01-01

Sleep is widely recognized as essential, but without a clear singular function. Inadequate sleep impairs cognition, metabolism, immune function, and many other processes. Work in genetic model systems has greatly expanded our understanding of basic sleep neurobiology as well as introduced new concepts for why we sleep. Among these is an idea with its roots in human work nearly 50 years old: sleep in early life is crucial for normal brain maturation. Nearly all known species that sleep do so more while immature, and this increased sleep coincides with a period of exuberant synaptogenesis and massive neural circuit remodeling. Adequate sleep also appears critical for normal neurodevelopmental progression. This article describes recent findings regarding molecular and circuit mechanisms of sleep, with a focus on development and the insights garnered from models amenable to detailed genetic analyses. PMID:27183564

High intralocus variability and interlocus recombination promote immunological diversity in a minimal major histocompatibility system.

PubMed

Wilson, Anthony B; Whittington, Camilla M; Bahr, Angela

2014-12-20

The genes of the major histocompatibility complex (MHC/MH) have attracted considerable scientific interest due to their exceptional levels of variability and important function as part of the adaptive immune system. Despite a large number of studies on MH class II diversity of both model and non-model organisms, most research has focused on patterns of genetic variability at individual loci, failing to capture the functional diversity of the biologically active dimeric molecule. Here, we take a systematic approach to the study of MH variation, analyzing patterns of genetic variation at MH class IIα and IIβ loci of the seahorse, which together form the immunologically active peptide binding cleft of the MH class II molecule. The seahorse carries a minimal class II system, consisting of single copies of both MH class IIα and IIβ, which are physically linked and inherited in a Mendelian fashion. Both genes are ubiquitously expressed and detectible in the brood pouch of male seahorses throughout pregnancy. Genetic variability of the two genes is high, dominated by non-synonymous variation concentrated in their peptide-binding regions. Coding variation outside these regions is negligible, a pattern thought to be driven by intra- and interlocus recombination. Despite the tight physical linkage of MH IIα and IIβ loci, recombination has produced novel composite alleles, increasing functional diversity at sites responsible for antigen recognition. Antigen recognition by the adaptive immune system of the seahorse is enhanced by high variability at both MH class IIα and IIβ loci. Strong positive selection on sites involved in pathogen recognition, coupled with high levels of intra- and interlocus recombination, produce a patchwork pattern of genetic variation driven by genetic hitchhiking. Studies focusing on variation at individual MH loci may unintentionally overlook an important component of ecologically relevant variation.

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.

Advances in the Study of Heart Development and Disease Using Zebrafish

PubMed Central

Brown, Daniel R.; Samsa, Leigh Ann; Qian, Li; Liu, Jiandong

2016-01-01

Animal models of cardiovascular disease are key players in the translational medicine pipeline used to define the conserved genetic and molecular basis of disease. Congenital heart diseases (CHDs) are the most common type of human birth defect and feature structural abnormalities that arise during cardiac development and maturation. The zebrafish, Danio rerio, is a valuable vertebrate model organism, offering advantages over traditional mammalian models. These advantages include the rapid, stereotyped and external development of transparent embryos produced in large numbers from inexpensively housed adults, vast capacity for genetic manipulation, and amenability to high-throughput screening. With the help of modern genetics and a sequenced genome, zebrafish have led to insights in cardiovascular diseases ranging from CHDs to arrhythmia and cardiomyopathy. Here, we discuss the utility of zebrafish as a model system and summarize zebrafish cardiac morphogenesis with emphasis on parallels to human heart diseases. Additionally, we discuss the specific tools and experimental platforms utilized in the zebrafish model including forward screens, functional characterization of candidate genes, and high throughput applications. PMID:27335817

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

PubMed

Walker, Jeffrey A

2010-12-01

A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).

Fuzzy multiobjective models for optimal operation of a hydropower system

NASA Astrophysics Data System (ADS)

Teegavarapu, Ramesh S. V.; Ferreira, André R.; Simonovic, Slobodan P.

2013-06-01

Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.

Is there a doctor in the house? : The presence of physicians in the direct-to-consumer genetic testing context.

PubMed

Howard, Heidi Carmen; Borry, Pascal

2012-04-01

Over the last couple of years, many commercial companies, the majority of which are based in the USA, have been advertising and offering direct-to-consumer (DTC) genetic testing services outside of the established health care system, and often without any involvement from a health care professional. In the last year, however, a number of DTC genetic testing companies have changed their provision model such that consumers must now contact a health care professional before being able to order the genetic testing service. In discussing the advent of this new model of service provision, this article also reviews the ethical and social issues surrounding DTC genetic testing and addresses the potential motivations for change, some barriers to achieving truly appropriate medical supervision and the present reality of DTC genetic testing for some psychiatric and neurological disorders. Since the advent of these commercial activities, critics have pointed a finger at the lack of medical supervision surrounding these services. The discussion herein, however, reveals how difficult it may be, despite the addition of a physician, to actually achieve adequate medical supervision within the present context of DTC genetic testing.

Using bioinformatics and systems genetics to dissect HDL-cholesterol genetics in an MRL/MpJ × SM/J intercross[S

PubMed Central

Leduc, Magalie S.; Blair, Rachael Hageman; Verdugo, Ricardo A.; Tsaih, Shirng-Wern; Walsh, Kenneth; Churchill, Gary A.; Paigen, Beverly

2012-01-01

A higher incidence of coronary artery disease is associated with a lower level of HDL-cholesterol. We searched for genetic loci influencing HDL-cholesterol in F2 mice from a cross between MRL/MpJ and SM/J mice. Quantitative trait loci (QTL) mapping revealed one significant HDL QTL (Apoa2 locus), four suggestive QTL on chromosomes 10, 11, 13, and 18 and four additional QTL on chromosomes 1 proximal, 3, 4, and 7 after adjusting HDL for the strong Apoa2 locus. A novel nonsynonymous polymorphism supports Lipg as the QTL gene for the chromosome 18 QTL, and a difference in Abca1 expression in liver tissue supports it as the QTL gene for the chromosome 4 QTL. Using weighted gene co-expression network analysis, we identified a module that after adjustment for Apoa2, correlated with HDL, was genetically determined by a QTL on chromosome 11, and overlapped with the HDL QTL. A combination of bioinformatics tools and systems genetics helped identify several candidate genes for both the chromosome 11 HDL and module QTL based on differential expression between the parental strains, cis regulation of expression, and causality modeling. We conclude that integrating systems genetics to a more-traditional genetics approach improves the power of complex trait gene identification. PMID:22498810

Building a genome engineering toolbox in nonmodel prokaryotic microbes.

PubMed

Freed, Emily; Fenster, Jacob; Smolinski, Sharon L; Walker, Julie; Henard, Calvin A; Gill, Ryan; Eckert, Carrie A

2018-05-11

The realization of a sustainable bioeconomy requires our ability to understand and engineer complex design principles for the development of platform organisms capable of efficient conversion of cheap and sustainable feedstocks (e.g., sunlight, CO 2 , and nonfood biomass) into biofuels and bioproducts at sufficient titers and costs. For model microbes, such as Escherichia coli, advances in DNA reading and writing technologies are driving the adoption of new paradigms for engineering biological systems. Unfortunately, microbes with properties of interest for the utilization of cheap and renewable feedstocks, such as photosynthesis, autotrophic growth, and cellulose degradation, have very few, if any, genetic tools for metabolic engineering. Therefore, it is important to develop "design rules" for building a genetic toolbox for novel microbes. Here, we present an overview of our current understanding of these rules for the genetic manipulation of prokaryotic microbes and the available genetic tools to expand our ability to genetically engineer nonmodel systems. © 2018 Wiley Periodicals, Inc.

Systems genetics identifies Sestrin 3 as a regulator of a proconvulsant gene network in human epileptic hippocampus

PubMed Central

Johnson, Michael R.; Rossetti, Tiziana; Speed, Doug; Srivastava, Prashant K.; Chadeau-Hyam, Marc; Hajji, Nabil; Dabrowska, Aleksandra; Rotival, Maxime; Razzaghi, Banafsheh; Kovac, Stjepana; Wanisch, Klaus; Grillo, Federico W.; Slaviero, Anna; Langley, Sarah R.; Shkura, Kirill; Roncon, Paolo; De, Tisham; Mattheisen, Manuel; Niehusmann, Pitt; O’Brien, Terence J.; Petrovski, Slave; von Lehe, Marec; Hoffmann, Per; Eriksson, Johan; Coffey, Alison J.; Cichon, Sven; Walker, Matthew; Simonato, Michele; Danis, Bénédicte; Mazzuferi, Manuela; Foerch, Patrik; Schoch, Susanne; De Paola, Vincenzo; Kaminski, Rafal M.; Cunliffe, Vincent T.; Becker, Albert J.; Petretto, Enrico

2015-01-01

Gene-regulatory network analysis is a powerful approach to elucidate the molecular processes and pathways underlying complex disease. Here we employ systems genetics approaches to characterize the genetic regulation of pathophysiological pathways in human temporal lobe epilepsy (TLE). Using surgically acquired hippocampi from 129 TLE patients, we identify a gene-regulatory network genetically associated with epilepsy that contains a specialized, highly expressed transcriptional module encoding proconvulsive cytokines and Toll-like receptor signalling genes. RNA sequencing analysis in a mouse model of TLE using 100 epileptic and 100 control hippocampi shows the proconvulsive module is preserved across-species, specific to the epileptic hippocampus and upregulated in chronic epilepsy. In the TLE patients, we map the trans-acting genetic control of this proconvulsive module to Sestrin 3 (SESN3), and demonstrate that SESN3 positively regulates the module in macrophages, microglia and neurons. Morpholino-mediated Sesn3 knockdown in zebrafish confirms the regulation of the transcriptional module, and attenuates chemically induced behavioural seizures in vivo. PMID:25615886

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.

Biological Diversity in the Patent System

PubMed Central

Oldham, Paul; Hall, Stephen; Forero, Oscar

2013-01-01

Biological diversity in the patent system is an enduring focus of controversy but empirical analysis of the presence of biodiversity in the patent system has been limited. To address this problem we text mined 11 million patent documents for 6 million Latin species names from the Global Names Index (GNI) established by the Global Biodiversity Information Facility (GBIF) and Encyclopedia of Life (EOL). We identified 76,274 full Latin species names from 23,882 genera in 767,955 patent documents. 25,595 species appeared in the claims section of 136,880 patent documents. This reveals that human innovative activity involving biodiversity in the patent system focuses on approximately 4% of taxonomically described species and between 0.8–1% of predicted global species. In this article we identify the major features of the patent landscape for biological diversity by focusing on key areas including pharmaceuticals, neglected diseases, traditional medicines, genetic engineering, foods, biocides, marine genetic resources and Antarctica. We conclude that the narrow focus of human innovative activity and ownership of genetic resources is unlikely to be in the long term interest of humanity. We argue that a broader spectrum of biodiversity needs to be opened up to research and development based on the principles of equitable benefit-sharing, respect for the objectives of the Convention on Biological Diversity, human rights and ethics. Finally, we argue that alternative models of innovation, such as open source and commons models, are required to open up biodiversity for research that addresses actual and neglected areas of human need. The research aims to inform the implementation of the 2010 Nagoya Protocol on Access to Genetic Resources and the Equitable Sharing of Benefits Arising from their Utilization and international debates directed to the governance of genetic resources. Our research also aims to inform debates under the Intergovernmental Committee on Intellectual Property and Genetic Resources, Traditional Knowledge and Folklore at the World Intellectual Property Organization. PMID:24265714

Modeling human diseases: an education in interactions and interdisciplinary approaches.

PubMed

Zon, Leonard

2016-06-01

Traditionally, most investigators in the biomedical arena exploit one model system in the course of their careers. Occasionally, an investigator will switch models. The selection of a suitable model system is a crucial step in research design. Factors to consider include the accuracy of the model as a reflection of the human disease under investigation, the numbers of animals needed and ease of husbandry, its physiology and developmental biology, and the ability to apply genetics and harness the model for drug discovery. In my lab, we have primarily used the zebrafish but combined it with other animal models and provided a framework for others to consider the application of developmental biology for therapeutic discovery. Our interdisciplinary approach has led to many insights into human diseases and to the advancement of candidate drugs to clinical trials. Here, I draw on my experiences to highlight the importance of combining multiple models, establishing infrastructure and genetic tools, forming collaborations, and interfacing with the medical community for successful translation of basic findings to the clinic. © 2016. Published by The Company of Biologists Ltd.

Perceptron Genetic to Recognize Openning Strategy Ruy Lopez

NASA Astrophysics Data System (ADS)

Azmi, Zulfian; Mawengkang, Herman

2018-01-01

The application of Perceptron method is not effective for coding on hardware based systems because it is not real time learning. With Genetic algorithm approach in calculating and searching the best weight (fitness value) system will do learning only one iteration. And the results of this analysis were tested in the case of the introduction of the opening pattern of chess Ruy Lopez. The Analysis with Perceptron Model with Algorithm Approach Genetics from group Artificial Neural Network for open Ruy Lopez. The data is processed with base open chess, with step eight a position white Pion from end open chess. Using perceptron method have many input and one output process many weight and refraction until output equal goal. Data trained and test with software Matlab and system can recognize the chess opening Ruy Lopez or Not open Ruy Lopez with Real time.

Found in Translation: Applying Lessons from Model Systems to Strigolactone Signaling in Parasitic Plants.

PubMed

Lumba, Shelley; Subha, Asrinus; McCourt, Peter

2017-07-01

Strigolactones (SLs) are small molecules that act as endogenous hormones to regulate plant development as well as exogenous cues that help parasitic plants to infect their hosts. Given that parasitic plants are experimentally challenging systems, researchers are using two approaches to understand how they respond to host-derived SLs. The first involves extrapolating information on SLs from model genetic systems to dissect their roles in parasitic plants. The second uses chemicals to probe SL signaling directly in the parasite Striga hermonthica. These approaches indicate that parasitic plants have co-opted a family of α/β hydrolases to perceive SLs. The importance of this genetic and chemical information cannot be overstated since parasitic plant infestations are major obstacles to food security in the developing world. Copyright © 2017 Elsevier Ltd. All rights reserved.

Caenorhabditis elegans as a powerful alternative model organism to promote research in genetic toxicology and biomedicine.

PubMed

Honnen, Sebastian

2017-05-01

In view of increased life expectancy the risk for disturbed integrity of genetic information increases. This inevitably holds the implication for higher incidence of age-related diseases leading to considerable cost increase in health care systems. To develop preventive strategies it is crucial to evaluate external and internal noxae as possible threats to our DNA. Especially the interplay of DNA damage response (DDR) and DNA repair (DR) mechanisms needs further deciphering. Moreover, there is a distinct need for alternative in vivo test systems for basic research and also risk assessment in toxicology. Especially the evaluation of combinational toxicity of environmentally present genotoxins and adverse effects of clinically used DNA damaging anticancer drugs is a major challenge for modern toxicology. This review focuses on the applicability of Caenorhabditis elegans as a model organism to unravel and tackle scientific questions related to the biological consequences of genotoxin exposure and highlights methods for studying DDR and DR. In this regard large-scale in vivo screens of mixtures of chemicals and extensive parallel sequencing are highlighted as unique advantages of C. elegans. In addition, concise information regarding evolutionary conserved molecular mechanisms of the DDR and DR as well as currently available data obtained from the use of prototypical genotoxins and preferential read-outs of genotoxin testing are discussed. The use of established protocols, which are already available in the community, is encouraged to facilitate and further improve the implementation of C. elegans as a powerful genetic model system in genetic toxicology and biomedicine.

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.

Candidate innate immune system gene expression in the ecological model Daphnia

PubMed Central

Decaestecker, Ellen; Labbé, Pierrick; Ellegaard, Kirsten; Allen, Judith E.; Little, Tom J.

2011-01-01

The last ten years have witnessed increasing interest in host–pathogen interactions involving invertebrate hosts. The invertebrate innate immune system is now relatively well characterised, but in a limited range of genetic model organisms and under a limited number of conditions. Immune systems have been little studied under real-world scenarios of environmental variation and parasitism. Thus, we have investigated expression of candidate innate immune system genes in the water flea Daphnia, a model organism for ecological genetics, and whose capacity for clonal reproduction facilitates an exceptionally rigorous control of exposure dose or the study of responses at many time points. A unique characteristic of the particular Daphnia clones and pathogen strain combinations used presently is that they have been shown to be involved in specific host–pathogen coevolutionary interactions in the wild. We choose five genes, which are strong candidates to be involved in Daphnia–pathogen interactions, given that they have been shown to code for immune effectors in related organisms. Differential expression of these genes was quantified by qRT-PCR following exposure to the bacterial pathogen Pasteuria ramosa. Constitutive expression levels differed between host genotypes, and some genes appeared to show correlated expression. However, none of the genes appeared to show a major modification of expression level in response to Pasteuria exposure. By applying knowledge from related genetic model organisms (e.g. Drosophila) to models for the study of evolutionary ecology and coevolution (i.e. Daphnia), the candidate gene approach is temptingly efficient. However, our results show that detection of only weak patterns is likely if one chooses target genes for study based on previously identified genome sequences by comparison to homologues from other related organisms. Future work on the Daphnia–Pasteuria system will need to balance a candidate gene approach with more comprehensive approaches to de novo identify immune system genes specific to the Daphnia–Pasteuria interaction. PMID:21550363

Candidate innate immune system gene expression in the ecological model Daphnia.

PubMed

Decaestecker, Ellen; Labbé, Pierrick; Ellegaard, Kirsten; Allen, Judith E; Little, Tom J

2011-10-01

The last ten years have witnessed increasing interest in host-pathogen interactions involving invertebrate hosts. The invertebrate innate immune system is now relatively well characterised, but in a limited range of genetic model organisms and under a limited number of conditions. Immune systems have been little studied under real-world scenarios of environmental variation and parasitism. Thus, we have investigated expression of candidate innate immune system genes in the water flea Daphnia, a model organism for ecological genetics, and whose capacity for clonal reproduction facilitates an exceptionally rigorous control of exposure dose or the study of responses at many time points. A unique characteristic of the particular Daphnia clones and pathogen strain combinations used presently is that they have been shown to be involved in specific host-pathogen coevolutionary interactions in the wild. We choose five genes, which are strong candidates to be involved in Daphnia-pathogen interactions, given that they have been shown to code for immune effectors in related organisms. Differential expression of these genes was quantified by qRT-PCR following exposure to the bacterial pathogen Pasteuria ramosa. Constitutive expression levels differed between host genotypes, and some genes appeared to show correlated expression. However, none of the genes appeared to show a major modification of expression level in response to Pasteuria exposure. By applying knowledge from related genetic model organisms (e.g. Drosophila) to models for the study of evolutionary ecology and coevolution (i.e. Daphnia), the candidate gene approach is temptingly efficient. However, our results show that detection of only weak patterns is likely if one chooses target genes for study based on previously identified genome sequences by comparison to homologues from other related organisms. Future work on the Daphnia-Pasteuria system will need to balance a candidate gene approach with more comprehensive approaches to de novo identify immune system genes specific to the Daphnia-Pasteuria interaction. Copyright © 2011 Elsevier Ltd. All rights reserved.

Environmental, genetic, and ecophysiological variation of western and Utah juniper and their hybrids: A model system for vegetation response to climate change. Final report

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

Nowak, R.S.; Tausch, R.J.

1998-11-01

This report focuses on the following two research projects relating to the biological effects of climate change: Hybridization and genetic diversity populations of Utah (Juniperus osteosperma) and western (Juniperus occidentalis) juniper: Evidence from nuclear ribosomal and chloroplast DNA; and Ecophysiological patterns of pinyon and juniper.

Network Architecture Predisposes an Enzyme to Either Pharmacologic or Genetic Targeting.

PubMed

Jensen, Karin J; Moyer, Christian B; Janes, Kevin A

2016-02-24

Chemical inhibition and genetic knockdown of enzymes are not equivalent in cells, but network-level mechanisms that cause discrepancies between knockdown and inhibitor perturbations are not understood. Here we report that enzymes regulated by negative feedback are robust to knockdown but susceptible to inhibition. Using the Raf-MEK-ERK kinase cascade as a model system, we find that ERK activation is resistant to genetic knockdown of MEK but susceptible to a comparable degree of chemical MEK inhibition. We demonstrate that negative feedback from ERK to Raf causes this knockdown-versus-inhibitor discrepancy in vivo. Exhaustive mathematical modeling of three-tiered enzyme cascades suggests that this result is general: negative autoregulation or feedback favors inhibitor potency, whereas positive autoregulation or feedback favors knockdown potency. Our findings provide a rationale for selecting pharmacologic versus genetic perturbations in vivo and point out the dangers of using knockdown approaches in search of drug targets.

Impacts of biogeographic history and marginal population genetics on species range limits: a case study of Liriodendron chinense.

PubMed

Yang, Aihong; Dick, Christopher W; Yao, Xiaohong; Huang, Hongwen

2016-05-10

Species ranges are influenced by past climate oscillations, geographical constraints, and adaptive potential to colonize novel habitats at range limits. This study used Liriodendron chinense, an important temperate Asian tree species, as a model system to evaluate the roles of biogeographic history and marginal population genetics in determining range limits. We examined the demographic history and genetic diversity of 29 L. chinense populations using both chloroplast and nuclear microsatellite loci. Significant phylogeographic structure was recovered with haplotype clusters coinciding with major mountain regions. Long-term demographical stability was suggested by mismatch distribution analyses, neutrality tests, and ecological niche models (ENM) and suggested the existence of LGM refuges within mountain regions. Differences in genetic diversity between central and marginal populations were not significant for either genomic region. However, asymmetrical gene flow was inferred from central populations to marginal populations, which could potentially limit range adaptation and expansion of L. chinense.

Evaluation of water resources system vulnerability based on co-operative co-evolutionary genetic algorithm and projection pursuit model under the DPSIR framework

NASA Astrophysics Data System (ADS)

Zhao, Y.; Su, X. H.; Wang, M. H.; Li, Z. Y.; Li, E. K.; Xu, X.

2017-08-01

Water resources vulnerability control management is essential because it is related to the benign evolution of socio-economic, environmental and water resources system. Research on water resources system vulnerability is helpful to realization of water resources sustainable utilization. In this study, the DPSIR framework of driving forces-pressure-state-impact-response was adopted to construct the evaluation index system of water resources system vulnerability. Then the co-evolutionary genetic algorithm and projection pursuit were used to establish evaluation model of water resources system vulnerability. Tengzhou City in Shandong Province was selected as a study area. The system vulnerability was analyzed in terms of driving forces, pressure, state, impact and response on the basis of the projection value calculated by the model. The results show that the five components all belong to vulnerability Grade II, the vulnerability degree of impact and state were higher than other components due to the fierce imbalance in supply-demand and the unsatisfied condition of water resources utilization. It is indicated that the influence of high speed socio-economic development and the overuse of the pesticides have already disturbed the benign development of water environment to some extents. While the indexes in response represented lower vulnerability degree than the other components. The results of the evaluation model are coincident with the status of water resources system in the study area, which indicates that the model is feasible and effective.

Ecological systems as computer networks: Long distance sea dispersal as a communication medium between island plant populations.

PubMed

Sanaa, Adnen; Ben Abid, Samir; Boulila, Abdennacer; Messaoud, Chokri; Boussaid, Mohamed; Ben Fadhel, Najeh

2016-06-01

Ecological systems are known to exchange genetic material through animal species migration and seed dispersal for plants. Isolated plant populations have developed long distance dispersal as a means of propagation which rely on meteorological such as anemochory and hydrochory for coast, island and river bank dwelling species. Long distance dispersal by water, in particular, in the case of water current bound islands, calls for the analogy with computer networks, where each island and nearby mainland site plays the role of a network node, the water currents play the role of a transmission channel, and water borne seeds as data packets. In this paper we explore this analogy to model long distance dispersal of seeds among island and mainland populations, when traversed with water currents, in order to model and predict their future genetic diversity. The case of Pancratium maritimum L. populations in Tunisia is used as a proof of concept, where their genetic diversity is extrapolated. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

A standard-enabled workflow for synthetic biology.

PubMed

Myers, Chris J; Beal, Jacob; Gorochowski, Thomas E; Kuwahara, Hiroyuki; Madsen, Curtis; McLaughlin, James Alastair; Mısırlı, Göksel; Nguyen, Tramy; Oberortner, Ernst; Samineni, Meher; Wipat, Anil; Zhang, Michael; Zundel, Zach

2017-06-15

A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select parts to create systems, and modeling and simulation tools to evaluate alternative design choices. Data standards enable the ready exchange of information within such a workflow, allowing repositories and tools to be connected from a diversity of sources. The present paper describes one such workflow that utilizes, among others, the Synthetic Biology Open Language (SBOL) to describe genetic designs, the Systems Biology Markup Language to model these designs, and SBOL Visual to visualize these designs. We describe how a standard-enabled workflow can be used to produce types of design information, including multiple repositories and software tools exchanging information using a variety of data standards. Recently, the ACS Synthetic Biology journal has recommended the use of SBOL in their publications. © 2017 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

Molecular Genetics Information System (MOLGENIS): alternatives in developing local experimental genomics databases.

PubMed

Swertz, Morris A; De Brock, E O; Van Hijum, Sacha A F T; De Jong, Anne; Buist, Girbe; Baerends, Richard J S; Kok, Jan; Kuipers, Oscar P; Jansen, Ritsert C

2004-09-01

Genomic research laboratories need adequate infrastructure to support management of their data production and research workflow. But what makes infrastructure adequate? A lack of appropriate criteria makes any decision on buying or developing a system difficult. Here, we report on the decision process for the case of a molecular genetics group establishing a microarray laboratory. Five typical requirements for experimental genomics database systems were identified: (i) evolution ability to keep up with the fast developing genomics field; (ii) a suitable data model to deal with local diversity; (iii) suitable storage of data files in the system; (iv) easy exchange with other software; and (v) low maintenance costs. The computer scientists and the researchers of the local microarray laboratory considered alternative solutions for these five requirements and chose the following options: (i) use of automatic code generation; (ii) a customized data model based on standards; (iii) storage of datasets as black boxes instead of decomposing them in database tables; (iv) loosely linking to other programs for improved flexibility; and (v) a low-maintenance web-based user interface. Our team evaluated existing microarray databases and then decided to build a new system, Molecular Genetics Information System (MOLGENIS), implemented using code generation in a period of three months. This case can provide valuable insights and lessons to both software developers and a user community embarking on large-scale genomic projects. http://www.molgenis.nl

Establishment of a stable transfection system for genetic manipulation of Babesia gibsoni.

PubMed

Liu, Mingming; Adjou Moumouni, Paul Franck; Asada, Masahito; Hakimi, Hassan; Masatani, Tatsunori; Vudriko, Patrick; Lee, Seung-Hun; Kawazu, Shin-Ichiro; Yamagishi, Junya; Xuan, Xuenan

2018-04-23

Genetic manipulation techniques, such as transfection, have been previously reported in many protozoan parasites. In Babesia, stable transfection systems have only been established for bovine Babesia parasites. We recently reported a transient transfection system and the selection of promoter candidates for Babesia gibsoni. The establishment of a stable transfection system for B. gibsoni is considered to be urgent to improve our understanding of the basic biology of canine Babesia parasites for a better control of babesiosis. GFP-expressing parasites were observed by fluorescence microscopy as early as two weeks after drug selection, and consistently expressed GFP for more than 3 months without drug pressure. Genome integration was confirmed by PCR, sequencing and Southern blot analysis. We present the first successful establishment of a stable transfection system for B. gibsoni. This finding will facilitate functional analysis of Babesia genomes using genetic manipulation and will serve as a foundation for the development of tick-Babesia and host-Babesia infection models.

The influence of genetic selection and feed system on the reproductive performance of spring-calving dairy cows within future pasture-based production systems.

PubMed

Coleman, J; Pierce, K M; Berry, D P; Brennan, A; Horan, B

2009-10-01

Three genetic groups of Holstein-Friesian dairy cows were established from within the Moorepark (Teagasc, Ireland) dairy research herd: LowNA, indicative of the Irish national average-genetic-merit North American Holstein-Friesian; HighNA, high-genetic-merit North American Holstein-Friesian; HighNZ, high-genetic-merit New Zealand Holstein-Friesian. Genetic merit in this study was based on the Irish total merit index, the Economic Breeding Index. Animals from within each genetic group were randomly allocated to 1 of 2 possible post-European Union-milk-quota pasture-based feeding systems (FS): 1) The Moorepark (MP) pasture system (2.64 cows/ha and 500 kg of concentrate supplement per cow per lactation) and 2) a high output per hectare (HC) pasture system (2.85 cows/ha and 1,200 kg of concentrate supplement per cow per lactation). A total of 126, 128, and 140 spring-calving dairy cows were used during the years 2006, 2007, and 2008, respectively. Each group had an individual farmlet of 17 paddocks, and all groups were managed similarly throughout the study. The effects of genetic group, FS, and the interaction between genetic group and FS on reproductive performance, body weight, body condition score, and blood metabolite concentrations were studied using mixed models with factorial arrangements of genetic groups and FS. Odds ratios were used in the analysis of binary fertility traits, and survival analysis was used in the analysis of survival after first calving. When treatment means were compared, the HighNA and HighNZ genotypes (with greater genetic merit for fertility performance) had greater first-service pregnancy rates and had a greater proportion of cows pregnant after 42 d of the breeding season than the LowNA group. Both HighNA and HighNZ genotypes were submitted for artificial insemination earlier in the breeding season and had greater survival than the LowNA genotype. There was no significant FS or genotype by FS interactions for any of the reproductive, blood metabolite, body weight, or body condition score measures. The results demonstrate that increased genetic merit for fertility traits resulted in improved reproductive performance and that the poor reproductive capacity of inferior-genetic-merit animals for fertility was not improved through concentrate supplementation at pasture.

Genetics-based control of a mimo boiler-turbine plant

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

Dimeo, R.M.; Lee, K.Y.

1994-12-31

A genetic algorithm is used to develop an optimal controller for a non-linear, multi-input/multi-output boiler-turbine plant. The algorithm is used to train a control system for the plant over a wide operating range in an effort to obtain better performance. The results of the genetic algorithm`s controller designed from the linearized plant model at a nominal operating point. Because the genetic algorithm is well-suited to solving traditionally difficult optimization problems it is found that the algorithm is capable of developing the controller based on input/output information only. This controller achieves a performance comparable to the standard linear quadratic regulator.

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.

Species mtDNA genetic diversity explained by infrapopulation size in a host-symbiont system.

PubMed

Doña, Jorge; Moreno-García, Marina; Criscione, Charles D; Serrano, David; Jovani, Roger

2015-12-01

Understanding what shapes variation in genetic diversity among species remains a major challenge in evolutionary ecology, and it has been seldom studied in parasites and other host-symbiont systems. Here, we studied mtDNA variation in a host-symbiont non-model system: 418 individual feather mites from 17 feather mite species living on 17 different passerine bird species. We explored how a surrogate of census size, the median infrapopulation size (i.e., the median number of individual parasites per infected host individual), explains mtDNA genetic diversity. Feather mite species genetic diversity was positively correlated with mean infrapopulation size, explaining 34% of the variation. As expected from the biology of feather mites, we found bottleneck signatures for most of the species studied but, in particular, three species presented extremely low mtDNA diversity values given their infrapopulation size. Their star-like haplotype networks (in contrast with more reticulated networks for the other species) suggested that their low genetic diversity was the consequence of severe bottlenecks or selective sweeps. Our study shows for the first time that mtDNA diversity can be explained by infrapopulation sizes, and suggests that departures from this relationship could be informative of underlying ecological and evolutionary processes.

A non-classical phase diagram for virus-bacterial co-evolution mediated by CRISPR

NASA Astrophysics Data System (ADS)

Han, Pu; Deem, Michael

CRISPR is a newly discovered prokaryotic immune system. Bacteria and archaea with this system incorporate genetic material from invading viruses into their genomes, providing protection against future infection by similar viruses. Due to the cost of CRISPR, bacteria can lose the acquired immunity. We will show an intriguing phase diagram of the virus extinction probability, which when the rate of losing the acquired immunity is small, is more complex than that of the classic predator-prey model. As the CRISPR incorporates genetic material, viruses are under pressure to evolve to escape the recognition by CRISPR, and this co-evolution leads to a non-trivial phase structure that cannot be explained by the classical predator-prey model.

Arabidopsis non-host resistance to powdery mildews.

PubMed

Lipka, Ulrike; Fuchs, Rene; Lipka, Volker

2008-08-01

Immunity of an entire plant species against all genetic variants of a particular parasite is referred to as non-host resistance. Although non-host resistance represents the most common and durable form of plant resistance in nature, it has thus far been poorly understood at the molecular level. Recently, novel model systems have established the first mechanistic insights. The genetic dissection of Arabidopsis non-host resistance to non-adapted biotrophic powdery mildew fungi provided evidence for functionally redundant but operationally distinct pre- and post-invasion immune responses. Conceptually, these complex and successive defence mechanisms explain the durable and robust nature of non-host resistance. Pathogen lifestyle and infection biology, ecological parameters and the evolutionary relationship of the interaction partners determine differences and commonalities in other model systems.

The role of latitudinal, genetic and temperature variation in the induction of diapause of Papilio glaucus (Lepidoptera: Papilionidae).

PubMed

Ryan, Sean F; Valella, Patti; Thivierge, Gabrielle; Aardema, Matthew L; Scriber, J Mark

2018-04-01

A key adaptation in insects for dealing with variable environmental conditions is the ability to diapause. The tiger swallowtail butterflies, Papilio glaucus and P. canadensis are ideal species to explore the genetic causes and population genetic consequences of diapause because divergence in this trait is believed to be a salient factor in maintaining a hybrid zone between these species. Yet little is known about the factors that influence diapause induction in this system. Here we explored how spatial (latitudinal), environmental (temperature) and genetic (hybridization) factors affect diapause induction in this system. Specifically, a series of growth chamber experiments using wild caught individuals from across the eastern United States were performed to: (1) evaluate how critical photoperiod varies with latitude, (2) isolate the stage in which induction occurs, (3) test whether changes in temperature affected rates of diapause induction, and (4) explore how the incidence of diapause is affected in hybrid offspring. We find that induction occurs in the larval stage, is not sensitive to a relatively broad range of temperatures, appears to have a complex genetic basis (i.e., is not simply a dominant trait following a Mendelian inheritance pattern) and that the critical photoperiod increases by 0.4 h with each increasing degree in latitude. This work deepens our understanding of how spatial, environmental and genetic variation influences a key seasonal adaptation (diapause induction) in a well-developed ecological model system and will make possible future studies that explore how climatic variation affects the population dynamics and genetics of this system. © 2016 Institute of Zoology, Chinese Academy of Sciences.

Bio-Inspired Genetic Algorithms with Formalized Crossover Operators for Robotic Applications.

PubMed

Zhang, Jie; Kang, Man; Li, Xiaojuan; Liu, Geng-Yang

2017-01-01

Genetic algorithms are widely adopted to solve optimization problems in robotic applications. In such safety-critical systems, it is vitally important to formally prove the correctness when genetic algorithms are applied. This paper focuses on formal modeling of crossover operations that are one of most important operations in genetic algorithms. Specially, we for the first time formalize crossover operations with higher-order logic based on HOL4 that is easy to be deployed with its user-friendly programing environment. With correctness-guaranteed formalized crossover operations, we can safely apply them in robotic applications. We implement our technique to solve a path planning problem using a genetic algorithm with our formalized crossover operations, and the results show the effectiveness of our technique.

Precise and in situ genetic humanization of 6 Mb of mouse immunoglobulin genes.

PubMed

Macdonald, Lynn E; Karow, Margaret; Stevens, Sean; Auerbach, Wojtek; Poueymirou, William T; Yasenchak, Jason; Frendewey, David; Valenzuela, David M; Giallourakis, Cosmas C; Alt, Frederick W; Yancopoulos, George D; Murphy, Andrew J

2014-04-08

Genetic humanization, which involves replacing mouse genes with their human counterparts, can create powerful animal models for the study of human genes and diseases. One important example of genetic humanization involves mice humanized for their Ig genes, allowing for human antibody responses within a mouse background (HumAb mice) and also providing a valuable platform for the generation of fully human antibodies as therapeutics. However, existing HumAb mice do not have fully functional immune systems, perhaps because of the manner in which they were genetically humanized. Heretofore, most genetic humanizations have involved disruption of the endogenous mouse gene with simultaneous introduction of a human transgene at a new and random location (so-called KO-plus-transgenic humanization). More recent efforts have attempted to replace mouse genes with their human counterparts at the same genetic location (in situ humanization), but such efforts involved laborious procedures and were limited in size and precision. We describe a general and efficient method for very large, in situ, and precise genetic humanization using large compound bacterial artificial chromosome-based targeting vectors introduced into mouse ES cells. We applied this method to genetically humanize 3-Mb segments of both the mouse heavy and κ light chain Ig loci, by far the largest genetic humanizations ever described. This paper provides a detailed description of our genetic humanization approach, and the companion paper reports that the humoral immune systems of mice bearing these genetically humanized loci function as efficiently as those of WT mice.

Genetic architecture of the Delis-Kaplan Executive Function System Trail Making Test: evidence for distinct genetic influences on executive function.

PubMed

Vasilopoulos, Terrie; Franz, Carol E; Panizzon, Matthew S; Xian, Hong; Grant, Michael D; Lyons, Michael J; Toomey, Rosemary; Jacobson, Kristen C; Kremen, William S

2012-03-01

To examine how genes and environments contribute to relationships among Trail Making Test (TMT) conditions and the extent to which these conditions have unique genetic and environmental influences. Participants included 1,237 middle-aged male twins from the Vietnam Era Twin Study of Aging. The Delis-Kaplan Executive Function System TMT included visual searching, number and letter sequencing, and set-shifting components. Phenotypic correlations among TMT conditions ranged from 0.29 to 0.60, and genes accounted for the majority (58-84%) of each correlation. Overall heritability ranged from 0.34 to 0.62 across conditions. Phenotypic factor analysis suggested a single factor. In contrast, genetic models revealed a single common genetic factor but also unique genetic influences separate from the common factor. Genetic variance (i.e., heritability) of number and letter sequencing was completely explained by the common genetic factor while unique genetic influences separate from the common factor accounted for 57% and 21% of the heritabilities of visual search and set shifting, respectively. After accounting for general cognitive ability, unique genetic influences accounted for 64% and 31% of those heritabilities. A common genetic factor, most likely representing a combination of speed and sequencing, accounted for most of the correlation among TMT 1-4. Distinct genetic factors, however, accounted for a portion of variance in visual scanning and set shifting. Thus, although traditional phenotypic shared variance analysis techniques suggest only one general factor underlying different neuropsychological functions in nonpatient populations, examining the genetic underpinnings of cognitive processes with twin analysis can uncover more complex etiological processes.

Heterosis Is a Systemic Property Emerging From Non-linear Genotype-Phenotype Relationships: Evidence From in Vitro Genetics and Computer Simulations.

PubMed

Fiévet, Julie B; Nidelet, Thibault; Dillmann, Christine; de Vienne, Dominique

2018-01-01

Heterosis, the superiority of hybrids over their parents for quantitative traits, represents a crucial issue in plant and animal breeding as well as evolutionary biology. Heterosis has given rise to countless genetic, genomic and molecular studies, but has rarely been investigated from the point of view of systems biology. We hypothesized that heterosis is an emergent property of living systems resulting from frequent concave relationships between genotypic variables and phenotypes, or between different phenotypic levels. We chose the enzyme-flux relationship as a model of the concave genotype-phenotype (GP) relationship, and showed that heterosis can be easily created in the laboratory. First, we reconstituted in vitro the upper part of glycolysis. We simulated genetic variability of enzyme activity by varying enzyme concentrations in test tubes. Mixing the content of "parental" tubes resulted in "hybrids," whose fluxes were compared to the parental fluxes. Frequent heterotic fluxes were observed, under conditions that were determined analytically and confirmed by computer simulation. Second, to test this model in a more realistic situation, we modeled the glycolysis/fermentation network in yeast by considering one input flux, glucose, and two output fluxes, glycerol and acetaldehyde. We simulated genetic variability by randomly drawing parental enzyme concentrations under various conditions, and computed the parental and hybrid fluxes using a system of differential equations. Again we found that a majority of hybrids exhibited positive heterosis for metabolic fluxes. Cases of negative heterosis were due to local convexity between certain enzyme concentrations and fluxes. In both approaches, heterosis was maximized when the parents were phenotypically close and when the distributions of parental enzyme concentrations were contrasted and constrained. These conclusions are not restricted to metabolic systems: they only depend on the concavity of the GP relationship, which is commonly observed at various levels of the phenotypic hierarchy, and could account for the pervasiveness of heterosis.

Encapsulated Optically Responsive Cell Systems: Toward Smart Implants in Biomedicine.

PubMed

Boss, Christophe; Bouche, Nicolas; De Marchi, Umberto

2018-04-01

Managing increasingly prevalent chronic diseases will require close continuous monitoring of patients. Cell-based biosensors may be used for implantable diagnostic systems to monitor health status. Cells are indeed natural sensors in the body. Functional cellular systems can be maintained in the body for long-term implantation using cell encapsulation technology. By taking advantage of recent progress in miniaturized optoelectronic systems, the genetic engineering of optically responsive cells may be combined with cell encapsulation to generate smart implantable cell-based sensing systems. In biomedical research, cell-based biosensors may be used to study cell signaling, therapeutic effects, and dosing of bioactive molecules in preclinical models. Today, a wide variety of genetically encoded fluorescent sensors have been developed for real-time imaging of living cells. Here, recent developments in genetically encoded sensors, cell encapsulation, and ultrasmall optical systems are highlighted. The integration of these components in a new generation of biosensors is creating innovative smart in vivo cell-based systems, bringing novel perspectives for biomedical research and ultimately allowing unique health monitoring applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Chemical event chain model of coupled genetic oscillators.

PubMed

Jörg, David J; Morelli, Luis G; Jülicher, Frank

2018-03-01

We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

Chemical event chain model of coupled genetic oscillators

NASA Astrophysics Data System (ADS)

Jörg, David J.; Morelli, Luis G.; Jülicher, Frank

2018-03-01

We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays.

Applications of the CRISPR-Cas9 system in cancer biology

PubMed Central

Sánchez-Rivera, Francisco J.; Jacks, Tyler

2015-01-01

Preface The prokaryotic type II clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 system is rapidly revolutionizing the field of genetic engineering, allowing researchers to alter the genomes of a large variety of organisms with relative ease. Experimental approaches based on this versatile technology have the potential to transform the field of cancer genetics. Here we review current approaches based on CRISPR-Cas9 for functional studies of cancer genes, with emphasis on its applicability for the development of the next-generation models of human cancer. PMID:26040603

A simplified fractional order impedance model and parameter identification method for lithium-ion batteries

PubMed Central

Yang, Qingxia; Xu, Jun; Cao, Binggang; Li, Xiuqing

2017-01-01

Identification of internal parameters of lithium-ion batteries is a useful tool to evaluate battery performance, and requires an effective model and algorithm. Based on the least square genetic algorithm, a simplified fractional order impedance model for lithium-ion batteries and the corresponding parameter identification method were developed. The simplified model was derived from the analysis of the electrochemical impedance spectroscopy data and the transient response of lithium-ion batteries with different states of charge. In order to identify the parameters of the model, an equivalent tracking system was established, and the method of least square genetic algorithm was applied using the time-domain test data. Experiments and computer simulations were carried out to verify the effectiveness and accuracy of the proposed model and parameter identification method. Compared with a second-order resistance-capacitance (2-RC) model and recursive least squares method, small tracing voltage fluctuations were observed. The maximum battery voltage tracing error for the proposed model and parameter identification method is within 0.5%; this demonstrates the good performance of the model and the efficiency of the least square genetic algorithm to estimate the internal parameters of lithium-ion batteries. PMID:28212405

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.

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

A Worldwide Competition to Compare the Speed and Chemotactic Accuracy of Neutrophil-Like Cells

PubMed Central

Wong, Elisabeth; Hamza, Bashar; Bae, Albert; Martel, Joseph; Kataria, Rama; Keizer-Gunnink, Ineke; Kortholt, Arjan; Van Haastert, Peter J. M.; Charras, Guillaume; Janetopoulos, Christopher; Irimia, Daniel

2016-01-01

Chemotaxis is the ability to migrate towards the source of chemical gradients. It underlies the ability of neutrophils and other immune cells to hone in on their targets and defend against invading pathogens. Given the importance of neutrophil migration to health and disease, it is crucial to understand the basic mechanisms controlling chemotaxis so that strategies can be developed to modulate cell migration in clinical settings. Because of the complexity of human genetics, Dictyostelium and HL60 cells have long served as models system for studying chemotaxis. Since many of our current insights into chemotaxis have been gained from these two model systems, we decided to compare them side by side in a set of winner-take-all races, the Dicty World Races. These worldwide competitions challenge researchers to genetically engineer and pharmacologically enhance the model systems to compete in microfluidic racecourses. These races bring together technological innovations in genetic engineering and precision measurement of cell motility. Fourteen teams participated in the inaugural Dicty World Race 2014 and contributed cell lines, which they tuned for enhanced speed and chemotactic accuracy. The race enabled large-scale analyses of chemotaxis in complex environments and revealed an intriguing balance of speed and accuracy of the model cell lines. The successes of the first race validated the concept of using fun-spirited competition to gain insights into the complex mechanisms controlling chemotaxis, while the challenges of the first race will guide further technological development and planning of future events. PMID:27332963

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

Meganucleases Revolutionize the Production of Genetically Engineered Pigs for the Study of Human Diseases.

PubMed

Redel, Bethany K; Prather, Randall S

2016-04-01

Animal models of human diseases are critically necessary for developing an in-depth knowledge of disease development and progression. In addition, animal models are vital to the development of potential treatments or even cures for human diseases. Pigs are exceptional models as their size, physiology, and genetics are closer to that of humans than rodents. In this review, we discuss the use of pigs in human translational research and the evolving technology that has increased the efficiency of genetically engineering pigs. With the emergence of the clustered, regularly interspaced, short palindromic repeat (CRISPR)/CRISPR-associated (Cas) protein 9 system technology, the cost and time it takes to genetically engineer pigs has markedly decreased. We will also discuss the use of another meganuclease, the transcription activator-like effector nucleases , to produce pigs with severe combined immunodeficiency by developing targeted modifications of the recombination activating gene 2 (RAG2).RAG2mutant pigs may become excellent animals to facilitate the development of xenotransplantation, regenerative medicine, and tumor biology. The use of pig biomedical models is vital for furthering the knowledge of, and for treating human, diseases. © The Author(s) 2015.

Fashion sketch design by interactive genetic algorithms

NASA Astrophysics Data System (ADS)

Mok, P. Y.; Wang, X. X.; Xu, J.; Kwok, Y. L.

2012-11-01

Computer aided design is vitally important for the modern industry, particularly for the creative industry. Fashion industry faced intensive challenges to shorten the product development process. In this paper, a methodology is proposed for sketch design based on interactive genetic algorithms. The sketch design system consists of a sketch design model, a database and a multi-stage sketch design engine. First, a sketch design model is developed based on the knowledge of fashion design to describe fashion product characteristics by using parameters. Second, a database is built based on the proposed sketch design model to define general style elements. Third, a multi-stage sketch design engine is used to construct the design. Moreover, an interactive genetic algorithm (IGA) is used to accelerate the sketch design process. The experimental results have demonstrated that the proposed method is effective in helping laypersons achieve satisfied fashion design sketches.

A Road Map for Precision Medicine in the Epilepsies

PubMed Central

2015-01-01

Summary Technological advances have paved the way for accelerated genomic discovery and are bringing precision medicine clearly into view. Epilepsy research in particular is well-suited to serve as a model for the development and deployment of targeted therapeutics in precision medicine because of the rapidly expanding genetic knowledge base in epilepsy, the availability of good in vitro and in vivo model systems to efficiently study the biological consequences of genetic mutations, the ability to turn these models into effective drug screening platforms, and the establishment of collaborative research groups. Moving forward, it is critical that we strengthen these collaborations, particularly through integrated research platforms to provide robust analyses both for accurate personal genome analysis and gene and drug discovery. Similarly, the implementation of clinical trial networks will allow the expansion of patient sample populations with genetically defined epilepsy so that drug discovery can be translated into clinical practice. PMID:26416172

Genetic control of root growth: from genes to networks

PubMed Central

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

2016-01-01

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

Using Movies to Analyse Gene Circuit Dynamics in Single Cells

PubMed Central

Locke, James CW; Elowitz, Michael B

2010-01-01

Preface Many bacterial systems rely on dynamic genetic circuits to control critical processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages wash out critical dynamics that are either unsynchronized between cells or driven by fluctuations, or ‘noise,’ in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis, and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems. PMID:19369953

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

PubMed Central

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

2014-01-01

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

Stochastic many-body problems in ecology, evolution, neuroscience, and systems biology

NASA Astrophysics Data System (ADS)

Butler, Thomas C.

Using the tools of many-body theory, I analyze problems in four different areas of biology dominated by strong fluctuations: The evolutionary history of the genetic code, spatiotemporal pattern formation in ecology, spatiotemporal pattern formation in neuroscience and the robustness of a model circadian rhythm circuit in systems biology. In the first two research chapters, I demonstrate that the genetic code is extremely optimal (in the sense that it manages the effects of point mutations or mistranslations efficiently), more than an order of magnitude beyond what was previously thought. I further show that the structure of the genetic code implies that early proteins were probably only loosely defined. Both the nature of early proteins and the extreme optimality of the genetic code are interpreted in light of recent theory [1] as evidence that the evolution of the genetic code was driven by evolutionary dynamics that were dominated by horizontal gene transfer. I then explore the optimality of a proposed precursor to the genetic code. The results show that the precursor code has only limited optimality, which is interpreted as evidence that the precursor emerged prior to translation, or else never existed. In the next part of the dissertation, I introduce a many-body formalism for reaction-diffusion systems described at the mesoscopic scale with master equations. I first apply this formalism to spatially-extended predator-prey ecosystems, resulting in the prediction that many-body correlations and fluctuations drive population cycles in time, called quasicycles. Most of these results were previously known, but were derived using the system size expansion [2, 3]. I next apply the analytical techniques developed in the study of quasi-cycles to a simple model of Turing patterns in a predator-prey ecosystem. This analysis shows that fluctuations drive the formation of a new kind of spatiotemporal pattern formation that I name "quasi-patterns." These quasi-patterns exist over a much larger range of physically accessible parameters than the patterns predicted in mean field theory and therefore account for the apparent observations in ecology of patterns in regimes where Turing patterns do not occur. I further show that quasi-patterns have statistical properties that allow them to be distinguished empirically from mean field Turing patterns. I next analyze a model of visual cortex in the brain that has striking similarities to the activator-inhibitor model of ecosystem quasi-pattern formation. Through analysis of the resulting phase diagram, I show that the architecture of the neural network in the visual cortex is configured to make the visual cortex robust to unwanted internally generated spatial structure that interferes with normal visual function. I also predict that some geometric visual hallucinations are quasi-patterns and that the visual cortex supports a new phase of spatially scale invariant behavior present far from criticality. In the final chapter, I explore the effects of fluctuations on cycles in systems biology, specifically the pervasive phenomenon of circadian rhythms. By exploring the behavior of a generic stochastic model of circadian rhythms, I show that the circadian rhythm circuit exploits leaky mRNA production to safeguard the cycle from failure. I also show that this safeguard mechanism is highly robust to changes in the rate of leaky mRNA production. Finally, I explore the failure of the deterministic model in two different contexts, one where the deterministic model predicts cycles where they do not exist, and another context in which cycles are not predicted by the deterministic model.

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.

D-VASim: an interactive virtual laboratory environment for the simulation and analysis of genetic circuits.

PubMed

Baig, Hasan; Madsen, Jan

2017-01-15

Simulation and behavioral analysis of genetic circuits is a standard approach of functional verification prior to their physical implementation. Many software tools have been developed to perform in silico analysis for this purpose, but none of them allow users to interact with the model during runtime. The runtime interaction gives the user a feeling of being in the lab performing a real world experiment. In this work, we present a user-friendly software tool named D-VASim (Dynamic Virtual Analyzer and Simulator), which provides a virtual laboratory environment to simulate and analyze the behavior of genetic logic circuit models represented in an SBML (Systems Biology Markup Language). Hence, SBML models developed in other software environments can be analyzed and simulated in D-VASim. D-VASim offers deterministic as well as stochastic simulation; and differs from other software tools by being able to extract and validate the Boolean logic from the SBML model. D-VASim is also capable of analyzing the threshold value and propagation delay of a genetic circuit model. D-VASim is available for Windows and Mac OS and can be downloaded from bda.compute.dtu.dk/downloads/. haba@dtu.dk, jama@dtu.dk. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Taste and pheromone perception in the fruit fly Drosophila melanogaster.

PubMed

Ebbs, Michelle L; Amrein, Hubert

2007-08-01

Taste is an essential sense for detection of nutrient-rich food and avoidance of toxic substances. The Drosophila melanogaster gustatory system provides an excellent model to study taste perception and taste-elicited behaviors. "The fly" is unique in the animal kingdom with regard to available experimental tools, which include a wide repertoire of molecular-genetic analyses (i.e., efficient production of transgenics and gene knockouts), elegant behavioral assays, and the possibility to conduct electrophysiological investigations. In addition, fruit flies, like humans, recognize sugars as a food source, but avoid bitter tasting substances that are often toxic to insects and mammals alike. This paper will present recent research progress in the field of taste and contact pheromone perception in the fruit fly. First, we shall describe the anatomical properties of the Drosophila gustatory system and survey the family of taste receptors to provide an appropriate background. We shall then review taste and pheromone perception mainly from a molecular genetic perspective that includes behavioral, electrophysiological and imaging analyses of wild type flies and flies with genetically manipulated taste cells. Finally, we shall provide an outlook of taste research in this elegant model system for the next few years.

Contributions of dopamine-related genes and environmental factors to highly sensitive personality: a multi-step neuronal system-level approach.

PubMed

Chen, Chunhui; Chen, Chuansheng; Moyzis, Robert; Stern, Hal; He, Qinghua; Li, He; Li, Jin; Zhu, Bi; Dong, Qi

2011-01-01

Traditional behavioral genetic studies (e.g., twin, adoption studies) have shown that human personality has moderate to high heritability, but recent molecular behavioral genetic studies have failed to identify quantitative trait loci (QTL) with consistent effects. The current study adopted a multi-step approach (ANOVA followed by multiple regression and permutation) to assess the cumulative effects of multiple QTLs. Using a system-level (dopamine system) genetic approach, we investigated a personality trait deeply rooted in the nervous system (the Highly Sensitive Personality, HSP). 480 healthy Chinese college students were given the HSP scale and genotyped for 98 representative polymorphisms in all major dopamine neurotransmitter genes. In addition, two environment factors (stressful life events and parental warmth) that have been implicated for their contributions to personality development were included to investigate their relative contributions as compared to genetic factors. In Step 1, using ANOVA, we identified 10 polymorphisms that made statistically significant contributions to HSP. In Step 2, these polymorphism's main effects and interactions were assessed using multiple regression. This model accounted for 15% of the variance of HSP (p<0.001). Recent stressful life events accounted for an additional 2% of the variance. Finally, permutation analyses ascertained the probability of obtaining these findings by chance to be very low, p ranging from 0.001 to 0.006. Dividing these loci by the subsystems of dopamine synthesis, degradation/transport, receptor and modulation, we found that the modulation and receptor subsystems made the most significant contribution to HSP. The results of this study demonstrate the utility of a multi-step neuronal system-level approach in assessing genetic contributions to individual differences in human behavior. It can potentially bridge the gap between the high heritability estimates based on traditional behavioral genetics and the lack of reproducible genetic effects observed currently from molecular genetic studies.

Contributions of Dopamine-Related Genes and Environmental Factors to Highly Sensitive Personality: A Multi-Step Neuronal System-Level Approach

PubMed Central

Chen, Chunhui; Chen, Chuansheng; Moyzis, Robert; Stern, Hal; He, Qinghua; Li, He; Li, Jin; Zhu, Bi; Dong, Qi

2011-01-01

Traditional behavioral genetic studies (e.g., twin, adoption studies) have shown that human personality has moderate to high heritability, but recent molecular behavioral genetic studies have failed to identify quantitative trait loci (QTL) with consistent effects. The current study adopted a multi-step approach (ANOVA followed by multiple regression and permutation) to assess the cumulative effects of multiple QTLs. Using a system-level (dopamine system) genetic approach, we investigated a personality trait deeply rooted in the nervous system (the Highly Sensitive Personality, HSP). 480 healthy Chinese college students were given the HSP scale and genotyped for 98 representative polymorphisms in all major dopamine neurotransmitter genes. In addition, two environment factors (stressful life events and parental warmth) that have been implicated for their contributions to personality development were included to investigate their relative contributions as compared to genetic factors. In Step 1, using ANOVA, we identified 10 polymorphisms that made statistically significant contributions to HSP. In Step 2, these polymorphism's main effects and interactions were assessed using multiple regression. This model accounted for 15% of the variance of HSP (p<0.001). Recent stressful life events accounted for an additional 2% of the variance. Finally, permutation analyses ascertained the probability of obtaining these findings by chance to be very low, p ranging from 0.001 to 0.006. Dividing these loci by the subsystems of dopamine synthesis, degradation/transport, receptor and modulation, we found that the modulation and receptor subsystems made the most significant contribution to HSP. The results of this study demonstrate the utility of a multi-step neuronal system-level approach in assessing genetic contributions to individual differences in human behavior. It can potentially bridge the gap between the high heritability estimates based on traditional behavioral genetics and the lack of reproducible genetic effects observed currently from molecular genetic studies. PMID:21765900

Peromyscus as a model system for human hepatitis C: An opportunity to advance our understanding of a complex host parasite system.

PubMed

Vandegrift, Kurt J; Critchlow, Justin T; Kapoor, Amit; Friedman, David A; Hudson, Peter J

2017-01-01

Worldwide, there are 185 million people infected with hepatitis C virus and approximately 350,000 people die each year from hepatitis C associated liver diseases. Human hepatitis C research has been hampered by the lack of an appropriate in vivo model system. Most of the in vivo research has been conducted on chimpanzees, which is complicated by ethical concerns, small sample sizes, high costs, and genetic heterogeneity. The house mouse system has led to greater understanding of a wide variety of human pathogens, but it is unreasonable to expect Mus musculus to be a good model system for every human pathogen. Alternative animal models can be developed in these cases. Ferrets (influenza), cotton rats (human respiratory virus), and woodchucks (hepatitis B) are all alternative models that have led to a greater understanding of human pathogens. Rodent models are tractable, genetically amenable and inbred and outbred strains can provide homogeneity in results. Recently, a rodent homolog of hepatitis C was discovered and isolated from the liver of a Peromyscus maniculatus. This represents the first small mammal (mouse) model system for human hepatitis C and it offers great potential to contribute to our understanding and ultimately aid in our efforts to combat this serious public health concern. Peromyscus are available commercially and can be used to inform questions about the origin, transmission, persistence, pathology, and rational treatment of hepatitis C. Here, we provide a disease ecologist's overview of this new virus and some suggestions for useful future experiments. Copyright © 2016. Published by Elsevier Ltd.

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

Decade Review (1999-2009): Artificial Intelligence Techniques in Student Modeling

NASA Astrophysics Data System (ADS)

Drigas, Athanasios S.; Argyri, Katerina; Vrettaros, John

Artificial Intelligence applications in educational field are getting more and more popular during the last decade (1999-2009) and that is why much relevant research has been conducted. In this paper, we present the most interesting attempts to apply artificial intelligence methods such as fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro - fuzzy systems and genetic programming neural networks (GPNN) in student modeling. This latest research trend is a part of every Intelligent Tutoring System and aims at generating and updating a student model in order to modify learning content to fit individual needs or to provide reliable assessment and feedback to student's answers. In this paper, we make a brief presentation of methods used to point out their qualities and then we attempt a navigation to the most representative studies sought in the decade of our interest after classifying them according to the principal aim they attempted to serve.

An efficient algorithm for computing fixed length attractors based on bounded model checking in synchronous Boolean networks with biochemical applications.

PubMed

Li, X Y; Yang, G W; Zheng, D S; Guo, W S; Hung, W N N

2015-04-28

Genetic regulatory networks are the key to understanding biochemical systems. One condition of the genetic regulatory network under different living environments can be modeled as a synchronous Boolean network. The attractors of these Boolean networks will help biologists to identify determinant and stable factors. Existing methods identify attractors based on a random initial state or the entire state simultaneously. They cannot identify the fixed length attractors directly. The complexity of including time increases exponentially with respect to the attractor number and length of attractors. This study used the bounded model checking to quickly locate fixed length attractors. Based on the SAT solver, we propose a new algorithm for efficiently computing the fixed length attractors, which is more suitable for large Boolean networks and numerous attractors' networks. After comparison using the tool BooleNet, empirical experiments involving biochemical systems demonstrated the feasibility and efficiency of our approach.

Optogenetics: a new enlightenment age for zebrafish neurobiology.

PubMed

Del Bene, Filippo; Wyart, Claire

2012-03-01

Zebrafish became a model of choice for neurobiology because of the transparency of its brain and because of its amenability to genetic manipulation. In particular, at early stages of development the intact larva is an ideal system to apply optical techniques for deep imaging in the nervous system, as well as genetically encoded tools for targeting subsets of neurons and monitoring and manipulating their activity. For these applications,new genetically encoded optical tools, fluorescent sensors, and light-gated channels have been generated,creating the field of "optogenetics." It is now possible to monitor and control neuronal activity with minimal perturbation and unprecedented spatio-temporal resolution.We describe here the main achievements that have occurred in the last decade in imaging and manipulating neuronal activity in intact zebrafish larvae. We provide also examples of functional dissection of neuronal circuits achieved with the applications of these techniques in the visual and locomotor systems.

Can Yeast (S. cerevisiae) Metabolic Volatiles Provide Polymorphic Signaling?

PubMed Central

Arguello, J. Roman; Sellanes, Carolina; Lou, Yann Ru; Raguso, Robert A.

2013-01-01

Chemical signaling between organisms is a ubiquitous and evolutionarily dynamic process that helps to ensure mate recognition, location of nutrients, avoidance of toxins, and social cooperation. Evolutionary changes in chemical communication systems progress through natural variation within the organism generating the signal as well as the responding individuals. A promising yet poorly understood system with which to probe the importance of this variation exists between D. melanogaster and S. cerevisiae. D. melanogaster relies on yeast for nutrients, while also serving as a vector for yeast cell dispersal. Both are outstanding genetic and genomic models, with Drosophila also serving as a preeminent model for sensory neurobiology. To help develop these two genetic models as an ecological model, we have tested if - and to what extent - S. cerevisiae is capable of producing polymorphic signaling through variation in metabolic volatiles. We have carried out a chemical phenotyping experiment for 14 diverse accessions within a common garden random block design. Leveraging genomic sequences for 11 of the accessions, we ensured a genetically broad sample and tested for phylogenetic signal arising from phenotypic dataset. Our results demonstrate that significant quantitative differences for volatile blends do exist among S. cerevisiae accessions. Of particular ecological relevance, the compounds driving the blend differences (acetoin, 2-phenyl ethanol and 3-methyl-1-butanol) are known ligands for D. melanogasters chemosensory receptors, and are related to sensory behaviors. Though unable to correlate the genetic and volatile measurements, our data point clear ways forward for behavioral assays aimed at understanding the implications of this variation. PMID:23990899

Living on the edge of chaos: minimally nonlinear models of genetic regulatory dynamics.

PubMed

Hanel, Rudolf; Pöchacker, Manfred; Thurner, Stefan

2010-12-28

Linearized catalytic reaction equations (modelling, for example, the dynamics of genetic regulatory networks), under the constraint that expression levels, i.e. molecular concentrations of nucleic material, are positive, exhibit non-trivial dynamical properties, which depend on the average connectivity of the reaction network. In these systems, an inflation of the edge of chaos and multi-stability have been demonstrated to exist. The positivity constraint introduces a nonlinearity, which makes chaotic dynamics possible. Despite the simplicity of such minimally nonlinear systems, their basic properties allow us to understand the fundamental dynamical properties of complex biological reaction networks. We analyse the Lyapunov spectrum, determine the probability of finding stationary oscillating solutions, demonstrate the effect of the nonlinearity on the effective in- and out-degree of the active interaction network, and study how the frequency distributions of oscillatory modes of such a system depend on the average connectivity.

Juxtaposition of chemical and mutation-induced developmental defects in zebrafish reveal a copper-chelating activity for kalihinol F.

PubMed

Sandoval, Imelda T; Manos, Elizabeth J; Van Wagoner, Ryan M; Delacruz, Richard Glenn C; Edes, Kornelia; Winge, Dennis R; Ireland, Chris M; Jones, David A

2013-06-20

A major hurdle in using complex systems for drug screening is the difficulty of defining the mechanistic targets of small molecules. The zebrafish provides an excellent model system for juxtaposing developmental phenotypes with mechanism discovery using organism genetics. We carried out a phenotype-based screen of uncharacterized small molecules in zebrafish that produced a variety of chemically induced phenotypes with potential genetic parallels. Specifically, kalihinol F caused an undulated notochord, defects in pigment formation, hematopoiesis, and neural development. These phenotypes were strikingly similar to the zebrafish mutant, calamity, an established model of copper deficiency. Further studies into the mechanism of action of kalihinol F revealed a copper-chelating activity. Our data support this mechanism of action for kalihinol F and the utility of zebrafish as an effective system for identifying therapeutic and target pathways. Copyright © 2013 Elsevier Ltd. All rights reserved.

The neurobiological basis of human aggression: A review on genetic and epigenetic mechanisms.

PubMed

Waltes, Regina; Chiocchetti, Andreas G; Freitag, Christine M

2016-07-01

Aggression is an evolutionary conserved behavior present in most species including humans. Inadequate aggression can lead to long-term detrimental personal and societal effects. Here, we differentiate between proactive and reactive forms of aggression and review the genetic determinants of it. Heritability estimates of aggression in general vary between studies due to differing assessment instruments for aggressive behavior (AB) as well as age and gender of study participants. In addition, especially non-shared environmental factors shape AB. Current hypotheses suggest that environmental effects such as early life stress or chronic psychosocial risk factors (e.g., maltreatment) and variation in genes related to neuroendocrine, dopaminergic as well as serotonergic systems increase the risk to develop AB. In this review, we summarize the current knowledge of the genetics of human aggression based on twin studies, genetic association studies, animal models, and epigenetic analyses with the aim to differentiate between mechanisms associated with proactive or reactive aggression. We hypothesize that from a genetic perspective, the aminergic systems are likely to regulate both reactive and proactive aggression, whereas the endocrine pathways seem to be more involved in regulation of reactive aggression through modulation of impulsivity. Epigenetic studies on aggression have associated non-genetic risk factors with modifications of the stress response and the immune system. Finally, we point to the urgent need for further genome-wide analyses and the integration of genetic and epigenetic information to understand individual differences in reactive and proactive AB. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

TRIENNIAL LACTATION SYMPOSIUM: Systems biology of regulatory mechanisms of nutrient metabolism in lactation.

PubMed

McNamara, J P

2015-12-01

A major role of the dairy cow is to convert low-quality plant materials into high-quality protein and other nutrients for humans. We must select and manage cows with the goal of having animals of the greatest efficiency matched to their environment. We have increased efficiency tremendously over the years, yet the variation in productive and reproductive efficiency among animals is still large. In part, this is because of a lack of full integration of genetic, nutritional, and reproductive biology into management decisions. However, integration across these disciplines is increasing as the biological research findings show specific control points at which genetics, nutrition, and reproduction interact. An ordered systems biology approach that focuses on why and how cells regulate energy and N use and on how and why organs interact through endocrine and neurocrine mechanisms will speed improvements in efficiency. More sophisticated dairy managers will demand better information to improve the efficiency of their animals. Using genetic improvement and animal management to improve milk productive and reproductive efficiency requires a deeper understanding of metabolic processes throughout the life cycle. Using existing metabolic models, we can design experiments specifically to integrate data from global transcriptional profiling into models that describe nutrient use in farm animals. A systems modeling approach can help focus our research to make faster and larger advances in efficiency and determine how this knowledge can be applied on the farms.

Engineering Strategies to Decode and Enhance the Genomes of Coral Symbionts.

PubMed

Levin, Rachel A; Voolstra, Christian R; Agrawal, Shobhit; Steinberg, Peter D; Suggett, David J; van Oppen, Madeleine J H

2017-01-01

Elevated sea surface temperatures from a severe and prolonged El Niño event (2014-2016) fueled by climate change have resulted in mass coral bleaching (loss of dinoflagellate photosymbionts, Symbiodinium spp., from coral tissues) and subsequent coral mortality, devastating reefs worldwide. Genetic variation within and between Symbiodinium species strongly influences the bleaching tolerance of corals, thus recent papers have called for genetic engineering of Symbiodinium to elucidate the genetic basis of bleaching-relevant Symbiodinium traits. However, while Symbiodinium has been intensively studied for over 50 years, genetic transformation of Symbiodinium has seen little success likely due to the large evolutionary divergence between Symbiodinium and other model eukaryotes rendering standard transformation systems incompatible. Here, we integrate the growing wealth of Symbiodinium next-generation sequencing data to design tailored genetic engineering strategies. Specifically, we develop a testable expression construct model that incorporates endogenous Symbiodinium promoters, terminators, and genes of interest, as well as an internal ribosomal entry site from a Symbiodinium virus. Furthermore, we assess the potential for CRISPR/Cas9 genome editing through new analyses of the three currently available Symbiodinium genomes. Finally, we discuss how genetic engineering could be applied to enhance the stress tolerance of Symbiodinium , and in turn, coral reefs.

Hair Cortisol in Twins: Heritability and Genetic Overlap with Psychological Variables and Stress-System Genes.

PubMed

Rietschel, Liz; Streit, Fabian; Zhu, Gu; McAloney, Kerrie; Frank, Josef; Couvy-Duchesne, Baptiste; Witt, Stephanie H; Binz, Tina M; McGrath, John; Hickie, Ian B; Hansell, Narelle K; Wright, Margaret J; Gillespie, Nathan A; Forstner, Andreas J; Schulze, Thomas G; Wüst, Stefan; Nöthen, Markus M; Baumgartner, Markus R; Walker, Brian R; Crawford, Andrew A; Colodro-Conde, Lucía; Medland, Sarah E; Martin, Nicholas G; Rietschel, Marcella

2017-11-10

Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-individual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC; (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism; using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables.

Drosophila and experimental neurology in the post-genomic era.

PubMed

Shulman, Joshua M

2015-12-01

For decades, the fruit fly, Drosophila melanogaster, has been among the premiere genetic model systems for probing fundamental neurobiology, including elucidation of mechanisms responsible for human neurologic disorders. Flies continue to offer virtually unparalleled versatility and speed for genetic manipulation, strong genomic conservation, and a nervous system that recapitulates a range of cellular and network properties relevant to human disease. I focus here on four critical challenges emerging from recent advances in our understanding of the genomic basis of human neurologic disorders where innovative experimental strategies are urgently needed: (1) pinpointing causal genes from associated genomic loci; (2) confirming the functional impact of allelic variants; (3) elucidating nervous system roles for novel or poorly studied genes; and (4) probing network interactions within implicated regulatory pathways. Drosophila genetic approaches are ideally suited to address each of these potential translational roadblocks, and will therefore contribute to mechanistic insights and potential breakthrough therapies for complex genetic disorders in the coming years. Strategic collaboration between neurologists, human geneticists, and the Drosophila research community holds great promise to accelerate progress in the post-genomic era. Copyright © 2015 Elsevier Inc. All rights reserved.

Genetic influences on heart rate variability

PubMed Central

Golosheykin, Simon; Grant, Julia D.; Novak, Olga V.; Heath, Andrew C.; Anokhin, Andrey P.

2016-01-01

Heart rate variability (HRV) is the variation of cardiac inter-beat intervals over time resulting largely from the interplay between the sympathetic and parasympathetic branches of the autonomic nervous system. Individual differences in HRV are associated with emotion regulation, personality, psychopathology, cardiovascular health, and mortality. Previous studies have shown significant heritability of HRV measures. Here we extend genetic research on HRV by investigating sex differences in genetic underpinnings of HRV, the degree of genetic overlap among different measurement domains of HRV, and phenotypic and genetic relationships between HRV and the resting heart rate (HR). We performed electrocardiogram (ECG) recordings in a large population-representative sample of young adult twins (n = 1060 individuals) and computed HRV measures from three domains: time, frequency, and nonlinear dynamics. Genetic and environmental influences on HRV measures were estimated using linear structural equation modeling of twin data. The results showed that variability of HRV and HR measures can be accounted for by additive genetic and non-shared environmental influences (AE model), with no evidence for significant shared environmental effects. Heritability estimates ranged from 47 to 64%, with little difference across HRV measurement domains. Genetic influences did not differ between genders for most variables except the square root of the mean squared differences between successive R-R intervals (RMSSD, higher heritability in males) and the ratio of low to high frequency power (LF/HF, distinct genetic factors operating in males and females). The results indicate high phenotypic and especially genetic correlations between HRV measures from different domains, suggesting that >90% of genetic influences are shared across measures. Finally, about 40% of genetic variance in HRV was shared with HR. In conclusion, both HR and HRV measures are highly heritable traits in the general population of young adults, with high degree of genetic overlap across different measurement domains. PMID:27114045

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.

Environment, dysbiosis, immunity and sex-specific susceptibility: a translational hypothesis for regressive autism pathogenesis.

PubMed

Mezzelani, Alessandra; Landini, Martina; Facchiano, Francesco; Raggi, Maria Elisabetta; Villa, Laura; Molteni, Massimo; De Santis, Barbara; Brera, Carlo; Caroli, Anna Maria; Milanesi, Luciano; Marabotti, Anna

2015-05-01

Autism is an increasing neurodevelopmental disease that appears by 3 years of age, has genetic and/or environmental etiology, and often shows comorbid situations, such as gastrointestinal (GI) disorders. Autism has also a striking sex-bias, not fully genetically explainable. Our goal was to explain how and in which predisposing conditions some compounds can impair neurodevelopment, why this occurs in the first years of age, and, primarily, why more in males than females. We reviewed articles regarding the genetic and environmental etiology of autism and toxins effects on animal models selected from PubMed and databases about autism and toxicology. Our hypothesis proposes that in the first year of life, the decreasing of maternal immune protection and child immune-system immaturity create an immune vulnerability to infection diseases that, especially if treated with antibiotics, could facilitate dysbiosis and GI disorders. This condition triggers a vicious circle between immune system impairment and increasing dysbiosis that leads to leaky gut and neurochemical compounds and/or neurotoxic xenobiotics production and absorption. This alteration affects the 'gut-brain axis' communication that connects gut with central nervous system via immune system. Thus, metabolic pathways impaired in autistic children can be affected by genetic alterations or by environment-xenobiotics interference. In addition, in animal models many xenobiotics exert their neurotoxicity in a sex-dependent manner. We integrate fragmented and multi-disciplinary information in a unique hypothesis and first disclose a possible environmental origin for the imbalance of male:female distribution of autism, reinforcing the idea that exogenous factors are related to the recent rise of this disease.

A methodology to annotate systems biology markup language models with the synthetic biology open language.

PubMed

Roehner, Nicholas; Myers, Chris J

2014-02-21

Recently, we have begun to witness the potential of synthetic biology, noted here in the form of bacteria and yeast that have been genetically engineered to produce biofuels, manufacture drug precursors, and even invade tumor cells. The success of these projects, however, has often failed in translation and application to new projects, a problem exacerbated by a lack of engineering standards that combine descriptions of the structure and function of DNA. To address this need, this paper describes a methodology to connect the systems biology markup language (SBML) to the synthetic biology open language (SBOL), existing standards that describe biochemical models and DNA components, respectively. Our methodology involves first annotating SBML model elements such as species and reactions with SBOL DNA components. A graph is then constructed from the model, with vertices corresponding to elements within the model and edges corresponding to the cause-and-effect relationships between these elements. Lastly, the graph is traversed to assemble the annotating DNA components into a composite DNA component, which is used to annotate the model itself and can be referenced by other composite models and DNA components. In this way, our methodology can be used to build up a hierarchical library of models annotated with DNA components. Such a library is a useful input to any future genetic technology mapping algorithm that would automate the process of composing DNA components to satisfy a behavioral specification. Our methodology for SBML-to-SBOL annotation is implemented in the latest version of our genetic design automation (GDA) software tool, iBioSim.

Using prognostic models in CLL to personalize approach to clinical care: Are we there yet?

PubMed

Mina, Alain; Sandoval Sus, Jose; Sleiman, Elsa; Pinilla-Ibarz, Javier; Awan, Farrukh T; Kharfan-Dabaja, Mohamed A

2018-03-01

Four decades ago, two staging systems were developed to help stratify CLL into different prognostic categories. These systems, the Rai and the Binet staging, depended entirely on abnormal exam findings and evidence of anemia and thrombocytopenia. Better understanding of biologic, genetic, and molecular characteristics of CLL have contributed to better appreciating its clinical heterogeneity. New prognostic models, the GCLLSG prognostic index and the CLL-IPI, emerged. They incorporate biologic and genetic information related to CLL and are capable of predicting survival outcomes and cases anticipated to need therapy earlier in the disease course. Accordingly, these newer models are helping develop better informed surveillance strategies and ultimately tailor treatment intensity according to presence (or lack thereof) of certain prognostic markers. This represents a step towards personalizing care of CLL patients. We anticipate that as more prognostic factors continue to be identified, the GCLLSG prognostic index and CLL-IPI models will undergo further revisions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Constraints on decision making: implications from genetics, personality, and addiction.

PubMed

Baker, Travis E; Stockwell, Tim; Holroyd, Clay B

2013-09-01

An influential neurocomputational theory of the biological mechanisms of decision making, the "basal ganglia go/no-go model," holds that individual variability in decision making is determined by differences in the makeup of a striatal system for approach and avoidance learning. The model has been tested empirically with the probabilistic selection task (PST), which determines whether individuals learn better from positive or negative feedback. In accordance with the model, in the present study we examined whether an individual's ability to learn from positive and negative reinforcement can be predicted by genetic factors related to the midbrain dopamine system. We also asked whether psychiatric and personality factors related to substance dependence and dopamine affect PST performance. Although we found characteristics that predicted individual differences in approach versus avoidance learning, these observations were qualified by additional findings that appear inconsistent with the predictions of the go/no-go model. These results highlight a need for future research to validate the PST as a measure of basal ganglia reward learning.

Genetic modelling in schizophrenia according to HLA typing.

PubMed

Smeraldi, E; Macciardi, F; Gasperini, M; Orsini, A; Bellodi, L; Fabio, G; Morabito, A

1986-09-01

Studying families of schizophrenic patients, we observed that the risk of developing the overt form of the illness could be enhanced by some factors. Among these various factors we focused our attention on a biological variable, namely the presence or the absence of particular HLA antigens: partitioning our schizophrenic patients according to their HLA structure (i.e. those with HLA-A1 or CRAG-A1 antigens and those with HLA-non-CRAG-A1 antigens, respectively), revealed different illness distribution in the two groups. From a genetic point of view, this finding suggests the presence of heterogeneity in the hypothetical liability system related to schizophrenia and we evaluated the heterogeneity hypothesis by applying alternative genetic models to our data, trying to detect more biologically homogeneous subgroups of the disease.

Modeling Viral Infectious Diseases and Development of Antiviral Therapies Using Human Induced Pluripotent Stem Cell-Derived Systems.

PubMed

Trevisan, Marta; Sinigaglia, Alessandro; Desole, Giovanna; Berto, Alessandro; Pacenti, Monia; Palù, Giorgio; Barzon, Luisa

2015-07-13

The recent biotechnology breakthrough of cell reprogramming and generation of induced pluripotent stem cells (iPSCs), which has revolutionized the approaches to study the mechanisms of human diseases and to test new drugs, can be exploited to generate patient-specific models for the investigation of host-pathogen interactions and to develop new antimicrobial and antiviral therapies. Applications of iPSC technology to the study of viral infections in humans have included in vitro modeling of viral infections of neural, liver, and cardiac cells; modeling of human genetic susceptibility to severe viral infectious diseases, such as encephalitis and severe influenza; genetic engineering and genome editing of patient-specific iPSC-derived cells to confer antiviral resistance.

Ceratopteris richardii: a productive model for revealing secrets of signaling and development

NASA Technical Reports Server (NTRS)

Chatterjee, A.; Roux, S. J.

2000-01-01

Ceratopteris richardii is an aquatic fern grown in tropical and subtropical regions of the world. It is proven to be a productive model system for studies in the genetics, biochemistry, and cell biology of basic biologic processes that occur in early gametophytic development. It provides several advantages to biologists, especially those interested in gravitational biology, polarity development, and in the genetics of sexual development. It is easy to culture, has a relatively short life cycle, and offers an array of attractive features that facilitate genetic studies. The germination and early development of large populations of genetically identical spores are easy to synchronize, and both the direction of polarity development and cell-level gravity responses can be measured and readily manipulated within the first 24 h of spore development. Although there is no reliable transformation system available yet in Ceratopteris, recent studies suggest that the technique of RNA interference can be used to block translation of specific genes in a related fern, Marsilea, and current studies will soon reveal the applicability of this approach, as well as of other transformation approaches, in Ceratopteris. A recently completed expressed sequence tag (EST) sequencing project makes available the partial sequence of more than 2000 cDNAs, representing a significant percentage of the genes being expressed during the first 24 h of spore germination, when many developmentally interesting processes are occurring. A microarray of these ESTs is being constructed, so especially for those scientists interested in basic cellular phenomena that occur early in spore germination, the availability of the ESTs and of the microarray will make Ceratopteris an even more attractive model system.

Ceratopteris richardii: a productive model for revealing secrets of signaling and development.

PubMed

Chatterjee, A; Roux, S J

2000-09-01

Ceratopteris richardii is an aquatic fern grown in tropical and subtropical regions of the world. It is proven to be a productive model system for studies in the genetics, biochemistry, and cell biology of basic biologic processes that occur in early gametophytic development. It provides several advantages to biologists, especially those interested in gravitational biology, polarity development, and in the genetics of sexual development. It is easy to culture, has a relatively short life cycle, and offers an array of attractive features that facilitate genetic studies. The germination and early development of large populations of genetically identical spores are easy to synchronize, and both the direction of polarity development and cell-level gravity responses can be measured and readily manipulated within the first 24 h of spore development. Although there is no reliable transformation system available yet in Ceratopteris, recent studies suggest that the technique of RNA interference can be used to block translation of specific genes in a related fern, Marsilea, and current studies will soon reveal the applicability of this approach, as well as of other transformation approaches, in Ceratopteris. A recently completed expressed sequence tag (EST) sequencing project makes available the partial sequence of more than 2000 cDNAs, representing a significant percentage of the genes being expressed during the first 24 h of spore germination, when many developmentally interesting processes are occurring. A microarray of these ESTs is being constructed, so especially for those scientists interested in basic cellular phenomena that occur early in spore germination, the availability of the ESTs and of the microarray will make Ceratopteris an even more attractive model system.

[Sporulation or competence development? A genetic regulatory network model of cell-fate determination in Bacillus subtilis].

PubMed

Lu, Zhenghui; Zhou, Yuling; Zhang, Xiaozhou; Zhang, Guimin

2015-11-01

Bacillus subtilis is a generally recognized as safe (GRAS) strain that has been widely used in industries including fodder, food, and biological control. In addition, B. subtilis expression system also plays a significant role in the production of industrial enzymes. However, its application is limited by its low sporulation frequency and transformation efficiency. Immense studies have been done on interpreting the molecular mechanisms of sporulation and competence development, whereas only few of them were focused on improving sporulation frequency and transformation efficiency of B. subtilis by genetic modification. The main challenge is that sporulation and competence development, as the two major developmental events in the stationary phase of B. subtilis, are regulated by the complicated intracellular genetic regulatory systems. In addition, mutual regulatory mechanisms also exist in these two developmental events. With the development of genetic and metabolic engineering, constructing genetic regulatory networks is currently one of the most attractive research fields, together with the genetic information of cell growth, metabolism, and development, to guide the industrial application. In this review, the mechanisms of sporulation and competence development of B. subtilis, their interactions, and the genetic regulation of cell growth were interpreted. In addition, the roles of these regulatory networks in guiding basic and applied research of B. subtilis and its related species were discussed.

Pollination Mode and Mating System Explain Patterns in Genetic Differentiation in Neotropical Plants

PubMed Central

Ballesteros-Mejia, Liliana; Lima, Natácia E.; Lima-Ribeiro, Matheus S.

2016-01-01

We studied genetic diversity and differentiation patterns in Neotropical plants to address effects of life history traits (LHT) and ecological attributes based on an exhaustive literature survey. We used generalized linear mixed models (GLMMs) to test the effects as fixed and random factors of growth form, pollination and dispersal modes, mating and breeding systems, geographical range and habitat on patterns of genetic diversity (HS, HeS, π and h), inbreeding coefficient (FIS), allelic richness (AR) and differentiation among populations (FST) for both nuclear and chloroplast genomes. In addition, we used phylogenetic generalized least squares (pGLS) to account for phylogenetic independence on predictor variables and verify the robustness of the results from significant GLMMs. In general, GLMM revealed more significant relationships among LHTs and genetic patterns than pGLS. After accounting for phylogenetic independence (i.e., using pGLS), FST for nuclear microsatellites was significantly related to pollination mode, mating system and habitat. Plants specifically with outcrossing mating system had lower FST. Moreover, AR was significantly related to pollination mode and geographical range and HeS for nuclear dominant markers was significantly related to habitat. Our findings showed that different results might be retrieved when phylogenetic non-independence is taken into account and that LHTs and ecological attributes affect substantially the genetic pattern in Neotropical plants, hence may drive key evolutionary processes in plants. PMID:27472384

Oxytocin in animal models of autism spectrum disorder.

PubMed

Peñagarikano, Olga

2017-02-01

Autism spectrum disorder is a behavioral disorder characterized by impairments in social interaction and communication together with the presence of stereotyped behaviors and restricted interests. Although highly genetic, its etiology is complex which correlates with the extensive heterogeneity found in its clinical manifestation, adding to the challenge of understanding its pathophysiology and develop targeted pharmacotherapies. The neuropeptide oxytocin is part of a highly conserved system involved in the regulation of social behavior, and both animal and human research have shown that variation in the oxytocin system accounts for interindividual differences in the expression of social behaviors in mammals. In autism, recent studies in human patients and animal models are starting to reveal that alterations in the oxytocin system are more common than previously anticipated. Genetic variation in the key players involved in the system (i.e., oxytocin receptor, oxytocin, and CD38) has been found associated with autism in humans, and animal models of the disorder converge in an altered oxytocin system and/or dysfunction in oxytocin related biological processes. Furthermore, oxytocin administration exerts a behavioral and neurobiological response, and thus, the oxytocin system has become a promising potential therapeutical target for autism. Animal models represent a valuable tool to aid in the research into the potential therapeutic use of oxytocin. In this review, I aim to discuss the main findings related to oxytocin research in autism with a focus on findings in animal models. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 202-213, 2017. © 2016 Wiley Periodicals, Inc.

Genetical genomics of Populus leaf shape variation

DOE PAGES

Drost, Derek R.; Puranik, Swati; Novaes, Evandro; ...

2015-06-30

Leaf morphology varies extensively among plant species and is under strong genetic control. Mutagenic screens in model systems have identified genes and established molecular mechanisms regulating leaf initiation, development, and shape. However, it is not known whether this diversity across plant species is related to naturally occurring variation at these genes. Quantitative trait locus (QTL) analysis has revealed a polygenic control for leaf shape variation in different species suggesting that loci discovered by mutagenesis may only explain part of the naturally occurring variation in leaf shape. Here we undertook a genetical genomics study in a poplar intersectional pseudo-backcross pedigree tomore » identify genetic factors controlling leaf shape. Here, the approach combined QTL discovery in a genetic linkage map anchored to the Populus trichocarpa reference genome sequence and transcriptome analysis.« less

Effective size of density-dependent two-sex populations: the effect of mating systems.

PubMed

Myhre, A M; Engen, S; SAEther, B-E

2017-08-01

Density dependence in vital rates is a key feature affecting temporal fluctuations of natural populations. This has important implications for the rate of random genetic drift. Mating systems also greatly affect effective population sizes, but knowledge of how mating system and density regulation interact to affect random genetic drift is poor. Using theoretical models and simulations, we compare N e in short-lived, density-dependent animal populations with different mating systems. We study the impact of a fluctuating, density-dependent sex ratio and consider both a stable and a fluctuating environment. We find a negative relationship between annual N e /N and adult population size N due to density dependence, suggesting that loss of genetic variation is reduced at small densities. The magnitude of this decrease was affected by mating system and life history. A male-biased, density-dependent sex ratio reduces the rate of genetic drift compared to an equal, density-independent sex ratio, but a stochastic change towards male bias reduces the N e /N ratio. Environmental stochasticity amplifies temporal fluctuations in population size and is thus vital to consider in estimation of effective population sizes over longer time periods. Our results on the reduced loss of genetic variation at small densities, particularly in polygamous populations, indicate that density regulation may facilitate adaptive evolution at small population sizes. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Genetic Architecture of the Delis-Kaplan Executive Function System Trail Making Test: Evidence for Distinct Genetic Influences on Executive Function

PubMed Central

Vasilopoulos, Terrie; Franz, Carol E.; Panizzon, Matthew S.; Xian, Hong; Grant, Michael D.; Lyons, Michael J; Toomey, Rosemary; Jacobson, Kristen C.; Kremen, William S.

2012-01-01

Objective To examine how genes and environments contribute to relationships among Trail Making test conditions and the extent to which these conditions have unique genetic and environmental influences. Method Participants included 1237 middle-aged male twins from the Vietnam-Era Twin Study of Aging (VESTA). The Delis-Kaplan Executive Function System Trail Making test included visual searching, number and letter sequencing, and set-shifting components. Results Phenotypic correlations among Trails conditions ranged from 0.29 – 0.60, and genes accounted for the majority (58–84%) of each correlation. Overall heritability ranged from 0.34 to 0.62 across conditions. Phenotypic factor analysis suggested a single factor. In contrast, genetic models revealed a single common genetic factor but also unique genetic influences separate from the common factor. Genetic variance (i.e., heritability) of number and letter sequencing was completely explained by the common genetic factor while unique genetic influences separate from the common factor accounted for 57% and 21% of the heritabilities of visual search and set-shifting, respectively. After accounting for general cognitive ability, unique genetic influences accounted for 64% and 31% of those heritabilities. Conclusions A common genetic factor, most likely representing a combination of speed and sequencing accounted for most of the correlation among Trails 1–4. Distinct genetic factors, however, accounted for a portion of variance in visual scanning and set-shifting. Thus, although traditional phenotypic shared variance analysis techniques suggest only one general factor underlying different neuropsychological functions in non-patient populations, examining the genetic underpinnings of cognitive processes with twin analysis can uncover more complex etiological processes. PMID:22201299

Plasticity of genetic interactions in metabolic networks of yeast.

PubMed

Harrison, Richard; Papp, Balázs; Pál, Csaba; Oliver, Stephen G; Delneri, Daniela

2007-02-13

Why are most genes dispensable? The impact of gene deletions may depend on the environment (plasticity), the presence of compensatory mechanisms (mutational robustness), or both. Here, we analyze the interaction between these two forces by exploring the condition-dependence of synthetic genetic interactions that define redundant functions and alternative pathways. We performed systems-level flux balance analysis of the yeast (Saccharomyces cerevisiae) metabolic network to identify genetic interactions and then tested the model's predictions with in vivo gene-deletion studies. We found that the majority of synthetic genetic interactions are restricted to certain environmental conditions, partly because of the lack of compensation under some (but not all) nutrient conditions. Moreover, the phylogenetic cooccurrence of synthetically interacting pairs is not significantly different from random expectation. These findings suggest that these gene pairs have at least partially independent functions, and, hence, compensation is only a byproduct of their evolutionary history. Experimental analyses that used multiple gene deletion strains not only confirmed predictions of the model but also showed that investigation of false predictions may both improve functional annotation within the model and also lead to the discovery of higher-order genetic interactions. Our work supports the view that functional redundancy may be more apparent than real, and it offers a unified framework for the evolution of environmental adaptation and mutational robustness.

Genetic Testing Registry

MedlinePlus

... Splign Vector Alignment Search Tool (VAST) All Data & Software Resources... Domains & Structures BioSystems Cn3D Conserved Domain Database (CDD) Conserved Domain Search Service (CD Search) Structure (Molecular Modeling Database) Vector Alignment ...

Plants as models for the study of human pathogenesis.

PubMed

Guttman, David S

2004-05-01

There are many common disease mechanisms used by bacterial pathogens of plants and humans. They use common means of attachment, secretion and genetic regulation. They share many virulence factors, such as extracellular polysaccharides and some type III secreted effectors. Plant and human innate immune systems also share many similarities. Many of these shared bacterial virulence mechanisms are homologous, but even more appear to have independently converged on a common function. This combination of homologous and analogous systems reveals conserved and critical steps in the disease process. Given these similarities, and the many experimental advantages of plant biology, including ease of replication, stringent genetic and reproductive control, and high throughput with low cost, it is proposed that plants would make excellent models for the study of human pathogenesis.

Modeling a synthetic multicellular clock: repressilators coupled by quorum sensing.

PubMed

Garcia-Ojalvo, Jordi; Elowitz, Michael B; Strogatz, Steven H

2004-07-27

Diverse biochemical rhythms are generated by thousands of cellular oscillators that somehow manage to operate synchronously. In fields ranging from circadian biology to endocrinology, it remains an exciting challenge to understand how collective rhythms emerge in multicellular structures. Using mathematical and computational modeling, we study the effect of coupling through intercell signaling in a population of Escherichia coli cells expressing a synthetic biological clock. Our results predict that a diverse and noisy community of such genetic oscillators interacting through a quorum-sensing mechanism should self-synchronize in a robust way, leading to a substantially improved global rhythmicity in the system. As such, the particular system of coupled genetic oscillators considered here might be a good candidate to provide the first quantitative example of a synchronization transition in a population of biological oscillators.

Modeling a synthetic multicellular clock: Repressilators coupled by quorum sensing

NASA Astrophysics Data System (ADS)

Garcia-Ojalvo, Jordi; Elowitz, Michael B.; Strogatz, Steven H.

2004-07-01

Diverse biochemical rhythms are generated by thousands of cellular oscillators that somehow manage to operate synchronously. In fields ranging from circadian biology to endocrinology, it remains an exciting challenge to understand how collective rhythms emerge in multicellular structures. Using mathematical and computational modeling, we study the effect of coupling through intercell signaling in a population of Escherichia coli cells expressing a synthetic biological clock. Our results predict that a diverse and noisy community of such genetic oscillators interacting through a quorum-sensing mechanism should self-synchronize in a robust way, leading to a substantially improved global rhythmicity in the system. As such, the particular system of coupled genetic oscillators considered here might be a good candidate to provide the first quantitative example of a synchronization transition in a population of biological oscillators.

Williams syndrome as a model of genetically determined right-hemisphere dominance.

PubMed

Bogdanov, N N; Solonichenko, V G

1997-01-01

Studies were carried out on the dermatoglyphics (skin ridge marks) on the hands of children with Williams syndrome; this is an inherited disease with cardiovascular pathology and a characteristic facial phenotype ("elf" facies), along with specific mental and cognitive disturbances. The results suggest a characteristic dermatoglyphic type with the presence of complex whorls on the fingers and a clear predominance of marks of greater complexity on the left hand; this is a very rare trait in normal people and in those with other inherited nervous system disorders. The features of the dermatoglyphic pattern serve as a characteristic marker of a genetically determined state of the human central nervous system, and suggests directions for neurophysiological studies of children with Williams syndrome as a unique model for analysis of higher nervous function in humans.

Software tool for data mining and its applications

NASA Astrophysics Data System (ADS)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

A software tool for data mining is introduced, which integrates pattern recognition (PCA, Fisher, clustering, hyperenvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, Hyper Envelop, support vector machine, visualization. The principle and knowledge representation of some function models of data mining are described. The software tool of data mining is realized by Visual C++ under Windows 2000. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining has satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

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/).

Sex-biased dispersal creates spatial genetic structure in a parthenogenetic ant with a dependent-lineage reproductive system.

PubMed

Kuhn, A; Bauman, D; Darras, H; Aron, S

2017-10-01

Reproduction and dispersal are key aspects of species life history that influence spatial genetic structure in populations. Several ant species in the genus Cataglyphis have evolved a unique breeding system in which new reproductives (that is, queens and males) are produced asexually by parthenogenesis; in contrast, non-reproductives (that is, workers) are produced via sexual reproduction by mates from distinct genetic lineages. We investigated how these two coexisting reproductive methods affect population-level spatial genetic structure using the ant Cataglyphis mauritanica as a model. We obtained genotypes for queens and their male mates from 338 colonies, and we found that the two lineages present in the study population occurred with equal frequency. Furthermore, analysis of spatial genetic structure revealed strong sex-biased dispersal. Because queens were produced by parthenogenesis and because they dispersed over short distances, there was an extreme level of spatial structuring: a mosaic of patches composed of clonal queens was formed. Males, on the other hand, dispersed over several hundred metres and, thus, across patches, ensuring successful interlineage mating.

A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks

PubMed Central

Zaikin, Alexey; Míguez, Joaquín

2017-01-01

We compare three state-of-the-art Bayesian inference methods for the estimation of the unknown parameters in a stochastic model of a genetic network. In particular, we introduce a stochastic version of the paradigmatic synthetic multicellular clock model proposed by Ullner et al., 2007. By introducing dynamical noise in the model and assuming that the partial observations of the system are contaminated by additive noise, we enable a principled mechanism to represent experimental uncertainties in the synthesis of the multicellular system and pave the way for the design of probabilistic methods for the estimation of any unknowns in the model. Within this setup, we tackle the Bayesian estimation of a subset of the model parameters. Specifically, we compare three Monte Carlo based numerical methods for the approximation of the posterior probability density function of the unknown parameters given a set of partial and noisy observations of the system. The schemes we assess are the particle Metropolis-Hastings (PMH) algorithm, the nonlinear population Monte Carlo (NPMC) method and the approximate Bayesian computation sequential Monte Carlo (ABC-SMC) scheme. We present an extensive numerical simulation study, which shows that while the three techniques can effectively solve the problem there are significant differences both in estimation accuracy and computational efficiency. PMID:28797087

Population-genetic models of sex-limited genomic imprinting.

PubMed

Kelly, S Thomas; Spencer, Hamish G

2017-06-01

Genomic imprinting is a form of epigenetic modification involving parent-of-origin-dependent gene expression, usually the inactivation of one gene copy in some tissues, at least, for some part of the diploid life cycle. Occurring at a number of loci in mammals and flowering plants, this mode of non-Mendelian expression can be viewed more generally as parentally-specific differential gene expression. The effects of natural selection on genetic variation at imprinted loci have previously been examined in a several population-genetic models. Here we expand the existing one-locus, two-allele population-genetic models of viability selection with genomic imprinting to include sex-limited imprinting, i.e., imprinted expression occurring only in one sex, and differential viability between the sexes. We first consider models of complete inactivation of either parental allele and these models are subsequently generalized to incorporate differential expression. Stable polymorphic equilibrium was possible without heterozygote advantage as observed in some prior models of imprinting in both sexes. In contrast to these latter models, in the sex-limited case it was critical whether the paternally inherited or maternally inherited allele was inactivated. The parental origin of inactivated alleles had a different impact on how the population responded to the different selection pressures between the sexes. Under the same fitness parameters, imprinting in the other sex altered the number of possible equilibrium states and their stability. When the parental origin of imprinted alleles and the sex in which they are inactive differ, an allele cannot be inactivated in consecutive generations. The system dynamics became more complex with more equilibrium points emerging. Our results show that selection can interact with epigenetic factors to maintain genetic variation in previously unanticipated ways. Copyright © 2017 Elsevier Inc. All rights reserved.

Development of sensory systems in zebrafish (Danio rerio)

NASA Technical Reports Server (NTRS)

Moorman, S. J.

2001-01-01

Zebrafish possess all of the classic sensory modalities: taste, tactile, smell, balance, vision, and hearing. For each sensory system, this article provides a brief overview of the system in the adult zebrafish followed by a more detailed overview of the development of the system. By far the majority of studies performed in each of the sensory systems of the zebrafish have involved some aspect of molecular biology or genetics. Although molecular biology and genetics are not major foci of the paper, brief discussions of some of the mutant strains of zebrafish that have developmental defects in each specific sensory system are included. The development of the sensory systems is only a small sampling of the work being done using zebrafish and provides a mere glimpse of the potential of this model for the study of vertebrate development, physiology, and human disease.

Genetic programming-based mathematical modeling of influence of weather parameters in BOD5 removal by Lemna minor.

PubMed

Chandrasekaran, Sivapragasam; Sankararajan, Vanitha; Neelakandhan, Nampoothiri; Ram Kumar, Mahalakshmi

2017-11-04

This study, through extensive experiments and mathematical modeling, reveals that other than retention time and wastewater temperature (T w ), atmospheric parameters also play important role in the effective functioning of aquatic macrophyte-based treatment system. Duckweed species Lemna minor is considered in this study. It is observed that the combined effect of atmospheric temperature (T atm ), wind speed (U w ), and relative humidity (RH) can be reflected through one parameter, namely the "apparent temperature" (T a ). A total of eight different models are considered based on the combination of input parameters and the best mathematical model is arrived at which is validated through a new experimental set-up outside the modeling period. The validation results are highly encouraging. Genetic programming (GP)-based models are found to reveal deeper understandings of the wetland process.

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.

Genetic programming for evolving due-date assignment models in job shop environments.

PubMed

Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

2014-01-01

Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.

ScaleNet: A literature-based model of scale insect biology and systematics

USDA-ARS?s Scientific Manuscript database

Scale insects (Hemiptera: Coccoidea) are small herbivorous insects found in all continents except Antarctica. They are extremely invasive, and many species are serious agricultural pests. They are also emerging models for studies of the evolution of genetic systems, endosymbiosis, and plant-insect i...

MHC class II is an important genetic risk factor for canine systemic lupus erythematosus (SLE)-related disease: implications for reproductive success.

PubMed

Wilbe, M; Andersson, G

2012-01-01

Major histocompatibility complex (MHC) class II genes are important genetic risk factors for development of immune-mediated diseases in mammals. Recently, the dog (Canis lupus familiaris) has emerged as a useful model organism to identify critical MHC class II genotypes that contribute to development of these diseases. Therefore, a study aimed to evaluate a potential genetic association between the dog leukocyte antigen (DLA) class II region and an immune-mediated disease complex in dogs of the Nova Scotia duck tolling retriever breed was performed. We show that DLA is one of several genetic risk factors for this disease complex and that homozygosity of the risk haplotype is disadvantageous. Importantly, the disease is complex and has many genetic risk factors and therefore we cannot provide recommendations for breeders exclusively on the basis of genetic testing for DLA class II genotype. © 2012 Blackwell Verlag GmbH.

A deterministic computer simulation model of life-cycle lamb and wool production.

PubMed

Wang, C T; Dickerson, G E

1991-11-01

A deterministic mathematical computer model was developed to simulate effects on life-cycle efficiency of lamb and wool production from genetic improvement of performance traits under alternative management systems. Genetic input parameters can be varied for age at puberty, length of anestrus, fertility, precocity of fertility, number born, milk yield, mortality, growth rate, body fat, and wool growth. Management options include mating systems, lambing intervals, feeding levels, creep feeding, weaning age, marketing age or weight, and culling policy. Simulated growth of animals is linear from birth to inflection point, then slows asymptotically to specified mature empty BW and fat content when nutrition is not limiting. The ME intake requirement to maintain normal condition is calculated daily or weekly for maintenance, protein and fat deposition, wool growth, gestation, and lactation. Simulated feed intake is the minimum of availability, DM physical limit, or ME physiological limit. Tissue catabolism occurs when intake is below the requirement for essential functions. Mortality increases when BW is depressed. Equations developed for calculations of biological functions were validated with published and unpublished experimental data. Lifetime totals are accumulated for TDN, DM, and protein intake and for market lamb equivalent output values of empty body or carcass lean and wool from both lambs and ewes. These measures of efficiency for combinations of genetic, management, and marketing variables can provide the relative economic weighting of traits needed to derive optimal criteria for genetic selection among and within breeds under defined industry production systems.

The Role of Abcb5 Alleles in Susceptibility to Haloperidol-Induced Toxicity in Mice and Humans

PubMed Central

Zheng, Ming; Zhang, Haili; Dill, David L.; Clark, J. David; Tu, Susan; Yablonovitch, Arielle L.; Tan, Meng How; Zhang, Rui; Rujescu, Dan; Wu, Manhong; Tessarollo, Lino; Vieira, Wilfred; Gottesman, Michael M.; Deng, Suhua; Eberlin, Livia S.; Zare, Richard N.; Billard, Jean-Martin; Gillet, Jean-Pierre; Li, Jin Billy; Peltz, Gary

2015-01-01

Background We know very little about the genetic factors affecting susceptibility to drug-induced central nervous system (CNS) toxicities, and this has limited our ability to optimally utilize existing drugs or to develop new drugs for CNS disorders. For example, haloperidol is a potent dopamine antagonist that is used to treat psychotic disorders, but 50% of treated patients develop characteristic extrapyramidal symptoms caused by haloperidol-induced toxicity (HIT), which limits its clinical utility. We do not have any information about the genetic factors affecting this drug-induced toxicity. HIT in humans is directly mirrored in a murine genetic model, where inbred mouse strains are differentially susceptible to HIT. Therefore, we genetically analyzed this murine model and performed a translational human genetic association study. Methods and Findings A whole genome SNP database and computational genetic mapping were used to analyze the murine genetic model of HIT. Guided by the mouse genetic analysis, we demonstrate that genetic variation within an ABC-drug efflux transporter (Abcb5) affected susceptibility to HIT. In situ hybridization results reveal that Abcb5 is expressed in brain capillaries, and by cerebellar Purkinje cells. We also analyzed chromosome substitution strains, imaged haloperidol abundance in brain tissue sections and directly measured haloperidol (and its metabolite) levels in brain, and characterized Abcb5 knockout mice. Our results demonstrate that Abcb5 is part of the blood-brain barrier; it affects susceptibility to HIT by altering the brain concentration of haloperidol. Moreover, a genetic association study in a haloperidol-treated human cohort indicates that human ABCB5 alleles had a time-dependent effect on susceptibility to individual and combined measures of HIT. Abcb5 alleles are pharmacogenetic factors that affect susceptibility to HIT, but it is likely that additional pharmacogenetic susceptibility factors will be discovered. Conclusions ABCB5 alleles alter susceptibility to HIT in mouse and humans. This discovery leads to a new model that (at least in part) explains inter-individual differences in susceptibility to a drug-induced CNS toxicity. PMID:25647612

Fruitful research: drug target discovery for neurodegenerative diseases in Drosophila.

PubMed

Konsolaki, Mary

2013-12-01

Although vertebrate model systems have obvious advantages in the study of human disease, invertebrate organisms have contributed enormously to this field as well. The conservation of genome structure and physiology among organisms poses unexpected peculiarities, and the redundancy in certain gene families or the presence of polymorphisms that can slightly alter gene expression can, in certain instances, bring invertebrate systems, such as Drosophila, closer to humans than mice and vice versa. This necessitates the analysis of disease pathways in multiple model organisms. The author highlights findings from Drosophila models of neurodegenerative diseases that have occurred in the past few years. She also highlights and discusses various molecular, genetic and genomic tools used in flies, as well as methods for generating disease models. Finally, the author describes Drosophila models of Alzheimer's, Parkinson's tri-nucleotide repeat diseases, and Fragile X syndrome and summarizes insights in disease mechanisms that have been discovered directly in fly models. Full genome genetic screens in Drosophila can lead to the rapid identification of drug target candidates that can be subsequently validated in a vertebrate system. In addition, the Drosophila models of neurodegeneration may often show disease phenotypes that are absent in equivalent mouse models. The author believes that the extensive contribution of Drosophila to both new disease drug target discovery, in addition to target validation, makes them indispensible to drug discovery and development.

Solubility of polyethers in hydrocarbons at low temperatures. A model for potential genetic backbones on warm titans.

PubMed

McLendon, Christopher; Opalko, F Jeffrey; Illangkoon, Heshan I; Benner, Steven A

2015-03-01

Ethers are proposed here as the repeating backbone linking units in linear genetic biopolymers that might support Darwinian evolution in hydrocarbon oceans. Hydrocarbon oceans are found in our own solar system as methane mixtures on Titan. They may be found as mixtures of higher alkanes (propane, for example) on warmer hydrocarbon-rich planets in exosolar systems ("warm Titans"). We report studies on the solubility of several short polyethers in propane over its liquid range (from 85 to 231 K, or -188 °C to -42 °C). These show that polyethers are reasonably soluble in propane at temperatures down to ca. 200 K. However, their solubilities drop dramatically at still lower temperatures and become immeasurably low below 170 K, still well above the ∼ 95 K in Titan's oceans. Assuming that a liquid phase is essential for any living system, and genetic biopolymers must dissolve in that biosolvent to support Darwinism, these data suggest that we must look elsewhere to identify linear biopolymers that might support genetics in Titan's surface oceans. However, genetic molecules with polyether backbones may be suitable to support life in hydrocarbon oceans on warm Titans, where abundant organics and environments lacking corrosive water might make it easier for life to originate.

Evolutionary Technologies: Fundamentals and Applications to Information/Communication Systems and Manufacturing/Logistics Systems

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Kawakami, Hiroshi; Tsujimura, Yasuhiro; Handa, Hisashi; Lin, Lin; Okamoto, Azuma

As efficient utilization of computational resources is increasing, evolutionary technology based on the Genetic Algorithm (GA), Genetic Programming (GP), Evolution Strategy (ES) and other Evolutionary Computations (ECs) is making rapid progress, and its social recognition and the need as applied technology are increasing. This is explained by the facts that EC offers higher robustness for knowledge information processing systems, intelligent production and logistics systems, most advanced production scheduling and other various real-world problems compared to the approaches based on conventional theories, and EC ensures flexible applicability and usefulness for any unknown system environment even in a case where accurate mathematical modeling fails in the formulation. In this paper, we provide a comprehensive survey of the current state-of-the-art in the fundamentals and applications of evolutionary technologies.

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

PubMed Central

Evans, Jonathan P; Gasparini, Clelia

2013-01-01

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

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.

Maintenance and expression of the S. cerevisiae mitochondrial genome--from genetics to evolution and systems biology.

PubMed

Lipinski, Kamil A; Kaniak-Golik, Aneta; Golik, Pawel

2010-01-01

As a legacy of their endosymbiotic eubacterial origin, mitochondria possess a residual genome, encoding only a few proteins and dependent on a variety of factors encoded by the nuclear genome for its maintenance and expression. As a facultative anaerobe with well understood genetics and molecular biology, Saccharomyces cerevisiae is the model system of choice for studying nucleo-mitochondrial genetic interactions. Maintenance of the mitochondrial genome is controlled by a set of nuclear-coded factors forming intricately interconnected circuits responsible for replication, recombination, repair and transmission to buds. Expression of the yeast mitochondrial genome is regulated mostly at the post-transcriptional level, and involves many general and gene-specific factors regulating splicing, RNA processing and stability and translation. A very interesting aspect of the yeast mitochondrial system is the relationship between genome maintenance and gene expression. Deletions of genes involved in many different aspects of mitochondrial gene expression, notably translation, result in an irreversible loss of functional mtDNA. The mitochondrial genetic system viewed from the systems biology perspective is therefore very fragile and lacks robustness compared to the remaining systems of the cell. This lack of robustness could be a legacy of the reductive evolution of the mitochondrial genome, but explanations involving selective advantages of increased evolvability have also been postulated. Copyright © 2009 Elsevier B.V. All rights reserved.

CRISPR/Cas9 for Human Genome Engineering and Disease Research.

PubMed

Xiong, Xin; Chen, Meng; Lim, Wendell A; Zhao, Dehua; Qi, Lei S

2016-08-31

The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9) system, a versatile RNA-guided DNA targeting platform, has been revolutionizing our ability to modify, manipulate, and visualize the human genome, which greatly advances both biological research and therapeutics development. Here, we review the current development of CRISPR/Cas9 technologies for gene editing, transcription regulation, genome imaging, and epigenetic modification. We discuss the broad application of this system to the study of functional genomics, especially genome-wide genetic screening, and to therapeutics development, including establishing disease models, correcting defective genetic mutations, and treating diseases.

Early onset of disc degeneration in SM/J mice is associated with changes in ion transport systems and fibrotic events.

PubMed

Zhang, Ying; Xiong, Chi; Kudelko, Mateusz; Li, Yan; Wang, Cheng; Wong, Yuk Lun; Tam, Vivian; Rai, Muhammad Farooq; Cheverud, James; Lawson, Heather A; Sandell, Linda; Chan, Wilson C W; Cheah, Kathryn S E; Sham, Pak C; Chan, Danny

2018-04-09

Intervertebral disc degeneration (IDD) causes back pain and sciatica, affecting quality of life and resulting in high economic/social burden. The etiology of IDD is not well understood. Along with aging and environmental factors, genetic factors also influence the onset, progression and severity of IDD. Genetic studies of risk factors for IDD using human cohorts are limited by small sample size and low statistical power. Animal models amenable to genetic and functional studies of IDD provide desirable alternatives. Despite differences in size and cellular content as compared to human intervertebral discs (IVDs), the mouse is a powerful model for genetics and assessment of cellular changes relevant to human biology. Here, we provide evidence for early onset disc degeneration in SM/J relative to LG/J mice with poor and good tissue healing capacity respectively. In the first few months of life, LG/J mice maintain a relatively constant pool of notochordal-like cells in the nucleus pulposus (NP) of the IVD. In contrast, chondrogenic events are observed in SM/J mice beginning as early as one-week-old, with progressive fibrotic changes. Further, the extracellular matrix changes in the NP are consistent with IVD degeneration. Leveraging on the genomic data of two parental and two recombinant inbred lines, we assessed the genetic contribution to the NP changes and identified processes linked to the regulation of ion transport systems. Significantly, "transport" system is also in the top three gene ontology (GO) terms from a comparative proteomic analysis of the mouse NP. These findings support the potential of the SM/J, LG/J and their recombinant inbred lines for future genetic and biological analysis in mice and validation of candidate genes and biological relevance in human cohort studies. The proteomic data has been deposited to the ProteomeXchange Consortium via the PRIDE [1] partner repository with the dataset identifier PXD008784. Copyright © 2017. Published by Elsevier B.V.

VHBuild.com: A Web-Based System for Managing Knowledge in Projects.

ERIC Educational Resources Information Center

Li, Heng; Tang, Sandy; Man, K. F.; Love, Peter E. D.

2002-01-01

Describes an intelligent Web-based construction project management system called VHBuild.com which integrates project management, knowledge management, and artificial intelligence technologies. Highlights include an information flow model; time-cost optimization based on genetic algorithms; rule-based drawing interpretation; and a case-based…

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...

Which experimental systems should we use for human microbiome science?

PubMed

Douglas, Angela E

2018-03-01

Microbiome science is revealing that the phenotype and health of animals, including humans, depend on the sustained function of their resident microorganisms. In this essay, I argue for thoughtful choice of model systems for human microbiome science. A greater variety of experimental systems, including wider use of invertebrate models, would benefit biomedical research, while systems ill-suited to experimental and genetic manipulation can be used to address very limited sets of scientific questions. Microbiome science benefits from the coordinated use of multiple systems, which is facilitated by networks of researchers with expertise in different experimental systems.

Using a system of differential equations that models cattle growth to uncover the genetic basis of complex traits.

PubMed

Freua, Mateus Castelani; Santana, Miguel Henrique de Almeida; Ventura, Ricardo Vieira; Tedeschi, Luis Orlindo; Ferraz, José Bento Sterman

2017-08-01

The interplay between dynamic models of biological systems and genomics is based on the assumption that genetic variation of the complex trait (i.e., outcome of model behavior) arises from component traits (i.e., model parameters) in lower hierarchical levels. In order to provide a proof of concept of this statement for a cattle growth model, we ask whether model parameters map genomic regions that harbor quantitative trait loci (QTLs) already described for the complex trait. We conducted a genome-wide association study (GWAS) with a Bayesian hierarchical LASSO method in two parameters of the Davis Growth Model, a system of three ordinary differential equations describing DNA accretion, protein synthesis and degradation, and fat synthesis. Phenotypic and genotypic data were available for 893 Nellore (Bos indicus) cattle. Computed values for parameter k 1 (DNA accretion rate) ranged from 0.005 ± 0.003 and for α (constant for energy for maintenance requirement) 0.134 ± 0.024. The expected biological interpretation of the parameters is confirmed by QTLs mapped for k 1 and α. QTLs within genomic regions mapped for k 1 are expected to be correlated with the DNA pool: body size and weight. Single nucleotide polymorphisms (SNPs) which were significant for α mapped QTLs that had already been associated with residual feed intake, feed conversion ratio, average daily gain (ADG), body weight, and also dry matter intake. SNPs identified for k 1 were able to additionally explain 2.2% of the phenotypic variability of the complex ADG, even when SNPs for k 1 did not match the genomic regions associated with ADG. Although improvements are needed, our findings suggest that genomic analysis on component traits may help to uncover the genetic basis of more complex traits, particularly when lower biological hierarchies are mechanistically described by mathematical simulation models.

Symbiotic conversations are revealed under genetic interrogation

PubMed Central

Ruby, Edward G.

2013-01-01

The recent development and application of molecular genetics to the symbionts of invertebrate animal species have advanced our knowledge of the biochemical communication that occurs between the host and its bacterial symbionts. In particular, the ability to manipulate these associations experimentally by introducing genetic variants of the symbionts into naive hosts has allowed the discovery of novel colonization mechanisms and factors. In addition, the role of the symbionts in inducing normal host development has been revealed, and its molecular basis described. In this Review, I discuss many of these developments, focusing on what has been discovered in five well-understood model systems. PMID:18794913

Enhanced energy transport in genetically engineered excitonic networks.

PubMed

Park, Heechul; Heldman, Nimrod; Rebentrost, Patrick; Abbondanza, Luigi; Iagatti, Alessandro; Alessi, Andrea; Patrizi, Barbara; Salvalaggio, Mario; Bussotti, Laura; Mohseni, Masoud; Caruso, Filippo; Johnsen, Hannah C; Fusco, Roberto; Foggi, Paolo; Scudo, Petra F; Lloyd, Seth; Belcher, Angela M

2016-02-01

One of the challenges for achieving efficient exciton transport in solar energy conversion systems is precise structural control of the light-harvesting building blocks. Here, we create a tunable material consisting of a connected chromophore network on an ordered biological virus template. Using genetic engineering, we establish a link between the inter-chromophoric distances and emerging transport properties. The combination of spectroscopy measurements and dynamic modelling enables us to elucidate quantum coherent and classical incoherent energy transport at room temperature. Through genetic modifications, we obtain a significant enhancement of exciton diffusion length of about 68% in an intermediate quantum-classical regime.

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

PubMed

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

2014-01-01

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

Zymomonas mobilis as a model system for production of biofuels and biochemicals

DOE PAGES

Yang, Shihui; Fei, Qiang; Zhang, Yaoping; ...

2016-09-15

Zymomonas mobilis is a natural ethanologen with many desirable industrial biocatalyst characteristics. In this review, we will discuss work to develop Z. mobilis as a model system for biofuel production from the perspectives of substrate utilization, development for industrial robustness, potential product spectrum, strain evaluation and fermentation strategies. Lastly, this review also encompasses perspectives related to classical genetic tools and emerging technologies in this context.

Zymomonas mobilis as a model system for production of biofuels and biochemicals

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

Yang, Shihui; Fei, Qiang; Zhang, Yaoping

Zymomonas mobilis is a natural ethanologen with many desirable industrial biocatalyst characteristics. In this review, we will discuss work to develop Z. mobilis as a model system for biofuel production from the perspectives of substrate utilization, development for industrial robustness, potential product spectrum, strain evaluation and fermentation strategies. Lastly, this review also encompasses perspectives related to classical genetic tools and emerging technologies in this context.

Family Background Buys an Education in Minnesota but Not in Sweden

PubMed Central

Johnson, Wendy; Deary, Ian J.; Silventoinen, Karri; Tynelius, Per; Rasmussen, Finn

2010-01-01

Educational attainment, the highest degree or level of schooling obtained, is associated with important life outcomes, at both the individual level and the group level. Because of this, and because education is expensive, the allocation of education across society is an important social issue. A dynamic quantitative environmental-genetic model can help document the effects of social allocation patterns. We used this model to compare the moderating effect of general intelligence on the environmental and genetic factors that influence educational attainment in Sweden and the U.S. state of Minnesota. Patterns of genetic influence on educational outcomes were similar in these two regions, but patterns of shared environmental influence differed markedly. In Sweden, shared environmental influence on educational attainment was particularly important for people of high intelligence, whereas in Minnesota, shared environmental influences on educational attainment were particularly important for people of low intelligence. This difference may be the result of differing access to education: state-supported access (on the basis of ability) to a uniform higher-education system in Sweden, versus family-supported access to a more diverse higher-education system in the United States. PMID:20679521

Modeling delay in genetic networks: From delay birth-death processes to delay stochastic differential equations

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

Gupta, Chinmaya; López, José Manuel; Azencott, Robert

Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemicalmore » Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay.« less

Genetic modulation of the iris transillumination defect: a systems genetics analysis using the expanded family of BXD glaucoma strains

PubMed Central

Swaminathan, Shankar; Lu, Hong; Williams, Robert W; Lu, Lu; Jablonski, Monica M

2013-01-01

We investigated the contributions of Tyrp1 and Gpnmb to the iris transillumination defect (TID) in five age cohorts of BXD mice. Using systems genetics, we also evaluated the role of other known pigmentation genes (PGs). Mapping studies indicate that Tyrp1 contributes to the phenotype at all ages, yet the TID maps to Gpnmb only in the oldest cohort. Composite interval mapping reveals secondary loci viz. Oca2, Myo5a, Prkcz, and Zbtb20 that modulate the phenotype in the age groups up to 10–13 months. The contributions of Tyrp1 and Gpnmb were highly significant in all age cohorts. Moreover, in young mice, all six gene candidates had substantial interactions in our model. Our model accounted for 71–88% of the explained variance of the TID phenotype across the age bins. These results demonstrate that along with Tyrp1 and Gpnmb, Oca2, Myo5a, Prkcz, and Zbtb20 modulate the TID in an age-dependent manner. PMID:23582180

Family background buys an education in Minnesota but not in Sweden.

PubMed

Johnson, Wendy; Deary, Ian J; Silventoinen, Karri; Tynelius, Per; Rasmussen, Finn

2010-09-01

Educational attainment, the highest degree or level of schooling obtained, is associated with important life outcomes, at both the individual level and the group level. Because of this, and because education is expensive, the allocation of education across society is an important social issue. A dynamic quantitative environmental-genetic model can help document the effects of social allocation patterns. We used this model to compare the moderating effect of general intelligence on the environmental and genetic factors that influence educational attainment in Sweden and the U.S. state of Minnesota. Patterns of genetic influence on educational outcomes were similar in these two regions, but patterns of shared environmental influence differed markedly. In Sweden, shared environmental influence on educational attainment was particularly important for people of high intelligence, whereas in Minnesota, shared environmental influences on educational attainment were particularly important for people of low intelligence. This difference may be the result of differing access to education: state-supported access (on the basis of ability) to a uniform higher-education system in Sweden versus family-supported access to a more diverse higher-education system in the United States.

Identification of an urban fractured-rock aquifer dynamics using an evolutionary self-organizing modelling

NASA Astrophysics Data System (ADS)

Hong, Yoon-Seok; Rosen, Michael R.

2002-03-01

An urban fractured-rock aquifer system, where disposal of storm water is via 'soak holes' drilled directly into the top of fractured-rock basalt, has a highly dynamic nature where theories or knowledge to generate the model are still incomplete and insufficient. Therefore, formulating an accurate mechanistic model, usually based on first principles (physical and chemical laws, mass balance, and diffusion and transport, etc.), requires time- and money-consuming tasks. Instead of a human developing the mechanistic-based model, this paper presents an approach to automatic model evolution in genetic programming (GP) to model dynamic behaviour of groundwater level fluctuations affected by storm water infiltration. This GP evolves mathematical models automatically that have an understandable structure using function tree representation by methods of natural selection ('survival of the fittest') through genetic operators (reproduction, crossover, and mutation). The simulation results have shown that GP is not only capable of predicting the groundwater level fluctuation due to storm water infiltration but also provides insight into the dynamic behaviour of a partially known urban fractured-rock aquifer system by allowing knowledge extraction of the evolved models. Our results show that GP can work as a cost-effective modelling tool, enabling us to create prototype models quickly and inexpensively and assists us in developing accurate models in less time, even if we have limited experience and incomplete knowledge for an urban fractured-rock aquifer system affected by storm water infiltration.

Genetic thinking in the study of social relationships: Five points of entry

PubMed Central

Reiss, David

2014-01-01

For nearly a generation, researchers studying human behavioral development have combined genetically informed research designs with careful measures of social relationships: parenting, sibling relationships, peer relationships, marital processes, social class stratifications and patterns of social engagement in the elderly. In what way have these genetically informed studies altered the construction and testing of social theories of human development? We consider five points where genetic thinking is taking hold. First, genetic findings suggest an alternative scenario for explaining social data. Associations between measures of the social environment and human development may be due to genes that influence both. Second, genetic studies add to other prompts to study the early developmental origins of current social phenomena in mid-life and beyond. Third, genetic analyses promise to bring to the surface understudied social systems, such as sibling relationships, that have an impact on human development independent of genotype. Fourth, genetic analyses anchor in neurobiology individual differences in resilience and sensitivity to both adverse and favorable social environments. Finally, genetic analyses increase the utility of laboratory simulations of human social processes and of animal models. PMID:25419225

Genetic modification of the diarrhoeal pathogen Cryptosporidium parvum.

PubMed

Vinayak, Sumiti; Pawlowic, Mattie C; Sateriale, Adam; Brooks, Carrie F; Studstill, Caleb J; Bar-Peled, Yael; Cipriano, Michael J; Striepen, Boris

2015-07-23

Recent studies into the global causes of severe diarrhoea in young children have identified the protozoan parasite Cryptosporidium as the second most important diarrhoeal pathogen after rotavirus. Diarrhoeal disease is estimated to be responsible for 10.5% of overall child mortality. Cryptosporidium is also an opportunistic pathogen in the contexts of human immunodeficiency virus (HIV)-caused AIDS and organ transplantation. There is no vaccine and only a single approved drug that provides no benefit for those in gravest danger: malnourished children and immunocompromised patients. Cryptosporidiosis drug and vaccine development is limited by the poor tractability of the parasite, which includes a lack of systems for continuous culture, facile animal models, and molecular genetic tools. Here we describe an experimental framework to genetically modify this important human pathogen. We established and optimized transfection of C. parvum sporozoites in tissue culture. To isolate stable transgenics we developed a mouse model that delivers sporozoites directly into the intestine, a Cryptosporidium clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 system, and in vivo selection for aminoglycoside resistance. We derived reporter parasites suitable for in vitro and in vivo drug screening, and we evaluated the basis of drug susceptibility by gene knockout. We anticipate that the ability to genetically engineer this parasite will be transformative for Cryptosporidium research. Genetic reporters will provide quantitative correlates for disease, cure and protection, and the role of parasite genes in these processes is now open to rigorous investigation.

Advances in Engineering the Fly Genome with the CRISPR-Cas System

PubMed Central

Bier, Ethan; Harrison, Melissa M.; O’Connor-Giles, Kate M.; Wildonger, Jill

2018-01-01

Drosophila has long been a premier model for the development and application of cutting-edge genetic approaches. The CRISPR-Cas system now adds the ability to manipulate the genome with ease and precision, providing a rich toolbox to interrogate relationships between genotype and phenotype, to delineate and visualize how the genome is organized, to illuminate and manipulate RNA, and to pioneer new gene drive technologies. Myriad transformative approaches have already originated from the CRISPR-Cas system, which will likely continue to spark the creation of tools with diverse applications. Here, we provide an overview of how CRISPR-Cas gene editing has revolutionized genetic analysis in Drosophila and highlight key areas for future advances. PMID:29301946

Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

NASA Astrophysics Data System (ADS)

Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur

2017-06-01

The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.

Genetic Programming for Automatic Hydrological Modelling

NASA Astrophysics Data System (ADS)

Chadalawada, Jayashree; Babovic, Vladan

2017-04-01

One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development, Water Resources Research, 47(11).

Cockayne syndrome pathogenesis: lessons from mouse models.

PubMed

Jaarsma, Dick; van der Pluijm, Ingrid; van der Horst, Gijsbertus T J; Hoeijmakers, Jan H J

2013-01-01

Cockayne syndrome (CS) is a rare multisystem disorder characterized by cachectic dwarfism, nervous system abnormalities and features of premature aging. CS symptoms are associated with mutations in 5 genes, CSA, CSB, XPB, XPD and XPG encoding for proteins involved in the transcription-coupled subpathway of nucleotide excision DNA repair (NER). Mutant mice have been generated for all CS-associated genes and provide tools to examine how the cellular defects translate into CS symptoms. Mice deficient for Csa or Csb genetically mimic CS in man, and develop mild CS symptoms including reduced fat tissue, photoreceptor cell loss, and mild, but characteristic, nervous system pathology. These mild CS models are converted into severe CS models with short life span, progressive nervous system degeneration and cachectic dwarfism after simultaneous complete inactivation of global genome NER. A spectrum of mild-to-severe CS-like symptoms occurs in Xpb, Xpd, and Xpg mice that genetically mimic patients with a disorder that combines CS symptoms with another NER syndrome, xeroderma pigmentosum. In conclusion, CS mouse models mice develop a range of CS phenotypes and open promising perspectives for testing interventional approaches. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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.

Bionic models for identification of biological systems

NASA Astrophysics Data System (ADS)

Gerget, O. M.

2017-01-01

This article proposes a clinical decision support system that processes biomedical data. For this purpose a bionic model has been designed based on neural networks, genetic algorithms and immune systems. The developed system has been tested on data from pregnant women. The paper focuses on the approach to enable selection of control actions that can minimize the risk of adverse outcome. The control actions (hyperparameters of a new type) are further used as an additional input signal. Its values are defined by a hyperparameter optimization method. A software developed with Python is briefly described.

Algebraic properties of automata associated to Petri nets and applications to computation in biological systems.

PubMed

Egri-Nagy, Attila; Nehaniv, Chrystopher L

2008-01-01

Biochemical and genetic regulatory networks are often modeled by Petri nets. We study the algebraic structure of the computations carried out by Petri nets from the viewpoint of algebraic automata theory. Petri nets comprise a formalized graphical modeling language, often used to describe computation occurring within biochemical and genetic regulatory networks, but the semantics may be interpreted in different ways in the realm of automata. Therefore, there are several different ways to turn a Petri net into a state-transition automaton. Here, we systematically investigate different conversion methods and describe cases where they may yield radically different algebraic structures. We focus on the existence of group components of the corresponding transformation semigroups, as these reflect symmetries of the computation occurring within the biological system under study. Results are illustrated by applications to the Petri net modelling of intermediary metabolism. Petri nets with inhibition are shown to be computationally rich, regardless of the particular interpretation method. Along these lines we provide a mathematical argument suggesting a reason for the apparent all-pervasiveness of inhibitory connections in living systems.

Yeast as a model system for mammalian seven-transmembrane segment receptors

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

Jeansonne, N.E.

1994-05-01

Investigators have used the budding yeast Saccharomyces cerevisiae as a model system in which to study the {beta}-adrenergic receptor, the T-cell receptor pathway, initiation of mammalian DNA replication, initiation of mammalian transcription, secretion, the CDC2 kinase system, cell cycle control, and aging, as well as the function of oncogenes. This list continues to growth with the discovery of an immunoglobulin heavy-chain binding homologue in yeast, an Rb binding protein homologue, and a possible yeast arrestin. Yeast is relatively easy to maintain, to grow, and to genetically manipulate. A single gene can be overexpressed, selectively mutated or deleted from its chromosomalmore » location. In this way, the in vivo function of a gene can be studied. It has become reasonable to consider yeast as a model system for studying the seven transmembrane segments (7-TMS) receptor family. Currently, subtypes of the {beta}-adrenergic receptor are being studied in yeast. The receptor and its G{sub {alpha}}-G-protein, trigger the mating pheromone receptor pathway. This provides a powerful assay for determining receptor function. Studies expressing the muscarinic cholinergic receptor in yeast are underway. The yeast pheromone receptor belongs to this receptor family, sharing sequences and secondary structure homology. An effective strategy has been to identify a yeast pathway or process which is homologous to a mammalian system. The pathway is delineated in yeast, identifying other genetic components. Then yeast genes are used to screen for human homologues of these components. The putative human homologues are then expressed in yeast and in mammalian cells to determine function. When this type of {open_quotes}mixing and matching{close_quotes} works, yeast genetics can be a powerful tool. 115 refs.« less

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.

CRISPR-Cas9: from Genome Editing to Cancer Research

PubMed Central

Chen, Si; Sun, Heng; Miao, Kai; Deng, Chu-Xia

2016-01-01

Cancer development is a multistep process triggered by innate and acquired mutations, which cause the functional abnormality and determine the initiation and progression of tumorigenesis. Gene editing is a widely used engineering tool for generating mutations that enhance tumorigenesis. The recent developed clustered regularly interspaced short palindromic repeats-CRISPR-associated 9 (CRISPR-Cas9) system renews the genome editing approach into a more convenient and efficient way. By rapidly introducing genetic modifications in cell lines, organs and animals, CRISPR-Cas9 system extends the gene editing into whole genome screening, both in loss-of-function and gain-of-function manners. Meanwhile, the system accelerates the establishment of animal cancer models, promoting in vivo studies for cancer research. Furthermore, CRISPR-Cas9 system is modified into diverse innovative tools for observing the dynamic bioprocesses in cancer studies, such as image tracing for targeted DNA, regulation of transcription activation or repression. Here, we view recent technical advances in the application of CRISPR-Cas9 system in cancer genetics, large-scale cancer driver gene hunting, animal cancer modeling and functional studies. PMID:27994508

Comparison of linear, skewed-linear, and proportional hazard models for the analysis of lambing interval in Ripollesa ewes.

PubMed

Casellas, J; Bach, R

2012-06-01

Lambing interval is a relevant reproductive indicator for sheep populations under continuous mating systems, although there is a shortage of selection programs accounting for this trait in the sheep industry. Both the historical assumption of small genetic background and its unorthodox distribution pattern have limited its implementation as a breeding objective. In this manuscript, statistical performances of 3 alternative parametrizations [i.e., symmetric Gaussian mixed linear (GML) model, skew-Gaussian mixed linear (SGML) model, and piecewise Weibull proportional hazard (PWPH) model] have been compared to elucidate the preferred methodology to handle lambing interval data. More specifically, flock-by-flock analyses were performed on 31,986 lambing interval records (257.3 ± 0.2 d) from 6 purebred Ripollesa flocks. Model performances were compared in terms of deviance information criterion (DIC) and Bayes factor (BF). For all flocks, PWPH models were clearly preferred; they generated a reduction of 1,900 or more DIC units and provided BF estimates larger than 100 (i.e., PWPH models against linear models). These differences were reduced when comparing PWPH models with different number of change points for the baseline hazard function. In 4 flocks, only 2 change points were required to minimize the DIC, whereas 4 and 6 change points were needed for the 2 remaining flocks. These differences demonstrated a remarkable degree of heterogeneity across sheep flocks that must be properly accounted for in genetic evaluation models to avoid statistical biases and suboptimal genetic trends. Within this context, all 6 Ripollesa flocks revealed substantial genetic background for lambing interval with heritabilities ranging between 0.13 and 0.19. This study provides the first evidence of the suitability of PWPH models for lambing interval analysis, clearly discarding previous parametrizations focused on mixed linear models.

Arabidopsis: an adequate model for dicot root systems

USDA-ARS?s Scientific Manuscript database

In the search for answers to pressing root developmental genetic issues, plant science has turned to a small genome dicot plant (Arabidopsis) to be used as a model to study and use to develop hypotheses for testing other species. Through out the published research only three classes of root are des...

Developing a Drosophila Model of Schwannomatosis

DTIC Science & Technology

2012-08-01

the entire Drosophila melanogaster genome and compared...et al., 2009; Hanahan and Weinberg, 2011). Over the last decade, the fruit fly Drosophila melanogaster has become an important model system for cancer...studies. Reduced redundancy in the Drosophila genome compared with that of humans, coupled with the ability to conduct large-scale genetic screens

In Vitro Tissue-Engineered Skeletal Muscle Models for Studying Muscle Physiology and Disease.

PubMed

Khodabukus, Alastair; Prabhu, Neel; Wang, Jason; Bursac, Nenad

2018-04-25

Healthy skeletal muscle possesses the extraordinary ability to regenerate in response to small-scale injuries; however, this self-repair capacity becomes overwhelmed with aging, genetic myopathies, and large muscle loss. The failure of small animal models to accurately replicate human muscle disease, injury and to predict clinically-relevant drug responses has driven the development of high fidelity in vitro skeletal muscle models. Herein, the progress made and challenges ahead in engineering biomimetic human skeletal muscle tissues that can recapitulate muscle development, genetic diseases, regeneration, and drug response is discussed. Bioengineering approaches used to improve engineered muscle structure and function as well as the functionality of satellite cells to allow modeling muscle regeneration in vitro are also highlighted. Next, a historical overview on the generation of skeletal muscle cells and tissues from human pluripotent stem cells, and a discussion on the potential of these approaches to model and treat genetic diseases such as Duchenne muscular dystrophy, is provided. Finally, the need to integrate multiorgan microphysiological systems to generate improved drug discovery technologies with the potential to complement or supersede current preclinical animal models of muscle disease is described. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design optimization of space launch vehicles using a genetic algorithm

NASA Astrophysics Data System (ADS)

Bayley, Douglas James

The United States Air Force (USAF) continues to have a need for assured access to space. In addition to flexible and responsive spacelift, a reduction in the cost per launch of space launch vehicles is also desirable. For this purpose, an investigation of the design optimization of space launch vehicles has been conducted. Using a suite of custom codes, the performance aspects of an entire space launch vehicle were analyzed. A genetic algorithm (GA) was employed to optimize the design of the space launch vehicle. A cost model was incorporated into the optimization process with the goal of minimizing the overall vehicle cost. The other goals of the design optimization included obtaining the proper altitude and velocity to achieve a low-Earth orbit. Specific mission parameters that are particular to USAF space endeavors were specified at the start of the design optimization process. Solid propellant motors, liquid fueled rockets, and air-launched systems in various configurations provided the propulsion systems for two, three and four-stage launch vehicles. Mass properties models, an aerodynamics model, and a six-degree-of-freedom (6DOF) flight dynamics simulator were all used to model the system. The results show the feasibility of this method in designing launch vehicles that meet mission requirements. Comparisons to existing real world systems provide the validation for the physical system models. However, the ability to obtain a truly minimized cost was elusive. The cost model uses an industry standard approach, however, validation of this portion of the model was challenging due to the proprietary nature of cost figures and due to the dependence of many existing systems on surplus hardware.

[The genetic control of mouse coat color and its applications in genetics teaching].

PubMed

Xing, Wanjin; Morigen, Morigen

2014-10-01

Mice are the most commonly used mammalian model. The coat colors of mice are typical Mendelian traits, which have various colors such as white, black, yellow and agouti. The inheritance of mouse coat color is usually stated as an example only in teaching the knowledge of recessive lethal alleles. After searched the related literatures and summarized the molecular mechanisms of mouse coat color inheritance, we further expanded the application of this example into the introduction of the basic concepts of alleles and Mendelian laws, demonstration of the gene structure and function, regulation of gene expression, gene interaction, epigenetic modification, quantitative genetics, as well as evolutionary genetics. By running this example through the whole genetics-teaching lectures, we help the student to form a systemic and developmental view of genetic analysis. At the same time, this teaching approach not only highlights the advancement and integrity of genetics, but also results in a good teaching effect on inspiring the students' interest and attracting students' attention.

Genetic parameters for growth characteristics of free-range chickens under univariate random regression models.

PubMed

Rovadoscki, Gregori A; Petrini, Juliana; Ramirez-Diaz, Johanna; Pertile, Simone F N; Pertille, Fábio; Salvian, Mayara; Iung, Laiza H S; Rodriguez, Mary Ana P; Zampar, Aline; Gaya, Leila G; Carvalho, Rachel S B; Coelho, Antonio A D; Savino, Vicente J M; Coutinho, Luiz L; Mourão, Gerson B

2016-09-01

Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that genetic gain for body weight can be achieved by selection. Also, selection for body weight at 42 days of age can be maintained as a selection criterion. © 2016 Poultry Science Association Inc.

Environmental efficiency of alternative dairy systems: a productive efficiency approach.

PubMed

Toma, L; March, M; Stott, A W; Roberts, D J

2013-01-01

Agriculture across the globe needs to produce "more with less." Productivity should be increased in a sustainable manner so that the environment is not further degraded, management practices are both socially acceptable and economically favorable, and future generations are not disadvantaged. The objective of this paper was to compare the environmental efficiency of 2 divergent strains of Holstein-Friesian cows across 2 contrasting dairy management systems (grazing and nongrazing) over multiple years and so expose any genetic × environment (G × E) interaction. The models were an extension of the traditional efficiency analysis to account for undesirable outputs (pollutants), and estimate efficiency measures that allow for the asymmetric treatment of desirable outputs (i.e., milk production) and undesirable outputs. Two types of models were estimated, one considering production inputs (land, nitrogen fertilizers, feed, and cows) and the other not, thus allowing the assessment of the effect of inputs by comparing efficiency values and rankings between models. Each model type had 2 versions, one including 2 types of pollutants (greenhouse gas emissions, nitrogen surplus) and the other 3 (greenhouse gas emissions, nitrogen surplus, and phosphorus surplus). Significant differences were found between efficiency scores among the systems. Results indicated no G × E interaction; however, even though the select genetic merit herd consuming a diet with a higher proportion of concentrated feeds was most efficient in the majority of models, cows of the same genetic merit on higher forage diets could be just as efficient. Efficiency scores for the low forage groups were less variable from year to year, which reflected the uniformity of purchased concentrate feeds. The results also indicate that inputs play an important role in the measurement of environmental efficiency of dairy systems and that animal health variables (incidence of udder health disorders and body condition score) have a significant effect on the environmental efficiency of each dairy system. We conclude that traditional narrow measures of performance may not always distinguish dairy farming systems best fitted to future requirements. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Panmictic and Clonal Evolution on a Single Patchy Resource Produces Polymorphic Foraging Guilds

PubMed Central

Getz, Wayne M.; Salter, Richard; Lyons, Andrew J.; Sippl-Swezey, Nicolas

2015-01-01

We develop a stochastic, agent-based model to study how genetic traits and experiential changes in the state of agents and available resources influence individuals’ foraging and movement behaviors. These behaviors are manifest as decisions on when to stay and exploit a current resource patch or move to a particular neighboring patch, based on information of the resource qualities of the patches and the anticipated level of intraspecific competition within patches. We use a genetic algorithm approach and an individual’s biomass as a fitness surrogate to explore the foraging strategy diversity of evolving guilds under clonal versus hermaphroditic sexual reproduction. We first present the resource exploitation processes, movement on cellular arrays, and genetic algorithm components of the model. We then discuss their implementation on the Nova software platform. This platform seamlessly combines the dynamical systems modeling of consumer-resource interactions with agent-based modeling of individuals moving over a landscapes, using an architecture that lays transparent the following four hierarchical simulation levels: 1.) within-patch consumer-resource dynamics, 2.) within-generation movement and competition mitigation processes, 3.) across-generation evolutionary processes, and 4.) multiple runs to generate the statistics needed for comparative analyses. The focus of our analysis is on the question of how the biomass production efficiency and the diversity of guilds of foraging strategy types, exploiting resources over a patchy landscape, evolve under clonal versus random hermaphroditic sexual reproduction. Our results indicate greater biomass production efficiency under clonal reproduction only at higher population densities, and demonstrate that polymorphisms evolve and are maintained under random mating systems. The latter result questions the notion that some type of associative mating structure is needed to maintain genetic polymorphisms among individuals exploiting a common patchy resource on an otherwise spatially homogeneous landscape. PMID:26274613

The effects of intraspecific competition and stabilizing selection on a polygenic trait.

PubMed Central

Bürger, Reinhard; Gimelfarb, Alexander

2004-01-01

The equilibrium properties of an additive multilocus model of a quantitative trait under frequency- and density-dependent selection are investigated. Two opposing evolutionary forces are assumed to act: (i) stabilizing selection on the trait, which favors genotypes with an intermediate phenotype, and (ii) intraspecific competition mediated by that trait, which favors genotypes whose effect on the trait deviates most from that of the prevailing genotypes. Accordingly, fitnesses of genotypes have a frequency-independent component describing stabilizing selection and a frequency- and density-dependent component modeling competition. We study how the equilibrium structure, in particular, number, degree of polymorphism, and genetic variance of stable equilibria, is affected by the strength of frequency dependence, and what role the number of loci, the amount of recombination, and the demographic parameters play. To this end, we employ a statistical and numerical approach, complemented by analytical results, and explore how the equilibrium properties averaged over a large number of genetic systems with a given number of loci and average amount of recombination depend on the ecological and demographic parameters. We identify two parameter regions with a transitory region in between, in which the equilibrium properties of genetic systems are distinctively different. These regions depend on the strength of frequency dependence relative to pure stabilizing selection and on the demographic parameters, but not on the number of loci or the amount of recombination. We further study the shape of the fitness function observed at equilibrium and the extent to which the dynamics in this model are adaptive, and we present examples of equilibrium distributions of genotypic values under strong frequency dependence. Consequences for the maintenance of genetic variation, the detection of disruptive selection, and models of sympatric speciation are discussed. PMID:15280253

Theoretical Modeling and Computer Simulations for the Origins and Evolution of Reproducing Molecular Systems and Complex Systems with Many Interactive Parts

NASA Technical Reports Server (NTRS)

Liang, Shoudan

2000-01-01

Our research effort has produced nine publications in peer-reviewed journals listed at the end of this report. The work reported here are in the following areas: (1) genetic network modeling; (2) autocatalytic model of pre-biotic evolution; (3) theoretical and computational studies of strongly correlated electron systems; (4) reducing thermal oscillations in atomic force microscope; (5) transcription termination mechanism in prokaryotic cells; and (6) the low glutamine usage in thennophiles obtained by studying completely sequenced genomes. We discuss the main accomplishments of these publications.

Chemical and radiation mutagenesis: Induction and detection by whole genome sequencing

USDA-ARS?s Scientific Manuscript database

Brachypodium distachyon has emerged as an effective model system to address fundamental questions in grass biology. With its small sequenced genome, short generation time and rapidly expanding array of genetic tools B. distachyon is an ideal system to elucidate the molecular basis of important trai...

Drug-induced and genetic alterations in stress-responsive systems: Implications for specific addictive diseases.

PubMed

Zhou, Yan; Proudnikov, Dmitri; Yuferov, Vadim; Kreek, Mary Jeanne

2010-02-16

From the earliest work in our laboratory, we hypothesized, and with studies conducted in both clinical research and animal models, we have shown that drugs of abuse, administered or self-administered, on a chronic basis, profoundly alter stress-responsive systems. Alterations of expression of specific genes involved in stress responsivity, with increases or decreases in mRNA levels, receptor, and neuropeptide levels, and resultant changes in hormone levels, have been documented to occur after chronic intermittent exposure to heroin, morphine, other opiates, cocaine, other stimulants, and alcohol in animal models and in human molecular genetics. The best studied of the stress-responsive systems in humans and mammalian species in general is undoubtedly the HPA axis. In addition, there are stress-responsive systems in other parts in the brain itself, and some of these include components of the HPA axis, such as CRF and CRF receptors, along with POMC gene and gene products. Several other stress-responsive systems are known to influence the HPA axis, such as the vasopressin-vasopressin receptor system. Orexin-hypocretin, acting at its receptors, may effect changes which suggest that it should be properly categorized as a stress-responsive system. However, less is known about the interactions and connectivity of some of these different neuropeptide and receptor systems, and in particular, about the possible connectivity of fast-acting (e.g., glutamate and GABA) and slow-acting (including dopamine, serotonin, and norepinephrine) neurotransmitters with each of these stress-responsive components and the resultant impact, especially in the setting of chronic exposure to drugs of abuse. Several of these stress-responsive systems and components, primarily based on our laboratory-based and human molecular genetics research of addictive diseases, will be briefly discussed in this review. Copyright 2009 Elsevier B.V. All rights reserved.

Pricing and location decisions in multi-objective facility location problem with M/M/m/k queuing systems

NASA Astrophysics Data System (ADS)

Tavakkoli-Moghaddam, Reza; Vazifeh-Noshafagh, Samira; Taleizadeh, Ata Allah; Hajipour, Vahid; Mahmoudi, Amin

2017-01-01

This article presents a new multi-objective model for a facility location problem with congestion and pricing policies. This model considers situations in which immobile service facilities are congested by a stochastic demand following M/M/m/k queues. The presented model belongs to the class of mixed-integer nonlinear programming models and NP-hard problems. To solve such a hard model, a new multi-objective optimization algorithm based on a vibration theory, namely multi-objective vibration damping optimization (MOVDO), is developed. In order to tune the algorithms parameters, the Taguchi approach using a response metric is implemented. The computational results are compared with those of the non-dominated ranking genetic algorithm and non-dominated sorting genetic algorithm. The outputs demonstrate the robustness of the proposed MOVDO in large-sized problems.

How animal models of leukaemias have already benefited patients.

PubMed

Ablain, Julien; Nasr, Rihab; Zhu, Jun; Bazarbachi, Ali; Lallemand-Breittenbach, Valérie; de Thé, Hugues

2013-04-01

The relative genetic simplicity of leukaemias, the development of which likely relies on a limited number of initiating events has made them ideal for disease modelling, particularly in the mouse. Animal models provide incomparable insights into the mechanisms of leukaemia development and allow exploration of the molecular pillars of disease maintenance, an aspect often biased in cell lines or ex vivo systems. Several of these models, which faithfully recapitulate the characteristics of the human disease, have been used for pre-clinical purposes and have been instrumental in predicting therapy response in patients. We plea for a wider use of genetically defined animal models in the design of clinical trials, with a particular focus on reassessment of existing cancer or non-cancer drugs, alone or in combination. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Type VI secretion systems of human gut Bacteroidales segregate into three genetic architectures, two of which are contained on mobile genetic elements.

PubMed

Coyne, Michael J; Roelofs, Kevin G; Comstock, Laurie E

2016-01-15

Type VI secretion systems (T6SSs) are contact-dependent antagonistic systems employed by Gram negative bacteria to intoxicate other bacteria or eukaryotic cells. T6SSs were recently discovered in a few Bacteroidetes strains, thereby extending the presence of these systems beyond Proteobacteria. The present study was designed to analyze in a global nature the diversity, abundance, and properties of T6SSs in the Bacteroidales, the most predominant Gram negative bacterial order of the human gut. By performing extensive bioinformatics analyses and creating hidden Markov models for Bacteroidales Tss proteins, we identified 130 T6SS loci in 205 human gut Bacteroidales genomes. Of the 13 core T6SS proteins of Proteobacteria, human gut Bacteroidales T6SS loci encode orthologs of nine, and an additional five other core proteins not present in Proteobacterial T6SSs. The Bacteroidales T6SS loci segregate into three distinct genetic architectures with extensive DNA identity between loci of a given genetic architecture. We found that divergent DNA regions of a genetic architecture encode numerous types of effector and immunity proteins and likely include new classes of these proteins. TheT6SS loci of genetic architecture 1 are contained on highly similar integrative conjugative elements (ICEs), as are the T6SS loci of genetic architecture 2, whereas the T6SS loci of genetic architecture 3 are not and are confined to Bacteroides fragilis. Using collections of co-resident Bacteroidales strains from human subjects, we provide evidence for the transfer of genetic architecture 1 T6SS loci among co-resident Bacteroidales species in the human gut. However, we also found that established ecosystems can harbor strains with distinct T6SS of all genetic architectures. This is the first study to comprehensively analyze of the presence and diversity of T6SS loci within an order of bacteria and to analyze T6SSs of bacteria from a natural community. These studies demonstrate that more than half of our gut Bacteroidales, equivalent to about ¼ of the bacteria of this ecosystem, encode T6SSs. The data reveal several novel properties of these systems and suggest that antagonism between or distributed defense among these abundant intestinal bacteria may be common in established human gut communities.

GENETIC VARIANTS, IMMUNE FUNCTION AND RISK OF PRE-ECLAMPSIA AMONG AMERICAN INDIANS

PubMed Central

Best, Lyle G.; Nadeau, Melanie; Davis, Kylie; Lamb, Felicia; Bercier, Shellee; Anderson, Cindy M.

2011-01-01

Objective To determine the prevalence in an American Indian population of genetic variants with putative effects on immune function and determine if they are associated with pre-eclampsia. Methods In a study of 66 cases and 130 matched controls, six single nucleotide polymorphisms (SNP) with either previously demonstrated or postulated modulating effects on the immune system were genotyped. Allele frequencies and various genetic models were evaluated by conditional logistic regression in both univariate and multiply adjusted models. Results Although most genetic variants lacked evidence of association with pre-eclampsia, the minor allele of the CRP related, rs1205 SNP in a dominant model with adjustment for age at delivery, nulliparity and body mass index, exhibited an odds ratio of 0.259 (95% CI of 0.08 – 0.81, p=0.020) in relation to severe pre-eclampsia (48 cases). The allelic prevalence of this variant was 46.1% in this population. Conclusion Of the six SNPs related to immune function in this study, a functional variant in the 3'UTR of the CRP gene was shown to be associated with severe pre-eclampsia in an American Indian population. PMID:22004660

Mathematical Modeling of Intestinal Iron Absorption Using Genetic Programming

PubMed Central

Colins, Andrea; Gerdtzen, Ziomara P.; Nuñez, Marco T.; Salgado, J. Cristian

2017-01-01

Iron is a trace metal, key for the development of living organisms. Its absorption process is complex and highly regulated at the transcriptional, translational and systemic levels. Recently, the internalization of the DMT1 transporter has been proposed as an additional regulatory mechanism at the intestinal level, associated to the mucosal block phenomenon. The short-term effect of iron exposure in apical uptake and initial absorption rates was studied in Caco-2 cells at different apical iron concentrations, using both an experimental approach and a mathematical modeling framework. This is the first report of short-term studies for this system. A non-linear behavior in the apical uptake dynamics was observed, which does not follow the classic saturation dynamics of traditional biochemical models. We propose a method for developing mathematical models for complex systems, based on a genetic programming algorithm. The algorithm is aimed at obtaining models with a high predictive capacity, and considers an additional parameter fitting stage and an additional Jackknife stage for estimating the generalization error. We developed a model for the iron uptake system with a higher predictive capacity than classic biochemical models. This was observed both with the apical uptake dataset used for generating the model and with an independent initial rates dataset used to test the predictive capacity of the model. The model obtained is a function of time and the initial apical iron concentration, with a linear component that captures the global tendency of the system, and a non-linear component that can be associated to the movement of DMT1 transporters. The model presented in this paper allows the detailed analysis, interpretation of experimental data, and identification of key relevant components for this complex biological process. This general method holds great potential for application to the elucidation of biological mechanisms and their key components in other complex systems. PMID:28072870

Distinct developmental genetic mechanisms underlie convergently evolved tooth gain in sticklebacks

PubMed Central

Ellis, Nicholas A.; Glazer, Andrew M.; Donde, Nikunj N.; Cleves, Phillip A.; Agoglia, Rachel M.; Miller, Craig T.

2015-01-01

Teeth are a classic model system of organogenesis, as repeated and reciprocal epithelial and mesenchymal interactions pattern placode formation and outgrowth. Less is known about the developmental and genetic bases of tooth formation and replacement in polyphyodonts, which are vertebrates with continual tooth replacement. Here, we leverage natural variation in the threespine stickleback fish Gasterosteus aculeatus to investigate the genetic basis of tooth development and replacement. We find that two derived freshwater stickleback populations have both convergently evolved more ventral pharyngeal teeth through heritable genetic changes. In both populations, evolved tooth gain manifests late in development. Using pulse-chase vital dye labeling to mark newly forming teeth in adult fish, we find that both high-toothed freshwater populations have accelerated tooth replacement rates relative to low-toothed ancestral marine fish. Despite the similar evolved phenotype of more teeth and an accelerated adult replacement rate, the timing of tooth number divergence and the spatial patterns of newly formed adult teeth are different in the two populations, suggesting distinct developmental mechanisms. Using genome-wide linkage mapping in marine-freshwater F2 genetic crosses, we find that the genetic basis of evolved tooth gain in the two freshwater populations is largely distinct. Together, our results support a model whereby increased tooth number and an accelerated tooth replacement rate have evolved convergently in two independently derived freshwater stickleback populations using largely distinct developmental and genetic mechanisms. PMID:26062935

Environment, dysbiosis, immunity and sex-specific susceptibility: A translational hypothesis for regressive autism pathogenesis

PubMed Central

Mezzelani, Alessandra; Landini, Martina; Facchiano, Francesco; Raggi, Maria Elisabetta; Villa, Laura; Molteni, Massimo; De Santis, Barbara; Brera, Carlo; Caroli, Anna Maria; Milanesi, Luciano; Marabotti, Anna

2015-01-01

Background Autism is an increasing neurodevelopmental disease that appears by 3 years of age, has genetic and/or environmental etiology, and often shows comorbid situations, such as gastrointestinal (GI) disorders. Autism has also a striking sex-bias, not fully genetically explainable. Objective Our goal was to explain how and in which predisposing conditions some compounds can impair neurodevelopment, why this occurs in the first years of age, and, primarily, why more in males than females. Methods We reviewed articles regarding the genetic and environmental etiology of autism and toxins effects on animal models selected from PubMed and databases about autism and toxicology. Discussion Our hypothesis proposes that in the first year of life, the decreasing of maternal immune protection and child immune-system immaturity create an immune vulnerability to infection diseases that, especially if treated with antibiotics, could facilitate dysbiosis and GI disorders. This condition triggers a vicious circle between immune system impairment and increasing dysbiosis that leads to leaky gut and neurochemical compounds and/or neurotoxic xenobiotics production and absorption. This alteration affects the ‘gut-brain axis’ communication that connects gut with central nervous system via immune system. Thus, metabolic pathways impaired in autistic children can be affected by genetic alterations or by environment–xenobiotics interference. In addition, in animal models many xenobiotics exert their neurotoxicity in a sex-dependent manner. Conclusions We integrate fragmented and multi-disciplinary information in a unique hypothesis and first disclose a possible environmental origin for the imbalance of male:female distribution of autism, reinforcing the idea that exogenous factors are related to the recent rise of this disease. PMID:24621061

The Genetic Basis for Variation in Sensitivity to Lead Toxicity in Drosophila melanogaster.

PubMed

Zhou, Shanshan; Morozova, Tatiana V; Hussain, Yasmeen N; Luoma, Sarah E; McCoy, Lenovia; Yamamoto, Akihiko; Mackay, Trudy F C; Anholt, Robert R H

2016-07-01

Lead toxicity presents a worldwide health problem, especially due to its adverse effects on cognitive development in children. However, identifying genes that give rise to individual variation in susceptibility to lead toxicity is challenging in human populations. Our goal was to use Drosophila melanogaster to identify evolutionarily conserved candidate genes associated with individual variation in susceptibility to lead exposure. To identify candidate genes associated with variation in susceptibility to lead toxicity, we measured effects of lead exposure on development time, viability and adult activity in the Drosophila melanogaster Genetic Reference Panel (DGRP) and performed genome-wide association analyses to identify candidate genes. We used mutants to assess functional causality of candidate genes and constructed a genetic network associated with variation in sensitivity to lead exposure, on which we could superimpose human orthologs. We found substantial heritabilities for all three traits and identified candidate genes associated with variation in susceptibility to lead exposure for each phenotype. The genetic architectures that determine variation in sensitivity to lead exposure are highly polygenic. Gene ontology and network analyses showed enrichment of genes associated with early development and function of the nervous system. Drosophila melanogaster presents an advantageous model to study the genetic underpinnings of variation in susceptibility to lead toxicity. Evolutionary conservation of cellular pathways that respond to toxic exposure allows predictions regarding orthologous genes and pathways across phyla. Thus, studies in the D. melanogaster model system can identify candidate susceptibility genes to guide subsequent studies in human populations. Zhou S, Morozova TV, Hussain YN, Luoma SE, McCoy L, Yamamoto A, Mackay TF, Anholt RR. 2016. The genetic basis for variation in sensitivity to lead toxicity in Drosophila melanogaster. Environ Health Perspect 124:1062-1070; http://dx.doi.org/10.1289/ehp.1510513.

Using a genetic, observational study as a strategy to estimate the potential cost-effectiveness of pharmacological CCR5 blockade in dialysis patients.

PubMed

Muntinghe, Friso L H; Vegter, Stefan; Verduijn, Marion; Boeschoten, Elisabeth W; Dekker, Friedo W; Navis, Gerjan; Postma, Maarten

2011-07-01

Randomized clinical trials are expensive and time consuming. Therefore, strategies are needed to prioritise tracks for drug development. Genetic association studies may provide such a strategy by considering the differences between genotypes as a proxy for a natural, lifelong, randomized at conception, clinical trial. Previously an association with better survival was found in dialysis patients with systemic inflammation carrying a deletion variant of the CC-chemokine receptor 5 (CCR5). We hypothesized that in an analogous manner, pharmacological CCR5 blockade could protect against inflammation-driven mortality and estimated if such a treatment would be cost-effective. A genetic screen and treat strategy was modelled using a decision-analytic Markov model, in which patients were screened for the CCR5 deletion 32 polymorphism and those with the wild type and systemic inflammation were treated with pharmacological CCR5 blockers. Kidney transplantation and mortality rates were calculated using patient level data. Extensive sensitivity analyses were performed. The cost-effectiveness of the genetic screen and treat strategy was &OV0556;18 557 per life year gained and &OV0556;21 896 per quality-adjusted life years gained. Concordance between the genetic association and pharmacological effectiveness was a main driver of cost-effectiveness. Sensitivity analyses showed that even a modest effectiveness of pharmacological CCR5 blockade would result in a treatment strategy that is good value for money. Pharmacological blockade of the CCR5 receptor in inflamed dialysis patients can be incorporated in a potentially cost-effective screen and treat programme. These findings provide formal rationale for clinical studies. This study illustrates the potential of genetic association studies for drug development, as a source of Mendelian randomized evidence from an observational setting.

The hypocretin system and psychiatric disorders.

PubMed

Pizza, Fabio; Magnani, Michele; Indrio, Camilla; Plazzi, Giuseppe

2014-02-01

The hypocretin system is constituted by a small group of hypothalamic neurons with widespread connections within the entire central nervous system producing two neuropeptides involved in several key physiological functions such as the regulation of sleep and wakefulness, motor control, autonomic functions, metabolism, feeding behavior, and reward. Narcolepsy with cataplexy is a neurological disorder regarded as a disease model for the selective hypocretin system damage, and also shares several psychopatological traits and comorbidities with psychiatric disorders. We reviewed the available literature on the involvement of the hypocretin system in psychiatric nosography. Different evidences such as cerebrospinal hypocretin-1 levels, genetic polymorphisms of the neuropeptides or their receptors, response to treatments, clinical, experimental and functional data directly or indirectly linked the hypocretin system to schizophrenia, mood, anxiety and eating disorders, as well as to addiction. Future genetic and pharmacological studies will disentangle the hypocretin system role in the field of psychiatry.

Generation and comparison of CRISPR-Cas9 and Cre-mediated genetically engineered mouse models of sarcoma

PubMed Central

Huang, Jianguo; Chen, Mark; Whitley, Melodi Javid; Kuo, Hsuan-Cheng; Xu, Eric S.; Walens, Andrea; Mowery, Yvonne M.; Van Mater, David; Eward, William C.; Cardona, Diana M.; Luo, Lixia; Ma, Yan; Lopez, Omar M.; Nelson, Christopher E.; Robinson-Hamm, Jacqueline N.; Reddy, Anupama; Dave, Sandeep S.; Gersbach, Charles A.; Dodd, Rebecca D.; Kirsch, David G.

2017-01-01

Genetically engineered mouse models that employ site-specific recombinase technology are important tools for cancer research but can be costly and time-consuming. The CRISPR-Cas9 system has been adapted to generate autochthonous tumours in mice, but how these tumours compare to tumours generated by conventional recombinase technology remains to be fully explored. Here we use CRISPR-Cas9 to generate multiple subtypes of primary sarcomas efficiently in wild type and genetically engineered mice. These data demonstrate that CRISPR-Cas9 can be used to generate multiple subtypes of soft tissue sarcomas in mice. Primary sarcomas generated with CRISPR-Cas9 and Cre recombinase technology had similar histology, growth kinetics, copy number variation and mutational load as assessed by whole exome sequencing. These results show that sarcomas generated with CRISPR-Cas9 technology are similar to sarcomas generated with conventional modelling techniques and suggest that CRISPR-Cas9 can be used to more rapidly generate genotypically and phenotypically similar cancers. PMID:28691711

Novel gene function revealed by mouse mutagenesis screens for models of age-related disease.

PubMed

Potter, Paul K; Bowl, Michael R; Jeyarajan, Prashanthini; Wisby, Laura; Blease, Andrew; Goldsworthy, Michelle E; Simon, Michelle M; Greenaway, Simon; Michel, Vincent; Barnard, Alun; Aguilar, Carlos; Agnew, Thomas; Banks, Gareth; Blake, Andrew; Chessum, Lauren; Dorning, Joanne; Falcone, Sara; Goosey, Laurence; Harris, Shelley; Haynes, Andy; Heise, Ines; Hillier, Rosie; Hough, Tertius; Hoslin, Angela; Hutchison, Marie; King, Ruairidh; Kumar, Saumya; Lad, Heena V; Law, Gemma; MacLaren, Robert E; Morse, Susan; Nicol, Thomas; Parker, Andrew; Pickford, Karen; Sethi, Siddharth; Starbuck, Becky; Stelma, Femke; Cheeseman, Michael; Cross, Sally H; Foster, Russell G; Jackson, Ian J; Peirson, Stuart N; Thakker, Rajesh V; Vincent, Tonia; Scudamore, Cheryl; Wells, Sara; El-Amraoui, Aziz; Petit, Christine; Acevedo-Arozena, Abraham; Nolan, Patrick M; Cox, Roger; Mallon, Anne-Marie; Brown, Steve D M

2016-08-18

Determining the genetic bases of age-related disease remains a major challenge requiring a spectrum of approaches from human and clinical genetics to the utilization of model organism studies. Here we report a large-scale genetic screen in mice employing a phenotype-driven discovery platform to identify mutations resulting in age-related disease, both late-onset and progressive. We have utilized N-ethyl-N-nitrosourea mutagenesis to generate pedigrees of mutagenized mice that were subject to recurrent screens for mutant phenotypes as the mice aged. In total, we identify 105 distinct mutant lines from 157 pedigrees analysed, out of which 27 are late-onset phenotypes across a range of physiological systems. Using whole-genome sequencing we uncover the underlying genes for 44 of these mutant phenotypes, including 12 late-onset phenotypes. These genes reveal a number of novel pathways involved with age-related disease. We illustrate our findings by the recovery and characterization of a novel mouse model of age-related hearing loss.

Novel gene function revealed by mouse mutagenesis screens for models of age-related disease

PubMed Central

Potter, Paul K.; Bowl, Michael R.; Jeyarajan, Prashanthini; Wisby, Laura; Blease, Andrew; Goldsworthy, Michelle E.; Simon, Michelle M.; Greenaway, Simon; Michel, Vincent; Barnard, Alun; Aguilar, Carlos; Agnew, Thomas; Banks, Gareth; Blake, Andrew; Chessum, Lauren; Dorning, Joanne; Falcone, Sara; Goosey, Laurence; Harris, Shelley; Haynes, Andy; Heise, Ines; Hillier, Rosie; Hough, Tertius; Hoslin, Angela; Hutchison, Marie; King, Ruairidh; Kumar, Saumya; Lad, Heena V.; Law, Gemma; MacLaren, Robert E.; Morse, Susan; Nicol, Thomas; Parker, Andrew; Pickford, Karen; Sethi, Siddharth; Starbuck, Becky; Stelma, Femke; Cheeseman, Michael; Cross, Sally H.; Foster, Russell G.; Jackson, Ian J.; Peirson, Stuart N.; Thakker, Rajesh V.; Vincent, Tonia; Scudamore, Cheryl; Wells, Sara; El-Amraoui, Aziz; Petit, Christine; Acevedo-Arozena, Abraham; Nolan, Patrick M.; Cox, Roger; Mallon, Anne-Marie; Brown, Steve D. M.

2016-01-01

Determining the genetic bases of age-related disease remains a major challenge requiring a spectrum of approaches from human and clinical genetics to the utilization of model organism studies. Here we report a large-scale genetic screen in mice employing a phenotype-driven discovery platform to identify mutations resulting in age-related disease, both late-onset and progressive. We have utilized N-ethyl-N-nitrosourea mutagenesis to generate pedigrees of mutagenized mice that were subject to recurrent screens for mutant phenotypes as the mice aged. In total, we identify 105 distinct mutant lines from 157 pedigrees analysed, out of which 27 are late-onset phenotypes across a range of physiological systems. Using whole-genome sequencing we uncover the underlying genes for 44 of these mutant phenotypes, including 12 late-onset phenotypes. These genes reveal a number of novel pathways involved with age-related disease. We illustrate our findings by the recovery and characterization of a novel mouse model of age-related hearing loss. PMID:27534441

Mammalian synthetic biology for studying the cell

PubMed Central

Mathur, Melina; Xiang, Joy S.

2017-01-01

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. PMID:27932576

Genetic manipulation and monitoring of autophagy in Drosophila.

PubMed

Neufeld, Thomas P

2008-01-01

Drosophila melanogaster provides a model system useful for many aspects of the study of autophagy in vivo. These include testing and validation of genes potentially involved in autophagy, discovery of novel genes through genetic screening for mutations that affect autophagy, and analysis of potential roles of autophagy in specific developmental or physiological processes. In recent years, a number of techniques and transgenic and mutant fly strains have been developed to facilitate autophagy analysis in this system. Here, protocols are described for activating or inhibiting autophagy in Drosophila, and for examining the progression of autophagy in vivo through imaging-based assays. The goal of this chapter is to provide a resource both for autophagy investigators with limited familiarity with fly genetics, as well as for experienced Drosophila biologists who wish to test for connections between autophagy and a given gene, pathway or process.

Using Zebrafish to Test the Genetic Basis of Human Craniofacial Diseases.

PubMed

Machado, R Grecco; Eames, B Frank

2017-10-01

Genome-wide association studies (GWASs) opened an innovative and productive avenue to investigate the molecular basis of human craniofacial disease. However, GWASs identify candidate genes only; they do not prove that any particular one is the functional villain underlying disease or just an unlucky genomic bystander. Genetic manipulation of animal models is the best approach to reveal which genetic loci identified from human GWASs are functionally related to specific diseases. The purpose of this review is to discuss the potential of zebrafish to resolve which candidate genetic loci are mechanistic drivers of craniofacial diseases. Many anatomic, embryonic, and genetic features of craniofacial development are conserved among zebrafish and mammals, making zebrafish a good model of craniofacial diseases. Also, the ability to manipulate gene function in zebrafish was greatly expanded over the past 20 y, enabling systems such as Gateway Tol2 and CRISPR-Cas9 to test gain- and loss-of-function alleles identified from human GWASs in coding and noncoding regions of DNA. With the optimization of genetic editing methods, large numbers of candidate genes can be efficiently interrogated. Finding the functional villains that underlie diseases will permit new treatments and prevention strategies and will increase understanding of how gene pathways operate during normal development.

Accelerating Genetic Gains in Legumes for the Development of Prosperous Smallholder Agriculture: Integrating Genomics, Phenotyping, Systems Modelling and Agronomy.

PubMed

Varshney, Rajeev K; Thudi, Mahendar; Pandey, Manish K; Tardieu, Francois; Ojiewo, Chris; Vadez, Vincent; Whitbread, Anthony M; Siddique, Kadambot H M; Nguyen, Henry T; Carberry, Peter S; Bergvinson, David

2018-03-05

Grain legumes form an important component of the human diet, feed for livestock and replenish soil fertility through biological nitrogen fixation. Globally, the demand for food legumes is increasing as they complement cereals in protein requirements and possess a high percentage of digestible protein. Climate change has enhanced the frequency and intensity of drought stress that is posing serious production constraints, especially in rainfed regions where most legumes are produced. Genetic improvement of legumes, like other crops, is mostly based on pedigree and performance-based selection over the last half century. For achieving faster genetic gains in legumes in rainfed conditions, this review article proposes the integration of modern genomics approaches, high throughput phenomics and simulation modelling as support for crop improvement that leads to improved varieties that perform with appropriate agronomy. Selection intensity, generation interval and improved operational efficiencies in breeding are expected to further enhance the genetic gain in experiment plots. Improved seed access to farmers, combined with appropriate agronomic packages in farmers' fields, will deliver higher genetic gains. Enhanced genetic gains including not only productivity but also nutritional and market traits will increase the profitability of farmers and the availability of affordable nutritious food especially in developing countries.

Education and alcohol use: A study of gene-environment interaction in young adulthood.

PubMed

Barr, Peter B; Salvatore, Jessica E; Maes, Hermine; Aliev, Fazil; Latvala, Antti; Viken, Richard; Rose, Richard J; Kaprio, Jaakko; Dick, Danielle M

2016-08-01

The consequences of heavy alcohol use remain a serious public health problem. Consistent evidence has demonstrated that both genetic and social influences contribute to alcohol use. Research on gene-environment interaction (GxE) has also demonstrated that these social and genetic influences do not act independently. Instead, certain environmental contexts may limit or exacerbate an underlying genetic predisposition. However, much of the work on GxE and alcohol use has focused on adolescence and less is known about the important environmental contexts in young adulthood. Using data from the young adult wave of the Finnish Twin Study, FinnTwin12 (N = 3402), we used biometric twin modeling to test whether education moderated genetic risk for alcohol use as assessed by drinking frequency and intoxication frequency. Education is important because it offers greater access to personal resources and helps determine one's position in the broader stratification system. Results from the twin models show that education did not moderate genetic variance components and that genetic risk was constant across levels of education. Instead, education moderated environmental variance so that under conditions of low education, environmental influences explained more of the variation in alcohol use outcomes. The implications and limitations of these results are discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Heritable variation in host tolerance and resistance inferred from a wild host-parasite system.

PubMed

Mazé-Guilmo, Elise; Loot, Géraldine; Páez, David J; Lefèvre, Thierry; Blanchet, Simon

2014-03-22

Hosts have evolved two distinct defence strategies against parasites: resistance (which prevents infection or limit parasite growth) and tolerance (which alleviates the fitness consequences of infection). However, heritable variation in resistance and tolerance and the genetic correlation between these two traits have rarely been characterized in wild host populations. Here, we estimate these parameters for both traits in Leuciscus burdigalensis, a freshwater fish parasitized by Tracheliastes polycolpus. We used a genetic database to construct a full-sib pedigree in a wild L. burdigalensis population. We then used univariate animal models to estimate inclusive heritability (i.e. all forms of genetic and non-genetic inheritance) in resistance and tolerance. Finally, we assessed the genetic correlation between these two traits using a bivariate animal model. We found significant heritability for resistance (H = 17.6%; 95% CI: 7.2-32.2%) and tolerance (H = 18.8%; 95% CI: 4.4-36.1%), whereas we found no evidence for the existence of a genetic correlation between these traits. Furthermore, we confirm that resistance and tolerance are strongly affected by environmental effects. Our results demonstrate that (i) heritable variation exists for parasite resistance and tolerance in wild host populations, and (ii) these traits can evolve independently in populations.

Education and Alcohol Use: A Study of Gene-Environment Interaction in Young Adulthood

PubMed Central

Barr, Peter B.; Salvatore, Jessica E.; Maes, Hermine; Aliev, Fazil; Latvala, Antti; Viken, Richard; Rose, Richard J.; Kaprio, Jaakko; Dick, Danielle M.

2016-01-01

The consequences of heavy alcohol use remain a serious public health problem. Consistent evidence has demonstrated that both genetic and social influences contribute to alcohol use. Research on gene-environment interaction (GxE) has also demonstrated that these social and genetic influences do not act independently. Instead, certain environmental contexts may limit or exacerbate an underlying genetic predisposition. However, much of the work on GxE and alcohol use has focused on adolescence and less is known about the important environmental contexts in young adulthood. Using data from the young adult wave of the Finnish Twin Study, FinnTwin12 (N=3,402), we used biometric twin modeling to test whether education moderated genetic risk for alcohol use as assessed by drinking frequency and intoxication frequency. Education is important because it offers greater access to personal resources and helps determine one’s position in the broader stratification system. Results from the twin models show that education did not moderate genetic variance components and that genetic risk was constant across levels of education. Instead, education moderated environmental variance so that under conditions of low education, environmental influences explained more of the variation in alcohol use outcomes. The implications and limitations of these results are discussed. PMID:27367897

Multi-channel acoustic recording and automated analysis of Drosophila courtship songs

PubMed Central

2013-01-01

Background Drosophila melanogaster has served as a powerful model system for genetic studies of courtship songs. To accelerate research on the genetic and neural mechanisms underlying courtship song, we have developed a sensitive recording system to simultaneously capture the acoustic signals from 32 separate pairs of courting flies as well as software for automated segmentation of songs. Results Our novel hardware design enables recording of low amplitude sounds in most laboratory environments. We demonstrate the power of this system by collecting, segmenting and analyzing over 18 hours of courtship song from 75 males from five wild-type strains of Drosophila melanogaster. Our analysis reveals previously undetected modulation of courtship song features and extensive natural genetic variation for most components of courtship song. Despite having a large dataset with sufficient power to detect subtle modulations of song, we were unable to identify previously reported periodic rhythms in the inter-pulse interval of song. We provide detailed instructions for assembling the hardware and for using our open-source segmentation software. Conclusions Analysis of a large dataset of acoustic signals from Drosophila melanogaster provides novel insight into the structure and dynamics of species-specific courtship songs. Our new system for recording and analyzing fly acoustic signals should therefore greatly accelerate future studies of the genetics, neurobiology and evolution of courtship song. PMID:23369160

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.

Modeling a synthetic multicellular clock: Repressilators coupled by quorum sensing

PubMed Central

Garcia-Ojalvo, Jordi; Elowitz, Michael B.; Strogatz, Steven H.

2004-01-01

Diverse biochemical rhythms are generated by thousands of cellular oscillators that somehow manage to operate synchronously. In fields ranging from circadian biology to endocrinology, it remains an exciting challenge to understand how collective rhythms emerge in multicellular structures. Using mathematical and computational modeling, we study the effect of coupling through intercell signaling in a population of Escherichia coli cells expressing a synthetic biological clock. Our results predict that a diverse and noisy community of such genetic oscillators interacting through a quorum-sensing mechanism should self-synchronize in a robust way, leading to a substantially improved global rhythmicity in the system. As such, the particular system of coupled genetic oscillators considered here might be a good candidate to provide the first quantitative example of a synchronization transition in a population of biological oscillators. PMID:15256602

Connectivity in a pond system influences migration and genetic structure in threespine stickleback.

PubMed

Seymour, Mathew; Räsänen, Katja; Holderegger, Rolf; Kristjánsson, Bjarni K

2013-03-01

Neutral genetic structure of natural populations is primarily influenced by migration (the movement of individuals and, subsequently, their genes) and drift (the statistical chance of losing genetic diversity over time). Migration between populations is influenced by several factors, including individual behavior, physical barriers, and environmental heterogeneity among populations. However, drift is expected to be stronger in populations with low immigration rate and small effective population size. With the technological advancement in geological information systems and spatial analysis tools, landscape genetics now allows the development of realistic migration models and increased insight to important processes influencing diversity of natural populations. In this study, we investigated the relationship between landscape connectivity and genetic distance of threespine stickleback (Gasterosteus aculeatus) inhabiting a pond complex in Belgjarskógur, Northeast Iceland. We used two landscape genetic approaches (i.e., least-cost-path and isolation-by-resistance) and asked whether gene flow, as measured by genetic distance, was more strongly associated with Euclidean distance (isolation-by-distance) or with landscape connectivity provided by areas prone to flooding (as indicated by Carex sp. cover)? We found substantial genetic structure across the study area, with pairwise genetic distances among populations (DPS) ranging from 0.118 to 0.488. Genetic distances among populations were more strongly correlated with least-cost-path and isolation-by-resistance than with Euclidean distance, whereas the relative contribution of isolation-by-resistance and Euclidian distance could not be disentangled. These results indicate that migration among stickleback populations occurs via periodically flooded areas. Overall, this study highlights the importance of transient landscape elements influencing migration and genetic structure of populations at small spatial scales.

PTPN22 1858C > T polymorphism and susceptibility to systemic lupus erythematosus: a meta-analysis update.

PubMed

de Lima, Suelen Cristina; Adelino, José Eduardo; Crovella, Sergio; de Azevedo Silva, Jaqueline; Sandrin-Garcia, Paula

2017-11-01

Studies performed in the past years showed PTNP22 1858 C > T (rs2476601) polymorphism as associated with systemic lupus erythematosus susceptibility, although conflicting findings are still found. In this context, a powerful statistical study, such as meta-analysis, is necessary to establish a consensus. The aim of this study was to evaluate association studies between the PTPN22 1858 C > T polymorphism and SLE by a meta-analysis update, including three recently published studies in the last three years. A total of 3868 SLE patients and 7458 healthy individuals were considered herein, enclosing 19 studies from Asian, American, European and Latin ethnic groups. Odds ratio (OR) was performed for allelic, dominant and recessive genetic models. Statistically significant association was found between the PTPN22 1858 C > T polymorphism and susceptibility to SLE in all inheritance models. Allelic genetic model data (OR = 1.54, 95% confidence interval (CI) = 1.38-1.72, p value=.000) shows that T allele confers increased SLE susceptibility. As well as recessive genetic model (OR = 2.04, 95% CI = 1.09-3.82, p value = .030) for T/T genotype. Instead, dominant genetic model shows that C/C genotype confers lower susceptibility for SLE development (OR = 0.62, 95% CI = 0.54-0.72, p value = .000). In addition, we provided an ethnicity-derived meta-analysis. The results showed association in Caucasian (OR = 1.47, p value = .000) and Latin (OR = 2.41, p value = .000) ethnic groups. However, rs2476601 polymorphism is not associated nor in Asian (OR= 1.31; p value = .54) and African (OR = 2.04; p value=.22) populations. In conclusion, present meta-analysis update confirms that T allele and T/T genotype in PTPN22 1858 C > T polymorphism confers SLE susceptibility, particular in Caucasian and Latin groups, suggesting PTPN22 1858 C > T as a potential genetic marker in SLE susceptibility.

Overview of Genetically Engineered Mouse Models of Distinct Breast Cancer Subtypes.

PubMed

Usary, Jerry; Darr, David Brian; Pfefferle, Adam D; Perou, Charles M

2016-03-18

Advances in the screening of new therapeutic options have significantly reduced the breast cancer death rate over the last decade. Despite these advances, breast cancer remains the second leading cause of cancer death among women. This is due in part to the complexity of the disease, which is characterized by multiple subtypes that are driven by different genetic mechanisms and that likely arise from different cell types of origin. Because these differences often drive treatment options and outcomes, it is important to select relevant preclinical model systems to study new therapeutic interventions and tumor biology. Described in this unit are the characteristics and applications of validated genetically engineered mouse models (GEMMs) of basal-like, luminal, and claudin-low human subtypes of breast cancer. These different subtypes have different clinical outcomes and require different treatment strategies. These GEMMs can be considered faithful surrogates of their human disease counterparts. They represent alternative preclinical tumor models to cell line and patient-derived xenografts for preclinical drug discovery and tumor biology studies. Copyright © 2016 John Wiley & Sons, Inc.

Mouse Models for Investigating the Developmental Bases of Human Birth Defects

PubMed Central

MOON, ANNE M.

2006-01-01

Clinicians and basic scientists share an interest in discovering how genetic or environmental factors interact to perturb normal development and cause birth defects and human disease. Given the complexity of such interactions, it is not surprising that 4% of human infants are born with a congenital malformation, and cardiovascular defects occur in nearly 1%. Our research is based on the fundamental hypothesis that an understanding of normal and abnormal development will permit us to generate effective strategies for both prevention and treatment of human birth defects. Animal models are invaluable in these efforts because they allow one to interrogate the genetic, molecular and cellular events that distinguish normal from abnormal development. Several features of the mouse make it a particularly powerful experimental model: it is a mammalian system with similar embryology, anatomy and physiology to humans; genes, proteins and regulatory programs are largely conserved between human and mouse; and finally, gene targeting in murine embryonic stem cells has made the mouse genome amenable to sophisticated genetic manipulation currently unavailable in any other model organism. PMID:16641221

Petunia, Your Next Supermodel?

PubMed Central

Vandenbussche, Michiel; Chambrier, Pierre; Rodrigues Bento, Suzanne; Morel, Patrice

2016-01-01

Plant biology in general, and plant evo–devo in particular would strongly benefit from a broader range of available model systems. In recent years, technological advances have facilitated the analysis and comparison of individual gene functions in multiple species, representing now a fairly wide taxonomic range of the plant kingdom. Because genes are embedded in gene networks, studying evolution of gene function ultimately should be put in the context of studying the evolution of entire gene networks, since changes in the function of a single gene will normally go together with further changes in its network environment. For this reason, plant comparative biology/evo–devo will require the availability of a defined set of ‘super’ models occupying key taxonomic positions, in which performing gene functional analysis and testing genetic interactions ideally is as straightforward as, e.g., in Arabidopsis. Here we review why petunia has the potential to become one of these future supermodels, as a representative of the Asterid clade. We will first detail its intrinsic qualities as a model system. Next, we highlight how the revolution in sequencing technologies will now finally allows exploitation of the petunia system to its full potential, despite that petunia has already a long history as a model in plant molecular biology and genetics. We conclude with a series of arguments in favor of a more diversified multi-model approach in plant biology, and we point out where the petunia model system may further play a role, based on its biological features and molecular toolkit. PMID:26870078

Rediscovering the chick embryo as a model to study retinal development

PubMed Central

2012-01-01

The embryonic chick occupies a privileged place among animal models used in developmental studies. Its rapid development and accessibility for visualization and experimental manipulation are just some of the characteristics that have made it a vertebrate model of choice for more than two millennia. Until a few years ago, the inability to perform genetic manipulations constituted a major drawback of this system. However, the completion of the chicken genome project and the development of techniques to manipulate gene expression have allowed this classic animal model to enter the molecular age. Such techniques, combined with the embryological manipulations that this system is well known for, provide a unique toolkit to study the genetic basis of neural development. A major advantage of these approaches is that they permit targeted gene misexpression with extremely high spatiotemporal resolution and over a large range of developmental stages, allowing functional analysis at a level, speed and ease that is difficult to achieve in other systems. This article provides a general overview of the chick as a developmental model focusing more specifically on its application to the study of eye development. Special emphasis is given to the state of the art of the techniques that have made gene gain- and loss-of-function studies in this model a reality. In addition, we discuss some methodological considerations derived from our own experience that we believe will be beneficial to researchers working with this system. PMID:22738172

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.

Sensitivity Analysis of Genetic Algorithm Parameters for Optimal Groundwater Monitoring Network Design

NASA Astrophysics Data System (ADS)

Abdeh-Kolahchi, A.; Satish, M.; Datta, B.

2004-05-01

A state art groundwater monitoring network design is introduced. The method combines groundwater flow and transport results with optimization Genetic Algorithm (GA) to identify optimal monitoring well locations. Optimization theory uses different techniques to find a set of parameter values that minimize or maximize objective functions. The suggested groundwater optimal monitoring network design is based on the objective of maximizing the probability of tracking a transient contamination plume by determining sequential monitoring locations. The MODFLOW and MT3DMS models included as separate modules within the Groundwater Modeling System (GMS) are used to develop three dimensional groundwater flow and contamination transport simulation. The groundwater flow and contamination simulation results are introduced as input to the optimization model, using Genetic Algorithm (GA) to identify the groundwater optimal monitoring network design, based on several candidate monitoring locations. The groundwater monitoring network design model is used Genetic Algorithms with binary variables representing potential monitoring location. As the number of decision variables and constraints increase, the non-linearity of the objective function also increases which make difficulty to obtain optimal solutions. The genetic algorithm is an evolutionary global optimization technique, which is capable of finding the optimal solution for many complex problems. In this study, the GA approach capable of finding the global optimal solution to a groundwater monitoring network design problem involving 18.4X 1018 feasible solutions will be discussed. However, to ensure the efficiency of the solution process and global optimality of the solution obtained using GA, it is necessary that appropriate GA parameter values be specified. The sensitivity analysis of genetic algorithms parameters such as random number, crossover probability, mutation probability, and elitism are discussed for solution of monitoring network design.

The relative influence of habitat amount and configuration on genetic structure across multiple spatial scales

PubMed Central

Millette, Katie L; Keyghobadi, Nusha

2015-01-01

Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (FST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent. PMID:25628865

The relative influence of habitat amount and configuration on genetic structure across multiple spatial scales.

PubMed

Millette, Katie L; Keyghobadi, Nusha

2015-01-01

Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (F ST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent.

Gene Mutations and Genomic Rearrangements in the Mouse as a Result of Transposon Mobilization from Chromosomal Concatemers

PubMed Central

Geurts, Aron M; Collier, Lara S; Geurts, Jennifer L; Oseth, Leann L; Bell, Matthew L; Mu, David; Lucito, Robert; Godbout, Susan A; Green, Laura E; Lowe, Scott W; Hirsch, Betsy A; Leinwand, Leslie A; Largaespada, David A

2006-01-01

Previous studies of the Sleeping Beauty (SB) transposon system, as an insertional mutagen in the germline of mice, have used reverse genetic approaches. These studies have led to its proposed use for regional saturation mutagenesis by taking a forward-genetic approach. Thus, we used the SB system to mutate a region of mouse Chromosome 11 in a forward-genetic screen for recessive lethal and viable phenotypes. This work represents the first reported use of an insertional mutagen in a phenotype-driven approach. The phenotype-driven approach was successful in both recovering visible and behavioral mutants, including dominant limb and recessive behavioral phenotypes, and allowing for the rapid identification of candidate gene disruptions. In addition, a high frequency of recessive lethal mutations arose as a result of genomic rearrangements near the site of transposition, resulting from transposon mobilization. The results suggest that the SB system could be used in a forward-genetic approach to recover interesting phenotypes, but that local chromosomal rearrangements should be anticipated in conjunction with single-copy, local transposon insertions in chromosomes. Additionally, these mice may serve as a model for chromosome rearrangements caused by transposable elements during the evolution of vertebrate genomes. PMID:17009875

Attraction Basins as Gauges of Robustness against Boundary Conditions in Biological Complex Systems

PubMed Central

Demongeot, Jacques; Goles, Eric; Morvan, Michel; Noual, Mathilde; Sené, Sylvain

2010-01-01

One fundamental concept in the context of biological systems on which researches have flourished in the past decade is that of the apparent robustness of these systems, i.e., their ability to resist to perturbations or constraints induced by external or boundary elements such as electromagnetic fields acting on neural networks, micro-RNAs acting on genetic networks and even hormone flows acting both on neural and genetic networks. Recent studies have shown the importance of addressing the question of the environmental robustness of biological networks such as neural and genetic networks. In some cases, external regulatory elements can be given a relevant formal representation by assimilating them to or modeling them by boundary conditions. This article presents a generic mathematical approach to understand the influence of boundary elements on the dynamics of regulation networks, considering their attraction basins as gauges of their robustness. The application of this method on a real genetic regulation network will point out a mathematical explanation of a biological phenomenon which has only been observed experimentally until now, namely the necessity of the presence of gibberellin for the flower of the plant Arabidopsis thaliana to develop normally. PMID:20700525

Caenorhabditis elegans as a Model to Study the Molecular and Genetic Mechanisms of Drug Addiction.

PubMed

Engleman, Eric A; Katner, Simon N; Neal-Beliveau, Bethany S

2016-01-01

Drug addiction takes a massive toll on society. Novel animal models are needed to test new treatments and understand the basic mechanisms underlying addiction. Rodent models have identified the neurocircuitry involved in addictive behavior and indicate that rodents possess some of the same neurobiologic mechanisms that mediate addiction in humans. Recent studies indicate that addiction is mechanistically and phylogenetically ancient and many mechanisms that underlie human addiction are also present in invertebrates. The nematode Caenorhabditis elegans has conserved neurobiologic systems with powerful molecular and genetic tools and a rapid rate of development that enables cost-effective translational discovery. Emerging evidence suggests that C. elegans is an excellent model to identify molecular mechanisms that mediate drug-induced behavior and potential targets for medications development for various addictive compounds. C. elegans emit many behaviors that can be easily quantitated including some that involve interactions with the environment. Ethanol (EtOH) is the best-studied drug-of-abuse in C. elegans and at least 50 different genes/targets have been identified as mediating EtOH's effects and polymorphisms in some orthologs in humans are associated with alcohol use disorders. C. elegans has also been shown to display dopamine and cholinergic system-dependent attraction to nicotine and demonstrate preference for cues previously associated with nicotine. Cocaine and methamphetamine have been found to produce dopamine-dependent reward-like behaviors in C. elegans. These behavioral tests in combination with genetic/molecular manipulations have led to the identification of dozens of target genes/systems in C. elegans that mediate drug effects. The one target/gene identified as essential for drug-induced behavioral responses across all drugs of abuse was the cat-2 gene coding for tyrosine hydroxylase, which is consistent with the role of dopamine neurotransmission in human addiction. Overall, C. elegans can be used to model aspects of drug addiction and identify systems and molecular mechanisms that mediate drug effects. The findings are surprisingly consistent with analogous findings in higher-level organisms. Further, model refinement is warranted to improve model validity and increase utility for medications development. Copyright © 2016. Published by Elsevier Inc.

Genetic architecture of natural variation in Drosophila melanogaster aggressive behavior

PubMed Central

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

2015-01-01

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

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.

Systemic bacterial infection and immune defense phenotypes in Drosophila melanogaster.

PubMed

Khalil, Sarah; Jacobson, Eliana; Chambers, Moria C; Lazzaro, Brian P

2015-05-13

The fruit fly Drosophila melanogaster is one of the premier model organisms for studying the function and evolution of immune defense. Many aspects of innate immunity are conserved between insects and mammals, and since Drosophila can readily be genetically and experimentally manipulated, they are powerful for studying immune system function and the physiological consequences of disease. The procedure demonstrated here allows infection of flies by introduction of bacteria directly into the body cavity, bypassing epithelial barriers and more passive forms of defense and allowing focus on systemic infection. The procedure includes protocols for the measuring rates of host mortality, systemic pathogen load, and degree of induction of the host immune system. This infection procedure is inexpensive, robust and quantitatively repeatable, and can be used in studies of functional genetics, evolutionary life history, and physiology.

Data Sufficiency Assessment and Pumping Test Design for Groundwater Prediction Using Decision Theory and Genetic Algorithms

NASA Astrophysics Data System (ADS)

McPhee, J.; William, Y. W.

2005-12-01

This work presents a methodology for pumping test design based on the reliability requirements of a groundwater model. Reliability requirements take into consideration the application of the model results in groundwater management, expressed in this case as a multiobjective management model. The pumping test design is formulated as a mixed-integer nonlinear programming (MINLP) problem and solved using a combination of genetic algorithm (GA) and gradient-based optimization. Bayesian decision theory provides a formal framework for assessing the influence of parameter uncertainty over the reliability of the proposed pumping test. The proposed methodology is useful for selecting a robust design that will outperform all other candidate designs under most potential 'true' states of the system

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

A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities

PubMed Central

Vizeacoumar, Franco J; Arnold, Roland; Vizeacoumar, Frederick S; Chandrashekhar, Megha; Buzina, Alla; Young, Jordan T F; Kwan, Julian H M; Sayad, Azin; Mero, Patricia; Lawo, Steffen; Tanaka, Hiromasa; Brown, Kevin R; Baryshnikova, Anastasia; Mak, Anthony B; Fedyshyn, Yaroslav; Wang, Yadong; Brito, Glauber C; Kasimer, Dahlia; Makhnevych, Taras; Ketela, Troy; Datti, Alessandro; Babu, Mohan; Emili, Andrew; Pelletier, Laurence; Wrana, Jeff; Wainberg, Zev; Kim, Philip M; Rottapel, Robert; O'Brien, Catherine A; Andrews, Brenda; Boone, Charles; Moffat, Jason

2013-01-01

Improved efforts are necessary to define the functional product of cancer mutations currently being revealed through large-scale sequencing efforts. Using genome-scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co-culture competition assays to generate a high-confidence genetic interaction network of differentially essential or differential essentiality (DiE) genes. The network uncovered examples of conserved genetic interactions, densely connected functional modules derived from comparative genomics with model systems data, functions for uncharacterized genes in the human genome and targetable vulnerabilities. Finally, we demonstrate a general applicability of DiE gene signatures in determining genetic dependencies of other non-isogenic cancer cell lines. For example, the PTEN−/− DiE genes reveal a signature that can preferentially classify PTEN-dependent genotypes across a series of non-isogenic cell lines derived from the breast, pancreas and ovarian cancers. Our reference network suggests that many cancer vulnerabilities remain to be discovered through systematic derivation of a network of differentially essential genes in an isogenic cancer cell model. PMID:24104479

Genetic control of root growth: from genes to networks.

PubMed

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

2016-01-01

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

Determination of optimum allocation and pricing of distributed generation using genetic algorithm methodology

NASA Astrophysics Data System (ADS)

Mwakabuta, Ndaga Stanslaus

Electric power distribution systems play a significant role in providing continuous and "quality" electrical energy to different classes of customers. In the context of the present restrictions on transmission system expansions and the new paradigm of "open and shared" infrastructure, new approaches to distribution system analyses, economic and operational decision-making need investigation. This dissertation includes three layers of distribution system investigations. In the basic level, improved linear models are shown to offer significant advantages over previous models for advanced analysis. In the intermediate level, the improved model is applied to solve the traditional problem of operating cost minimization using capacitors and voltage regulators. In the advanced level, an artificial intelligence technique is applied to minimize cost under Distributed Generation injection from private vendors. Soft computing techniques are finding increasing applications in solving optimization problems in large and complex practical systems. The dissertation focuses on Genetic Algorithm for investigating the economic aspects of distributed generation penetration without compromising the operational security of the distribution system. The work presents a methodology for determining the optimal pricing of distributed generation that would help utilities make a decision on how to operate their system economically. This would enable modular and flexible investments that have real benefits to the electric distribution system. Improved reliability for both customers and the distribution system in general, reduced environmental impacts, increased efficiency of energy use, and reduced costs of energy services are some advantages.

A Mariner Transposon-Based Signature-Tagged Mutagenesis System for the Analysis of Oral Infection by Listeria monocytogenes

PubMed Central

Cummins, Joanne; Casey, Pat G.; Joyce, Susan A.; Gahan, Cormac G. M.

2013-01-01

Listeria monocytogenes is a Gram-positive foodborne pathogen and the causative agent of listerosis a disease that manifests predominately as meningitis in the non-pregnant individual or infection of the fetus and spontaneous abortion in pregnant women. Common-source outbreaks of foodborne listeriosis are associated with significant morbidity and mortality. However, relatively little is known concerning the mechanisms that govern infection via the oral route. In order to aid functional genetic analysis of the gastrointestinal phase of infection we designed a novel signature-tagged mutagenesis (STM) system based upon the invasive L. monocytogenes 4b serotype H7858 strain. To overcome the limitations of gastrointestinal infection by L. monocytogenes in the mouse model we created a H7858 strain that is genetically optimised for oral infection in mice. Furthermore our STM system was based upon a mariner transposon to favour numerous and random transposition events throughout the L. monocytogenes genome. Use of the STM bank to investigate oral infection by L. monocytogenes identified 21 insertion mutants that demonstrated significantly reduced potential for infection in our model. The sites of transposon insertion included lmOh7858_0671 (encoding an internalin homologous to Lmo0610), lmOh7858_0898 (encoding a putative surface-expressed LPXTG protein homologous to Lmo0842), lmOh7858_2579 (encoding the HupDGC hemin transport system) and lmOh7858_0399 (encoding a putative fructose specific phosphotransferase system). We propose that this represents an optimised STM system for functional genetic analysis of foodborne/oral infection by L. monocytogenes. PMID:24069416

MCF-10A-NeoST: A New Cell System for Studying Cell-ECM and Cell-Cell Interactions in Breast Cancer

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

Zantek, Nicole Dodge; Walker-Daniels, Jennifer; Stewart, Jane

2001-08-22

There is a continuing need for genetically matched cell systems to model cellular behaviors that are frequently observed in aggressive breast cancers. We report here the isolation and initial characterization of a spontaneously arising variant of MCF-10A cells, NeoST, which provides a new model to study cell adhesion and signal transduction in breast cancer. NeoST cells recapitulate important biological and biochemical features of metastatic breast cancer, including anchorage-independent growth, invasiveness in threedimensional reconstituted membranes, loss of E-cadherin expression, and increased tyrosine kinase activity. A comprehensive analysis of tyrosine kinase expression revealed overexpression or functional activation of the Axl, FAK, andmore » EphA2 tyrosine kinases in transformed MCF-10A cells. MCF-10A and these new derivatives provide a genetically matched model to study defects in cell adhesion and signaling that are relevant to cellular behaviors that often typify aggressive breast cancer cells.« less

Comparison of genetic algorithm and imperialist competitive algorithms in predicting bed load transport in clean pipe.

PubMed

Ebtehaj, Isa; Bonakdari, Hossein

2014-01-01

The existence of sediments in wastewater greatly affects the performance of the sewer and wastewater transmission systems. Increased sedimentation in wastewater collection systems causes problems such as reduced transmission capacity and early combined sewer overflow. The article reviews the performance of the genetic algorithm (GA) and imperialist competitive algorithm (ICA) in minimizing the target function (mean square error of observed and predicted Froude number). To study the impact of bed load transport parameters, using four non-dimensional groups, six different models have been presented. Moreover, the roulette wheel selection method is used to select the parents. The ICA with root mean square error (RMSE) = 0.007, mean absolute percentage error (MAPE) = 3.5% show better results than GA (RMSE = 0.007, MAPE = 5.6%) for the selected model. All six models return better results than the GA. Also, the results of these two algorithms were compared with multi-layer perceptron and existing equations.

Space Synthetic Biology Project

NASA Technical Reports Server (NTRS)

Howard, David; Roman, Monsi; Mansell, James (Matt)

2015-01-01

Synthetic biology is an effort to make genetic engineering more useful by standardizing sections of genetic code. By standardizing genetic components, biological engineering will become much more similar to traditional fields of engineering, in which well-defined components and subsystems are readily available in markets. Specifications of the behavior of those components and subsystems can be used to model a system which incorporates them. Then, the behavior of the novel system can be simulated and optimized. Finally, the components and subsystems can be purchased and assembled to create the optimized system, which most often will exhibit behavior similar to that indicated by the model. The Space Synthetic Biology project began in 2012 as a multi-Center effort. The purpose of this project was to harness Synthetic Biology principals to enable NASA's missions. A central target for application was to Environmental Control & Life Support (ECLS). Engineers from NASA Marshall Space Flight Center's (MSFC's) ECLS Systems Development Branch (ES62) were brought into the project to contribute expertise in operational ECLS systems. Project lead scientists chose to pursue the development of bioelectrochemical technologies to spacecraft life support. Therefore, the ECLS element of the project became essentially an effort to develop a bioelectrochemical ECLS subsystem. Bioelectrochemical systems exploit the ability of many microorganisms to drive their metabolisms by direct or indirect utilization of electrical potential gradients. Whereas many microorganisms are capable of deriving the energy required for the processes of interest (such as carbon dioxide (CO2) fixation) from sunlight, it is believed that subsystems utilizing electrotrophs will exhibit smaller mass, volume, and power requirements than those that derive their energy from sunlight. In the first 2 years of the project, MSFC personnel conducted modeling, simulation, and conceptual design efforts to assist the project in selecting the best approaches to the application of bioelectrochemical technologies to ECLS. Figure 1 shows results of simulation of charge transport in an experimental system. Figure 2 shows one of five conceptual designs for ECLS subsystems based on bioelectrochemical reactors. Also during the first 2 years, some work was undertaken to gather fundamental data (conductivities, overpotentials) relevant to the modeling efforts.

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.

Crozier's paradox revisited: maintenance of genetic recognition systems by disassortative mating.

PubMed

Holman, Luke; van Zweden, Jelle S; Linksvayer, Timothy A; d'Ettorre, Patrizia

2013-09-27

Organisms are predicted to behave more favourably towards relatives, and kin-biased cooperation has been found in all domains of life from bacteria to vertebrates. Cooperation based on genetic recognition cues is paradoxical because it disproportionately benefits individuals with common phenotypes, which should erode the required cue polymorphism. Theoretical models suggest that many recognition loci likely have some secondary function that is subject to diversifying selection, keeping them variable. Here, we use individual-based simulations to investigate the hypothesis that the dual use of recognition cues to facilitate social behaviour and disassortative mating (e.g. for inbreeding avoidance) can maintain cue diversity over evolutionary time. Our model shows that when organisms mate disassortatively with respect to their recognition cues, cooperation and recognition locus diversity can persist at high values, especially when outcrossed matings produce more surviving offspring. Mating system affects cue diversity via at least four distinct mechanisms, and its effects interact with other parameters such as population structure. Also, the attrition of cue diversity is less rapid when cooperation does not require an exact cue match. Using a literature review, we show that there is abundant empirical evidence that heritable recognition cues are simultaneously used in social and sexual behaviour. Our models show that mate choice is one possible resolution of the paradox of genetic kin recognition, and the literature review suggests that genetic recognition cues simultaneously inform assortative cooperation and disassortative mating in a large range of taxa. However, direct evidence is scant and there is substantial scope for future work.

Evolution of eumetazoan nervous systems: insights from cnidarians.

PubMed

Kelava, Iva; Rentzsch, Fabian; Technau, Ulrich

2015-12-19

Cnidarians, the sister group to bilaterians, have a simple diffuse nervous system. This morphological simplicity and their phylogenetic position make them a crucial group in the study of the evolution of the nervous system. The development of their nervous systems is of particular interest, as by uncovering the genetic programme that underlies it, and comparing it with the bilaterian developmental programme, it is possible to make assumptions about the genes and processes involved in the development of ancestral nervous systems. Recent advances in sequencing methods, genetic interference techniques and transgenic technology have enabled us to get a first glimpse into the molecular network underlying the development of a cnidarian nervous system-in particular the nervous system of the anthozoan Nematostella vectensis. It appears that much of the genetic network of the nervous system development is partly conserved between cnidarians and bilaterians, with Wnt and bone morphogenetic protein (BMP) signalling, and Sox genes playing a crucial part in the differentiation of neurons. However, cnidarians possess some specific characteristics, and further studies are necessary to elucidate the full regulatory network. The work on cnidarian neurogenesis further accentuates the need to study non-model organisms in order to gain insights into processes that shaped present-day lineages during the course of evolution. © 2015 The Authors.

Stakeholder perspectives on decision-analytic modeling frameworks to assess genetic services policy.

PubMed

Guzauskas, Gregory F; Garrison, Louis P; Stock, Jacquie; Au, Sylvia; Doyle, Debra Lochner; Veenstra, David L

2013-01-01

Genetic services policymakers and insurers often make coverage decisions in the absence of complete evidence of clinical utility and under budget constraints. We evaluated genetic services stakeholder opinions on the potential usefulness of decision-analytic modeling to inform coverage decisions, and asked them to identify genetic tests for decision-analytic modeling studies. We presented an overview of decision-analytic modeling to members of the Western States Genetic Services Collaborative Reimbursement Work Group and state Medicaid representatives and conducted directed content analysis and an anonymous survey to gauge their attitudes toward decision-analytic modeling. Participants also identified and prioritized genetic services for prospective decision-analytic evaluation. Participants expressed dissatisfaction with current processes for evaluating insurance coverage of genetic services. Some participants expressed uncertainty about their comprehension of decision-analytic modeling techniques. All stakeholders reported openness to using decision-analytic modeling for genetic services assessments. Participants were most interested in application of decision-analytic concepts to multiple-disorder testing platforms, such as next-generation sequencing and chromosomal microarray. Decision-analytic modeling approaches may provide a useful decision tool to genetic services stakeholders and Medicaid decision-makers.

Ames interactive molecular model building system - A 3-D computer modelling system applied to the study of the origin of life

NASA Technical Reports Server (NTRS)

Coeckelenbergh, Y.; Macelroy, R. D.; Rein, R.

1978-01-01

The investigation of specific interactions among biological molecules must take into consideration the stereochemistry of the structures. Thus, models of the molecules are essential for describing the spatial organization of potentially interacting groups, and estimations of conformation are required for a description of spatial organization. Both the function of visualizing molecules, and that of estimating conformation through calculations of energy, are part of the molecular modeling system described in the present paper. The potential uses of the system in investigating some aspects of the origin of life rest on the assumption that translation of conformation from genetic elements to catalytic elements would have been required for the development of the first replicating systems subject to the process of biological evolution.

Exploring Middle School Students' Understanding of Three Conceptual Models in Genetics

NASA Astrophysics Data System (ADS)

Bresler Freidenreich, Hava; Golan Duncan, Ravit; Shea, Nicole

2011-11-01

Genetics is the cornerstone of modern biology and a critical aspect of scientific literacy. Research has shown, however, that many high school graduates lack fundamental understandings in genetics necessary to make informed decisions about issues and emerging technologies in this domain, such as genetic screening, genetically modified foods, etc. Genetic literacy entails understanding three interrelated models: a genetic model that describes patterns of genetic inheritance, a meiotic model that describes the process by which genes are segregated into sex cells, and a molecular model that describes the mechanisms that link genotypes to phenotypes within an individual. Currently, much of genetics instruction, especially in terms of the molecular model, occurs at the high school level, and we know little about the ways in which middle school students can reason about these models. Furthermore, we do not know the extent to which carefully designed instruction can help younger students develop coherent and interrelated understandings in genetics. In this paper, we discuss a research study aimed at elucidating middle school students' abilities to reason about the three genetic models. As part of our research, we designed an eight-week inquiry unit that was implemented in a combined sixth- to eighth-grade science classroom. We describe our instructional design and report results based on an analysis of written assessments, clinical interviews, and artifacts of the unit. Our findings suggest that middle school students are able to successfully reason about all three genetic models.

A reverse engineering algorithm for neural networks, applied to the subthalamopallidal network of basal ganglia.

PubMed

Floares, Alexandru George

2008-01-01

Modeling neural networks with ordinary differential equations systems is a sensible approach, but also very difficult. This paper describes a new algorithm based on linear genetic programming which can be used to reverse engineer neural networks. The RODES algorithm automatically discovers the structure of the network, including neural connections, their signs and strengths, estimates its parameters, and can even be used to identify the biophysical mechanisms involved. The algorithm is tested on simulated time series data, generated using a realistic model of the subthalamopallidal network of basal ganglia. The resulting ODE system is highly accurate, and results are obtained in a matter of minutes. This is because the problem of reverse engineering a system of coupled differential equations is reduced to one of reverse engineering individual algebraic equations. The algorithm allows the incorporation of common domain knowledge to restrict the solution space. To our knowledge, this is the first time a realistic reverse engineering algorithm based on linear genetic programming has been applied to neural networks.

A stochastic conflict resolution model for trading pollutant discharge permits in river systems.

PubMed

Niksokhan, Mohammad Hossein; Kerachian, Reza; Amin, Pedram

2009-07-01

This paper presents an efficient methodology for developing pollutant discharge permit trading in river systems considering the conflict of interests of involving decision-makers and the stakeholders. In this methodology, a trade-off curve between objectives is developed using a powerful and recently developed multi-objective genetic algorithm technique known as the Nondominated Sorting Genetic Algorithm-II (NSGA-II). The best non-dominated solution on the trade-off curve is defined using the Young conflict resolution theory, which considers the utility functions of decision makers and stakeholders of the system. These utility functions are related to the total treatment cost and a fuzzy risk of violating the water quality standards. The fuzzy risk is evaluated using the Monte Carlo analysis. Finally, an optimization model provides the trading discharge permit policies. The practical utility of the proposed methodology in decision-making is illustrated through a realistic example of the Zarjub River in the northern part of Iran.

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.

Metabolic basis for the self-referential genetic code.

PubMed

Guimarães, Romeu Cardoso

2011-08-01

An investigation of the biosynthesis pathways producing glycine and serine was necessary to clarify an apparent inconsistency between the self-referential model (SRM) for the formation of the genetic code and the model of coevolution of encodings and of amino acid biosynthesis routes. According to the SRM proposal, glycine was the first amino acid encoded, followed by serine. The coevolution model does not state precisely which the first encodings were, only presenting a list of about ten early assignments including the derivation of glycine from serine-this being derived from the glycolysis intermediate glycerate, which reverses the order proposed by the self-referential model. Our search identified the glycine-serine pathway of syntheses based on one-carbon sources, involving activities of the glycine decarboxylase complex and its associated serine hydroxymethyltransferase, which is consistent with the order proposed by the self-referential model and supports its rationale for the origin of the genetic code: protein synthesis was developed inside an early metabolic system, serving the function of a sink of amino acids; the first peptides were glycine-rich and fit for the function of building the early ribonucleoproteins; glycine consumption in proteins drove the fixation of the glycine-serine pathway.

Uniqueness of polymorphism for a discrete, selection-migration model with genetic dominance

Treesearch

James F. Selgrade; James H. Roberds

2009-01-01

The migration into a natural population of a controlled population, e.g., a transgenic population, is studied using a one island selection-migration model. A 2-dimensional system of nonlinear difference equations describes changes in allele frequency and population size between generations. Biologically reasonable conditions are obtained which guarantee the existence...

The State of the Art of the Zebrafish Model for Toxicology and Toxicologic Pathology Research—Advantages and Current Limitations

PubMed Central

Spitsbergen, Jan M.; Kent, Michael L.

2007-01-01

The zebrafish (Danio rerio) is now the pre-eminent vertebrate model system for clarification of the roles of specific genes and signaling pathways in development. The zebrafish genome will be completely sequenced within the next 1–2 years. Together with the substantial historical database regarding basic developmental biology, toxicology, and gene transfer, the rich foundation of molecular genetic and genomic data makes zebrafish a powerful model system for clarifying mechanisms in toxicity. In contrast to the highly advanced knowledge base on molecular developmental genetics in zebrafish, our database regarding infectious and noninfectious diseases and pathologic lesions in zebrafish lags far behind the information available on most other domestic mammalian and avian species, particularly rodents. Currently, minimal data are available regarding spontaneous neoplasm rates or spontaneous aging lesions in any of the commonly used wild-type or mutant lines of zebrafish. Therefore, to fully utilize the potential of zebrafish as an animal model for understanding human development, disease, and toxicology we must greatly advance our knowledge on zebrafish diseases and pathology. PMID:12597434

Brain trauma and autophagy: What flies and mice can teach us about conserved responses.

PubMed

Ratliff, Eric P; Barekat, Ayeh; Lipinski, Marta M; Finley, Kim D

2016-11-01

Drosophila models have been successfully used to identify many genetic components that affect neurodegenerative disorders. Recently, there has been a growing interest in identifying innate and environmental factors that influence the individual outcomes following traumatic brain injury (TBI). This includes both severe TBI and more subtle, mild TBI (mTBI), which is common in people playing contact sports. Autophagy, as a clearance pathway, exerts protective effects in multiple neurological disease models. In a recent publication, we highlighted the development of a novel repetitive mTBI system using Drosophila, which recapitulates several phenotypes associated with trauma in mammalian models. In particular, flies subjected to mTBI exhibit an acute impairment of the macroautophagy/autophagy pathway that is restored 1 wk following traumatic injury exposure. These phenotypes closely resemble temporary autophagy defects observed in a mouse TBI model. Through these studies, we also identified methods to directly assess autophagic responses in the fly nervous system and laid the groundwork for future studies designed to identify genetic, epigenetic and environmental factors that have an impact on TBI outcomes.

USSR Space Life Sciences Digest, issue 20

NASA Technical Reports Server (NTRS)

Hooke, Lydia Razran (Editor); Donaldson, P. Lynn (Editor); Teeter, Ronald (Editor); Garshnek, Victoria (Editor); Rowe, Joseph (Editor)

1988-01-01

Abstracts of research in the areas of biological rhythms, body fluids, botany, endrocrinology, enzymology, exobiology, genetics, human performance, immunology, life support systems, mathematical modeling, and numerous other topics related to space and life sciences are given.

Neuro-genetic system for optimization of GMI samples sensitivity.

PubMed

Pitta Botelho, A C O; Vellasco, M M B R; Hall Barbosa, C R; Costa Silva, E

2016-03-01

Magnetic sensors are largely used in several engineering areas. Among them, magnetic sensors based on the Giant Magnetoimpedance (GMI) effect are a new family of magnetic sensing devices that have a huge potential for applications involving measurements of ultra-weak magnetic fields. The sensitivity of magnetometers is directly associated with the sensitivity of their sensing elements. The GMI effect is characterized by a large variation of the impedance (magnitude and phase) of a ferromagnetic sample, when subjected to a magnetic field. Recent studies have shown that phase-based GMI magnetometers have the potential to increase the sensitivity by about 100 times. The sensitivity of GMI samples depends on several parameters, such as sample length, external magnetic field, DC level and frequency of the excitation current. However, this dependency is yet to be sufficiently well-modeled in quantitative terms. So, the search for the set of parameters that optimizes the samples sensitivity is usually empirical and very time consuming. This paper deals with this problem by proposing a new neuro-genetic system aimed at maximizing the impedance phase sensitivity of GMI samples. A Multi-Layer Perceptron (MLP) Neural Network is used to model the impedance phase and a Genetic Algorithm uses the information provided by the neural network to determine which set of parameters maximizes the impedance phase sensitivity. The results obtained with a data set composed of four different GMI sample lengths demonstrate that the neuro-genetic system is able to correctly and automatically determine the set of conditioning parameters responsible for maximizing their phase sensitivities. Copyright © 2015 Elsevier Ltd. All rights reserved.

Biological indicators of illness risk in offspring of bipolar parents: targeting the hypothalamic-pituitary-adrenal axis and immune system.

PubMed

Duffy, Anne; Lewitzka, Ute; Doucette, Sarah; Andreazza, Ana; Grof, Paul

2012-05-01

The study aims to provide a selective review of the literature pertaining to the hypothalamic-pituitary-adrenal (HPA) axis and immune abnormalities as informative biological indicators of vulnerability in bipolar disorder (BD). We summarize key findings relating to HPA axis and immunological abnormalities in bipolar patients and their high-risk offspring. Findings derive from a review of selected original papers published in the literature, and supplemented by papers identified through bibliography review. Neurobiological findings are discussed in the context of emergent BD in those at genetic risk and synthesized into a neurodevelopmental model of illness onset and progression. BD is associated with a number of genetic and possibly epigenetic abnormalities associated with neurotransmitter, hormonal and immunologically mediated neurobiological pathways. Data from clinical and high-risk studies implicate HPA axis and immune system abnormalities, which may represent inherited vulnerabilities important for the transition to illness onset. Post-mortem and clinical studies implicate intracellular signal transduction processes and disturbance in energy metabolism associated with established BD. Specifically, long-standing maladaptive alterations such as changes in neuronal systems may be mediated through changes in intracellular signalling pathways, oxidative stress, cellular energy metabolism and apoptosis associated with substantial burden of illness. Prospective longitudinal studies of endophenotypes and biomarkers such as HPA axis and immune abnormalities in high-risk offspring will be helpful to understand genetically mediated biological pathways associated with illness onset and progression. A clinical staging model describing emergent illness in those at genetic risk should facilitate this line of investigation. © 2011 Blackwell Publishing Asia Pty Ltd.

How Well Do Molecular and Pedigree Relatedness Correspond, in Populations with Diverse Mating Systems, and Various Types and Quantities of Molecular and Demographic Data?

PubMed

Kopps, Anna M; Kang, Jungkoo; Sherwin, William B; Palsbøll, Per J

2015-06-30

Kinship analyses are important pillars of ecological and conservation genetic studies with potentially far-reaching implications. There is a need for power analyses that address a range of possible relationships. Nevertheless, such analyses are rarely applied, and studies that use genetic-data-based-kinship inference often ignore the influence of intrinsic population characteristics. We investigated 11 questions regarding the correct classification rate of dyads to relatedness categories (relatedness category assignments; RCA) using an individual-based model with realistic life history parameters. We investigated the effects of the number of genetic markers; marker type (microsatellite, single nucleotide polymorphism SNP, or both); minor allele frequency; typing error; mating system; and the number of overlapping generations under different demographic conditions. We found that (i) an increasing number of genetic markers increased the correct classification rate of the RCA so that up to >80% first cousins can be correctly assigned; (ii) the minimum number of genetic markers required for assignments with 80 and 95% correct classifications differed between relatedness categories, mating systems, and the number of overlapping generations; (iii) the correct classification rate was improved by adding additional relatedness categories and age and mitochondrial DNA data; and (iv) a combination of microsatellite and single-nucleotide polymorphism data increased the correct classification rate if <800 SNP loci were available. This study shows how intrinsic population characteristics, such as mating system and the number of overlapping generations, life history traits, and genetic marker characteristics, can influence the correct classification rate of an RCA study. Therefore, species-specific power analyses are essential for empirical studies. Copyright © 2015 Kopps et al.

Generation of genetically modified mice using CRISPR/Cas9 and haploid embryonic stem cell systems

PubMed Central

JIN, Li-Fang; LI, Jin-Song

2016-01-01

With the development of high-throughput sequencing technology in the post-genomic era, researchers have concentrated their efforts on elucidating the relationships between genes and their corresponding functions. Recently, important progress has been achieved in the generation of genetically modified mice based on CRISPR/Cas9 and haploid embryonic stem cell (haESC) approaches, which provide new platforms for gene function analysis, human disease modeling, and gene therapy. Here, we review the CRISPR/Cas9 and haESC technology for the generation of genetically modified mice and discuss the key challenges in the application of these approaches. PMID:27469251

Supervised chaos genetic algorithm based state of charge determination for LiFePO4 batteries in electric vehicles

NASA Astrophysics Data System (ADS)

Shen, Yanqing

2018-04-01

LiFePO4 battery is developed rapidly in electric vehicle, whose safety and functional capabilities are influenced greatly by the evaluation of available cell capacity. Added with adaptive switch mechanism, this paper advances a supervised chaos genetic algorithm based state of charge determination method, where a combined state space model is employed to simulate battery dynamics. The method is validated by the experiment data collected from battery test system. Results indicate that the supervised chaos genetic algorithm based state of charge determination method shows great performance with less computation complexity and is little influenced by the unknown initial cell state.

Series Hybrid Electric Vehicle Power System Optimization Based on Genetic Algorithm

NASA Astrophysics Data System (ADS)

Zhu, Tianjun; Li, Bin; Zong, Changfu; Wu, Yang

2017-09-01

Hybrid electric vehicles (HEV), compared with conventional vehicles, have complex structures and more component parameters. If variables optimization designs are carried on all these parameters, it will increase the difficulty and the convergence of algorithm program, so this paper chooses the parameters which has a major influence on the vehicle fuel consumption to make it all work at maximum efficiency. First, HEV powertrain components modelling are built. Second, taking a tandem hybrid structure as an example, genetic algorithm is used in this paper to optimize fuel consumption and emissions. Simulation results in ADVISOR verify the feasibility of the proposed genetic optimization algorithm.

Genetic and epigenetic control of gene expression by CRISPR–Cas systems

PubMed Central

Lo, Albert; Qi, Lei

2017-01-01

The discovery and adaption of bacterial clustered regularly interspaced short palindromic repeats (CRISPR)–CRISPR-associated (Cas) systems has revolutionized the way researchers edit genomes. Engineering of catalytically inactivated Cas variants (nuclease-deficient or nuclease-deactivated [dCas]) combined with transcriptional repressors, activators, or epigenetic modifiers enable sequence-specific regulation of gene expression and chromatin state. These CRISPR–Cas-based technologies have contributed to the rapid development of disease models and functional genomics screening approaches, which can facilitate genetic target identification and drug discovery. In this short review, we will cover recent advances of CRISPR–dCas9 systems and their use for transcriptional repression and activation, epigenome editing, and engineered synthetic circuits for complex control of the mammalian genome. PMID:28649363

Genetic Ancestry, Serum Interferon-α Activity, and Autoantibodies in Systemic Lupus Erythematosus

PubMed Central

Ko, Kichul; Franek, Beverly S.; Marion, Miranda; Kaufman, Kenneth M.; Langefeld, Carl D.; Harley, John B.; Niewold, Timothy B.

2012-01-01

Objective To investigate and refine the relationships among systemic lupus erythematosus (SLE) and related autoantibodies, interferon-α (IFN-α), and various ancestral backgrounds. Methods We investigated quantitatively defined genetic ancestry through principal component analysis in place of self-reported ancestry. Results African ancestry was found to be associated with presence of anti-RNP antibody (p = 0.0026), and anti-RNP was correlated with high levels of IFN-α (p = 2.8 × 10−5). Conclusion Our data support a model in which African ancestry increases the likelihood of SLE-associated autoantibody formation, which subsequently results in higher levels of serum IFN-α. PMID:22505704

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.

Clustered Regularly Interspaced Short Palindromic Repeats/Cas9 Genetic Engineering: Robotic Genetic Surgery.

PubMed

Deshpande, Kaivalya; Vyas, Arpita; Balakrishnan, Archana; Vyas, Dinesh

2015-12-01

As a novel technology that utilizes the endogenous immune defense system in bacteria, CRISPR/Cas9 has transcended DNA engineering into a more pragmatic and clinically efficacious field. Using programmable sgRNA sequences and nucleases, the system effectively introduces double strand breaks in target genes within an entire organism. The applications of CRISPR range from biomedicine to drug development and epigenetic modification. Studies have demonstrated CRISPR mediated targeting of various tumorigenic genes and effector proteins known to be involved in colon carcinomas. This technology significantly expands the scope of gene manipulation and allows for an enhanced modeling of colon cancers, as well as various other malignancies.

Computerized decision support system for mass identification in breast using digital mammogram: a study on GA-based neuro-fuzzy approaches.

PubMed

Das, Arpita; Bhattacharya, Mahua

2011-01-01

In the present work, authors have developed a treatment planning system implementing genetic based neuro-fuzzy approaches for accurate analysis of shape and margin of tumor masses appearing in breast using digital mammogram. It is obvious that a complicated structure invites the problem of over learning and misclassification. In proposed methodology, genetic algorithm (GA) has been used for searching of effective input feature vectors combined with adaptive neuro-fuzzy model for final classification of different boundaries of tumor masses. The study involves 200 digitized mammograms from MIAS and other databases and has shown 86% correct classification rate.