Assembling networks of microbial genomes using linear programming.

PubMed

Holloway, Catherine; Beiko, Robert G

2010-11-20

Microbial genomes exhibit complex sets of genetic affinities due to lateral genetic transfer. Assessing the relative contributions of parent-to-offspring inheritance and gene sharing is a vital step in understanding the evolutionary origins and modern-day function of an organism, but recovering and showing these relationships is a challenging problem. We have developed a new approach that uses linear programming to find between-genome relationships, by treating tables of genetic affinities (here, represented by transformed BLAST e-values) as an optimization problem. Validation trials on simulated data demonstrate the effectiveness of the approach in recovering and representing vertical and lateral relationships among genomes. Application of the technique to a set comprising Aquifex aeolicus and 75 other thermophiles showed an important role for large genomes as 'hubs' in the gene sharing network, and suggested that genes are preferentially shared between organisms with similar optimal growth temperatures. We were also able to discover distinct and common genetic contributors to each sequenced representative of genus Pseudomonas. The linear programming approach we have developed can serve as an effective inference tool in its own right, and can be an efficient first step in a more-intensive phylogenomic analysis.

Genetic programming applied to RFI mitigation in radio astronomy

NASA Astrophysics Data System (ADS)

Staats, K.

2016-12-01

Genetic Programming is a type of machine learning that employs a stochastic search of a solutions space, genetic operators, a fitness function, and multiple generations of evolved programs to resolve a user-defined task, such as the classification of data. At the time of this research, the application of machine learning to radio astronomy was relatively new, with a limited number of publications on the subject. Genetic Programming had never been applied, and as such, was a novel approach to this challenging arena. Foundational to this body of research, the application Karoo GP was developed in the programming language Python following the fundamentals of tree-based Genetic Programming described in "A Field Guide to Genetic Programming" by Poli, et al. Karoo GP was tasked with the classification of data points as signal or radio frequency interference (RFI) generated by instruments and machinery which makes challenging astronomers' ability to discern the desired targets. The training data was derived from the output of an observation run of the KAT-7 radio telescope array built by the South African Square Kilometre Array (SKA-SA). Karoo GP, kNN, and SVM were comparatively employed, the outcome of which provided noteworthy correlations between input parameters, the complexity of the evolved hypotheses, and performance of raw data versus engineered features. This dissertation includes description of novel approaches to GP, such as upper and lower limits to the size of syntax trees, an auto-scaling multiclass classifier, and a Numpy array element manager. In addition to the research conducted at the SKA-SA, it is described how Karoo GP was applied to fine-tuning parameters of a weather prediction model at the South African Astronomical Observatory (SAAO), to glitch classification at the Laser Interferometer Gravitational-wave Observatory (LIGO), and to astro-particle physics at The Ohio State University.

Genetic Parallel Programming: design and implementation.

PubMed

Cheang, Sin Man; Leung, Kwong Sak; Lee, Kin Hong

2006-01-01

This paper presents a novel Genetic Parallel Programming (GPP) paradigm for evolving parallel programs running on a Multi-Arithmetic-Logic-Unit (Multi-ALU) Processor (MAP). The MAP is a Multiple Instruction-streams, Multiple Data-streams (MIMD), general-purpose register machine that can be implemented on modern Very Large-Scale Integrated Circuits (VLSIs) in order to evaluate genetic programs at high speed. For human programmers, writing parallel programs is more difficult than writing sequential programs. However, experimental results show that GPP evolves parallel programs with less computational effort than that of their sequential counterparts. It creates a new approach to evolving a feasible problem solution in parallel program form and then serializes it into a sequential program if required. The effectiveness and efficiency of GPP are investigated using a suite of 14 well-studied benchmark problems. Experimental results show that GPP speeds up evolution substantially.

Learning polynomial feedforward neural networks by genetic programming and backpropagation.

PubMed

Nikolaev, N Y; Iba, H

2003-01-01

This paper presents an approach to learning polynomial feedforward neural networks (PFNNs). The approach suggests, first, finding the polynomial network structure by means of a population-based search technique relying on the genetic programming paradigm, and second, further adjustment of the best discovered network weights by an especially derived backpropagation algorithm for higher order networks with polynomial activation functions. These two stages of the PFNN learning process enable us to identify networks with good training as well as generalization performance. Empirical results show that this approach finds PFNN which outperform considerably some previous constructive polynomial network algorithms on processing benchmark time series.

Management intensity and genetics affect loblolly pine seedling performance

Treesearch

Scott D. Roberts; Randall J. Rousseau; B. Landis Herrin

2012-01-01

Capturing potential genetic gains from tree improvement programs requires selection of the appropriate genetic stock and application of appropriate silvicultural management techniques. Limited information is available on how specific loblolly pine varietal genotypes perform under differing growing environments and management approaches. This study was established in...

An Approach to Self-Assembling Swarm Robots Using Multitree Genetic Programming

PubMed Central

An, Jinung

2013-01-01

In recent days, self-assembling swarm robots have been studied by a number of researchers due to their advantages such as high efficiency, stability, and scalability. However, there are still critical issues in applying them to practical problems in the real world. The main objective of this study is to develop a novel self-assembling swarm robot algorithm that overcomes the limitations of existing approaches. To this end, multitree genetic programming is newly designed to efficiently discover a set of patterns necessary to carry out the mission of the self-assembling swarm robots. The obtained patterns are then incorporated into their corresponding robot modules. The computational experiments prove the effectiveness of the proposed approach. PMID:23861655

An approach to self-assembling swarm robots using multitree genetic programming.

PubMed

Lee, Jong-Hyun; Ahn, Chang Wook; An, Jinung

2013-01-01

In recent days, self-assembling swarm robots have been studied by a number of researchers due to their advantages such as high efficiency, stability, and scalability. However, there are still critical issues in applying them to practical problems in the real world. The main objective of this study is to develop a novel self-assembling swarm robot algorithm that overcomes the limitations of existing approaches. To this end, multitree genetic programming is newly designed to efficiently discover a set of patterns necessary to carry out the mission of the self-assembling swarm robots. The obtained patterns are then incorporated into their corresponding robot modules. The computational experiments prove the effectiveness of the proposed approach.

Understanding the potential of state-based public health genomics programs to mitigate disparities in access to clinical genetic services.

PubMed

Senier, Laura; Tan, Catherine; Smollin, Leandra; Lee, Rachael

2018-06-12

State health agencies (SHAs) have developed public health genomics (PHG) programs that play an instrumental role in advancing precision public health, but there is limited research on their approaches. This study examines how PHG programs attempt to mitigate or forestall health disparities and inequities in the utilization of genomic medicine. We compared PHG programs in three states: Connecticut, Michigan, and Utah. We analyzed 85 in-depth interviews with SHA internal and external collaborators and program documents. We employed a qualitative coding process to capture themes relating to health disparities and inequities. Each SHA implemented population-level approaches to identify individuals who carry genetic variants that increase risk of hereditary cancers. However, each SHA developed a unique strategy-which we label public health action repertoires-to reach specific subgroups who faced barriers in accessing genetic services. These strategies varied across states given demographics of the state population, state-level partnerships, and availability of healthcare services. Our findings illustrate the imperative of tailoring PHG programs to local demographic characteristics and existing community resources. Furthermore, our study highlights how integrating genomics into precision public health will require multilevel, multisector collaboration to optimize efficacy and equity.

Algorithmic Trading with Developmental and Linear Genetic Programming

NASA Astrophysics Data System (ADS)

Wilson, Garnett; Banzhaf, Wolfgang

A developmental co-evolutionary genetic programming approach (PAM DGP) and a standard linear genetic programming (LGP) stock trading systemare applied to a number of stocks across market sectors. Both GP techniques were found to be robust to market fluctuations and reactive to opportunities associated with stock price rise and fall, with PAMDGP generating notably greater profit in some stock trend scenarios. Both algorithms were very accurate at buying to achieve profit and selling to protect assets, while exhibiting bothmoderate trading activity and the ability to maximize or minimize investment as appropriate. The content of the trading rules produced by both algorithms are also examined in relation to stock price trend scenarios.

A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules.

PubMed

Nguyen, Su; Mei, Yi; Xue, Bing; Zhang, Mengjie

2018-06-04

Designing effective dispatching rules for production systems is a difficult and timeconsuming task if it is done manually. In the last decade, the growth of computing power, advanced machine learning, and optimisation techniques has made the automated design of dispatching rules possible and automatically discovered rules are competitive or outperform existing rules developed by researchers. Genetic programming is one of the most popular approaches to discovering dispatching rules in the literature, especially for complex production systems. However, the large heuristic search space may restrict genetic programming from finding near optimal dispatching rules. This paper develops a new hybrid genetic programming algorithm for dynamic job shop scheduling based on a new representation, a new local search heuristic, and efficient fitness evaluators. Experiments show that the new method is effective regarding the quality of evolved rules. Moreover, evolved rules are also significantly smaller and contain more relevant attributes.

A novel recruitment message to increase enrollment into a smoking cessation treatment program: preliminary results from a randomized trial.

PubMed

Schnoll, Robert A; Cappella, Joseph; Lerman, Caryn; Pinto, Angela; Patterson, Freda; Wileyto, E Paul; Bigman, Cabral; Leone, Frank

2011-12-01

Most smokers do not utilize approved interventions for nicotine dependence, reducing the probability of cessation. Smoking cessation programs typically use recruitment messages emphasizing the health threats of smoking. Augmenting this threat message by describing the genetic aspects of nicotine addiction may enhance enrollment into a cessation program. During telephone recruitment, 125 treatment-seeking smokers were randomized to receive by phone either a standard threat message or a threat plus genetic prime message and were offered open-label varenicline and counseling. There was a greater rate of enrollment into the cessation program for the threat plus genetic prime participants (51.7%) versus the threat-only participants (37.7%; p = .03). Smokers who self-identified from racial/ethnic minority groups were less likely to enroll in the cessation program (p = .01) versus smokers who self-identified as Caucasian. These preliminary data suggest that a simple, affordable, and transportable communication approach enhances enrollment of smokers into a smoking cessation program. A larger clinical trial to evaluate a genetic prime message for improving recruitment into smoking cessation programs is warranted.

Genetic Algorithm Approaches for Actuator Placement

NASA Technical Reports Server (NTRS)

Crossley, William A.

2000-01-01

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

Developmental and Genetic Aspects of Clefting Disorders: A Clinical Approach

PubMed Central

Hanson, James W.; Thomson, Elizabeth J.; Muilrnnuth, Snn V.; Sandra, Alexander; Coan, Joan M.; Lipcamon, Larry D.; Hill, Ed

1990-01-01

This demonstration shows an interactive videodisc program that teaches the basic embryology of craniofacial development, the developmental and genetic aspects of orofacial clefts, and the process of diagnosing a patient with a clefting disorder. This program is designed for medical students, residents, and fellows in Pediatrics and Otolaryngology. It will also be of interest to members of cleft lip/palate teams. Imagesp1020-ap1021-ap1021-bp1021-c

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.

Role-playing is an effective instructional strategy for genetic counseling training: an investigation and comparative study.

PubMed

Xu, Xiao-Feng; Wang, Yan; Wang, Yan-Yan; Song, Ming; Xiao, Wen-Gang; Bai, Yun

2016-09-02

Genetic diseases represent a significant public health challenge in China that will need to be addressed by a correspondingly large number of professional genetic counselors. However, neither an official training program for genetic counseling, nor formal board certification, was available in China before 2015. In 2009, a genetic counseling training program based on role-playing was implemented as a pilot study at the Third Military Medical University to train third-year medical students. Questionnaires on participant attitudes to the program and role-playing were randomly administered to 324 students after they had finished their training. Pre- and post-training instructional tests, focusing on 42 key components of genetic counseling, were administered randomly to 200 participants to assess mastery of each component. Finally, scores in final examinations of 578 participants from 2009 to 2011 were compared to scores obtained by 614 non-participating students from 2006 to 2008 to further assess program efficacy. Both the training program and the instructional strategy of role-playing were accepted by most participants. Students believed that role-playing improved their practice of genetic counseling and medical genetics, enhanced their communication skills, and would likely contribute to future professional performance. The average understanding of 40 of the key points in genetic counseling was significantly improved, and most students approached excellent levels of mastery. Scores in final examinations and the percentages of students scoring above 90 were also significantly elevated. Role-playing is a feasible and effective instructional strategy for training genetic counselors in China as well as in other developing countries.

Surrogate-Assisted Genetic Programming With Simplified Models for Automated Design of Dispatching Rules.

PubMed

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

2017-09-01

Automated design of dispatching rules for production systems has been an interesting research topic over the last several years. Machine learning, especially genetic programming (GP), has been a powerful approach to dealing with this design problem. However, intensive computational requirements, accuracy and interpretability are still its limitations. This paper aims at developing a new surrogate assisted GP to help improving the quality of the evolved rules without significant computational costs. The experiments have verified the effectiveness and efficiency of the proposed algorithms as compared to those in the literature. Furthermore, new simplification and visualisation approaches have also been developed to improve the interpretability of the evolved rules. These approaches have shown great potentials and proved to be a critical part of the automated design system.

Persian walnut breeding in California

Treesearch

Charles A. Leslie; Gale H. McGranahan

2004-01-01

For over 50 years the University of California Davis Walnut Breeding Program has worked to address the needs of California walnut growers by identifying genetic approaches to problems and developing improved cultivars. The breeding program is a cooperative endeavor that draws on the efforts and resources of university researchers and facilities, USDA germplasm programs...

A holistic approach to genetic conservation of Pinus strobiformis

Treesearch

K.M. Waring; R. Sniezko; B.A. Goodrich; C. Wehenkel; J.J. Jacobs

2017-01-01

Pinus strobiformis (southwestern white pine) is threatened by both a rapidly changing climate and the tree disease white pine blister rust, caused by an introduced fungal pathogen, Cronartium ribicola. We began a proactive program in ~2009 to sustain P. strobiformis that includes genetic conservation, research, and management strategies. Research...

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.

Performance comparison of genetic algorithms and particle swarm optimization for model integer programming bus timetabling problem

NASA Astrophysics Data System (ADS)

Wihartiko, F. D.; Wijayanti, H.; Virgantari, F.

2018-03-01

Genetic Algorithm (GA) is a common algorithm used to solve optimization problems with artificial intelligence approach. Similarly, the Particle Swarm Optimization (PSO) algorithm. Both algorithms have different advantages and disadvantages when applied to the case of optimization of the Model Integer Programming for Bus Timetabling Problem (MIPBTP), where in the case of MIPBTP will be found the optimal number of trips confronted with various constraints. The comparison results show that the PSO algorithm is superior in terms of complexity, accuracy, iteration and program simplicity in finding the optimal solution.

The use of genetic programming to develop a predictor of swash excursion on sandy beaches

NASA Astrophysics Data System (ADS)

Passarella, Marinella; Goldstein, Evan B.; De Muro, Sandro; Coco, Giovanni

2018-02-01

We use genetic programming (GP), a type of machine learning (ML) approach, to predict the total and infragravity swash excursion using previously published data sets that have been used extensively in swash prediction studies. Three previously published works with a range of new conditions are added to this data set to extend the range of measured swash conditions. Using this newly compiled data set we demonstrate that a ML approach can reduce the prediction errors compared to well-established parameterizations and therefore it may improve coastal hazards assessment (e.g. coastal inundation). Predictors obtained using GP can also be physically sound and replicate the functionality and dependencies of previous published formulas. Overall, we show that ML techniques are capable of both improving predictability (compared to classical regression approaches) and providing physical insight into coastal processes.

Integrating Genetic Studies of Nicotine Addiction into Public Health Practice: Stakeholder Views on Challenges, Barriers and Opportunities

PubMed Central

Dingel, M.J.; Hicks, A.D.; Robinson, M.E.; Koenig, B.A.

2011-01-01

Objective: Will emerging genetic research strengthen tobacco control programs? In this empirical study, we interview stakeholders in tobacco control to illuminate debates about the role of genomics in public health. Methods: The authors performed open-ended interviews with 86 stakeholders from 5 areas of tobacco control: basic scientists, clinicians, tobacco prevention specialists, health payers, and pharmaceutical industry employees. Interviews were qualitatively analyzed using standard techniques. Results: The central tension is between the hope that an expanding genomic knowledge base will improve prevention and smoking cessation therapies and the fear that genetic research might siphon resources away from traditional and proven public health programs. While showing strong support for traditional public health approaches to tobacco control, stakeholders recognize weaknesses, specifically the difficulty of countering the powerful voice of the tobacco industry when mounting public campaigns and the problem of individuals who are resistant to treatment and continue smoking. Conclusions: In order for genetic research to be effectively translated into efforts to minimize the harm of smoking-related disease, the views of key stakeholders must be voiced and disagreements reconciled. Effective translation requires honest evaluation of both the strengths and limitations of genetic approaches. PMID:21757875

Computer Simulation Is an Undervalued Tool for Genetic Analysis: A Historical View and Presentation of SHIMSHON – A Web-Based Genetic Simulation Package

PubMed Central

Greenberg, David A.

2011-01-01

Computer simulation methods are under-used tools in genetic analysis because simulation approaches have been portrayed as inferior to analytic methods. Even when simulation is used, its advantages are not fully exploited. Here, I present SHIMSHON, our package of genetic simulation programs that have been developed, tested, used for research, and used to generated data for Genetic Analysis Workshops (GAW). These simulation programs, now web-accessible, can be used by anyone to answer questions about designing and analyzing genetic disease studies for locus identification. This work has three foci: (1) the historical context of SHIMSHON's development, suggesting why simulation has not been more widely used so far. (2) Advantages of simulation: computer simulation helps us to understand how genetic analysis methods work. It has advantages for understanding disease inheritance and methods for gene searches. Furthermore, simulation methods can be used to answer fundamental questions that either cannot be answered by analytical approaches or cannot even be defined until the problems are identified and studied, using simulation. (3) I argue that, because simulation was not accepted, there was a failure to grasp the meaning of some simulation-based studies of linkage. This may have contributed to perceived weaknesses in linkage analysis; weaknesses that did not, in fact, exist. PMID:22189467

Automatic programming via iterated local search for dynamic job shop scheduling.

PubMed

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

2015-01-01

Dispatching rules have been commonly used in practice for making sequencing and scheduling decisions. Due to specific characteristics of each manufacturing system, there is no universal dispatching rule that can dominate in all situations. Therefore, it is important to design specialized dispatching rules to enhance the scheduling performance for each manufacturing environment. Evolutionary computation approaches such as tree-based genetic programming (TGP) and gene expression programming (GEP) have been proposed to facilitate the design task through automatic design of dispatching rules. However, these methods are still limited by their high computational cost and low exploitation ability. To overcome this problem, we develop a new approach to automatic programming via iterated local search (APRILS) for dynamic job shop scheduling. The key idea of APRILS is to perform multiple local searches started with programs modified from the best obtained programs so far. The experiments show that APRILS outperforms TGP and GEP in most simulation scenarios in terms of effectiveness and efficiency. The analysis also shows that programs generated by APRILS are more compact than those obtained by genetic programming. An investigation of the behavior of APRILS suggests that the good performance of APRILS comes from the balance between exploration and exploitation in its search mechanism.

DEVELOPMENT OF A MULTI-TIERED INSECT RESISTANCE MANAGEMENT PROGRAM FOR GENETICALLY MODIFIED CORN HYBRIDS EXPRESSING THE PLANT INCORPORATED PROTECTANT, BACILLUS THURINGIENSIS

EPA Science Inventory

A significant increase in genetically modified corn planting driven by biofuel demand is expected for the 2007 growing season with future planted acreages approaching 80% of total corn plantings anticipated by 2009. As demand increases, incidence of farmer non-compliance with ma...

Genetic shifting: a novel approach for controlling vector-borne diseases.

PubMed

Powell, Jeffrey R; Tabachnick, Walter J

2014-06-01

Rendering populations of vectors of diseases incapable of transmitting pathogens through genetic methods has long been a goal of vector geneticists. We outline a method to achieve this goal that does not involve the introduction of any new genetic variants to the target population. Rather we propose that shifting the frequencies of naturally occurring alleles that confer refractoriness to transmission can reduce transmission below a sustainable level. The program employs methods successfully used in plant and animal breeding. Because no artificially constructed genetically modified organisms (GMOs) are introduced into the environment, the method is minimally controversial. We use Aedes aegypti and dengue virus (DENV) for illustrative purposes but point out that the proposed program is generally applicable to vector-borne disease control. Copyright © 2014 Elsevier Ltd. All rights reserved.

A comparison of machine learning techniques for survival prediction in breast cancer

PubMed Central

2011-01-01

Background The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established 70-gene signature. Results We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection. Conclusions Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data. PMID:21569330

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases.

PubMed

Heidema, A Geert; Boer, Jolanda M A; Nagelkerke, Nico; Mariman, Edwin C M; van der A, Daphne L; Feskens, Edith J M

2006-04-21

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association studies using the case-control design, the application of a combination of several methods, including the set association approach, MDR and the random forests approach, will likely be a useful strategy to find the important genes and interaction patterns involved in complex diseases.

Electrochemical impedance spectroscopy of supercapacitors: A novel analysis approach using evolutionary programming

NASA Astrophysics Data System (ADS)

Oz, Alon; Hershkovitz, Shany; Tsur, Yoed

2014-11-01

In this contribution we present a novel approach to analyze impedance spectroscopy measurements of supercapacitors. Transforming the impedance data into frequency-dependent capacitance allows us to use Impedance Spectroscopy Genetic Programming (ISGP) in order to find the distribution function of relaxation times (DFRT) of the processes taking place in the tested device. Synthetic data was generated in order to demonstrate this technique and a model for supercapacitor ageing process has been obtained.

Applying molecular genetic tools to the conservation and action plan for the critically endangered Far Eastern leopard (Panthera pardus orientalis).

PubMed

Uphyrkina, Olga; O'Brien, Stephen J

2003-08-01

A role for molecular genetic approaches in conservation of endangered taxa is now commonly recognized. Because conservation genetic analyses provide essential insights on taxonomic status, recent evolutionary history and current health of endangered taxa, they are considered in nearly all conservation programs. Genetic analyses of the critically endangered Far Eastern, or Amur leopard, Panthera pardus orientalis, have been done recently to address all of these questions and develop strategies for survival of the leopard in the wild. The genetic status and implication for conservation management of the Far Eastern leopard subspecies are discussed.

Genetic Network Programming with Reconstructed Individuals

NASA Astrophysics Data System (ADS)

Ye, Fengming; Mabu, Shingo; Wang, Lutao; Eto, Shinji; Hirasawa, Kotaro

A lot of research on evolutionary computation has been done and some significant classical methods such as Genetic Algorithm (GA), Genetic Programming (GP), Evolutionary Programming (EP), and Evolution Strategies (ES) have been studied. Recently, a new approach named Genetic Network Programming (GNP) has been proposed. GNP can evolve itself and find the optimal solution. It is based on the idea of Genetic Algorithm and uses the data structure of directed graphs. Many papers have demonstrated that GNP can deal with complex problems in the dynamic environments very efficiently and effectively. As a result, recently, GNP is getting more and more attentions and is used in many different areas such as data mining, extracting trading rules of stock markets, elevator supervised control systems, etc., and GNP has obtained some outstanding results. Focusing on the GNP's distinguished expression ability of the graph structure, this paper proposes a method named Genetic Network Programming with Reconstructed Individuals (GNP-RI). The aim of GNP-RI is to balance the exploitation and exploration of GNP, that is, to strengthen the exploitation ability by using the exploited information extensively during the evolution process of GNP and finally obtain better performances than that of GNP. In the proposed method, the worse individuals are reconstructed and enhanced by the elite information before undergoing genetic operations (mutation and crossover). The enhancement of worse individuals mimics the maturing phenomenon in nature, where bad individuals can become smarter after receiving a good education. In this paper, GNP-RI is applied to the tile-world problem which is an excellent bench mark for evaluating the proposed architecture. The performance of GNP-RI is compared with that of the conventional GNP. The simulation results show some advantages of GNP-RI demonstrating its superiority over the conventional GNPs.

Implementation of inpatient models of pharmacogenetics programs

PubMed Central

Cavallari, Larisa H.; Lee, Craig R.; Duarte, Julio D.; Nutescu, Edith A.; Weitzel, Kristin W.; Stouffer, George A.; Johnson, Julie A.

2017-01-01

Purpose The operational elements essential for establishing an inpatient pharmacogenetic service are reviewed, and the role of the pharmacist in the provision of genotype-guided drug therapy in pharmacogenetics programs at three institutions is highlighted. Summary Pharmacists are well positioned to assume important roles in facilitating the clinical use of genetic information to optimize drug therapy given their expertise in clinical pharmacology and therapeutics. Pharmacists have assumed important roles in implementing inpatient pharmacogenetics programs. This includes programs designed to incorporate genetic test results to optimize antiplatelet drug selection after percutaneous coronary intervention and personalize warfarin dosing. Pharmacist involvement occurs on many levels, including championing and leading pharmacogenetics implementation efforts, establishing clinical processes to support genotype-guided therapy, assisting the clinical staff with interpreting genetic test results and applying them to prescribing decisions, and educating other healthcare providers and patients on genomic medicine. The three inpatient pharmacogenetics programs described use reactive versus preemptive genotyping, the most feasible approach under the current third-party payment structure. All three sites also follow Clinical Pharmacogenetics Implementation Consortium guidelines for drug therapy recommendations based on genetic test results. Conclusion With the clinical emergence of pharmacogenetics into the inpatient setting, it is important that pharmacists caring for hospitalized patients are well prepared to serve as experts in interpreting and applying genetic test results to guide drug therapy decisions. Since genetic test results may not be available until after patient discharge, pharmacists practicing in the ambulatory care setting should also be prepared to assist with genotype-guided drug therapy as part of transitions in care. PMID:27864202

Implementation of inpatient models of pharmacogenetics programs.

PubMed

Cavallari, Larisa H; Lee, Craig R; Duarte, Julio D; Nutescu, Edith A; Weitzel, Kristin W; Stouffer, George A; Johnson, Julie A

2016-12-01

The operational elements essential for establishing an inpatient pharmacogenetic service are reviewed, and the role of the pharmacist in the provision of genotype-guided drug therapy in pharmacogenetics programs at three institutions is highlighted. Pharmacists are well positioned to assume important roles in facilitating the clinical use of genetic information to optimize drug therapy given their expertise in clinical pharmacology and therapeutics. Pharmacists have assumed important roles in implementing inpatient pharmacogenetics programs. This includes programs designed to incorporate genetic test results to optimize antiplatelet drug selection after percutaneous coronary intervention and personalize warfarin dosing. Pharmacist involvement occurs on many levels, including championing and leading pharmacogenetics implementation efforts, establishing clinical processes to support genotype-guided therapy, assisting the clinical staff with interpreting genetic test results and applying them to prescribing decisions, and educating other healthcare providers and patients on genomic medicine. The three inpatient pharmacogenetics programs described use reactive versus preemptive genotyping, the most feasible approach under the current third-party payment structure. All three sites also follow Clinical Pharmacogenetics Implementation Consortium guidelines for drug therapy recommendations based on genetic test results. With the clinical emergence of pharmacogenetics into the inpatient setting, it is important that pharmacists caring for hospitalized patients are well prepared to serve as experts in interpreting and applying genetic test results to guide drug therapy decisions. Since genetic test results may not be available until after patient discharge, pharmacists practicing in the ambulatory care setting should also be prepared to assist with genotype-guided drug therapy as part of transitions in care. Copyright © 2016 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Reflections on the Anopheles gambiae genome sequence, transgenic mosquitoes and the prospect for controlling malaria and other vector borne diseases.

PubMed

Tabachnick, Walter J

2003-09-01

The completion of the Anopheles gambiae Giles genome sequencing project is a milestone toward developing more effective strategies in reducing the impact of malaria and other vector borne diseases. The successes in developing transgenic approaches using mosquitoes have provided another essential new tool for further progress in basic vector genetics and the goal of disease control. The use of transgenic approaches to develop refractory mosquitoes is also possible. The ability to use genome sequence to identify genes, and transgenic approaches to construct refractory mosquitoes, has provided the opportunity that with the future development of an appropriate genetic drive system, refractory transgenes can be released into vector populations leading to nontransmitting mosquitoes. An. gambiae populations incapable of transmitting malaria. This compelling strategy will be very difficult to achieve and will require a broad substantial research program for success. The fundamental information that is required on genome structure, gene function and environmental effects on genetic expression are largely unknown. The ability to predict gene effects on phenotype is rudimentary, particularly in natural populations. As a result, the release of a refractory transgene into natural mosquito populations is imprecise and there is little ability to predict unintended consequences. The new genetic tools at hand provide opportunities to address an array of important issues, many of which can have immediate impact on the effectiveness of a host of strategies to control vector borne disease. Transgenic release approaches represent only one strategy that should be pursued. A balanced research program is required.

Marine biosurfaces research program

NASA Astrophysics Data System (ADS)

The Office of Naval Research (ONR) of the U.S. Navy is starting a basic research program to address the initial events that control colonization of surfaces by organisms in marine environments. The program “arises from the Navy's need to understand and ultimately control biofouling and biocorrosion in marine environments,” according to a Navy announcement.The program, “Biological Processes Controlling Surface Modification in the Marine Environment,” will emphasize the application of in situ techniques and modern molecular biological, biochemical, and biophysical approaches; it will also encourage the development of interdisciplinary projects. Specific areas of interest include sensing and response to environmental surface (physiology/physical chemistry), factors controlling movement to and retention at surfaces (behavior/hydrodynamics), genetic regulation of attachment (molecular genetics), and mechanisms of attachment (biochemistry/surface chemistry).

Application of GA package in functional packaging

NASA Astrophysics Data System (ADS)

Belousova, D. A.; Noskova, E. E.; Kapulin, D. V.

2018-05-01

The approach to application program for the task of configuration of the elements of the commutation circuit for design of the radio-electronic equipment on the basis of the genetic algorithm is offered. The efficiency of the used approach for commutation circuits with different characteristics for computer-aided design on radio-electronic manufacturing is shown. The prototype of the computer-aided design subsystem on the basis of a package GA for R with a set of the general functions for optimization of multivariate models is programmed.

Landscape genetics of the nonnative red fox of California.

PubMed

Sacks, Benjamin N; Brazeal, Jennifer L; Lewis, Jeffrey C

2016-07-01

Invasive mammalian carnivores contribute disproportionately to declines in global biodiversity. In California, nonnative red foxes (Vulpes vulpes) have significantly impacted endangered ground-nesting birds and native canids. These foxes derive primarily from captive-reared animals associated with the fur-farming industry. Over the past five decades, the cumulative area occupied by nonnative red fox increased to cover much of central and southern California. We used a landscape-genetic approach involving mitochondrial DNA (mtDNA) sequences and 13 microsatellites of 402 nonnative red foxes removed in predator control programs to investigate source populations, contemporary connectivity, and metapopulation dynamics. Both markers indicated high population structuring consistent with origins from multiple introductions and low subsequent gene flow. Landscape-genetic modeling indicated that population connectivity was especially low among coastal sampling sites surrounded by mountainous wildlands but somewhat higher through topographically flat, urban and agricultural landscapes. The genetic composition of populations tended to be stable for multiple generations, indicating a degree of demographic resilience to predator removal programs. However, in two sites where intensive predator control reduced fox abundance, we observed increases in immigration, suggesting potential for recolonization to counter eradication attempts. These findings, along with continued genetic monitoring, can help guide localized management of foxes by identifying points of introductions and routes of spread and evaluating the relative importance of reproduction and immigration in maintaining populations. More generally, the study illustrates the utility of a landscape-genetic approach for understanding invasion dynamics and metapopulation structure of one of the world's most destructive invasive mammals, the red fox.

Methods for identifying SNP interactions: a review on variations of Logic Regression, Random Forest and Bayesian logistic regression.

PubMed

Chen, Carla Chia-Ming; Schwender, Holger; Keith, Jonathan; Nunkesser, Robin; Mengersen, Kerrie; Macrossan, Paula

2011-01-01

Due to advancements in computational ability, enhanced technology and a reduction in the price of genotyping, more data are being generated for understanding genetic associations with diseases and disorders. However, with the availability of large data sets comes the inherent challenges of new methods of statistical analysis and modeling. Considering a complex phenotype may be the effect of a combination of multiple loci, various statistical methods have been developed for identifying genetic epistasis effects. Among these methods, logic regression (LR) is an intriguing approach incorporating tree-like structures. Various methods have built on the original LR to improve different aspects of the model. In this study, we review four variations of LR, namely Logic Feature Selection, Monte Carlo Logic Regression, Genetic Programming for Association Studies, and Modified Logic Regression-Gene Expression Programming, and investigate the performance of each method using simulated and real genotype data. We contrast these with another tree-like approach, namely Random Forests, and a Bayesian logistic regression with stochastic search variable selection.

Contrasting results from molecular and pedigree-based population diversity measures in captive zebra highlight challenges facing genetic management of zoo populations.

PubMed

Ito, Hideyuki; Ogden, Rob; Langenhorst, Tanya; Inoue-Murayama, Miho

2017-01-01

Zoo conservation breeding programs manage the retention of population genetic diversity through analysis of pedigree records. The range of demographic and genetic indices determined through pedigree analysis programs allows the conservation of diversity to be monitored relative to the particular founder population for a species. Such approaches are based on a number of well-documented founder assumptions, however without knowledge of actual molecular genetic diversity there is a risk that pedigree-based measures will be misinterpreted and population genetic diversity misunderstood. We examined the genetic diversity of the captive populations of Grevy's zebra, Hartmann's mountain zebra and plains zebra in Japan and the United Kingdom through analysis of mitochondrial DNA sequences. Very low nucleotide variability was observed in Grevy's zebra. The results were evaluated with respect to current and historic diversity in the wild, and indicate that low genetic diversity in the captive population is likely a result of low founder diversity, which in turn suggests relatively low wild genetic diversity prior to recent population declines. Comparison of molecular genetic diversity measures with analogous diversity indices generated from the studbook data for Grevy's zebra and Hartmann's mountain zebra show contrasting patterns, with Grevy's zebra displaying markedly less molecular diversity than mountain zebra, despite studbook analysis indicating that the Grevy's zebra population has substantially more founders, greater effective population size, lower mean kinship, and has suffered less loss of gene diversity. These findings emphasize the need to validate theoretical estimates of genetic diversity in captive breeding programs with empirical molecular genetic data. Zoo Biol. 36:87-94, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Spatial genetic analyses reveal cryptic population structure and migration patterns in a continuously harvested grey wolf (Canis lupus) population in north-eastern Europe.

PubMed

Hindrikson, Maris; Remm, Jaanus; Männil, Peep; Ozolins, Janis; Tammeleht, Egle; Saarma, Urmas

2013-01-01

Spatial genetics is a relatively new field in wildlife and conservation biology that is becoming an essential tool for unravelling the complexities of animal population processes, and for designing effective strategies for conservation and management. Conceptual and methodological developments in this field are therefore critical. Here we present two novel methodological approaches that further the analytical possibilities of STRUCTURE and DResD. Using these approaches we analyse structure and migrations in a grey wolf (Canislupus) population in north-eastern Europe. We genotyped 16 microsatellite loci in 166 individuals sampled from the wolf population in Estonia and Latvia that has been under strong and continuous hunting pressure for decades. Our analysis demonstrated that this relatively small wolf population is represented by four genetic groups. We also used a novel methodological approach that uses linear interpolation to statistically test the spatial separation of genetic groups. The new method, which is capable of using program STRUCTURE output, can be applied widely in population genetics to reveal both core areas and areas of low significance for genetic groups. We also used a recently developed spatially explicit individual-based method DResD, and applied it for the first time to microsatellite data, revealing a migration corridor and barriers, and several contact zones.

A tailored approach to BRAF and MLH1 methylation testing in a universal screening program for Lynch syndrome.

PubMed

Adar, Tomer; Rodgers, Linda H; Shannon, Kristen M; Yoshida, Makoto; Ma, Tianle; Mattia, Anthony; Lauwers, Gregory Y; Iafrate, Anthony J; Chung, Daniel C

2017-03-01

To determine the correlation between BRAF genotype and MLH1 promoter methylation in a screening program for Lynch syndrome (LS), a universal screening program for LS was established in two medical centers. Tumors with abnormal MLH1 staining were evaluated for both BRAF V600E genotype and MLH1 promoter methylation. Tumors positive for both were considered sporadic, and genetic testing was recommended for all others. A total 1011 colorectal cancer cases were screened for Lynch syndrome, and 148 (14.6%) exhibited absent MLH1 immunostaining. Both BRAF and MLH1 methylation testing were completed in 126 cases. Concordant results (both positive or both negative) were obtained in 86 (68.3%) and 16 (12.7%) cases, respectively, with 81% concordance overall. The positive and negative predictive values for a BRAF mutation in predicting MLH1 promoter methylation were 98.9% and 41%, respectively, and the negative predictive value fell to 15% in patients ≥70 years old. Using BRAF genotyping as a sole test to evaluate cases with absent MLH1 staining would have increased referral rates for genetic testing by 2.3-fold compared with MLH1 methylation testing alone (31% vs 13.5%, respectively, P<0.01). However, a hybrid approach that reserves MLH1 methylation testing for BRAF wild-type cases only would significantly decrease the number of methylation assays performed and reduce the referral rate for genetic testing to 12.7%. A BRAF mutation has an excellent positive predictive value but poor negative predictive value in predicting MLH1 promoter methylation. A hybrid use of these tests may reduce the number of low-risk patients referred to genetic counseling and facilitate wider implementation of Lynch syndrome screening programs.

LIGO detector characterization with genetic programming

NASA Astrophysics Data System (ADS)

Cavaglia, Marco; Staats, Kai; Errico, Luciano; Mogushi, Kentaro; Gabbard, Hunter

2017-01-01

Genetic Programming (GP) is a supervised approach to Machine Learning. GP has for two decades been applied to a diversity of problems, from predictive and financial modelling to data mining, from code repair to optical character recognition and product design. GP uses a stochastic search, tournament, and fitness function to explore a solution space. GP evolves a population of individual programs, through multiple generations, following the principals of biological evolution (mutation and reproduction) to discover a model that best fits or categorizes features in a given data set. We apply GP to categorization of LIGO noise and show that it can effectively be used to characterize the detector non-astrophysical noise both in low latency and offline searches. National Science Foundation award PHY-1404139.

Linkage and Association Mapping for Two Major Traits Used in the Maritime Pine Breeding Program: Height Growth and Stem Straightness

PubMed Central

Bink, Marco CAM; van Heerwaarden, Joost; Chancerel, Emilie; Boury, Christophe; Lesur, Isabelle; Isik, Fikret; Bouffier, Laurent; Plomion, Christophe

2016-01-01

Background Increasing our understanding of the genetic architecture of complex traits, through analyses of genotype-phenotype associations and of the genes/polymorphisms accounting for trait variation, is crucial, to improve the integration of molecular markers into forest tree breeding. In this study, two full-sib families and one breeding population of maritime pine were used to identify quantitative trait loci (QTLs) for height growth and stem straightness, through linkage analysis (LA) and linkage disequilibrium (LD) mapping approaches. Results The populations used for LA consisted of two unrelated three-generation full-sib families (n = 197 and n = 477). These populations were assessed for height growth or stem straightness and genotyped for 248 and 217 markers, respectively. The population used for LD mapping consisted of 661 founders of the first and second generations of the breeding program. This population was phenotyped for the same traits and genotyped for 2,498 single-nucleotide polymorphism (SNP) markers corresponding to 1,652 gene loci. The gene-based reference genetic map of maritime pine was used to localize and compare the QTLs detected by the two approaches, for both traits. LA identified three QTLs for stem straightness and two QTLs for height growth. The LD study yielded seven significant associations (P ≤ 0.001): four for stem straightness and three for height growth. No colocalisation was found between QTLs identified by LA and SNPs detected by LD mapping for the same trait. Conclusions This study provides the first comparison of LA and LD mapping approaches in maritime pine, highlighting the complementary nature of these two approaches for deciphering the genetic architecture of two mandatory traits of the breeding program. PMID:27806077

Linkage and Association Mapping for Two Major Traits Used in the Maritime Pine Breeding Program: Height Growth and Stem Straightness.

PubMed

Bartholomé, Jérôme; Bink, Marco Cam; van Heerwaarden, Joost; Chancerel, Emilie; Boury, Christophe; Lesur, Isabelle; Isik, Fikret; Bouffier, Laurent; Plomion, Christophe

2016-01-01

Increasing our understanding of the genetic architecture of complex traits, through analyses of genotype-phenotype associations and of the genes/polymorphisms accounting for trait variation, is crucial, to improve the integration of molecular markers into forest tree breeding. In this study, two full-sib families and one breeding population of maritime pine were used to identify quantitative trait loci (QTLs) for height growth and stem straightness, through linkage analysis (LA) and linkage disequilibrium (LD) mapping approaches. The populations used for LA consisted of two unrelated three-generation full-sib families (n = 197 and n = 477). These populations were assessed for height growth or stem straightness and genotyped for 248 and 217 markers, respectively. The population used for LD mapping consisted of 661 founders of the first and second generations of the breeding program. This population was phenotyped for the same traits and genotyped for 2,498 single-nucleotide polymorphism (SNP) markers corresponding to 1,652 gene loci. The gene-based reference genetic map of maritime pine was used to localize and compare the QTLs detected by the two approaches, for both traits. LA identified three QTLs for stem straightness and two QTLs for height growth. The LD study yielded seven significant associations (P ≤ 0.001): four for stem straightness and three for height growth. No colocalisation was found between QTLs identified by LA and SNPs detected by LD mapping for the same trait. This study provides the first comparison of LA and LD mapping approaches in maritime pine, highlighting the complementary nature of these two approaches for deciphering the genetic architecture of two mandatory traits of the breeding program.

The digital language of amino acids.

PubMed

Kurić, L

2007-11-01

The subject of this paper is a digital approach to the investigation of the biochemical basis of genetic processes. The digital mechanism of nucleic acid and protein bio-syntheses, the evolution of biomacromolecules and, especially, the biochemical evolution of genetic language have been analyzed by the application of cybernetic methods, information theory and system theory, respectively. This paper reports the discovery of new methods for developing the new technologies in genetics. It is about the most advanced digital technology which is based on program, cybernetics and informational systems and laws. The results in the practical application of the new technology could be useful in bioinformatics, genetics, biochemistry, medicine and other natural sciences.

A Study of Penalty Function Methods for Constraint Handling with Genetic Algorithm

NASA Technical Reports Server (NTRS)

Ortiz, Francisco

2004-01-01

COMETBOARDS (Comparative Evaluation Testbed of Optimization and Analysis Routines for Design of Structures) is a design optimization test bed that can evaluate the performance of several different optimization algorithms. A few of these optimization algorithms are the sequence of unconstrained minimization techniques (SUMT), sequential linear programming (SLP) and the sequential quadratic programming techniques (SQP). A genetic algorithm (GA) is a search technique that is based on the principles of natural selection or "survival of the fittest". Instead of using gradient information, the GA uses the objective function directly in the search. The GA searches the solution space by maintaining a population of potential solutions. Then, using evolving operations such as recombination, mutation and selection, the GA creates successive generations of solutions that will evolve and take on the positive characteristics of their parents and thus gradually approach optimal or near-optimal solutions. By using the objective function directly in the search, genetic algorithms can be effectively applied in non-convex, highly nonlinear, complex problems. The genetic algorithm is not guaranteed to find the global optimum, but it is less likely to get trapped at a local optimum than traditional gradient-based search methods when the objective function is not smooth and generally well behaved. The purpose of this research is to assist in the integration of genetic algorithm (GA) into COMETBOARDS. COMETBOARDS cast the design of structures as a constrained nonlinear optimization problem. One method used to solve constrained optimization problem with a GA to convert the constrained optimization problem into an unconstrained optimization problem by developing a penalty function that penalizes infeasible solutions. There have been several suggested penalty function in the literature each with there own strengths and weaknesses. A statistical analysis of some suggested penalty functions is performed in this study. Also, a response surface approach to robust design is used to develop a new penalty function approach. This new penalty function approach is then compared with the other existing penalty functions.

Genetics and genomics of disease resistance in salmonid species

PubMed Central

Yáñez, José M.; Houston, Ross D.; Newman, Scott

2014-01-01

Infectious and parasitic diseases generate large economic losses in salmon farming. A feasible and sustainable alternative to prevent disease outbreaks may be represented by genetic improvement for disease resistance. To include disease resistance into the breeding goal, prior knowledge of the levels of genetic variation for these traits is required. Furthermore, the information from the genetic architecture and molecular factors involved in resistance against diseases may be used to accelerate the genetic progress for these traits. In this regard, marker assisted selection and genomic selection are approaches which incorporate molecular information to increase the accuracy when predicting the genetic merit of selection candidates. In this article we review and discuss key aspects related to disease resistance in salmonid species, from both a genetic and genomic perspective, with emphasis in the applicability of disease resistance traits into breeding programs in salmonids. PMID:25505486

Hybrid Nested Partitions and Math Programming Framework for Large-scale Combinatorial Optimization

DTIC Science & Technology

2010-03-31

optimization problems: 1) exact algorithms and 2) metaheuristic algorithms . This project will integrate concepts from these two technologies to develop...optimal solutions within an acceptable amount of computation time, and 2) metaheuristic algorithms such as genetic algorithms , tabu search, and the...integer programming decomposition approaches, such as Dantzig Wolfe decomposition and Lagrangian relaxation, and metaheuristics such as the Nested

Genetically programmed superparamagnetic behavior of mammalian cells.

PubMed

Kim, Taeuk; Moore, David; Fussenegger, Martin

2012-12-31

Although magnetic fields and paramagnetic inorganic materials were abundant on planet earth during the entire evolution of living species the interaction of organisms with these physical forces remains a little-understood phenomenon. Interestingly, rather than being genetically encoded, organisms seem to accumulate and take advantage of inorganic nanoparticles to sense or react to magnetic fields. Using a synthetic biology-inspired approach we have genetically programmed mammalian cells to show superparamagnetic behavior. The combination of ectopic production of the human ferritin heavy chain 1 (hFTH1), engineering the cells for expression of an iron importer, the divalent metal ion transferase 1 (DMT1) and the design of an iron-loading culture medium to maximize cellular iron uptake enabled efficient iron mineralization in intracellular ferritin particles and conferred superparamagnetic behavior to the entire cell. When captured by a magnetic field the superparamagnetic cells reached attraction velocities of up to 30 μm/s and could be efficiently separated from complex cell mixtures using standard magnetic cell separation equipment. Technology that enables magnetic separation of genetically programmed superparamagnetic cells in the absence of inorganic particles could foster novel opportunities in diagnostics and cell-based therapies. Copyright © 2012 Elsevier B.V. All rights reserved.

The statistical analysis of multi-environment data: modeling genotype-by-environment interaction and its genetic basis

PubMed Central

Malosetti, Marcos; Ribaut, Jean-Marcel; van Eeuwijk, Fred A.

2013-01-01

Genotype-by-environment interaction (GEI) is an important phenomenon in plant breeding. This paper presents a series of models for describing, exploring, understanding, and predicting GEI. All models depart from a two-way table of genotype by environment means. First, a series of descriptive and explorative models/approaches are presented: Finlay–Wilkinson model, AMMI model, GGE biplot. All of these approaches have in common that they merely try to group genotypes and environments and do not use other information than the two-way table of means. Next, factorial regression is introduced as an approach to explicitly introduce genotypic and environmental covariates for describing and explaining GEI. Finally, QTL modeling is presented as a natural extension of factorial regression, where marker information is translated into genetic predictors. Tests for regression coefficients corresponding to these genetic predictors are tests for main effect QTL expression and QTL by environment interaction (QEI). QTL models for which QEI depends on environmental covariables form an interesting model class for predicting GEI for new genotypes and new environments. For realistic modeling of genotypic differences across multiple environments, sophisticated mixed models are necessary to allow for heterogeneity of genetic variances and correlations across environments. The use and interpretation of all models is illustrated by an example data set from the CIMMYT maize breeding program, containing environments differing in drought and nitrogen stress. To help readers to carry out the statistical analyses, GenStat® programs, 15th Edition and Discovery® version, are presented as “Appendix.” PMID:23487515

Experience of Preimplantation Genetic Diagnosis for Hemophilia at the University Hospital Virgen Del Rocío in Spain: Technical and Clinical Overview

PubMed Central

Fernández, Raquel M.; Peciña, Ana; Sánchez, Beatriz; Lozano-Arana, Maria Dolores; García-Lozano, Juan Carlos; Pérez-Garrido, Rosario; Núñez, Ramiro; Antiñolo, Guillermo

2015-01-01

Hemophilia A and B are the most common hereditary hemorrhagic disorders, with an X-linked mode of inheritance. Reproductive options for the families affected with hemophilia, aiming at the prevention of the birth of children with severe coagulation disorders, include preimplantation genetic diagnosis (PGD). Here we present the results of our PGD Program applied to hemophilia, at the Department of Genetics, Reproduction and Fetal Medicine of the University Hospital Virgen del Rocío in Seville. A total of 34 couples have been included in our program since 2005 (30 for hemophilia A and 4 for hemophilia B). Overall, 60 cycles were performed, providing a total of 508 embryos. The overall percentage of transfers per cycle was 81.7% and the live birth rate per cycle ranged from 10.3 to 24.1% depending on the methodological approach applied. Although PGD for hemophilia can be focused on gender selection of female embryos, our results demonstrate that methodological approaches that allow the diagnosis of the hemophilia status of every embryo have notorious advantages. Our PGD Program resulted in the birth of 12 healthy babies for 10 out of the 34 couples (29.4%), constituting a relevant achievement for the Spanish Public Health System within the field of haematological disorders. PMID:26258137

Bioethics for human geneticists: models for reasoning and methods for teaching.

PubMed Central

Parker, L. S.

1994-01-01

The ethical issues raised by the Human Genome Project (HGP) and by human genetics in general are not entirely novel. In fact, the ethical issues surrounding genetic research and the provision of genetic services fit into the evolution of bioethics, a field of inquiry which has its roots in concerns of the 1970s, concerns about the dignity and self-determination of individuals and about the development of medical technologies. Although bioethics has been largely occupied with patient-centered concerns, attention is currently shifting toward socially oriented issues, such as the justice of the existing health-care system. Genetic counseling has already incorporated many of the lessons of early bioethics and, as a profession, adheres to a consultand-centered ethic which reflects the values incorporated into the doctrine of informed consent, which is a cornerstone of bioethics. The mandate of the Ethical, Legal, and Social Implications Program of the HGP--to anticipate ethical problems arising from advances in genetics and to educate the public about genetics--reflects not only the nonpaternalistic approach of early bioethics but also bioethics' increasing attention to the ethical import of systemic and institutional factors, as well as an anticipatory and preventive approach to dealing with ethical concerns. Because bioethics has so much to contribute to current consideration of ethical issues in human genetics, it is important to provide training in ethics to those working in the field. Guidelines for using a case-oriented approach are suggested. PMID:8279464

Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species.

PubMed

Irizarry, Kristopher J L; Bryant, Doug; Kalish, Jordan; Eng, Curtis; Schmidt, Peggy L; Barrett, Gini; Barr, Margaret C

2016-01-01

Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs) that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.

Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species

PubMed Central

Irizarry, Kristopher J. L.; Bryant, Doug; Kalish, Jordan; Eng, Curtis; Schmidt, Peggy L.; Barrett, Gini; Barr, Margaret C.

2016-01-01

Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs) that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management. PMID:27376076

Topology-changing shape optimization with the genetic algorithm

NASA Astrophysics Data System (ADS)

Lamberson, Steven E., Jr.

The goal is to take a traditional shape optimization problem statement and modify it slightly to allow for prescribed changes in topology. This modification enables greater flexibility in the choice of parameters for the topology optimization problem, while improving the direct physical relevance of the results. This modification involves changing the optimization problem statement from a nonlinear programming problem into a form of mixed-discrete nonlinear programing problem. The present work demonstrates one possible way of using the Genetic Algorithm (GA) to solve such a problem, including the use of "masking bits" and a new modification to the bit-string affinity (BSA) termination criterion specifically designed for problems with "masking bits." A simple ten-bar truss problem proves the utility of the modified BSA for this type of problem. A more complicated two dimensional bracket problem is solved using both the proposed approach and a more traditional topology optimization approach (Solid Isotropic Microstructure with Penalization or SIMP) to enable comparison. The proposed approach is able to solve problems with both local and global constraints, which is something traditional methods cannot do. The proposed approach has a significantly higher computational burden --- on the order of 100 times larger than SIMP, although the proposed approach is able to offset this with parallel computing.

Alignment-free genetic sequence comparisons: a review of recent approaches by word analysis

PubMed Central

Steele, Joe; Bastola, Dhundy

2014-01-01

Modern sequencing and genome assembly technologies have provided a wealth of data, which will soon require an analysis by comparison for discovery. Sequence alignment, a fundamental task in bioinformatics research, may be used but with some caveats. Seminal techniques and methods from dynamic programming are proving ineffective for this work owing to their inherent computational expense when processing large amounts of sequence data. These methods are prone to giving misleading information because of genetic recombination, genetic shuffling and other inherent biological events. New approaches from information theory, frequency analysis and data compression are available and provide powerful alternatives to dynamic programming. These new methods are often preferred, as their algorithms are simpler and are not affected by synteny-related problems. In this review, we provide a detailed discussion of computational tools, which stem from alignment-free methods based on statistical analysis from word frequencies. We provide several clear examples to demonstrate applications and the interpretations over several different areas of alignment-free analysis such as base–base correlations, feature frequency profiles, compositional vectors, an improved string composition and the D2 statistic metric. Additionally, we provide detailed discussion and an example of analysis by Lempel–Ziv techniques from data compression. PMID:23904502

Hunter disease eClinic: interactive, computer-assisted, problem-based approach to independent learning about a rare genetic disease.

PubMed

Al-Jasmi, Fatma; Moldovan, Laura; Clarke, Joe T R

2010-10-25

Computer-based teaching (CBT) is a well-known educational device, but it has never been applied systematically to the teaching of a complex, rare, genetic disease, such as Hunter disease (MPS II). To develop interactive teaching software functioning as a virtual clinic for the management of MPS II. The Hunter disease eClinic, a self-training, user-friendly educational software program, available at the Lysosomal Storage Research Group (http://www.lysosomalstorageresearch.ca), was developed using the Adobe Flash multimedia platform. It was designed to function both to provide a realistic, interactive virtual clinic and instantaneous access to supporting literature on Hunter disease. The Hunter disease eClinic consists of an eBook and an eClinic. The eClinic is the interactive virtual clinic component of the software. Within an environment resembling a real clinic, the trainee is instructed to perform a medical history, to examine the patient, and to order appropriate investigation. The program provides clinical data derived from the management of actual patients with Hunter disease. The eBook provides instantaneous, electronic access to a vast collection of reference information to provide detailed background clinical and basic science, including relevant biochemistry, physiology, and genetics. In the eClinic, the trainee is presented with quizzes designed to provide immediate feedback on both trainee effectiveness and efficiency. User feedback on the merits of the program was collected at several seminars and formal clinical rounds at several medical centres, primarily in Canada. In addition, online usage statistics were documented for a 2-year period. Feedback was consistently positive and confirmed the practical benefit of the program. The online English-language version is accessed daily by users from all over the world; a Japanese translation of the program is also available. The Hunter disease eClinic employs a CBT model providing the trainee with realistic clinical problems, coupled with comprehensive basic and clinical reference information by instantaneous access to an electronic textbook, the eBook. The program was rated highly by attendees at national and international presentations. It provides a potential model for use as an educational approach to other rare genetic diseases.

Simulating a base population in honey bee for molecular genetic studies

PubMed Central

2012-01-01

Background Over the past years, reports have indicated that honey bee populations are declining and that infestation by an ecto-parasitic mite (Varroa destructor) is one of the main causes. Selective breeding of resistant bees can help to prevent losses due to the parasite, but it requires that a robust breeding program and genetic evaluation are implemented. Genomic selection has emerged as an important tool in animal breeding programs and simulation studies have shown that it yields more accurate breeding value estimates, higher genetic gain and low rates of inbreeding. Since genomic selection relies on marker data, simulations conducted on a genomic dataset are a pre-requisite before selection can be implemented. Although genomic datasets have been simulated in other species undergoing genetic evaluation, simulation of a genomic dataset specific to the honey bee is required since this species has a distinct genetic and reproductive biology. Our software program was aimed at constructing a base population by simulating a random mating honey bee population. A forward-time population simulation approach was applied since it allows modeling of genetic characteristics and reproductive behavior specific to the honey bee. Results Our software program yielded a genomic dataset for a base population in linkage disequilibrium. In addition, information was obtained on (1) the position of markers on each chromosome, (2) allele frequency, (3) χ2 statistics for Hardy-Weinberg equilibrium, (4) a sorted list of markers with a minor allele frequency less than or equal to the input value, (5) average r2 values of linkage disequilibrium between all simulated marker loci pair for all generations and (6) average r2 value of linkage disequilibrium in the last generation for selected markers with the highest minor allele frequency. Conclusion We developed a software program that takes into account the genetic and reproductive biology specific to the honey bee and that can be used to constitute a genomic dataset compatible with the simulation studies necessary to optimize breeding programs. The source code together with an instruction file is freely accessible at http://msproteomics.org/Research/Misc/honeybeepopulationsimulator.html PMID:22520469

Simulating a base population in honey bee for molecular genetic studies.

PubMed

Gupta, Pooja; Conrad, Tim; Spötter, Andreas; Reinsch, Norbert; Bienefeld, Kaspar

2012-06-27

Over the past years, reports have indicated that honey bee populations are declining and that infestation by an ecto-parasitic mite (Varroa destructor) is one of the main causes. Selective breeding of resistant bees can help to prevent losses due to the parasite, but it requires that a robust breeding program and genetic evaluation are implemented. Genomic selection has emerged as an important tool in animal breeding programs and simulation studies have shown that it yields more accurate breeding value estimates, higher genetic gain and low rates of inbreeding. Since genomic selection relies on marker data, simulations conducted on a genomic dataset are a pre-requisite before selection can be implemented. Although genomic datasets have been simulated in other species undergoing genetic evaluation, simulation of a genomic dataset specific to the honey bee is required since this species has a distinct genetic and reproductive biology. Our software program was aimed at constructing a base population by simulating a random mating honey bee population. A forward-time population simulation approach was applied since it allows modeling of genetic characteristics and reproductive behavior specific to the honey bee. Our software program yielded a genomic dataset for a base population in linkage disequilibrium. In addition, information was obtained on (1) the position of markers on each chromosome, (2) allele frequency, (3) χ(2) statistics for Hardy-Weinberg equilibrium, (4) a sorted list of markers with a minor allele frequency less than or equal to the input value, (5) average r(2) values of linkage disequilibrium between all simulated marker loci pair for all generations and (6) average r2 value of linkage disequilibrium in the last generation for selected markers with the highest minor allele frequency. We developed a software program that takes into account the genetic and reproductive biology specific to the honey bee and that can be used to constitute a genomic dataset compatible with the simulation studies necessary to optimize breeding programs. The source code together with an instruction file is freely accessible at http://msproteomics.org/Research/Misc/honeybeepopulationsimulator.html.

A Heuristics Approach for Classroom Scheduling Using Genetic Algorithm Technique

NASA Astrophysics Data System (ADS)

Ahmad, Izah R.; Sufahani, Suliadi; Ali, Maselan; Razali, Siti N. A. M.

2018-04-01

Reshuffling and arranging classroom based on the capacity of the audience, complete facilities, lecturing time and many more may lead to a complexity of classroom scheduling. While trying to enhance the productivity in classroom planning, this paper proposes a heuristic approach for timetabling optimization. A new algorithm was produced to take care of the timetabling problem in a university. The proposed of heuristics approach will prompt a superior utilization of the accessible classroom space for a given time table of courses at the university. Genetic Algorithm through Java programming languages were used in this study and aims at reducing the conflicts and optimizes the fitness. The algorithm considered the quantity of students in each class, class time, class size, time accessibility in each class and lecturer who in charge of the classes.

Initiating an undiagnosed diseases program in the Western Australian public health system.

PubMed

Baynam, Gareth; Broley, Stephanie; Bauskis, Alicia; Pachter, Nicholas; McKenzie, Fiona; Townshend, Sharron; Slee, Jennie; Kiraly-Borri, Cathy; Vasudevan, Anand; Hawkins, Anne; Schofield, Lyn; Helmholz, Petra; Palmer, Richard; Kung, Stefanie; Walker, Caroline E; Molster, Caron; Lewis, Barry; Mina, Kym; Beilby, John; Pathak, Gargi; Poulton, Cathryn; Groza, Tudor; Zankl, Andreas; Roscioli, Tony; Dinger, Marcel E; Mattick, John S; Gahl, William; Groft, Stephen; Tifft, Cynthia; Taruscio, Domenica; Lasko, Paul; Kosaki, Kenjiro; Wilhelm, Helene; Melegh, Bela; Carapetis, Jonathan; Jana, Sayanta; Chaney, Gervase; Johns, Allison; Owen, Peter Wynn; Daly, Frank; Weeramanthri, Tarun; Dawkins, Hugh; Goldblatt, Jack

2017-05-03

New approaches are required to address the needs of complex undiagnosed diseases patients. These approaches include clinical genomic diagnostic pipelines, utilizing intra- and multi-disciplinary platforms, as well as specialty-specific genomic clinics. Both are advancing diagnostic rates. However, complementary cross-disciplinary approaches are also critical to address those patients with multisystem disorders who traverse the bounds of multiple specialties and remain undiagnosed despite existing intra-specialty and genomic-focused approaches. The diagnostic possibilities of undiagnosed diseases include genetic and non-genetic conditions. The focus on genetic diseases addresses some of these disorders, however a cross-disciplinary approach is needed that also simultaneously addresses other disorder types. Herein, we describe the initiation and summary outcomes of a public health system approach for complex undiagnosed patients - the Undiagnosed Diseases Program-Western Australia (UDP-WA). Briefly the UDP-WA is: i) one of a complementary suite of approaches that is being delivered within health service, and with community engagement, to address the needs of those with severe undiagnosed diseases; ii) delivered within a public health system to support equitable access to health care, including for those from remote and regional areas; iii) providing diagnoses and improved patient care; iv) delivering a platform for in-service and real time genomic and phenomic education for clinicians that traverses a diverse range of specialties; v) retaining and recapturing clinical expertise; vi) supporting the education of junior and more senior medical staff; vii) designed to integrate with clinical translational research; and viii) is supporting greater connectedness for patients, families and medical staff. The UDP-WA has been initiated in the public health system to complement existing clinical genomic approaches; it has been targeted to those with a specific diagnostic need, and initiated by redirecting existing clinical and financial resources. The UDP-WA supports the provision of equitable and sustainable diagnostics and simultaneously supports capacity building in clinical care and translational research, for those with undiagnosed, typically rare, conditions.

Training the Millennial learner through experiential evolutionary scaffolding: implications for clinical supervision in graduate education programs.

PubMed

Venne, Vickie L; Coleman, Darrell

2010-12-01

They are the Millennials--Generation Y. Over the next few decades, they will be entering genetic counseling graduate training programs and the workforce. As a group, they are unlike previous youth generations in many ways, including the way they learn. Therefore, genetic counselors who teach and supervise need to understand the Millennials and explore new ways of teaching to ensure that the next cohort of genetic counselors has both skills and knowledge to represent our profession well. This paper will summarize the distinguishing traits of the Millennial generation as well as authentic learning and evolutionary scaffolding theories of learning that can enhance teaching and supervision. We will then use specific aspects of case preparation during clinical rotations to demonstrate how incorporating authentic learning theory into evolutionary scaffolding results in experiential evolutionary scaffolding, a method that potentially offers a more effective approach when teaching Millennials. We conclude with suggestions for future research.

Potential of SNP markers for the characterization of Brazilian cassava germplasm.

PubMed

de Oliveira, Eder Jorge; Ferreira, Cláudia Fortes; da Silva Santos, Vanderlei; de Jesus, Onildo Nunes; Oliveira, Gilmara Alvarenga Fachardo; da Silva, Maiane Suzarte

2014-06-01

High-throughput markers, such as SNPs, along with different methodologies were used to evaluate the applicability of the Bayesian approach and the multivariate analysis in structuring the genetic diversity in cassavas. The objective of the present work was to evaluate the diversity and genetic structure of the largest cassava germplasm bank in Brazil. Complementary methodological approaches such as discriminant analysis of principal components (DAPC), Bayesian analysis and molecular analysis of variance (AMOVA) were used to understand the structure and diversity of 1,280 accessions genotyped using 402 single nucleotide polymorphism markers. The genetic diversity (0.327) and the average observed heterozygosity (0.322) were high considering the bi-allelic markers. In terms of population, the presence of a complex genetic structure was observed indicating the formation of 30 clusters by DAPC and 34 clusters by Bayesian analysis. Both methodologies presented difficulties and controversies in terms of the allocation of some accessions to specific clusters. However, the clusters suggested by the DAPC analysis seemed to be more consistent for presenting higher probability of allocation of the accessions within the clusters. Prior information related to breeding patterns and geographic origins of the accessions were not sufficient for providing clear differentiation between the clusters according to the AMOVA analysis. In contrast, the F ST was maximized when considering the clusters suggested by the Bayesian and DAPC analyses. The high frequency of germplasm exchange between producers and the subsequent alteration of the name of the same material may be one of the causes of the low association between genetic diversity and geographic origin. The results of this study may benefit cassava germplasm conservation programs, and contribute to the maximization of genetic gains in breeding programs.

Identification of cancer genes that are independent of dominant proliferation and lineage programs

PubMed Central

Selfors, Laura M.; Stover, Daniel G.; Harris, Isaac S.; Brugge, Joan S.; Coloff, Jonathan L.

2017-01-01

Large, multidimensional cancer datasets provide a resource that can be mined to identify candidate therapeutic targets for specific subgroups of tumors. Here, we analyzed human breast cancer data to identify transcriptional programs associated with tumors bearing specific genetic driver alterations. Using an unbiased approach, we identified thousands of genes whose expression was enriched in tumors with specific genetic alterations. However, expression of the vast majority of these genes was not enriched if associations were analyzed within individual breast tumor molecular subtypes, across multiple tumor types, or after gene expression was normalized to account for differences in proliferation or tumor lineage. Together with linear modeling results, these findings suggest that most transcriptional programs associated with specific genetic alterations in oncogenes and tumor suppressors are highly context-dependent and are predominantly linked to differences in proliferation programs between distinct breast cancer subtypes. We demonstrate that such proliferation-dependent gene expression dominates tumor transcriptional programs relative to matched normal tissues. However, we also identified a relatively small group of cancer-associated genes that are both proliferation- and lineage-independent. A subset of these genes are attractive candidate targets for combination therapy because they are essential in breast cancer cell lines, druggable, enriched in stem-like breast cancer cells, and resistant to chemotherapy-induced down-regulation. PMID:29229826

Unleashing the power of human genetic variation knowledge: New Zealand stakeholder perspectives.

PubMed

Gu, Yulong; Warren, James Roy; Day, Karen Jean

2011-01-01

This study aimed to characterize the challenges in using genetic information in health care and to identify opportunities for improvement. Taking a grounded theory approach, semistructured interviews were conducted with 48 participants to collect multiple stakeholder perspectives on genetic services in New Zealand. Three themes emerged from the data: (1) four service delivery models were identified in operation, including both those expected models involving genetic counselors and variations that do not route through the formal genetic service program; (2) multiple barriers to sharing and using genetic information were perceived, including technological, organizational, institutional, legal, ethical, and social issues; and (3) impediments to wider use of genetic testing technology, including variable understanding of genetic test utilities among clinicians and the limited capacity of clinical genetic services. Targeting these problems, information technologies and knowledge management tools have the potential to support key tasks in genetic services delivery, improve knowledge processes, and enhance knowledge networks. Because of the effect of issues in genetic information and knowledge management, the potential of human genetic variation knowledge to enhance health care delivery has been put on a "leash."

How well can captive breeding programs conserve biodiversity? A review of salmonids

PubMed Central

Fraser, Dylan J

2008-01-01

Captive breeding programs are increasingly being initiated to prevent the imminent extinction of endangered species and/or populations. But how well can they conserve genetic diversity and fitness, or re-establish self-sustaining populations in the wild? A review of these complex questions and related issues in salmonid fishes reveals several insights and uncertainties. Most programs can maintain genetic diversity within populations over several generations, but available research suggests the loss of fitness in captivity can be rapid, its magnitude probably increasing with the duration in captivity. Over the long-term, there is likely tremendous variation between (i) programs in their capacity to maintain genetic diversity and fitness, and (ii) species or even intraspecific life-history types in both the severity and manner of fitness-costs accrued. Encouragingly, many new theoretical and methodological approaches now exist for current and future programs to potentially reduce these effects. Nevertheless, an unavoidable trade-off exists between conserving genetic diversity and fitness in certain instances, such as when captive-bred individuals are temporarily released into the wild. Owing to several confounding factors, there is also currently little evidence that captive-bred lines of salmonids can or cannot be reintroduced as self-sustaining populations. Most notably, the root causes of salmonid declines have not been mitigated where captive breeding programs exist. Little research has also addressed under what conditions an increase in population abundance due to captive-rearing might offset fitness reductions induced in captivity. Finally, more empirical investigation is needed to evaluate the genetic/fitness benefits and risks associated with (i) maintaining captive broodstocks as either single or multiple populations within one or more facilities, (ii) utilizing cryopreservation or surrogate broodstock technologies, and (iii) adopting other alternatives to captive-rearing such as translocations to new habitats. Management recommendations surrounding these issues are proposed, with the aim of facilitating meta-analyses and more general principles or guidelines for captive-breeding. These include the need for the following: (i) captive monitoring to involve, a priori, greater application of hypothesis testing through the use of well-designed experiments and (ii) improved documentation of procedures adopted by specific programs for reducing the loss of genetic diversity and fitness. PMID:25567798

Genetic Risk Score of NOS Gene Variants Associated with Myocardial Infarction Correlates with Coronary Incidence across Europe

PubMed Central

Carreras-Torres, Robert; Kundu, Suman; Zanetti, Daniela; Esteban, Esther

2014-01-01

Coronary artery disease (CAD) mortality and morbidity is present in the European continent in a four-fold gradient across populations, from the South (Spain and France) with the lowest CAD mortality, towards the North (Finland and UK). This observed gradient has not been fully explained by classical or single genetic risk factors, resulting in some cases in the so called Southern European or Mediterranean paradox. Here we approached population genetic risk estimates using genetic risk scores (GRS) constructed with single nucleotide polymorphisms (SNP) from nitric oxide synthases (NOS) genes. These SNPs appeared to be associated with myocardial infarction (MI) in 2165 cases and 2153 controls. The GRSs were computed in 34 general European populations. Although the contribution of these GRS was lower than 1% between cases and controls, the mean GRS per population was positively correlated with coronary incidence explaining 65–85% of the variation among populations (67% in women and 86% in men). This large contribution to CAD incidence variation among populations might be a result of colinearity with several other common genetic and environmental factors. These results are not consistent with the cardiovascular Mediterranean paradox for genetics and support a CAD genetic architecture mainly based on combinations of common genetic polymorphisms. Population genetic risk scores is a promising approach in public health interventions to develop lifestyle programs and prevent intermediate risk factors in certain subpopulations with specific genetic predisposition. PMID:24806096

Analysis of conservation priorities of Iberoamerican cattle based on autosomal microsatellite markers

PubMed Central

2013-01-01

Background Determining the value of livestock breeds is essential to define conservation priorities, manage genetic diversity and allocate funds. Within- and between-breed genetic diversity need to be assessed to preserve the highest intra-specific variability. Information on genetic diversity and risk status is still lacking for many Creole cattle breeds from the Americas, despite their distinct evolutionary trajectories and adaptation to extreme environmental conditions. Methods A comprehensive genetic analysis of 67 Iberoamerican cattle breeds was carried out with 19 FAO-recommended microsatellites to assess conservation priorities. Contributions to global diversity were investigated using alternative methods, with different weights given to the within- and between-breed components of genetic diversity. Information on Iberoamerican plus 15 worldwide cattle breeds was used to investigate the contribution of geographical breed groups to global genetic diversity. Results Overall, Creole cattle breeds showed a high level of genetic diversity with the highest level found in breeds admixed with zebu cattle, which were clearly differentiated from all other breeds. Within-breed kinships revealed seven highly inbred Creole breeds for which measures are needed to avoid further genetic erosion. However, if contribution to heterozygosity was the only criterion considered, some of these breeds had the lowest priority for conservation decisions. The Weitzman approach prioritized highly differentiated breeds, such as Guabalá, Romosinuano, Cr. Patagonico, Siboney and Caracú, while kinship-based methods prioritized mainly zebu-related breeds. With the combined approaches, breed ranking depended on the weights given to the within- and between-breed components of diversity. Overall, the Creole groups of breeds were generally assigned a higher priority for conservation than the European groups of breeds. Conclusions Conservation priorities differed significantly according to the weight given to within- and between-breed genetic diversity. Thus, when establishing conservation programs, it is necessary to also take into account other features. Creole cattle and local isolated breeds retain a high level of genetic diversity. The development of sustainable breeding and crossbreeding programs for Creole breeds, and the added value resulting from their products should be taken into consideration to ensure their long-term survival. PMID:24079454

Genetic Programming Transforms in Linear Regression Situations

NASA Astrophysics Data System (ADS)

Castillo, Flor; Kordon, Arthur; Villa, Carlos

The chapter summarizes the use of Genetic Programming (GP) inMultiple Linear Regression (MLR) to address multicollinearity and Lack of Fit (LOF). The basis of the proposed method is applying appropriate input transforms (model respecification) that deal with these issues while preserving the information content of the original variables. The transforms are selected from symbolic regression models with optimal trade-off between accuracy of prediction and expressional complexity, generated by multiobjective Pareto-front GP. The chapter includes a comparative study of the GP-generated transforms with Ridge Regression, a variant of ordinary Multiple Linear Regression, which has been a useful and commonly employed approach for reducing multicollinearity. The advantages of GP-generated model respecification are clearly defined and demonstrated. Some recommendations for transforms selection are given as well. The application benefits of the proposed approach are illustrated with a real industrial application in one of the broadest empirical modeling areas in manufacturing - robust inferential sensors. The chapter contributes to increasing the awareness of the potential of GP in statistical model building by MLR.

Potential Uses of Wild Germplasms of Grain Legumes for Crop Improvement

PubMed Central

Muñoz, Nacira; Liu, Ailin; Kan, Leo; Li, Man-Wah; Lam, Hon-Ming

2017-01-01

Challenged by population increase, climatic change, and soil deterioration, crop improvement is always a priority in securing food supplies. Although the production of grain legumes is in general lower than that of cereals, the nutritional value of grain legumes make them important components of food security. Nevertheless, limited by severe genetic bottlenecks during domestication and human selection, grain legumes, like other crops, have suffered from a loss of genetic diversity which is essential for providing genetic materials for crop improvement programs. Illustrated by whole-genome-sequencing, wild relatives of crops adapted to various environments were shown to maintain high genetic diversity. In this review, we focused on nine important grain legumes (soybean, peanut, pea, chickpea, common bean, lentil, cowpea, lupin, and pigeonpea) to discuss the potential uses of their wild relatives as genetic resources for crop breeding and improvement, and summarized the various genetic/genomic approaches adopted for these purposes. PMID:28165413

Reparametrization-based estimation of genetic parameters in multi-trait animal model using Integrated Nested Laplace Approximation.

PubMed

Mathew, Boby; Holand, Anna Marie; Koistinen, Petri; Léon, Jens; Sillanpää, Mikko J

2016-02-01

A novel reparametrization-based INLA approach as a fast alternative to MCMC for the Bayesian estimation of genetic parameters in multivariate animal model is presented. Multi-trait genetic parameter estimation is a relevant topic in animal and plant breeding programs because multi-trait analysis can take into account the genetic correlation between different traits and that significantly improves the accuracy of the genetic parameter estimates. Generally, multi-trait analysis is computationally demanding and requires initial estimates of genetic and residual correlations among the traits, while those are difficult to obtain. In this study, we illustrate how to reparametrize covariance matrices of a multivariate animal model/animal models using modified Cholesky decompositions. This reparametrization-based approach is used in the Integrated Nested Laplace Approximation (INLA) methodology to estimate genetic parameters of multivariate animal model. Immediate benefits are: (1) to avoid difficulties of finding good starting values for analysis which can be a problem, for example in Restricted Maximum Likelihood (REML); (2) Bayesian estimation of (co)variance components using INLA is faster to execute than using Markov Chain Monte Carlo (MCMC) especially when realized relationship matrices are dense. The slight drawback is that priors for covariance matrices are assigned for elements of the Cholesky factor but not directly to the covariance matrix elements as in MCMC. Additionally, we illustrate the concordance of the INLA results with the traditional methods like MCMC and REML approaches. We also present results obtained from simulated data sets with replicates and field data in rice.

Genetic management guidelines for captive propagation of freshwater mussels (unionoidea)

USGS Publications Warehouse

Jones, J.W.; Hallerman, E.M.; Neves, R.J.

2006-01-01

Although the greatest global diversity of freshwater mussels (???300 species) resides in the United States, the superfamily Unionoidea is also the most imperiled taxon of animals in the nation. Thirty-five species are considered extinct, 70 species are listed as endangered or threatened, and approximately 100 more are species of conservation concern. To prevent additional species losses, biologists have developed methods for propagating juvenile mussels for release into the wild to restore or augment populations. Since 1997, mussel propagation facilities in the United States have released over 1 million juveniles of more than a dozen imperiled species, and survival of these juveniles in the wild has been documented. With the expectation of continued growth of these programs, agencies and facilities involved with mussel propagation must seriously consider the genetic implications of releasing captive-reared progeny. We propose 10 guidelines to help maintain the genetic resources of cultured and wild populations. Preservation of genetic diversity will require robust genetic analysis of source populations to define conservation units for valid species, subspecies, and unique populations. Hatchery protocols must be implemented that minimize risks of artificial selection and other genetic hazards affecting adaptive traits of progeny subsequently released to the wild. We advocate a pragmatic, adaptive approach to species recovery that incorporates the principles of conservation genetics into breeding programs, and prioritizes the immediate demographic needs of critically endangered mussel species.

Genetic approaches refine ex situ lowland tapir (Tapirus terrestris) conservation.

PubMed

Gonçalves da Silva, Anders; Lalonde, Danielle R; Quse, Viviana; Shoemaker, Alan; Russello, Michael A

2010-01-01

Ex situ conservation management remains an important tool in the face of continued habitat loss and global environmental change. Here, we use microsatellite marker variation to evaluate conventional assumptions of pedigree-based ex situ population management and directly inform a captive lowland tapir breeding program within a range country. We found relatively high levels of genetic variation (N(total) = 41; mean H(E) = 0.67 across 10 variable loci) and little evidence for relatedness among founder individuals (N(founders) = 10; mean relatedness = -0.05). Seven of 29 putative parent-offspring relationships were excluded by parentage analysis based on allele sharing, and we identified 2 individuals of high genetic value to the population (mk

Programming of Essential Hypertension: What Pediatric Cardiologists Need to Know.

PubMed

Morgado, Joana; Sanches, Bruno; Anjos, Rui; Coelho, Constança

2015-10-01

Hypertension is recognized as one of the major contributing factors to cardiovascular disease, but its etiology remains incompletely understood. Known genetic and environmental influences can only explain a small part of the variability in cardiovascular disease risk. The missing heritability is currently one of the most important challenges in blood pressure and hypertension genetics. Recently, some promising approaches have emerged that move beyond the DNA sequence and focus on identification of blood pressure genes regulated by epigenetic mechanisms such as DNA methylation, histone modification and microRNAs. This review summarizes information on gene-environmental interactions that lead toward the developmental programming of hypertension with specific reference to epigenetics and provides pediatricians and pediatric cardiologists with a more complete understanding of its pathogenesis.

Development of Decision Support System for Remote Monitoring of PIP Corn

EPA Science Inventory

The EPA is developing a multi-level approach that utilizes satellite and airborne remote sensing to locate and monitor genetically modified corn in the agricultural landscape and pest infestation. The current status of the EPA IRM monitoring program based on remote sensed imager...

Current Landscape and New Paradigms of Proficiency Testing and External Quality Assessment for Molecular Genetics

PubMed Central

Kalman, Lisa V.; Lubin, Ira M.; Barker, Shannon; du Sart, Desiree; Elles, Rob; Grody, Wayne W.; Pazzagli, Mario; Richards, Sue; Schrijver, Iris; Zehnbauer, Barbara

2015-01-01

Context Participation in proficiency testing (PT) or external quality assessment (EQA) programs allows the assessment and comparison of test performance among different clinical laboratories and technologies. In addition to the approximately 2300 tests for individual genetic disorders, recent advances in technology have enabled the development of clinical tests which quickly and economically analyze the entire human genome. New PT/EQA approaches are needed to ensure the continued quality of these complex tests. Objective To review the availability and scope of PT/EQA for molecular genetic testing for inherited conditions in Europe, Australasia and the United States; to evaluate the successes and demonstrated value of available PT/EQA programs; and to examine the challenges to the provision of comprehensive PT/EQA posed by new laboratory practices and methodologies. Data Sources The available literature on this topic was reviewed and supplemented with personal experiences of several PT/EQA providers. Conclusions PT/EQA schemes are available for common genetic disorders tested in many clinical laboratories, but are not available for most genetic tests offered by only one or a few laboratories. Provision of broad, method-based PT schemes, such as DNA sequencing, would allow assessment of a large number of tests for which formal PT is not currently available. Participation in PT/EQA improves the quality of testing by identifying inaccuracies that laboratories can trace to errors in the testing process. Areas of research and development to ensure that PT/EQA programs can meet the needs of new and evolving genetic tests and technologies are identified and discussed. PMID:23808472

Experimental control of a fluidic pinball using genetic programming

NASA Astrophysics Data System (ADS)

Raibaudo, Cedric; Zhong, Peng; Noack, Bernd R.; Martinuzzi, Robert J.

2017-11-01

The wake stabilization of a triangular cluster of three rotating cylinders was investigated in the present study. Experiments were performed at Reynolds number Re 6000, and compared with URANS-2D simulations at same flow conditions. 2D2C PIV measurements and constant temperature anemometry were used to characterize the flow without and with actuation. Open-loop actuation was first considered for the identification of particular control strategies. Machine learning control was also implemented for the experimental study. Linear genetic programming has been used for the optimization of open-loop parameters and closed-loop controllers. Considering a cost function J based on the fluctuations of the velocity measured by the hot-wire sensor, significant performances were achieved using the machine learning approach. The present work is supported by the senior author's (R. J. Martinuzzi) NSERC discovery Grant. C. Raibaudo acknowledges the financial support of the University of Calgary Eyes-High PDF program.

The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations.

PubMed

Keenan, Alexandra B; Jenkins, Sherry L; Jagodnik, Kathleen M; Koplev, Simon; He, Edward; Torre, Denis; Wang, Zichen; Dohlman, Anders B; Silverstein, Moshe C; Lachmann, Alexander; Kuleshov, Maxim V; Ma'ayan, Avi; Stathias, Vasileios; Terryn, Raymond; Cooper, Daniel; Forlin, Michele; Koleti, Amar; Vidovic, Dusica; Chung, Caty; Schürer, Stephan C; Vasiliauskas, Jouzas; Pilarczyk, Marcin; Shamsaei, Behrouz; Fazel, Mehdi; Ren, Yan; Niu, Wen; Clark, Nicholas A; White, Shana; Mahi, Naim; Zhang, Lixia; Kouril, Michal; Reichard, John F; Sivaganesan, Siva; Medvedovic, Mario; Meller, Jaroslaw; Koch, Rick J; Birtwistle, Marc R; Iyengar, Ravi; Sobie, Eric A; Azeloglu, Evren U; Kaye, Julia; Osterloh, Jeannette; Haston, Kelly; Kalra, Jaslin; Finkbiener, Steve; Li, Jonathan; Milani, Pamela; Adam, Miriam; Escalante-Chong, Renan; Sachs, Karen; Lenail, Alex; Ramamoorthy, Divya; Fraenkel, Ernest; Daigle, Gavin; Hussain, Uzma; Coye, Alyssa; Rothstein, Jeffrey; Sareen, Dhruv; Ornelas, Loren; Banuelos, Maria; Mandefro, Berhan; Ho, Ritchie; Svendsen, Clive N; Lim, Ryan G; Stocksdale, Jennifer; Casale, Malcolm S; Thompson, Terri G; Wu, Jie; Thompson, Leslie M; Dardov, Victoria; Venkatraman, Vidya; Matlock, Andrea; Van Eyk, Jennifer E; Jaffe, Jacob D; Papanastasiou, Malvina; Subramanian, Aravind; Golub, Todd R; Erickson, Sean D; Fallahi-Sichani, Mohammad; Hafner, Marc; Gray, Nathanael S; Lin, Jia-Ren; Mills, Caitlin E; Muhlich, Jeremy L; Niepel, Mario; Shamu, Caroline E; Williams, Elizabeth H; Wrobel, David; Sorger, Peter K; Heiser, Laura M; Gray, Joe W; Korkola, James E; Mills, Gordon B; LaBarge, Mark; Feiler, Heidi S; Dane, Mark A; Bucher, Elmar; Nederlof, Michel; Sudar, Damir; Gross, Sean; Kilburn, David F; Smith, Rebecca; Devlin, Kaylyn; Margolis, Ron; Derr, Leslie; Lee, Albert; Pillai, Ajay

2018-01-24

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability. Copyright © 2017 Elsevier Inc. All rights reserved.

Alignment-free genetic sequence comparisons: a review of recent approaches by word analysis.

PubMed

Bonham-Carter, Oliver; Steele, Joe; Bastola, Dhundy

2014-11-01

Modern sequencing and genome assembly technologies have provided a wealth of data, which will soon require an analysis by comparison for discovery. Sequence alignment, a fundamental task in bioinformatics research, may be used but with some caveats. Seminal techniques and methods from dynamic programming are proving ineffective for this work owing to their inherent computational expense when processing large amounts of sequence data. These methods are prone to giving misleading information because of genetic recombination, genetic shuffling and other inherent biological events. New approaches from information theory, frequency analysis and data compression are available and provide powerful alternatives to dynamic programming. These new methods are often preferred, as their algorithms are simpler and are not affected by synteny-related problems. In this review, we provide a detailed discussion of computational tools, which stem from alignment-free methods based on statistical analysis from word frequencies. We provide several clear examples to demonstrate applications and the interpretations over several different areas of alignment-free analysis such as base-base correlations, feature frequency profiles, compositional vectors, an improved string composition and the D2 statistic metric. Additionally, we provide detailed discussion and an example of analysis by Lempel-Ziv techniques from data compression. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Obesogenic environments: environmental approaches to obesity prevention.

PubMed

Lipek, Tobias; Igel, Ulrike; Gausche, Ruth; Kiess, Wieland; Grande, Gesine

2015-05-01

Childhood obesity is a major concern for public health. There are multiple factors (e.g., genetic, social, and environmental) that contribute to unhealthy weight gain. Drawing from findings on "obesogenic environments" and core principles of preventive strategies to reduce health inequalities, this paper gives an overview of recent childhood prevention programs that target aspects of the physical environment ("environmental changes"). Out of the ten reviews we screened (including more than 300 studies), we identified very few that addressed aspects of the environment. We focus here on 14 programs that follow different approaches to environmental changes (e.g., access to/quality of playgrounds, changes in school cafeterias). Altering the environment offers opportunities for healthier behaviors and seems to be an effective strategy to prevent childhood obesity. However, the evaluation of those (mostly) multidimensional interventions does not allow drawing firm conclusions about the single effect of environmental changes. We conclude that obesity prevention programs should combine person-based and environmental approaches.

Decision support: Vulnerability, conservation, and restoration (Chapter 8)

Treesearch

Megan M. Friggens; Jeremiah R. Pinto; R. Kasten Dumroese; Nancy L. Shaw

2012-01-01

Current predictive tools, management options, restoration paradigms, and conservation programs are insufficient to meet the challenges of climate change in western North America. Scientific and management capabilities and resources will be sapped trying to identify risks to genetic resources and ecosystems and determine new approaches for mitigating and managing...

Hunter disease eClinic: interactive, computer-assisted, problem-based approach to independent learning about a rare genetic disease

PubMed Central

2010-01-01

Background Computer-based teaching (CBT) is a well-known educational device, but it has never been applied systematically to the teaching of a complex, rare, genetic disease, such as Hunter disease (MPS II). Aim To develop interactive teaching software functioning as a virtual clinic for the management of MPS II. Implementation and Results The Hunter disease eClinic, a self-training, user-friendly educational software program, available at the Lysosomal Storage Research Group (http://www.lysosomalstorageresearch.ca), was developed using the Adobe Flash multimedia platform. It was designed to function both to provide a realistic, interactive virtual clinic and instantaneous access to supporting literature on Hunter disease. The Hunter disease eClinic consists of an eBook and an eClinic. The eClinic is the interactive virtual clinic component of the software. Within an environment resembling a real clinic, the trainee is instructed to perform a medical history, to examine the patient, and to order appropriate investigation. The program provides clinical data derived from the management of actual patients with Hunter disease. The eBook provides instantaneous, electronic access to a vast collection of reference information to provide detailed background clinical and basic science, including relevant biochemistry, physiology, and genetics. In the eClinic, the trainee is presented with quizzes designed to provide immediate feedback on both trainee effectiveness and efficiency. User feedback on the merits of the program was collected at several seminars and formal clinical rounds at several medical centres, primarily in Canada. In addition, online usage statistics were documented for a 2-year period. Feedback was consistently positive and confirmed the practical benefit of the program. The online English-language version is accessed daily by users from all over the world; a Japanese translation of the program is also available. Conclusions The Hunter disease eClinic employs a CBT model providing the trainee with realistic clinical problems, coupled with comprehensive basic and clinical reference information by instantaneous access to an electronic textbook, the eBook. The program was rated highly by attendees at national and international presentations. It provides a potential model for use as an educational approach to other rare genetic diseases. PMID:20973983

Genomic-based-breeding tools for tropical maize improvement.

PubMed

Chakradhar, Thammineni; Hindu, Vemuri; Reddy, Palakolanu Sudhakar

2017-12-01

Maize has traditionally been the main staple diet in the Southern Asia and Sub-Saharan Africa and widely grown by millions of resource poor small scale farmers. Approximately, 35.4 million hectares are sown to tropical maize, constituting around 59% of the developing worlds. Tropical maize encounters tremendous challenges besides poor agro-climatic situations with average yields recorded <3 tones/hectare that is far less than the average of developed countries. On the contrary to poor yields, the demand for maize as food, feed, and fuel is continuously increasing in these regions. Heterosis breeding introduced in early 90 s improved maize yields significantly, but genetic gains is still a mirage, particularly for crop growing under marginal environments. Application of molecular markers has accelerated the pace of maize breeding to some extent. The availability of array of sequencing and genotyping technologies offers unrivalled service to improve precision in maize-breeding programs through modern approaches such as genomic selection, genome-wide association studies, bulk segregant analysis-based sequencing approaches, etc. Superior alleles underlying complex traits can easily be identified and introgressed efficiently using these sequence-based approaches. Integration of genomic tools and techniques with advanced genetic resources such as nested association mapping and backcross nested association mapping could certainly address the genetic issues in maize improvement programs in developing countries. Huge diversity in tropical maize and its inherent capacity for doubled haploid technology offers advantage to apply the next generation genomic tools for accelerating production in marginal environments of tropical and subtropical world. Precision in phenotyping is the key for success of any molecular-breeding approach. This article reviews genomic technologies and their application to improve agronomic traits in tropical maize breeding has been reviewed in detail.

Hybrid genetic algorithm in the Hopfield network for maximum 2-satisfiability problem

NASA Astrophysics Data System (ADS)

Kasihmuddin, Mohd Shareduwan Mohd; Sathasivam, Saratha; Mansor, Mohd. Asyraf

2017-08-01

Heuristic method was designed for finding optimal solution more quickly compared to classical methods which are too complex to comprehend. In this study, a hybrid approach that utilizes Hopfield network and genetic algorithm in doing maximum 2-Satisfiability problem (MAX-2SAT) was proposed. Hopfield neural network was used to minimize logical inconsistency in interpretations of logic clauses or program. Genetic algorithm (GA) has pioneered the implementation of methods that exploit the idea of combination and reproduce a better solution. The simulation incorporated with and without genetic algorithm will be examined by using Microsoft Visual 2013 C++ Express software. The performance of both searching techniques in doing MAX-2SAT was evaluate based on global minima ratio, ratio of satisfied clause and computation time. The result obtained form the computer simulation demonstrates the effectiveness and acceleration features of genetic algorithm in doing MAX-2SAT in Hopfield network.

Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery.

PubMed

Hickey, John M; Chiurugwi, Tinashe; Mackay, Ian; Powell, Wayne

2017-08-30

The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic prediction of breeding values has the potential to improve selection, reduce costs and provide a platform that unifies breeding approaches, biological discovery, and tools and methods. Here we compare and contrast some animal and plant breeding approaches to make a case for bringing the two together through the application of genomic selection. We propose a strategy for the use of genomic selection as a unifying approach to deliver innovative 'step changes' in the rate of genetic gain at scale.

Perceived knowledge and clinical comfort with genetics among Taiwanese nurses enrolled in a RN-to-BSN program.

PubMed

Hsiao, Chiu-Yueh; Lee, Shu-Hsin; Chen, Suh-Jen; Lin, Shu-Chin

2013-08-01

Advances in genetics have had a profound impact on health care. Yet, many nurses, as well as other health care providers, have limited genetic knowledge and feel uncomfortable integrating genetics into their practice. Very little is known about perceived genetic knowledge and clinical comfort among Taiwanese nurses enrolled in a Registered Nurse to Bachelor of Science in Nursing program. To examine perceived knowledge and clinical comfort with genetics among Taiwanese nurses enrolled in a Registered Nurse to Bachelor of Science in Nursing program and to assess how genetics has been integrated into their past and current nursing programs. The study also sought to examine correlations among perceived knowledge, integration of genetics into the nursing curriculum, and clinical comfort with genetics. A descriptive, cross-sectional study. Taiwanese nurses enrolled in a Registered Nurse to Bachelor of Science in Nursing program were recruited. A total of 190 of 220 nurses returned the completed survey (86.36% response rate). Descriptive statistics and the Pearson product-moment correlation were used for data analysis. Most nurses indicated limited perceived knowledge and clinical comfort with genetics. Curricular hours focused on genetics in a current nursing program were greater than those in past nursing programs. The use of genetic materials, attendance at genetic workshops and conferences, and clinically relevant genetics in nursing practice significantly related with perceived knowledge and clinical comfort with genetics. However, there were no correlations between prior genetic-based health care, perceived knowledge, and clinical comfort with genetics. This study demonstrated the need for emphasizing genetic education and practice to ensure health-related professionals become knowledgeable about genetic information. Given the rapidly developing genetic revolution, nurses and other health care providers need to utilize genetic discoveries to optimize health outcomes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Successful technical trading agents using genetic programming.

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

Othling, Andrew S.; Kelly, John A.; Pryor, Richard J.

2004-10-01

Genetic programming (GP) has proved to be a highly versatile and useful tool for identifying relationships in data for which a more precise theoretical construct is unavailable. In this project, we use a GP search to develop trading strategies for agent based economic models. These strategies use stock prices and technical indicators, such as the moving average convergence/divergence and various exponentially weighted moving averages, to generate buy and sell signals. We analyze the effect of complexity constraints on the strategies as well as the relative performance of various indicators. We also present innovations in the classical genetic programming algorithm thatmore » appear to improve convergence for this problem. Technical strategies developed by our GP algorithm can be used to control the behavior of agents in economic simulation packages, such as ASPEN-D, adding variety to the current market fundamentals approach. The exploitation of arbitrage opportunities by technical analysts may help increase the efficiency of the simulated stock market, as it does in the real world. By improving the behavior of simulated stock markets, we can better estimate the effects of shocks to the economy due to terrorism or natural disasters.« less

Long-term on-farm participatory maize breeding by stratified mass selection retains molecular diversity while improving agronomic performance.

PubMed

Alves, Mara Lisa; Belo, Maria; Carbas, Bruna; Brites, Cláudia; Paulo, Manuel; Mendes-Moreira, Pedro; Brites, Carla; Bronze, Maria do Rosário; Šatović, Zlatko; Vaz Patto, Maria Carlota

2018-02-01

Modern maize breeding programs gave rise to genetically uniform varieties that can affect maize's capacity to cope with increasing climate unpredictability. Maize populations, genetically more heterogeneous, can evolve and better adapt to a broader range of edaphic-climatic conditions. These populations usually suffer from low yields; it is therefore desirable to improve their agronomic performance while maintaining their valuable diversity levels. With this objective, a long-term participatory breeding/on-farm conservation program was established in Portugal. In this program, maize populations were subject to stratified mass selection. This work aimed to estimate the effect of on-farm stratified mass selection on the agronomic performance, quality, and molecular diversity of two historical maize populations. Multilocation field trials, comparing the initial populations with the derived selection cycles, showed that this selection methodology led to agronomic improvement for one of the populations. The molecular diversity analysis, using microsatellites, revealed that overall genetic diversity in both populations was maintained throughout selection. The comparison of quality parameters between the initial populations and the derived selection cycles was made using kernel from a common-garden experiment. This analysis showed that the majority of the quality traits evaluated progressed erratically over time. In conclusion, this breeding approach, through simple and low-cost methodologies, proved to be an alternative strategy for genetic resources' on-farm conservation.

Gene variants associated with antisocial behaviour: A latent variable approach

PubMed Central

Bentley, Mary Jane; Lin, Haiqun; Fernandez, Thomas V.; Lee, Maria; Yrigollen, Carolyn M.; Pakstis, Andrew J.; Katsovich, Liliya; Olds, David L.; Grigorenko, Elena L.; Leckman, James F.

2013-01-01

Objective The aim of this study was to determine if a latent variable approach might be useful in identifying shared variance across genetic risk alleles that is associated with antisocial behaviour at age 15 years. Methods Using a conventional latent variable approach, we derived an antisocial phenotype in 328 adolescents utilizing data from a 15-year follow-up of a randomized trial of a prenatal and infancy nurse-home visitation program in Elmira, New York. We then investigated, via a novel latent variable approach, 450 informative genetic polymorphisms in 71 genes previously associated with antisocial behaviour, drug use, affiliative behaviours, and stress response in 241 consenting individuals for whom DNA was available. Haplotype and Pathway analyses were also performed. Results Eight single-nucleotide polymorphisms (SNPs) from 8 genes contributed to the latent genetic variable that in turn accounted for 16.0% of the variance within the latent antisocial phenotype. The number of risk alleles was linearly related to the latent antisocial variable scores. Haplotypes that included the putative risk alleles for all 8 genes were also associated with higher latent antisocial variable scores. In addition, 33 SNPs from 63 of the remaining genes were also significant when added to the final model. Many of these genes interact on a molecular level, forming molecular networks. The results support a role for genes related to dopamine, norepinephrine, serotonin, glutamate, opioid, and cholinergic signaling as well as stress response pathways in mediating susceptibility to antisocial behaviour. Conclusions This preliminary study supports use of relevant behavioural indicators and latent variable approaches to study the potential “co-action” of gene variants associated with antisocial behaviour. It also underscores the cumulative relevance of common genetic variants for understanding the etiology of complex behaviour. If replicated in future studies, this approach may allow the identification of a ‘shared’ variance across genetic risk alleles associated with complex neuropsychiatric dimensional phenotypes using relatively small numbers of well-characterized research participants. PMID:23822756

Adapting legume crops to climate change using genomic approaches.

PubMed

Mousavi-Derazmahalleh, Mahsa; Bayer, Philipp E; Hane, James K; Valliyodan, Babu; Nguyen, Henry T; Nelson, Matthew N; Erskine, William; Varshney, Rajeev K; Papa, Roberto; Edwards, David

2018-03-30

Our agricultural system and hence food security is threatened by combination of events, such as increasing population, the impacts of climate change, and the need to a more sustainable development. Evolutionary adaptation may help some species to overcome environmental changes through new selection pressures driven by climate change. However, success of evolutionary adaptation is dependent on various factors, one of which is the extent of genetic variation available within species. Genomic approaches provide an exceptional opportunity to identify genetic variation that can be employed in crop improvement programs. In this review, we illustrate some of the routinely used genomics-based methods as well as recent breakthroughs, which facilitate assessment of genetic variation and discovery of adaptive genes in legumes. Although additional information is needed, the current utility of selection tools indicate a robust ability to utilize existing variation among legumes to address the challenges of climate uncertainty. © 2018 The Authors. Plant, Cell & Environment Published by John Wiley & Sons Ltd.

IMPACT: Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets, Complementary/Innovative Treatments, and Therapeutic Modalities

DTIC Science & Technology

2013-02-01

therapies (surgery, radiation and chemotherapy) have reached a therapeutic ceiling in improving the five- year overall survival rate of non-small cell...poor understanding of the disease and its resistance to the therapy . Lung cancer is a heterogeneous disease, resulting from accumulated genetic... a new promising approach to treatment of lung cancer. The program project IMPACT has proposed to integrate targeted therapy in the lung cancer

Order Batching in Warehouses by Minimizing Total Tardiness: A Hybrid Approach of Weighted Association Rule Mining and Genetic Algorithms

PubMed Central

Taheri, Shahrooz; Mat Saman, Muhamad Zameri; Wong, Kuan Yew

2013-01-01

One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order picking. However, in practice, customer orders have to be completed by certain due dates in order to avoid tardiness which is neglected in most of the related scientific papers. Consequently, we proposed a novel solution approach in order to minimize tardiness which consists of four phases. First of all, weighted association rule mining has been used to calculate associations between orders with respect to their due date. Next, a batching model based on binary integer programming has been formulated to maximize the associations between orders within each batch. Subsequently, the order picking phase will come up which used a Genetic Algorithm integrated with the Traveling Salesman Problem in order to identify the most suitable travel path. Finally, the Genetic Algorithm has been applied for sequencing the constructed batches in order to minimize tardiness. Illustrative examples and comparisons are presented to demonstrate the proficiency and solution quality of the proposed approach. PMID:23864823

Order batching in warehouses by minimizing total tardiness: a hybrid approach of weighted association rule mining and genetic algorithms.

PubMed

Azadnia, Amir Hossein; Taheri, Shahrooz; Ghadimi, Pezhman; Saman, Muhamad Zameri Mat; Wong, Kuan Yew

2013-01-01

One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order picking. However, in practice, customer orders have to be completed by certain due dates in order to avoid tardiness which is neglected in most of the related scientific papers. Consequently, we proposed a novel solution approach in order to minimize tardiness which consists of four phases. First of all, weighted association rule mining has been used to calculate associations between orders with respect to their due date. Next, a batching model based on binary integer programming has been formulated to maximize the associations between orders within each batch. Subsequently, the order picking phase will come up which used a Genetic Algorithm integrated with the Traveling Salesman Problem in order to identify the most suitable travel path. Finally, the Genetic Algorithm has been applied for sequencing the constructed batches in order to minimize tardiness. Illustrative examples and comparisons are presented to demonstrate the proficiency and solution quality of the proposed approach.

An alternative approach for neural network evolution with a genetic algorithm: crossover by combinatorial optimization.

PubMed

García-Pedrajas, Nicolás; Ortiz-Boyer, Domingo; Hervás-Martínez, César

2006-05-01

In this work we present a new approach to crossover operator in the genetic evolution of neural networks. The most widely used evolutionary computation paradigm for neural network evolution is evolutionary programming. This paradigm is usually preferred due to the problems caused by the application of crossover to neural network evolution. However, crossover is the most innovative operator within the field of evolutionary computation. One of the most notorious problems with the application of crossover to neural networks is known as the permutation problem. This problem occurs due to the fact that the same network can be represented in a genetic coding by many different codifications. Our approach modifies the standard crossover operator taking into account the special features of the individuals to be mated. We present a new model for mating individuals that considers the structure of the hidden layer and redefines the crossover operator. As each hidden node represents a non-linear projection of the input variables, we approach the crossover as a problem on combinatorial optimization. We can formulate the problem as the extraction of a subset of near-optimal projections to create the hidden layer of the new network. This new approach is compared to a classical crossover in 25 real-world problems with an excellent performance. Moreover, the networks obtained are much smaller than those obtained with classical crossover operator.

Evaluation of two-year Jewish genetic disease screening program in Atlanta: insight into community genetic screening approaches.

PubMed

Shao, Yunru; Liu, Shuling; Grinzaid, Karen

2015-04-01

Improvements in genetic testing technologies have led to the development of expanded carrier screening panels for the Ashkenazi Jewish population; however, there are major inconsistencies in current screening practices. A 2-year pilot program was launched in Atlanta in 2010 to promote and facilitate screening for 19 Jewish genetic diseases. We analyzed data from this program, including participant demographics and outreach efforts. This retrospective analysis is based on a de-identified dataset of 724 screenees. Data were obtained through medical chart review and questionnaires and included demographic information, screening results, response to outreach efforts, and follow-up behavior and preferences. We applied descriptive analysis, chi-square tests, and logistic regression to analyze the data and compare findings with published literature. The majority of participants indicated that they were not pregnant or did not have a partner who was pregnant were affiliated with Jewish organizations and reported 100 % AJ ancestry. Overall, carrier frequency was 1 in 3.9. Friends, rabbis, and family members were the most common influencers of the decision to receive screening. People who were older, had a history of pregnancy, and had been previously screened were more likely to educate others (all p < 0.05). Analysis of this 2-year program indicated that people who are ready to have children or expand their families are more likely to get screened and encourage others to be screened. The most effective outreach efforts targeted influencers who then encouraged screening in the target population. Educating influencers and increasing overall awareness were the most effective outreach strategies.

Knowledge of Genetics and Attitudes toward Genetic Testing among College Students in Saudi Arabia.

PubMed

Olwi, Duaa; Merdad, Leena; Ramadan, Eman

2016-01-01

Genetic testing has been gradually permeating the practice of medicine. Health-care providers may be confronted with new genetic approaches that require genetically informed decisions which will be influenced by patients' knowledge of genetics and their attitudes toward genetic testing. This study assesses the knowledge of genetics and attitudes toward genetic testing among college students. A cross-sectional study was conducted using a multistage stratified sample of 920 senior college students enrolled at King Abdulaziz University, Saudi Arabia. Information regarding knowledge of genetics, attitudes toward genetic testing, and sociodemographic data were collected using a self-administered questionnaire. In general, students had a good knowledge of genetics but lacked some fundamentals of genetics. The majority of students showed positive attitudes toward genetic testing, but some students showed negative attitudes toward certain aspects of genetic testing such as resorting to abortion in the case of an untreatable major genetic defect in an unborn fetus. The main significant predictors of knowledge were faculty, gender, academic year, and some prior awareness of 'genetic testing'. The main significant predictors of attitudes were gender, academic year, grade point average, and some prior awareness of 'genetic testing'. The knowledge of genetics among college students was higher than has been reported in other studies, and the attitudes toward genetic testing were fairly positive. Genetics educational programs that target youths may improve knowledge of genetics and create a public perception that further supports genetic testing. © 2016 S. Karger AG, Basel.

An ecological genetic delineation of local seed-source provenance for ecological restoration

PubMed Central

Krauss, Siegfried L; Sinclair, Elizabeth A; Bussell, John D; Hobbs, Richard J

2013-01-01

An increasingly important practical application of the analysis of spatial genetic structure within plant species is to help define the extent of local provenance seed collection zones that minimize negative impacts in ecological restoration programs. Here, we derive seed sourcing guidelines from a novel range-wide assessment of spatial genetic structure of 24 populations of Banksia menziesii (Proteaceae), a widely distributed Western Australian tree of significance in local ecological restoration programs. An analysis of molecular variance (AMOVA) of 100 amplified fragment length polymorphism (AFLP) markers revealed significant genetic differentiation among populations (ΦPT = 0.18). Pairwise population genetic dissimilarity was correlated with geographic distance, but not environmental distance derived from 15 climate variables, suggesting overall neutrality of these markers with regard to these climate variables. Nevertheless, Bayesian outlier analysis identified four markers potentially under selection, although these were not correlated with the climate variables. We calculated a global R-statistic using analysis of similarities (ANOSIM) to test the statistical significance of population differentiation and to infer a threshold seed collection zone distance of ∼60 km (all markers) and 100 km (outlier markers) when genetic distance was regressed against geographic distance. Population pairs separated by >60 km were, on average, twice as likely to be significantly genetically differentiated than population pairs separated by <60 km, suggesting that habitat-matched sites within a 30-km radius around a restoration site genetically defines a local provenance seed collection zone for B. menziesii. Our approach is a novel probability-based practical solution for the delineation of a local seed collection zone to minimize negative genetic impacts in ecological restoration. PMID:23919158

Multivariate approach in popcorn genotypes using the Ward-MLM strategy: morpho-agronomic analysis and incidence of Fusarium spp.

PubMed

Kurosawa, R N F; do Amaral Junior, A T; Silva, F H L; Dos Santos, A; Vivas, M; Kamphorst, S H; Pena, G F

2017-02-08

The multivariate analyses are useful tools to estimate the genetic variability between accessions. In the breeding programs, the Ward-Modified Location Model (MLM) multivariate method has been a powerful strategy to quantify variability using quantitative and qualitative variables simultaneously. The present study was proposed in view of the dearth of information about popcorn breeding programs under a multivariate approach using the Ward-MLM methodology. The objective of this study was thus to estimate the genetic diversity among 37 genotypes of popcorn aiming to identify divergent groups associated with morpho-agronomic traits and traits related to resistance to Fusarium spp. To this end, 7 qualitative and 17 quantitative variables were analyzed. The experiment was conducted in 2014, at Universidade Estadual do Norte Fluminense, located in Campos dos Goytacazes, RJ, Brazil. The Ward-MLM strategy allowed the identification of four groups as follows: Group I with 10 genotypes, Group II with 11 genotypes, Group III with 9 genotypes, and Group IV with 7 genotypes. Group IV was distant in relation to the other groups, while groups I, II, and III were near. The crosses between genotypes from the other groups with those of group IV allow an exploitation of heterosis. The Ward-MLM strategy provided an appropriate grouping of genotypes; ear weight, ear diameter, and grain yield were the traits that most contributed to the analysis of genetic diversity.

Invited review: Current state of genetic improvement in dairy sheep.

PubMed

Carta, A; Casu, Sara; Salaris, S

2009-12-01

Dairy sheep have been farmed traditionally in the Mediterranean basin in southern Europe, central Europe, eastern Europe, and in Near East countries. Currently, dairy sheep farming systems vary from extensive to intensive according to the economic relevance of the production chain and the specific environment and breed. Modern breeding programs were conceived in the 1960s. The most efficient selection scheme for local dairy sheep breeds is based on pyramidal management of the population with the breeders of nucleus flocks at the top, where pedigree and official milk recording, artificial insemination, controlled natural mating, and breeding value estimation are carried out to generate genetic progress. The genetic progress is then transferred to the commercial flocks through artificial insemination or natural-mating rams. Increasing milk yield is still the most profitable breeding objective for several breeds. Almost all milk is used for cheese production and, consequently, milk content traits are very important. Moreover, other traits are gaining interest for selection: machine milking ability and udder morphology, resistance to diseases (mastitis, internal parasites, scrapie), and traits related to the nutritional value of milk (fatty acid composition). Current breeding programs based on the traditional quantitative approach have achieved appreciable genetic gains for milk yield. In many cases, further selection goals such as milk composition, udder morphology, somatic cell count, and scrapie resistance have been implemented. However, the possibility of including other traits of selective interest is limited by high recording costs. Also, the organizational effort needed to apply the traditional quantitative approach limits the diffusion of current selection programs outside the European Mediterranean area. In this context, the application of selection schemes assisted by molecular information, to improve either traditional dairy traits or traits costly to record, seems to be attractive in dairy sheep. At the moment, the most effective strategy seems to be the strengthening of research projects aimed at finding causal mutations along the genes affecting traits of economic importance. However, genome-wide selection seems to be unfeasible in most dairy sheep breeds.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-01-01

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

Pediatric Predispositional Genetic Risk Communication: Potential Utility for Prevention and Control of Melanoma Risk as an Exemplar.

PubMed

Wu, Yelena P; Mays, Darren; Kohlmann, Wendy; Tercyak, Kenneth P

2017-10-01

Predispositional genetic testing among minor children is intensely debated due to the potential benefits and harms of providing this type of genetic information to children and their families. Existing guidelines on pediatric genetic testing state that predispositional testing could be appropriate for minors if preventive services exist that mitigate children's risk for or severity of the health condition in question. We use the example of hereditary melanoma to illustrate the rationale for and potential application of genetic risk communication for an adult-onset cancer to a pediatric population where childhood behaviors may reduce risk of disease later in life. We draw from the adult melanoma genetic risk communication and pediatric health behavior change literatures to suggest ways in which genetic test reporting and complementary education could be delivered to children who carry a hereditary risk for melanoma and their families in order to foster children's engagement in melanoma preventive behaviors. Genetic discoveries will continue to yield new opportunities to provide predispositional genetic risk information to unaffected individuals, including children, and could be delivered within programs that provide personalized and translational approaches to cancer prevention.

Combining US and Brazilian microsatellite data for a meta-analysis of sheep (Ovis aries) breed diversity: facilitating the FAO Global Plan of Action for Conserving Animal Genetic Resources.

PubMed

Paiva, Samuel Rezende; Mariante, Arthur da Silva; Blackburn, Harvey D

2011-01-01

Microsatellites are commonly used to understand genetic diversity among livestock populations. Nevertheless, most studies have involved the processing of samples in one laboratory or with common standards across laboratories. Our objective was to identify an approach to facilitate the merger of microsatellite data for cross-country comparison of genetic resources when samples were not evaluated in a single laboratory. Eleven microsatellites were included in the analysis of 13 US and 9 Brazilian sheep breeds (N = 706). A Bayesian approach was selected and evaluated with and without a shared set of samples analyzed by each country. All markers had a posterior probability of greater than 0.5, which was higher than predicted as reasonable by the software used. Sensitivity analysis indicated no difference between results with or without shared samples. Cluster analysis showed breeds to be partitioned by functional groups of hair, meat, or wool types (K = 7 and 12 of STRUCTURE). Cross-country comparison of hair breeds indicated substantial genetic distances and within breed variability. The selected approach can facilitate the merger and analysis of microsatellite data for cross-country comparison and extend the utility of previously collected molecular markers. In addition, the result of this type of analysis can be used in new and existing conservation programs.

Genomics screens for metastasis genes

PubMed Central

Yan, Jinchun; Huang, Qihong

2014-01-01

Metastasis is responsible for most cancer mortality. The process of metastasis is complex, requiring the coordinated expression and fine regulation of many genes in multiple pathways in both the tumor and host tissues. Identification and characterization of the genetic programs that regulate metastasis is critical to understanding the metastatic process and discovering molecular targets for the prevention and treatment of metastasis. Genomic approaches and functional genomic analyses can systemically discover metastasis genes. In this review, we summarize the genetic tools and methods that have been used to identify and characterize the genes that play critical roles in metastasis. PMID:22684367

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

Nord, Alex S.; Pattabiraman, Kartik; Visel, Axel

The forebrain is the seat of higher-order brain functions, and many human neuropsychiatric disorders are due to genetic defects affecting forebrain development, making it imperative to understand the underlying genetic circuitry. We report that recent progress now makes it possible to begin fully elucidating the genomic regulatory mechanisms that control forebrain gene expression. Here, we discuss the current knowledge of how transcription factors drive gene expression programs through their interactions with cis-acting genomic elements, such as enhancers; how analyses of chromatin and DNA modifications provide insights into gene expression states; and how these approaches yield insights into the evolution ofmore » the human brain.« less

Impact of human genome initiative-derived technology on genetic testing, screening and counseling: Cultural, ethical and legal issues

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

Trottier, R.W.; Hodgin, F.C.; Imara, M.

Genetic medical services provided by the Georgia Division of Public Health in two northern and two central districts are compared to services provided in a district in which a tertiary care facility is located. Genetics outreach public health nurses play key roles in Georgia's system of Children's Health Services Genetics Program, including significant roles as counselors and information sources on special needs social services and support organizations. Unique features of individual health districts, (e.g., the changing face of some rural communities in ethnocultural diversity and socioeconomic character), present new challenges to current and future genetics services delivery. Preparedness as tomore » educational needs of both health professionals and the lay population is of foremost concern in light of the ever expanding knowledge and technology in medical genetics. Perspectives on genetics and an overview of services offered by a local private sector counselor are included for comparison to state supported services. The nature of the interactions which transpire between private and public genetic services resources in Georgia will be described. A special focus of this research includes issues associated with sickle cell disease newborn screening service delivery process in Georgia, with particular attention paid to patient follow-up and transition to primary care. Of particular interest to this focus is the problem of loss to follow-up in the current system. Critical factors in education and counseling of sickle cell patients and the expectations of expanding roles of primary care physicians are discussed. The Florida approach to the delivery of genetic services contrasts to the Georgia model by placing more emphasis on a consultant-specialist team approach.« less

Impact of human genome initiative-derived technology on genetic testing, screening and counseling: Cultural, ethical and legal issues. Progress report

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

Trottier, R.W.; Hodgin, F.C.; Imara, M.

Genetic medical services provided by the Georgia Division of Public Health in two northern and two central districts are compared to services provided in a district in which a tertiary care facility is located. Genetics outreach public health nurses play key roles in Georgia`s system of Children`s Health Services Genetics Program, including significant roles as counselors and information sources on special needs social services and support organizations. Unique features of individual health districts, (e.g., the changing face of some rural communities in ethnocultural diversity and socioeconomic character), present new challenges to current and future genetics services delivery. Preparedness as tomore » educational needs of both health professionals and the lay population is of foremost concern in light of the ever expanding knowledge and technology in medical genetics. Perspectives on genetics and an overview of services offered by a local private sector counselor are included for comparison to state supported services. The nature of the interactions which transpire between private and public genetic services resources in Georgia will be described. A special focus of this research includes issues associated with sickle cell disease newborn screening service delivery process in Georgia, with particular attention paid to patient follow-up and transition to primary care. Of particular interest to this focus is the problem of loss to follow-up in the current system. Critical factors in education and counseling of sickle cell patients and the expectations of expanding roles of primary care physicians are discussed. The Florida approach to the delivery of genetic services contrasts to the Georgia model by placing more emphasis on a consultant-specialist team approach.« less

Testing the structure of a hydrological model using Genetic Programming

NASA Astrophysics Data System (ADS)

Selle, Benny; Muttil, Nitin

2011-01-01

SummaryGenetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that Genetic Programming can be used to test the structure of hydrological models and to identify dominant processes in hydrological systems. To test this, Genetic Programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, watertable depths and water ponding times during surface irrigation. Using Genetic Programming, a simple model of deep percolation was recurrently evolved in multiple Genetic Programming runs. This simple and interpretable model supported the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that Genetic Programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

An economic evaluation of a genetic screening program for Tay-Sachs disease.

PubMed Central

Nelson, W B; Swint, J M; Caskey, C T

1978-01-01

The resolution of policy questions relating to medical genetic screening programs will not be without considerable difficulty. Examples include such issues as the optimal degree of screening program expansion, the relative values of screening for different genetic diseases, the appropriate sources of program funding (public vs. private), and the relative value of funding expanded genetic screening programs vs. research directed toward elimination of genetic traits themselves. Information on the net impact of the relevant alternatives is greatly needed, and this need will increase if the National Genetics Act receives funding approval. We have provided what is hopefully a contribution toward this end. While our analysis pertains to a specific disease and a specific screening program for that disease, the methodology is readily generalizable to other genetic diseases, as well as programs of any size or structure. Hopefully, this will serve to stimulate further research efforts that we believe are needed for the objective consideration of resource allocation alternatives. PMID:418675

An economic evaluation of a genetic screening program for Tay-Sachs disease.

PubMed

Nelson, W B; Swint, J M; Caskey, C T

1978-03-01

The resolution of policy questions relating to medical genetic screening programs will not be without considerable difficulty. Examples include such issues as the optimal degree of screening program expansion, the relative values of screening for different genetic diseases, the appropriate sources of program funding (public vs. private), and the relative value of funding expanded genetic screening programs vs. research directed toward elimination of genetic traits themselves. Information on the net impact of the relevant alternatives is greatly needed, and this need will increase if the National Genetics Act receives funding approval. We have provided what is hopefully a contribution toward this end. While our analysis pertains to a specific disease and a specific screening program for that disease, the methodology is readily generalizable to other genetic diseases, as well as programs of any size or structure. Hopefully, this will serve to stimulate further research efforts that we believe are needed for the objective consideration of resource allocation alternatives.

Synthetic biology: advancing the design of diverse genetic systems

PubMed Central

Wang, Yen-Hsiang; Wei, Kathy Y.; Smolke, Christina D.

2013-01-01

A main objective of synthetic biology is to make the process of designing genetically-encoded biological systems more systematic, predictable, robust, scalable, and efficient. The examples of genetic systems in the field vary widely in terms of operating hosts, compositional approaches, and network complexity, ranging from a simple genetic switch to search-and-destroy systems. While significant advances in synthesis capabilities support the potential for the implementation of pathway- and genome-scale programs, several design challenges currently restrict the scale of systems that can be reasonably designed and implemented. Synthetic biology offers much promise in developing systems to address challenges faced in manufacturing, the environment and sustainability, and health and medicine, but the realization of this potential is currently limited by the diversity of available parts and effective design frameworks. As researchers make progress in bridging this design gap, advances in the field hint at ever more diverse applications for biological systems. PMID:23413816

Genetic and Epigenetic Regulation of Human Cardiac Reprogramming and Differentiation in Regenerative Medicine

PubMed Central

Burridge, Paul W.; Sharma, Arun; Wu, Joseph C.

2016-01-01

Regeneration or replacement of lost cardiomyocytes within the heart has the potential to revolutionize cardiovascular medicine. Numerous methodologies have been used to achieve this aim, including the engraftment of bone marrow- and heart-derived cells as well as the identification of modulators of adult cardiomyocyte proliferation. Recently, the conversion of human somatic cells into induced pluripotent stem cells and induced cardiomyocyte-like cells has transformed potential approaches toward this goal, and the engraftment of cardiac progenitors derived from human embryonic stem cells into patients is now feasible. Here we review recent advances in our understanding of the genetic and epigenetic control of human cardiogenesis, cardiac differentiation, and the induced reprogramming of somatic cells to cardiomyocytes. We also cover genetic programs for inducing the proliferation of endogenous cardiomyocytes and discuss the genetic state of cells used in cardiac regenerative medicine. PMID:26631515

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.

Probabilistic expert systems for forensic inference from DNA markers in horses: applications to confirm genealogies with lack of genetic data.

PubMed

Dobosz, Marina; Bocci, Chiara; Bonuglia, Margherita; Grasso, Cinzia; Merigioli, Sara; Russo, Alessandra; De Iuliis, Paolo

2010-01-01

Microsatellites have been used for parentage testing and individual identification in forensic science because they are highly polymorphic and show abundant sequences dispersed throughout most eukaryotic nuclear genomes. At present, genetic testing based on DNA technology is used for most domesticated animals, including horses, to confirm identity, to determine parentage, and to validate registration certificates. But if genetic data of one of the putative parents are missing, verifying a genealogy could be questionable. The aim of this paper is to illustrate a new approach to analyze complex cases of disputed relationship with microsatellites markers. These cases were solved by analyzing the genotypes of the offspring and other horses' genotypes in the pedigrees of the putative dam/sire with probabilistic expert systems (PESs). PES was especially efficient in supplying reliable, error-free Bayesian probabilities in complex cases with missing pedigree data. One of these systems was developed for forensic purposes (FINEX program) and is particularly valuable in human analyses. We applied this program to parentage analysis in horses, and we will illustrate how different cases have been successfully worked out.

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

A genetic programming approach for Burkholderia Pseudomallei diagnostic pattern discovery

PubMed Central

Yang, Zheng Rong; Lertmemongkolchai, Ganjana; Tan, Gladys; Felgner, Philip L.; Titball, Richard

2009-01-01

Motivation: Finding diagnostic patterns for fighting diseases like Burkholderia pseudomallei using biomarkers involves two key issues. First, exhausting all subsets of testable biomarkers (antigens in this context) to find a best one is computationally infeasible. Therefore, a proper optimization approach like evolutionary computation should be investigated. Second, a properly selected function of the antigens as the diagnostic pattern which is commonly unknown is a key to the diagnostic accuracy and the diagnostic effectiveness in clinical use. Results: A conversion function is proposed to convert serum tests of antigens on patients to binary values based on which Boolean functions as the diagnostic patterns are developed. A genetic programming approach is designed for optimizing the diagnostic patterns in terms of their accuracy and effectiveness. During optimization, it is aimed to maximize the coverage (the rate of positive response to antigens) in the infected patients and minimize the coverage in the non-infected patients while maintaining the fewest number of testable antigens used in the Boolean functions as possible. The final coverage in the infected patients is 96.55% using 17 of 215 (7.4%) antigens with zero coverage in the non-infected patients. Among these 17 antigens, BPSL2697 is the most frequently selected one for the diagnosis of Burkholderia Pseudomallei. The approach has been evaluated using both the cross-validation and the Jack–knife simulation methods with the prediction accuracy as 93% and 92%, respectively. A novel approach is also proposed in this study to evaluate a model with binary data using ROC analysis. Contact: z.r.yang@ex.ac.uk PMID:19561021

Genetic programming based models in plant tissue culture: An addendum to traditional statistical approach.

PubMed

Mridula, Meenu R; Nair, Ashalatha S; Kumar, K Satheesh

2018-02-01

In this paper, we compared the efficacy of observation based modeling approach using a genetic algorithm with the regular statistical analysis as an alternative methodology in plant research. Preliminary experimental data on in vitro rooting was taken for this study with an aim to understand the effect of charcoal and naphthalene acetic acid (NAA) on successful rooting and also to optimize the two variables for maximum result. Observation-based modelling, as well as traditional approach, could identify NAA as a critical factor in rooting of the plantlets under the experimental conditions employed. Symbolic regression analysis using the software deployed here optimised the treatments studied and was successful in identifying the complex non-linear interaction among the variables, with minimalistic preliminary data. The presence of charcoal in the culture medium has a significant impact on root generation by reducing basal callus mass formation. Such an approach is advantageous for establishing in vitro culture protocols as these models will have significant potential for saving time and expenditure in plant tissue culture laboratories, and it further reduces the need for specialised background.

A New Approach in Downscaling Microwave Soil Moisture Product using Machine Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid

2016-04-01

Understating the soil moisture pattern has significant impact on flood modeling, drought monitoring, and irrigation management. Although satellite retrievals can provide an unprecedented spatial and temporal resolution of soil moisture at a global-scale, their soil moisture products (with a spatial resolution of 25-50 km) are inadequate for regional study, where a resolution of 1-10 km is needed. In this study, a downscaling approach using Genetic Programming (GP), a specialized version of Genetic Algorithm (GA), is proposed to improve the spatial resolution of satellite soil moisture products. The GP approach was applied over a test watershed in United States using the coarse resolution satellite data (25 km) from Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture products, the fine resolution data (1 km) from Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index, and ground based data including land surface temperature, vegetation and other potential physical variables. The results indicated the great potential of this approach to derive the fine resolution soil moisture information applicable for data assimilation and other regional studies.

Programming social behavior by the maternal fragile X protein.

PubMed

Zupan, B; Sharma, A; Frazier, A; Klein, S; Toth, M

2016-07-01

The developing fetus and neonate are highly sensitive to maternal environment. Besides the well-documented effects of maternal stress, nutrition and infections, maternal mutations, by altering the fetal, perinatal and/or early postnatal environment, can impact the behavior of genetically normal offspring. Mutation/premutation in the X-linked FMR1 (encoding the translational regulator FMRP) in females, although primarily responsible for causing fragile X syndrome (FXS) in their children, may also elicit such maternal effects. We showed that a deficit in maternal FMRP in mice results in hyperactivity in the genetically normal offspring. To test if maternal FMRP has a broader intergenerational effect, we measured social behavior, a core dimension of neurodevelopmental disorders, in offspring of FMRP-deficient dams. We found that male offspring of Fmr1(+/-) mothers, independent of their own Fmr1 genotype, exhibit increased approach and reduced avoidance toward conspecific strangers, reminiscent of 'indiscriminate friendliness' or the lack of stranger anxiety, diagnosed in neglected children and in patients with Asperger's and Williams syndrome. Furthermore, social interaction failed to activate mesolimbic/amygdala regions, encoding social aversion, in these mice, providing a neurobiological basis for the behavioral abnormality. This work identifies a novel role for FMRP that extends its function beyond the well-established genetic function into intergenerational non-genetic inheritance/programming of social behavior and the corresponding neuronal circuit. As FXS premutation and some psychiatric conditions that can be associated with reduced FMRP expression are more prevalent in mothers than full FMR1 mutation, our findings potentially broaden the significance of FMRP-dependent programming of social behavior beyond the FXS population. © 2016 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Large-Scale Bi-Level Strain Design Approaches and Mixed-Integer Programming Solution Techniques

PubMed Central

Kim, Joonhoon; Reed, Jennifer L.; Maravelias, Christos T.

2011-01-01

The use of computational models in metabolic engineering has been increasing as more genome-scale metabolic models and computational approaches become available. Various computational approaches have been developed to predict how genetic perturbations affect metabolic behavior at a systems level, and have been successfully used to engineer microbial strains with improved primary or secondary metabolite production. However, identification of metabolic engineering strategies involving a large number of perturbations is currently limited by computational resources due to the size of genome-scale models and the combinatorial nature of the problem. In this study, we present (i) two new bi-level strain design approaches using mixed-integer programming (MIP), and (ii) general solution techniques that improve the performance of MIP-based bi-level approaches. The first approach (SimOptStrain) simultaneously considers gene deletion and non-native reaction addition, while the second approach (BiMOMA) uses minimization of metabolic adjustment to predict knockout behavior in a MIP-based bi-level problem for the first time. Our general MIP solution techniques significantly reduced the CPU times needed to find optimal strategies when applied to an existing strain design approach (OptORF) (e.g., from ∼10 days to ∼5 minutes for metabolic engineering strategies with 4 gene deletions), and identified strategies for producing compounds where previous studies could not (e.g., malate and serine). Additionally, we found novel strategies using SimOptStrain with higher predicted production levels (for succinate and glycerol) than could have been found using an existing approach that considers network additions and deletions in sequential steps rather than simultaneously. Finally, using BiMOMA we found novel strategies involving large numbers of modifications (for pyruvate and glutamate), which sequential search and genetic algorithms were unable to find. The approaches and solution techniques developed here will facilitate the strain design process and extend the scope of its application to metabolic engineering. PMID:21949695

Large-scale bi-level strain design approaches and mixed-integer programming solution techniques.

PubMed

Kim, Joonhoon; Reed, Jennifer L; Maravelias, Christos T

2011-01-01

The use of computational models in metabolic engineering has been increasing as more genome-scale metabolic models and computational approaches become available. Various computational approaches have been developed to predict how genetic perturbations affect metabolic behavior at a systems level, and have been successfully used to engineer microbial strains with improved primary or secondary metabolite production. However, identification of metabolic engineering strategies involving a large number of perturbations is currently limited by computational resources due to the size of genome-scale models and the combinatorial nature of the problem. In this study, we present (i) two new bi-level strain design approaches using mixed-integer programming (MIP), and (ii) general solution techniques that improve the performance of MIP-based bi-level approaches. The first approach (SimOptStrain) simultaneously considers gene deletion and non-native reaction addition, while the second approach (BiMOMA) uses minimization of metabolic adjustment to predict knockout behavior in a MIP-based bi-level problem for the first time. Our general MIP solution techniques significantly reduced the CPU times needed to find optimal strategies when applied to an existing strain design approach (OptORF) (e.g., from ∼10 days to ∼5 minutes for metabolic engineering strategies with 4 gene deletions), and identified strategies for producing compounds where previous studies could not (e.g., malate and serine). Additionally, we found novel strategies using SimOptStrain with higher predicted production levels (for succinate and glycerol) than could have been found using an existing approach that considers network additions and deletions in sequential steps rather than simultaneously. Finally, using BiMOMA we found novel strategies involving large numbers of modifications (for pyruvate and glutamate), which sequential search and genetic algorithms were unable to find. The approaches and solution techniques developed here will facilitate the strain design process and extend the scope of its application to metabolic engineering.

Genetic variation in polyploid forage grass: Assessing the molecular genetic variability in the Paspalum genus

PubMed Central

2013-01-01

Background Paspalum (Poaceae) is an important genus of the tribe Paniceae, which includes several species of economic importance for foraging, turf and ornamental purposes, and has a complex taxonomical classification. Because of the widespread interest in several species of this genus, many accessions have been conserved in germplasm banks and distributed throughout various countries around the world, mainly for the purposes of cultivar development and cytogenetic studies. Correct identification of germplasms and quantification of their variability are necessary for the proper development of conservation and breeding programs. Evaluation of microsatellite markers in different species of Paspalum conserved in a germplasm bank allowed assessment of the genetic differences among them and assisted in their proper botanical classification. Results Seventeen new polymorphic microsatellites were developed for Paspalum atratum Swallen and Paspalum notatum Flüggé, twelve of which were transferred to 35 Paspalum species and used to evaluate their variability. Variable degrees of polymorphism were observed within the species. Based on distance-based methods and a Bayesian clustering approach, the accessions were divided into three main species groups, two of which corresponded to the previously described Plicatula and Notata Paspalum groups. In more accurate analyses of P. notatum accessions, the genetic variation that was evaluated used thirty simple sequence repeat (SSR) loci and revealed seven distinct genetic groups and a correspondence of these groups to the three botanical varieties of the species (P. notatum var. notatum, P. notatum var. saurae and P. notatum var. latiflorum). Conclusions The molecular genetic approach employed in this study was able to distinguish many of the different taxa examined, except for species that belong to the Plicatula group, which has historically been recognized as a highly complex group. Our molecular genetic approach represents a valuable tool for species identification in the initial assessment of germplasm as well as for characterization, conservation and successful species hybridization. PMID:23759066

Hierarchical structure of the Sicilian goats revealed by Bayesian analyses of microsatellite information.

PubMed

Siwek, M; Finocchiaro, R; Curik, I; Portolano, B

2011-02-01

Genetic structure and relationship amongst the main goat populations in Sicily (Girgentana, Derivata di Siria, Maltese and Messinese) were analysed using information from 19 microsatellite markers genotyped on 173 individuals. A posterior Bayesian approach implemented in the program STRUCTURE revealed a hierarchical structure with two clusters at the first level (Girgentana vs. Messinese, Derivata di Siria and Maltese), explaining 4.8% of variation (amovaФ(ST) estimate). Seven clusters nested within these first two clusters (further differentiations of Girgentana, Derivata di Siria and Maltese), explaining 8.5% of variation (amovaФ(SC) estimate). The analyses and methods applied in this study indicate their power to detect subtle population structure. © 2010 The Authors, Animal Genetics © 2010 Stichting International Foundation for Animal Genetics.

A collaborative approach to cancer risk assessment services using genetic counselor extenders in a multi-system community hospital.

PubMed

Cohen, Stephanie A; Nixon, Dawn M

2016-10-01

This study aimed to evaluate a unique approach to cancer risk assessment for improved access by smaller rural communities. Local, on-site nurse navigators were trained and utilized as genetic counselor extenders (GCEs) to provide basic risk assessment and offer BRCA1/2 genetic testing to select patients based on a triaging process in collaboration with board-certified genetic counselors (CGCs). From August 2012 to July 2014, 12,477 family history questionnaires representing 8937 unique patients presenting for a screening mammogram or new oncology appointment were triaged. Of these, 8.2 % patients were identified at increased risk for hereditary breast cancer, and 4.2 % were identified at increased risk for other hereditary causes of cancer. A total of 75 of 1130 at-risk patients identified (6.6 %) completed a genetic risk assessment appointment; 23 with a GCE and 52 with a CGC. A review of the completed genetic test requisition forms from a 9-year pre-collaboration time period found that 16 % (20/125) did not appear to meet genetic testing criteria. Overall, there was a fourfold increase in patients accessing genetic services in this study period compared to the pre-collaboration time period. Efficiency of this model was assessed by determining time spent by the CGC in all activities related to the collaboration, which amounted to approximately 16 h/month. Adjustments have been made and the program continues to be monitored for opportunities to improve efficiency. This study demonstrates the feasibility of CGCs and GCEs collaborating to improve access to quality services in an efficient manner.

SHIPS: Spectral Hierarchical Clustering for the Inference of Population Structure in Genetic Studies

PubMed Central

Bouaziz, Matthieu; Paccard, Caroline; Guedj, Mickael; Ambroise, Christophe

2012-01-01

Inferring the structure of populations has many applications for genetic research. In addition to providing information for evolutionary studies, it can be used to account for the bias induced by population stratification in association studies. To this end, many algorithms have been proposed to cluster individuals into genetically homogeneous sub-populations. The parametric algorithms, such as Structure, are very popular but their underlying complexity and their high computational cost led to the development of faster parametric alternatives such as Admixture. Alternatives to these methods are the non-parametric approaches. Among this category, AWclust has proven efficient but fails to properly identify population structure for complex datasets. We present in this article a new clustering algorithm called Spectral Hierarchical clustering for the Inference of Population Structure (SHIPS), based on a divisive hierarchical clustering strategy, allowing a progressive investigation of population structure. This method takes genetic data as input to cluster individuals into homogeneous sub-populations and with the use of the gap statistic estimates the optimal number of such sub-populations. SHIPS was applied to a set of simulated discrete and admixed datasets and to real SNP datasets, that are data from the HapMap and Pan-Asian SNP consortium. The programs Structure, Admixture, AWclust and PCAclust were also investigated in a comparison study. SHIPS and the parametric approach Structure were the most accurate when applied to simulated datasets both in terms of individual assignments and estimation of the correct number of clusters. The analysis of the results on the real datasets highlighted that the clusterings of SHIPS were the more consistent with the population labels or those produced by the Admixture program. The performances of SHIPS when applied to SNP data, along with its relatively low computational cost and its ease of use make this method a promising solution to infer fine-scale genetic patterns. PMID:23077494

Developing genetic competency in undergraduate nursing students through the context of human disease and the constructivist framework

NASA Astrophysics Data System (ADS)

Tribble, Leta Meole

Nowhere is the influence of genetics more extensively seen than in medicine. More precise diagnostic testing, prevention methods, and risk counseling have resulted from recent decades of genetics research, including the Human Genome Project (HGP). The expansion in genetics knowledge and related technologies will drive a major paradigm shift from diagnosis and treatment to preventive medicine. Resulting from this predicted shift are educational challenges for healthcare professionals including both physicians and nurses. The largest group of healthcare providers is registered professional nurses whose work allows a unique and holistic view of patients and families, often caring for patients throughout the life span. Nurses need to understand basic genetic concepts including the role of genes in common diseases, to identify individuals at risk through the collection of informed family histories, to provide information about genetic testing and informed consent, and to know when and how to make appropriate referrals to genetic specialists. The purpose of this study was to expand the clinical application and use of genetic principles in patient management and care. To do this, a survey of South Carolina nursing educators from twenty two nursing programs was conducted to determine the extent of genetic content in the curriculum. The second part of the study was teaching a semester course in human genetics to undergraduate nursing students, a need identified in the literature review and supported by results of the nursing programs survey. Through the use of clinical case studies, PBL activities, and "shrink wrapped" lectures, all congruent with the constructivist viewpoint of learning, student's objective post-intervention measurements indicated significant improvement in content knowledge with an effect size of 1.6 and significant improvement in their ability to analyze and draw the family history in a pedigree format. An attitudinal tool used to assess student preferences of teaching approaches indicated preference for all three constructivist methods over traditional lecture.

Testing the Structure of Hydrological Models using Genetic Programming

NASA Astrophysics Data System (ADS)

Selle, B.; Muttil, N.

2009-04-01

Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

PubMed

Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

2015-03-01

A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

Imperative of preventive measures addressing the life-cycle.

PubMed

Yajnik, Chittaranjan S

2009-01-01

The epidemiological characteristics of chronic non-communicable diseases (NCD) are fast changing. The prevalence has risen to unprecedented levels, and the young and the underprivileged are increasingly affected. The classic view of the etiology of NCD consists of a genetic susceptibility which is precipitated by aging and modern lifestyle. In a virtual absence of any methods to tackle genetic susceptibility, the preventive approach has so far been focused on the control of lifestyle factors in those at high risk (old, and those with positive family history and elevated risk factors). Such an approach might help high risk individuals, but is unlikely to curtail the burgeoning epidemic of obesity and diabetes. Recent research has suggested that susceptibility to NCD originates in early life through non-genetic mechanisms (fetal programming). Tackling these may offer an exciting opportunity to control the NCD epidemic by influencing the susceptibility in a more durable manner than only controlling the lifestyle factors in adult life. The imperative is to address the life cycle rather than concentrate on the end stages. Copyright (c) 2009 S. Karger AG, Basel.

Approaching Science by Watching TV: What Do Entertainment Programs Contribute to Viewers' Competence in Genetic Engineering?

ERIC Educational Resources Information Center

Weinmann, Carina; Löb, Charlotte; Mattheiß, Tamara; Vorderer, Peter

2013-01-01

This study examined the potential of entertainment-education (E-E) for promoting engagement with a science issue. It was assumed that certain entertaining features of a media experience increase viewers' perceived knowledge about an issue. Drawing on different theoretical models of E-E and on persuasive effects of narrative media messages, three…

Discrete Optimization of Electronic Hyperpolarizabilities in a Chemical Subspace

DTIC Science & Technology

2009-05-01

molecular design. Methods for optimization in discrete spaces have been studied extensively and recently reviewed ( 5). Optimization methods include...integer programming, as in branch-and-bound techniques (including dead-end elimination [ 6]), simulated annealing ( 7), and genetic algorithms ( 8...These algorithms have found renewed interest and application in molecular and materials design (9- 12) . Recently, new approaches have been

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Genetic programming approach to evaluate complexity of texture images

NASA Astrophysics Data System (ADS)

Ciocca, Gianluigi; Corchs, Silvia; Gasparini, Francesca

2016-11-01

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

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.

Multi-objective evolutionary optimization for constructing neural networks for virtual reality visual data mining: application to geophysical prospecting.

PubMed

Valdés, Julio J; Barton, Alan J

2007-05-01

A method for the construction of virtual reality spaces for visual data mining using multi-objective optimization with genetic algorithms on nonlinear discriminant (NDA) neural networks is presented. Two neural network layers (the output and the last hidden) are used for the construction of simultaneous solutions for: (i) a supervised classification of data patterns and (ii) an unsupervised similarity structure preservation between the original data matrix and its image in the new space. A set of spaces are constructed from selected solutions along the Pareto front. This strategy represents a conceptual improvement over spaces computed by single-objective optimization. In addition, genetic programming (in particular gene expression programming) is used for finding analytic representations of the complex mappings generating the spaces (a composition of NDA and orthogonal principal components). The presented approach is domain independent and is illustrated via application to the geophysical prospecting of caves.

Artificial intelligence in peer review: How can evolutionary computation support journal editors?

PubMed

Mrowinski, Maciej J; Fronczak, Piotr; Fronczak, Agata; Ausloos, Marcel; Nedic, Olgica

2017-01-01

With the volume of manuscripts submitted for publication growing every year, the deficiencies of peer review (e.g. long review times) are becoming more apparent. Editorial strategies, sets of guidelines designed to speed up the process and reduce editors' workloads, are treated as trade secrets by publishing houses and are not shared publicly. To improve the effectiveness of their strategies, editors in small publishing groups are faced with undertaking an iterative trial-and-error approach. We show that Cartesian Genetic Programming, a nature-inspired evolutionary algorithm, can dramatically improve editorial strategies. The artificially evolved strategy reduced the duration of the peer review process by 30%, without increasing the pool of reviewers (in comparison to a typical human-developed strategy). Evolutionary computation has typically been used in technological processes or biological ecosystems. Our results demonstrate that genetic programs can improve real-world social systems that are usually much harder to understand and control than physical systems.

Texture segmentation by genetic programming.

PubMed

Song, Andy; Ciesielski, Vic

2008-01-01

This paper describes a texture segmentation method using genetic programming (GP), which is one of the most powerful evolutionary computation algorithms. By choosing an appropriate representation texture, classifiers can be evolved without computing texture features. Due to the absence of time-consuming feature extraction, the evolved classifiers enable the development of the proposed texture segmentation algorithm. This GP based method can achieve a segmentation speed that is significantly higher than that of conventional methods. This method does not require a human expert to manually construct models for texture feature extraction. In an analysis of the evolved classifiers, it can be seen that these GP classifiers are not arbitrary. Certain textural regularities are captured by these classifiers to discriminate different textures. GP has been shown in this study as a feasible and a powerful approach for texture classification and segmentation, which are generally considered as complex vision tasks.

Feature generation using genetic programming with application to fault classification.

PubMed

Guo, Hong; Jack, Lindsay B; Nandi, Asoke K

2005-02-01

One of the major challenges in pattern recognition problems is the feature extraction process which derives new features from existing features, or directly from raw data in order to reduce the cost of computation during the classification process, while improving classifier efficiency. Most current feature extraction techniques transform the original pattern vector into a new vector with increased discrimination capability but lower dimensionality. This is conducted within a predefined feature space, and thus, has limited searching power. Genetic programming (GP) can generate new features from the original dataset without prior knowledge of the probabilistic distribution. In this paper, a GP-based approach is developed for feature extraction from raw vibration data recorded from a rotating machine with six different conditions. The created features are then used as the inputs to a neural classifier for the identification of six bearing conditions. Experimental results demonstrate the ability of GP to discover autimatically the different bearing conditions using features expressed in the form of nonlinear functions. Furthermore, four sets of results--using GP extracted features with artificial neural networks (ANN) and support vector machines (SVM), as well as traditional features with ANN and SVM--have been obtained. This GP-based approach is used for bearing fault classification for the first time and exhibits superior searching power over other techniques. Additionaly, it significantly reduces the time for computation compared with genetic algorithm (GA), therefore, makes a more practical realization of the solution.

The use of integer programming to select bulls across breeding companies with volume price discounts.

PubMed

McConnel, M B; Galligan, D T

2004-10-01

Optimization programs are currently used to aid in the selection of bulls to be used in herd breeding programs. While these programs offer a systematic approach to the problem of semen selection, they ignore the impact of volume discounts. Volume discounts are discounts that vary depending on the number of straws purchased. The dynamic nature of volume discounts means that, in order to be adequately accounted for, they must be considered in the optimization routine. Failing to do this creates a missed economic opportunity because the potential benefits of optimally selecting and combining breeding company discount opportunities are not captured. To address these issues, an integer program was created which used binary decision variables to incorporate the effects of quantity discounts into the optimization program. A consistent set of trait criteria was used to select a group of bulls from 3 sample breeding companies. Three different selection programs were used to select the bulls, 2 traditional methods and the integer method. After the discounts were applied using each method, the integer program resulted in the lowest cost portfolio of bulls. A sensitivity analysis showed that the integer program also resulted in a low cost portfolio when the genetic trait goals were changed to be more or less stringent. In the sample application, a net benefit of the new approach over the traditional approaches was a 12.3 to 20.0% savings in semen cost.

Looking for Trouble: Preventive Genomic Sequencing in the General Population and the Role of Patient Choice

PubMed Central

Lázaro-Muñoz, Gabriel; Conley, John M.; Davis, Arlene M.; Van Riper, Marcia; Walker, Rebecca L.; Juengst, Eric T.

2015-01-01

Advances in genomics have led to calls for developing population-based preventive genomic sequencing (PGS) programs with the goal of identifying genetic health risks in adults without known risk factors. One critical issue for minimizing the harms and maximizing the benefits of PGS is determining the kind and degree of control individuals should have over the generation, use, and handling of their genomic information. In this article we examine whether PGS programs should offer individuals the opportunity to selectively opt-out of the sequencing or analysis of specific genomic conditions (the menu approach) or whether PGS should be implemented using an all-or-nothing panel approach. We conclude that any responsible scale up of PGS will require a menu approach that may seem impractical to some, but which draws its justification from a rich mix of normative, legal, and practical considerations. PMID:26147254

Genetic Counseling as an Educational Process.

ERIC Educational Resources Information Center

Eddy, James M.; St. Pierre, Richard

Historically genetic counseling programs have not included strong educational components or sound educational foundations. This paper deals with some of the drawbacks of current genetic counseling programs and the implications for education in the genetic counseling process. The author adopts a broad definition of genetic counseling which…

Genomic Perspectives of Transcriptional Regulation in Forebrain Development

DOE PAGES

Nord, Alex S.; Pattabiraman, Kartik; Visel, Axel; ...

2015-01-07

The forebrain is the seat of higher-order brain functions, and many human neuropsychiatric disorders are due to genetic defects affecting forebrain development, making it imperative to understand the underlying genetic circuitry. We report that recent progress now makes it possible to begin fully elucidating the genomic regulatory mechanisms that control forebrain gene expression. Here, we discuss the current knowledge of how transcription factors drive gene expression programs through their interactions with cis-acting genomic elements, such as enhancers; how analyses of chromatin and DNA modifications provide insights into gene expression states; and how these approaches yield insights into the evolution ofmore » the human brain.« less

Genetic Approaches to Reveal the Connectivity of Adult-Born Neurons

PubMed Central

Arenkiel, Benjamin R.

2011-01-01

Much has been learned about the environmental and molecular factors that influence the division, migration, and programmed cell death of adult-born neurons in the mammalian brain. However, detailed knowledge of the mechanisms that govern the formation and maintenance of functional circuit connectivity via adult neurogenesis remains elusive. Recent advances in genetic technologies now afford the ability to precisely target discrete brain tissues, neuronal subtypes, and even single neurons for vital reporter expression and controlled activity manipulations. Here, I review current viral tracing methods, heterologous receptor expression systems, and optogenetic technologies that hold promise toward elucidating the wiring diagrams and circuit properties of adult-born neurons. PMID:21519388

Toward Genomics-Based Breeding in C3 Cool-Season Perennial Grasses.

PubMed

Talukder, Shyamal K; Saha, Malay C

2017-01-01

Most important food and feed crops in the world belong to the C3 grass family. The future of food security is highly reliant on achieving genetic gains of those grasses. Conventional breeding methods have already reached a plateau for improving major crops. Genomics tools and resources have opened an avenue to explore genome-wide variability and make use of the variation for enhancing genetic gains in breeding programs. Major C3 annual cereal breeding programs are well equipped with genomic tools; however, genomic research of C3 cool-season perennial grasses is lagging behind. In this review, we discuss the currently available genomics tools and approaches useful for C3 cool-season perennial grass breeding. Along with a general review, we emphasize the discussion focusing on forage grasses that were considered orphan and have little or no genetic information available. Transcriptome sequencing and genotype-by-sequencing technology for genome-wide marker detection using next-generation sequencing (NGS) are very promising as genomics tools. Most C3 cool-season perennial grass members have no prior genetic information; thus NGS technology will enhance collinear study with other C3 model grasses like Brachypodium and rice. Transcriptomics data can be used for identification of functional genes and molecular markers, i.e., polymorphism markers and simple sequence repeats (SSRs). Genome-wide association study with NGS-based markers will facilitate marker identification for marker-assisted selection. With limited genetic information, genomic selection holds great promise to breeders for attaining maximum genetic gain of the cool-season C3 perennial grasses. Application of all these tools can ensure better genetic gains, reduce length of selection cycles, and facilitate cultivar development to meet the future demand for food and fodder.

Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs

PubMed Central

Jonas, Elisabeth; de Koning, Dirk-Jan

2015-01-01

Genomic selection is a promising development in agriculture, aiming improved production by exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. It opens opportunities for research, as novel algorithms and lab methodologies are developed. Genomic selection can be applied in many breeds and species. Further research on the implementation of genomic selection (GS) in breeding programs is highly desirable not only for the common good, but also the private sector (breeding companies). It has been projected that this approach will improve selection routines, especially in species with long reproduction cycles, late or sex-limited or expensive trait recording and for complex traits. The task of integrating GS into existing breeding programs is, however, not straightforward. Despite successful integration into breeding programs for dairy cattle, it has yet to be shown how much emphasis can be given to the genomic information and how much additional phenotypic information is needed from new selection candidates. Genomic selection is already part of future planning in many breeding companies of pigs and beef cattle among others, but further research is needed to fully estimate how effective the use of genomic information will be for the prediction of the performance of future breeding stock. Genomic prediction of production in crossbreeding and across-breed schemes, costs and choice of individuals for genotyping are reasons for a reluctance to fully rely on genomic information for selection decisions. Breeding objectives are highly dependent on the industry and the additional gain when using genomic information has to be considered carefully. This review synthesizes some of the suggested approaches in selected livestock species including cattle, pig, chicken, and fish. It outlines tasks to help understanding possible consequences when applying genomic information in breeding scenarios. PMID:25750652

Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs.

PubMed

Jonas, Elisabeth; de Koning, Dirk-Jan

2015-01-01

Genomic selection is a promising development in agriculture, aiming improved production by exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. It opens opportunities for research, as novel algorithms and lab methodologies are developed. Genomic selection can be applied in many breeds and species. Further research on the implementation of genomic selection (GS) in breeding programs is highly desirable not only for the common good, but also the private sector (breeding companies). It has been projected that this approach will improve selection routines, especially in species with long reproduction cycles, late or sex-limited or expensive trait recording and for complex traits. The task of integrating GS into existing breeding programs is, however, not straightforward. Despite successful integration into breeding programs for dairy cattle, it has yet to be shown how much emphasis can be given to the genomic information and how much additional phenotypic information is needed from new selection candidates. Genomic selection is already part of future planning in many breeding companies of pigs and beef cattle among others, but further research is needed to fully estimate how effective the use of genomic information will be for the prediction of the performance of future breeding stock. Genomic prediction of production in crossbreeding and across-breed schemes, costs and choice of individuals for genotyping are reasons for a reluctance to fully rely on genomic information for selection decisions. Breeding objectives are highly dependent on the industry and the additional gain when using genomic information has to be considered carefully. This review synthesizes some of the suggested approaches in selected livestock species including cattle, pig, chicken, and fish. It outlines tasks to help understanding possible consequences when applying genomic information in breeding scenarios.

Why evolutionary biologists should get seriously involved in ecological monitoring and applied biodiversity assessment programs

PubMed Central

Brodersen, Jakob; Seehausen, Ole

2014-01-01

While ecological monitoring and biodiversity assessment programs are widely implemented and relatively well developed to survey and monitor the structure and dynamics of populations and communities in many ecosystems, quantitative assessment and monitoring of genetic and phenotypic diversity that is important to understand evolutionary dynamics is only rarely integrated. As a consequence, monitoring programs often fail to detect changes in these key components of biodiversity until after major loss of diversity has occurred. The extensive efforts in ecological monitoring have generated large data sets of unique value to macro-scale and long-term ecological research, but the insights gained from such data sets could be multiplied by the inclusion of evolutionary biological approaches. We argue that the lack of process-based evolutionary thinking in ecological monitoring means a significant loss of opportunity for research and conservation. Assessment of genetic and phenotypic variation within and between species needs to be fully integrated to safeguard biodiversity and the ecological and evolutionary dynamics in natural ecosystems. We illustrate our case with examples from fishes and conclude with examples of ongoing monitoring programs and provide suggestions on how to improve future quantitative diversity surveys. PMID:25553061

Binary Image Classification: A Genetic Programming Approach to the Problem of Limited Training Instances.

PubMed

Al-Sahaf, Harith; Zhang, Mengjie; Johnston, Mark

2016-01-01

In the computer vision and pattern recognition fields, image classification represents an important yet difficult task. It is a challenge to build effective computer models to replicate the remarkable ability of the human visual system, which relies on only one or a few instances to learn a completely new class or an object of a class. Recently we proposed two genetic programming (GP) methods, one-shot GP and compound-GP, that aim to evolve a program for the task of binary classification in images. The two methods are designed to use only one or a few instances per class to evolve the model. In this study, we investigate these two methods in terms of performance, robustness, and complexity of the evolved programs. We use ten data sets that vary in difficulty to evaluate these two methods. We also compare them with two other GP and six non-GP methods. The results show that one-shot GP and compound-GP outperform or achieve results comparable to competitor methods. Moreover, the features extracted by these two methods improve the performance of other classifiers with handcrafted features and those extracted by a recently developed GP-based method in most cases.

A Comparison of Trajectory Optimization Methods for the Impulsive Minimum Fuel Rendezvous Problem

NASA Technical Reports Server (NTRS)

Hughes, Steven P.; Mailhe, Laurie M.; Guzman, Jose J.

2002-01-01

In this paper we present a comparison of optimization approaches to the minimum fuel rendezvous problem. Both indirect and direct methods are compared for a variety of test cases. The indirect approach is based on primer vector theory. The direct approaches are implemented numerically and include Sequential Quadratic Programming (SQP), Quasi-Newton, Simplex, Genetic Algorithms, and Simulated Annealing. Each method is applied to a variety of test cases including, circular to circular coplanar orbits, LEO to GEO, and orbit phasing in highly elliptic orbits. We also compare different constrained optimization routines on complex orbit rendezvous problems with complicated, highly nonlinear constraints.

Evolution of Autonomous Self-Righting Behaviors for Articulated Nanorovers

NASA Technical Reports Server (NTRS)

Tunstel, Edward

1999-01-01

Miniature rovers with articulated mobility mechanisms are being developed for planetary surface exploration on Mars and small solar system bodies. These vehicles are designed to be capable of autonomous recovery from overturning during surface operations. This paper describes a computational means of developing motion behaviors that achieve the autonomous recovery function. It proposes a control software design approach aimed at reducing the effort involved in developing self-righting behaviors. The approach is based on the integration of evolutionary computing with a dynamics simulation environment for evolving and evaluating motion behaviors. The automated behavior design approach is outlined and its underlying genetic programming infrastructure is described.

Bayesian estimation and use of high-throughput remote sensing indices for quantitative genetic analyses of leaf growth.

PubMed

Baker, Robert L; Leong, Wen Fung; An, Nan; Brock, Marcus T; Rubin, Matthew J; Welch, Stephen; Weinig, Cynthia

2018-02-01

We develop Bayesian function-valued trait models that mathematically isolate genetic mechanisms underlying leaf growth trajectories by factoring out genotype-specific differences in photosynthesis. Remote sensing data can be used instead of leaf-level physiological measurements. Characterizing the genetic basis of traits that vary during ontogeny and affect plant performance is a major goal in evolutionary biology and agronomy. Describing genetic programs that specifically regulate morphological traits can be complicated by genotypic differences in physiological traits. We describe the growth trajectories of leaves using novel Bayesian function-valued trait (FVT) modeling approaches in Brassica rapa recombinant inbred lines raised in heterogeneous field settings. While frequentist approaches estimate parameter values by treating each experimental replicate discretely, Bayesian models can utilize information in the global dataset, potentially leading to more robust trait estimation. We illustrate this principle by estimating growth asymptotes in the face of missing data and comparing heritabilities of growth trajectory parameters estimated by Bayesian and frequentist approaches. Using pseudo-Bayes factors, we compare the performance of an initial Bayesian logistic growth model and a model that incorporates carbon assimilation (A max ) as a cofactor, thus statistically accounting for genotypic differences in carbon resources. We further evaluate two remotely sensed spectroradiometric indices, photochemical reflectance (pri2) and MERIS Terrestrial Chlorophyll Index (mtci) as covariates in lieu of A max , because these two indices were genetically correlated with A max across years and treatments yet allow much higher throughput compared to direct leaf-level gas-exchange measurements. For leaf lengths in uncrowded settings, including A max improves model fit over the initial model. The mtci and pri2 indices also outperform direct A max measurements. Of particular importance for evolutionary biologists and plant breeders, hierarchical Bayesian models estimating FVT parameters improve heritabilities compared to frequentist approaches.

Application of the Linux cluster for exhaustive window haplotype analysis using the FBAT and Unphased programs.

PubMed

Mishima, Hiroyuki; Lidral, Andrew C; Ni, Jun

2008-05-28

Genetic association studies have been used to map disease-causing genes. A newly introduced statistical method, called exhaustive haplotype association study, analyzes genetic information consisting of different numbers and combinations of DNA sequence variations along a chromosome. Such studies involve a large number of statistical calculations and subsequently high computing power. It is possible to develop parallel algorithms and codes to perform the calculations on a high performance computing (HPC) system. However, most existing commonly-used statistic packages for genetic studies are non-parallel versions. Alternatively, one may use the cutting-edge technology of grid computing and its packages to conduct non-parallel genetic statistical packages on a centralized HPC system or distributed computing systems. In this paper, we report the utilization of a queuing scheduler built on the Grid Engine and run on a Rocks Linux cluster for our genetic statistical studies. Analysis of both consecutive and combinational window haplotypes was conducted by the FBAT (Laird et al., 2000) and Unphased (Dudbridge, 2003) programs. The dataset consisted of 26 loci from 277 extended families (1484 persons). Using the Rocks Linux cluster with 22 compute-nodes, FBAT jobs performed about 14.4-15.9 times faster, while Unphased jobs performed 1.1-18.6 times faster compared to the accumulated computation duration. Execution of exhaustive haplotype analysis using non-parallel software packages on a Linux-based system is an effective and efficient approach in terms of cost and performance.

Application of the Linux cluster for exhaustive window haplotype analysis using the FBAT and Unphased programs

PubMed Central

Mishima, Hiroyuki; Lidral, Andrew C; Ni, Jun

2008-01-01

Background Genetic association studies have been used to map disease-causing genes. A newly introduced statistical method, called exhaustive haplotype association study, analyzes genetic information consisting of different numbers and combinations of DNA sequence variations along a chromosome. Such studies involve a large number of statistical calculations and subsequently high computing power. It is possible to develop parallel algorithms and codes to perform the calculations on a high performance computing (HPC) system. However, most existing commonly-used statistic packages for genetic studies are non-parallel versions. Alternatively, one may use the cutting-edge technology of grid computing and its packages to conduct non-parallel genetic statistical packages on a centralized HPC system or distributed computing systems. In this paper, we report the utilization of a queuing scheduler built on the Grid Engine and run on a Rocks Linux cluster for our genetic statistical studies. Results Analysis of both consecutive and combinational window haplotypes was conducted by the FBAT (Laird et al., 2000) and Unphased (Dudbridge, 2003) programs. The dataset consisted of 26 loci from 277 extended families (1484 persons). Using the Rocks Linux cluster with 22 compute-nodes, FBAT jobs performed about 14.4–15.9 times faster, while Unphased jobs performed 1.1–18.6 times faster compared to the accumulated computation duration. Conclusion Execution of exhaustive haplotype analysis using non-parallel software packages on a Linux-based system is an effective and efficient approach in terms of cost and performance. PMID:18541045

Stigmatization of carrier status: social implications of heterozygote genetic screening programs.

PubMed Central

Kenen, R H; Schmidt, R M

1978-01-01

Possible latent psychological and social consequences ensuing from genetic screening programs need to be investigated during the planning phase of national genetic screening programs. The relatively few studies which have been performed to determine psychological, social, and economic consequences resulting from a genetic screening program are reviewed. Stigmatization of carrier-status, having major psychosocial implications in heterozygote genetic screening programs, is discussed and related to Erving Goffman's work in the area of stigmatization. Questions are raised regarding the relationship between such variables as religiosity and sex of the individual and acceptance of the status of newly identified carrier of a mutant gene. Severity of the deleterious gene and visibility of the carrier status are two important factors to consider in an estimation of potential stigma. Specific implications are discussed for four genetic diseases: Tay-Sachs, Sickle-Cell Anemia, Huntington's disease and Hemophilia. PMID:152585

Genetic algorithms using SISAL parallel programming language

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

Tejada, S.

1994-05-06

Genetic algorithms are a mathematical optimization technique developed by John Holland at the University of Michigan [1]. The SISAL programming language possesses many of the characteristics desired to implement genetic algorithms. SISAL is a deterministic, functional programming language which is inherently parallel. Because SISAL is functional and based on mathematical concepts, genetic algorithms can be efficiently translated into the language. Several of the steps involved in genetic algorithms, such as mutation, crossover, and fitness evaluation, can be parallelized using SISAL. In this paper I will l discuss the implementation and performance of parallel genetic algorithms in SISAL.

Amount of Genetics Education is Low Among Didactic Programs in Dietetics.

PubMed

Beretich, Kaitlan; Pope, Janet; Erickson, Dawn; Kennedy, Angela

2017-01-01

Nutritional genomics is a growing area of research. Research has shown registered dietitian nutritionists (RDNs) have limited knowledge of genetics. Limited research is available regarding how didactic programs in dietetics (DPDs) meet the genetics knowledge requirement of the Accreditation Council for Education in Nutrition and Dietetics (ACEND®). The purpose of this study was to determine the extent to which the study of nutritional genomics is incorporated into undergraduate DPDs in response to the Academy of Nutrition and Dietetics position statement on nutritional genomics. The sample included 62 DPD directors in the U.S. Most programs (63.9%) reported the ACEND genetics knowledge requirement was being met by integrating genetic information into the current curriculum. However, 88.7% of programs reported devoting only 1-10 clock hours to genetics education. While 60.3% of directors surveyed reported they were confident in their program's ability to teach information related to genetics, only 6 directors reported having specialized training in genetics. The overall amount of clock hours devoted to genetics education is low. DPD directors, faculty, and instructors are not adequately trained to provide this education to students enrolled in DPDs. Therefore, the primary recommendation of this study is the development of a standardized curriculum for genetics education in DPDs.

The African baobab (Adansonia digitata, Malvaceae): genetic resources in neglected populations of the Nuba Mountains, Sudan.

PubMed

Wiehle, Martin; Prinz, Kathleen; Kehlenbeck, Katja; Goenster, Sven; Mohamed, Seifeldin Ali; Finkeldey, Reiner; Buerkert, Andreas; Gebauer, Jens

2014-09-01

• Adansonia digitata L. is one of the most important indigenous fruit trees of mainland Africa. Despite its significance for subsistence and income generation of local communities, little is known about the genetic and morphological variability of East African populations of A. digitata, including those of Sudan. The aim of the current study, therefore, was to analyze genetic and morphological variability of different baobab populations in Kordofan, Sudan and to estimate the effect of human intervention on genetic differentiation and diversity.• A total of 306 trees were randomly sampled from seven spatially separated locations in the Nuba Mountains, Sudan, to cover a wide range of differing environmental gradients and management regimes ('homesteads' and 'wild'). Genetic analyses were conducted using nine microsatellite markers. Because of the tetraploid nature of A. digitata, different approaches were applied to estimate patterns of genetic diversity. Investigations were completed by measurements of dendrometric and fruit morphological characters.• Genetic diversity was balanced and did not differ between locations or management regimes, although tendencies of higher diversity in 'homesteads' were observed. A Bayesian cluster approach detected two distinct gene pools in the sample set, mainly caused by one highly diverse population close to a main road. The variability of tree characters and fruit morphometries was high, and significantly different between locations.• Results indicated a rather positive effect with human intervention. The observed populations provide a promising gene pool and likely comprise ecotypes well-adapted to environmental conditions at the northern distribution range of the species, which should be considered in conservation and management programs. © 2014 Botanical Society of America, Inc.

Groundnut improvement: use of genetic and genomic tools

PubMed Central

Janila, Pasupuleti; Nigam, S. N.; Pandey, Manish K.; Nagesh, P.; Varshney, Rajeev K.

2013-01-01

Groundnut (Arachis hypogaea L.), a self-pollinated legume is an important crop cultivated in 24 million ha world over for extraction of edible oil and food uses. The kernels are rich in oil (48–50%) and protein (25–28%), and are source of several vitamins, minerals, antioxidants, biologically active polyphenols, flavonoids, and isoflavones. Improved varieties of groundnut with high yield potential were developed and released for cultivation world over. The improved varieties belong to different maturity durations and possess resistance to diseases, tolerance to drought, enhanced oil content, and improved quality traits for food uses. Conventional breeding procedures along with the tools for phenotyping were largely used in groundnut improvement programs. Mutations were used to induce variability and wide hybridization was attempted to tap variability from wild species. Low genetic variability has been a bottleneck for groundnut improvement. The vast potential of wild species, reservoir of new alleles remains under-utilized. Development of linkage maps of groundnut during the last decade was followed by identification of markers and quantitative trait loci for the target traits. Consequently, the last decade has witnessed the deployment of molecular breeding approaches to complement the ongoing groundnut improvement programs in USA, China, India, and Japan. The other potential advantages of molecular breeding are the feasibility to target multiple traits for improvement and provide tools to tap new alleles from wild species. The first groundnut variety developed through marker-assisted back-crossing is a root-knot nematode-resistant variety, NemaTAM in USA. The uptake of molecular breeding approaches in groundnut improvement programs by NARS partners in India and many African countries is slow or needs to be initiated in part due to inadequate infrastructure, high genotyping costs, and human capacities. Availability of draft genome sequence for diploid (AA and BB) and tetraploid, AABB genome species of Arachis in coming years is expected to bring low-cost genotyping to the groundnut community that will facilitate use of modern genetics and breeding approaches such as genome-wide association studies for trait mapping and genomic selection for crop improvement. PMID:23443056

Software For Genetic Algorithms

NASA Technical Reports Server (NTRS)

Wang, Lui; Bayer, Steve E.

1992-01-01

SPLICER computer program is genetic-algorithm software tool used to solve search and optimization problems. Provides underlying framework and structure for building genetic-algorithm application program. Written in Think C.

Genetics Education in Nurse Residency Programs: A Natural Fit.

PubMed

Hamilton, Nalo M; Stenman, Christina W; Sang, Elaine; Palmer, Christina

2017-08-01

Scientific advances are shedding light on the genetic underpinning of common diseases. With such insight, the entire health care team is faced with the need to address patient questions regarding genetic risk, testing, and the psychosocial aspects of genetics information. Nurses are in a prime position to help with patient education about genetic conditions, yet they often lack adequate genetics education within their nursing curriculum to address patient questions and provide resources. One mechanism to address this knowledge deficit is the incorporation of a genetics-based curriculum into nurse residency programs. This article describes a novel genetics-based curriculum designed and implemented in the UCLA Health System Nurse Residency Program. J Contin Educ Nurs. 2017;48(8):379-384. Copyright 2017, SLACK Incorporated.

A reference consensus genetic map for molecular markers and economically important traits in faba bean (Vicia faba L.)

PubMed Central

2013-01-01

Background Faba bean (Vicia faba L.) is among the earliest domesticated crops from the Near East. Today this legume is a key protein feed and food worldwide and continues to serve an important role in culinary traditions throughout Middle East, Mediterranean region, China and Ethiopia. Adapted to a wide range of soil types, the main faba bean breeding objectives are to improve yield, resistance to biotic and abiotic stresses, seed quality and other agronomic traits. Genomic approaches aimed at enhancing faba bean breeding programs require high-quality genetic linkage maps to facilitate quantitative trait locus analysis and gene tagging for use in a marker-assisted selection. The objective of this study was to construct a reference consensus map in faba bean by joining the information from the most relevant maps reported so far in this crop. Results A combination of two approaches, increasing the number of anchor loci in diverse mapping populations and joining the corresponding genetic maps, was used to develop a reference consensus map in faba bean. The map was constructed from three main recombinant inbreed populations derived from four parental lines, incorporates 729 markers and is based on 69 common loci. It spans 4,602 cM with a range from 323 to 1041 loci in six main linkage groups or chromosomes, and an average marker density of one locus every 6 cM. Locus order is generally well maintained between the consensus map and the individual maps. Conclusion We have constructed a reliable and fairly dense consensus genetic linkage map that will serve as a basis for genomic approaches in faba bean research and breeding. The core map contains a larger number of markers than any previous individual map, covers existing gaps and achieves a wider coverage of the large faba bean genome as a whole. This tool can be used as a reference resource for studies in different genetic backgrounds, and provides a framework for transferring genetic information when using different marker technologies. Combined with syntenic approaches, the consensus map will increase marker density in selected genomic regions and will be useful for future faba bean molecular breeding applications. PMID:24377374

Genetic Modification of Short Rotation Poplar Biomass Feedstock for Efficient Conversion to Ethanol

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

Dinus, R.J.

2000-08-30

The Bioenergy Feedstock Development Program, Environmental Sciences Division, Oak Ridge National Laboratory is developing poplars (Populus species and hybrids) as sources of renewable energy, i.e., ethanol. Notable increases in adaptability, volume productivity, and pest/stress resistance have been achieved via classical selection and breeding and intensified cultural practices. Significant advances have also been made in the efficiencies of harvesting and handling systems. Given these and anticipated accomplishments, program leaders are considering shifting some attention to genetically modifying feedstock physical and chemical properties, so as to improve the efficiency with which feedstocks can be converted to ethanol. This report provides an in-depthmore » review and synthesis of opportunities for and feasibilities of genetically modifying feedstock qualities via classical selection and breeding, marker-aided selection and breeding, and genetic transformation. Information was collected by analysis of the literature, with emphasis on that published since 1995, and interviews with prominent scientists, breeders, and growers. Poplar research is well advanced, and literature is abundant. The report therefore primarily reflects advances in poplars, but data from other species, particularly other shortrotation hardwoods, are incorporated to fill gaps. An executive summary and recommendations for research, development, and technology transfer are provided immediately after the table of contents. The first major section of the report describes processes most likely to be used for conversion of poplar biomass to ethanol, the various physical and chemical properties of poplar feedstocks, and how such properties are expected to affect process efficiency. The need is stressed for improved understanding of the impact of change on both overall process and individual process step efficiencies. The second part documents advances in trait measurement instrumentation and methodology. The importance of these and future developments is emphasized, since trait measurement constitutes the largest cost associated with adding additional traits to improvement efforts, regardless of genetic approach. In subsequent sections, recent and projected advances in classical selection and breeding, marker-aided selection, and genetic transformation are documented and used to evaluate the feasibility of individual approaches. Interviews with specialists engaged in research and development on each approach were given particular emphasis in gauging feasibilities and defining future needs and directions. Summaries of important findings and major conclusions are presented at the end of individual sections. Closing portions describe the targeted workshop, conducted in December 1999 and list interviewees and literature cited in the text. Information obtained at the workshop was used to improve accuracy, refine conclusions, and recommend priorities for future research, development, and technology transfer.« less

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

PubMed

Azad, Raja Muhammad Atif; Ryan, Conor

2014-01-01

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

Report on an Investigation into an Entry Level Clinical Doctorate for the Genetic Counseling Profession and a Survey of the Association of Genetic Counseling Program Directors.

PubMed

Reiser, Catherine; LeRoy, Bonnie; Grubs, Robin; Walton, Carol

2015-10-01

The master's degree is the required entry-level degree for the genetic counseling profession in the US and Canada. In 2012 the Association of Genetic Counseling Program Directors (AGCPD) passed resolutions supporting retention of the master's as the entry-level and terminal degree and opposing introduction of an entry-level clinical doctorate (CD) degree. An AGCPD workgroup surveyed directors of all 34 accredited training programs with the objective of providing the Genetic Counseling Advanced Degrees Task Force (GCADTF) with information regarding potential challenges if master's programs were required to transition to an entry-level CD. Program demographics, projected ability to transition to an entry-level CD, factors influencing ability to transition, and potential effects of transition on programs, students and the genetic counseling workforce were characterized. Two programs would definitely be able to transition, four programs would close, thirteen programs would be at risk to close and fourteen programs would probably be able to transition with varying degrees of difficulty. The most frequently cited limiting factors were economic, stress on clinical sites, and administrative approval of a new degree/program. Student enrollment under an entry-level CD model was projected to decrease by 26.2 %, negatively impacting the workforce pipeline. The results further illuminate and justify AGCPD's position to maintain the master's as the entry-level degree.

A method for the dynamic management of genetic variability in dairy cattle

PubMed Central

Colleau, Jean-Jacques; Moureaux, Sophie; Briend, Michèle; Bechu, Jérôme

2004-01-01

According to the general approach developed in this paper, dynamic management of genetic variability in selected populations of dairy cattle is carried out for three simultaneous purposes: procreation of young bulls to be further progeny-tested, use of service bulls already selected and approval of recently progeny-tested bulls for use. At each step, the objective is to minimize the average pairwise relationship coefficient in the future population born from programmed matings and the existing population. As a common constraint, the average estimated breeding value of the new population, for a selection goal including many important traits, is set to a desired value. For the procreation of young bulls, breeding costs are additionally constrained. Optimization is fully analytical and directly considers matings. Corresponding algorithms are presented in detail. The efficiency of these procedures was tested on the current Norman population. Comparisons between optimized and real matings, clearly showed that optimization would have saved substantial genetic variability without reducing short-term genetic gains. PMID:15231230

Genetic Programming as Alternative for Predicting Development Effort of Individual Software Projects

PubMed Central

Chavoya, Arturo; Lopez-Martin, Cuauhtemoc; Andalon-Garcia, Irma R.; Meda-Campaña, M. E.

2012-01-01

Statistical and genetic programming techniques have been used to predict the software development effort of large software projects. In this paper, a genetic programming model was used for predicting the effort required in individually developed projects. Accuracy obtained from a genetic programming model was compared against one generated from the application of a statistical regression model. A sample of 219 projects developed by 71 practitioners was used for generating the two models, whereas another sample of 130 projects developed by 38 practitioners was used for validating them. The models used two kinds of lines of code as well as programming language experience as independent variables. Accuracy results from the model obtained with genetic programming suggest that it could be used to predict the software development effort of individual projects when these projects have been developed in a disciplined manner within a development-controlled environment. PMID:23226305

Dynamics of genetic variability in Anastrepha fraterculus (Diptera: Tephritidae) during adaptation to laboratory rearing conditions.

PubMed

Parreño, María A; Scannapieco, Alejandra C; Remis, María I; Juri, Marianela; Vera, María T; Segura, Diego F; Cladera, Jorge L; Lanzavecchia, Silvia B

2014-01-01

Anastrepha fraterculus is one of the most important fruit fly plagues in the American continent and only chemical control is applied in the field to diminish its population densities. A better understanding of the genetic variability during the introduction and adaptation of wild A. fraterculus populations to laboratory conditions is required for the development of stable and vigorous experimental colonies and mass-reared strains in support of successful Sterile Insect Technique (SIT) efforts. The present study aims to analyze the dynamics of changes in genetic variability during the first six generations under artificial rearing conditions in two populations: a) a wild population recently introduced to laboratory culture, named TW and, b) a long-established control line, named CL. Results showed a declining tendency of genetic variability in TW. In CL, the relatively high values of genetic variability appear to be maintained across generations and could denote an intrinsic capacity to avoid the loss of genetic diversity in time. The impact of evolutionary forces on this species during the adaptation process as well as the best approach to choose strategies to introduce experimental and mass-reared A. fraterculus strains for SIT programs are discussed.

Dynamics of genetic variability in Anastrepha fraterculus (Diptera: Tephritidae) during adaptation to laboratory rearing conditions

PubMed Central

2014-01-01

Background Anastrepha fraterculus is one of the most important fruit fly plagues in the American continent and only chemical control is applied in the field to diminish its population densities. A better understanding of the genetic variability during the introduction and adaptation of wild A. fraterculus populations to laboratory conditions is required for the development of stable and vigorous experimental colonies and mass-reared strains in support of successful Sterile Insect Technique (SIT) efforts. Methods The present study aims to analyze the dynamics of changes in genetic variability during the first six generations under artificial rearing conditions in two populations: a) a wild population recently introduced to laboratory culture, named TW and, b) a long-established control line, named CL. Results Results showed a declining tendency of genetic variability in TW. In CL, the relatively high values of genetic variability appear to be maintained across generations and could denote an intrinsic capacity to avoid the loss of genetic diversity in time. Discussion The impact of evolutionary forces on this species during the adaptation process as well as the best approach to choose strategies to introduce experimental and mass-reared A. fraterculus strains for SIT programs are discussed. PMID:25471362

Constraints in Genetic Programming

NASA Technical Reports Server (NTRS)

Janikow, Cezary Z.

1996-01-01

Genetic programming refers to a class of genetic algorithms utilizing generic representation in the form of program trees. For a particular application, one needs to provide the set of functions, whose compositions determine the space of program structures being evolved, and the set of terminals, which determine the space of specific instances of those programs. The algorithm searches the space for the best program for a given problem, applying evolutionary mechanisms borrowed from nature. Genetic algorithms have shown great capabilities in approximately solving optimization problems which could not be approximated or solved with other methods. Genetic programming extends their capabilities to deal with a broader variety of problems. However, it also extends the size of the search space, which often becomes too large to be effectively searched even by evolutionary methods. Therefore, our objective is to utilize problem constraints, if such can be identified, to restrict this space. In this publication, we propose a generic constraint specification language, powerful enough for a broad class of problem constraints. This language has two elements -- one reduces only the number of program instances, the other reduces both the space of program structures as well as their instances. With this language, we define the minimal set of complete constraints, and a set of operators guaranteeing offspring validity from valid parents. We also show that these operators are not less efficient than the standard genetic programming operators if one preprocesses the constraints - the necessary mechanisms are identified.

The Genetic Programming of Industrial Microorganisms.

ERIC Educational Resources Information Center

Hopwood, David A.

1981-01-01

Traces the development of the field of industrial microbial genetics, describing a range of techniques for genetic programing. Includes a discussion of site-directed mutagenesis, protoplast fusion, and recombinant DNA manipulations. (CS)

Efficient Breeding by Genomic Mating.

PubMed

Akdemir, Deniz; Sánchez, Julio I

2016-01-01

Selection in breeding programs can be done by using phenotypes (phenotypic selection), pedigree relationship (breeding value selection) or molecular markers (marker assisted selection or genomic selection). All these methods are based on truncation selection, focusing on the best performance of parents before mating. In this article we proposed an approach to breeding, named genomic mating, which focuses on mating instead of truncation selection. Genomic mating uses information in a similar fashion to genomic selection but includes information on complementation of parents to be mated. Following the efficiency frontier surface, genomic mating uses concepts of estimated breeding values, risk (usefulness) and coefficient of ancestry to optimize mating between parents. We used a genetic algorithm to find solutions to this optimization problem and the results from our simulations comparing genomic selection, phenotypic selection and the mating approach indicate that current approach for breeding complex traits is more favorable than phenotypic and genomic selection. Genomic mating is similar to genomic selection in terms of estimating marker effects, but in genomic mating the genetic information and the estimated marker effects are used to decide which genotypes should be crossed to obtain the next breeding population.

Imaging genetics approach to predict progression of Parkinson's diseases.

PubMed

Mansu Kim; Seong-Jin Son; Hyunjin Park

2017-07-01

Imaging genetics is a tool to extract genetic variants associated with both clinical phenotypes and imaging information. The approach can extract additional genetic variants compared to conventional approaches to better investigate various diseased conditions. Here, we applied imaging genetics to study Parkinson's disease (PD). We aimed to extract significant features derived from imaging genetics and neuroimaging. We built a regression model based on extracted significant features combining genetics and neuroimaging to better predict clinical scores of PD progression (i.e. MDS-UPDRS). Our model yielded high correlation (r = 0.697, p <; 0.001) and low root mean squared error (8.36) between predicted and actual MDS-UPDRS scores. Neuroimaging (from 123 I-Ioflupane SPECT) predictors of regression model were computed from independent component analysis approach. Genetic features were computed using image genetics approach based on identified neuroimaging features as intermediate phenotypes. Joint modeling of neuroimaging and genetics could provide complementary information and thus have the potential to provide further insight into the pathophysiology of PD. Our model included newly found neuroimaging features and genetic variants which need further investigation.

[Programmed mouse genome modifications].

PubMed

Babinet, C

1998-02-01

The availability, in the mouse, of embryonic stem cells (ES cells) which have the ability to colonize the germ line of a developing embryo, has opened entirely new avenues to the genetic approach of embryonic development, physiology and pathology of this animal. Indeed, it is now possible, using homologous recombination in ES cells, to introduce mutations in any gene as long as it has been cloned. Thus, null as well as more subtle mutations can be created. Furthermore, scenarios are currently being derived which will allow one to generate conditional mutations. Taken together, these methods offer a tremendous tool to study gene function in vivo; they also open the way to creating murine models of human genetic diseases.

Developing close combat behaviors for simulated soldiers using genetic programming techniques.

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

Pryor, Richard J.; Schaller, Mark J.

2003-10-01

Genetic programming is a powerful methodology for automatically producing solutions to problems in a variety of domains. It has been used successfully to develop behaviors for RoboCup soccer players and simple combat agents. We will attempt to use genetic programming to solve a problem in the domain of strategic combat, keeping in mind the end goal of developing sophisticated behaviors for compound defense and infiltration. The simplified problem at hand is that of two armed agents in a small room, containing obstacles, fighting against each other for survival. The base case and three changes are considered: a memory of positionsmore » using stacks, context-dependent genetic programming, and strongly typed genetic programming. Our work demonstrates slight improvements from the first two techniques, and no significant improvement from the last.« less

Understanding the genetic diversity and population structure of yam (Dioscorea alata L.) using microsatellite markers

PubMed Central

Arnau, Gemma; MN, Sheela; Chair, Hana; Lebot, Vincent; K, Abraham; Perrier, Xavier; Petro, Dalila; Penet, Laurent; Pavis, Claudie

2017-01-01

Yams (Dioscorea sp.) are staple food crops for millions of people in tropical and subtropical regions. Dioscorea alata, also known as greater yam, is one of the major cultivated species and most widely distributed throughout the tropics. Despite its economic and cultural importance, very little is known about its origin, diversity and genetics. As a consequence, breeding efforts for resistance to its main disease, anthracnose, have been fairly limited. The objective of this study was to contribute to the understanding of D. alata genetic diversity by genotyping 384 accessions from different geographical regions (South Pacific, Asia, Africa and the Caribbean), using 24 microsatellite markers. Diversity structuration was assessed via Principal Coordinate Analysis, UPGMA analysis and the Bayesian approach implemented in STRUCTURE. Our results revealed the existence of a wide genetic diversity and a significant structuring associated with geographic origin, ploidy levels and morpho-agronomic characteristics. Seventeen major groups of genetically close cultivars have been identified, including eleven groups of diploid cultivars, four groups of triploids and two groups of tetraploids. STRUCTURE revealed the existence of six populations in the diploid genetic pool and a few admixed cultivars. These results will be very useful for rationalizing D. alata genetic resources in breeding programs across different regions and for improving germplasm conservation methods. PMID:28355293

Genetic Structure of Bluefin Tuna in the Mediterranean Sea Correlates with Environmental Variables

PubMed Central

Riccioni, Giulia; Stagioni, Marco; Landi, Monica; Ferrara, Giorgia; Barbujani, Guido; Tinti, Fausto

2013-01-01

Background Atlantic Bluefin Tuna (ABFT) shows complex demography and ecological variation in the Mediterranean Sea. Genetic surveys have detected significant, although weak, signals of population structuring; catch series analyses and tagging programs identified complex ABFT spatial dynamics and migration patterns. Here, we tested the hypothesis that the genetic structure of the ABFT in the Mediterranean is correlated with mean surface temperature and salinity. Methodology We used six samples collected from Western and Central Mediterranean integrated with a new sample collected from the recently identified easternmost reproductive area of Levantine Sea. To assess population structure in the Mediterranean we used a multidisciplinary framework combining classical population genetics, spatial and Bayesian clustering methods and a multivariate approach based on factor analysis. Conclusions FST analysis and Bayesian clustering methods detected several subpopulations in the Mediterranean, a result also supported by multivariate analyses. In addition, we identified significant correlations of genetic diversity with mean salinity and surface temperature values revealing that ABFT is genetically structured along two environmental gradients. These results suggest that a preference for some spawning habitat conditions could contribute to shape ABFT genetic structuring in the Mediterranean. However, further studies should be performed to assess to what extent ABFT spawning behaviour in the Mediterranean Sea can be affected by environmental variation. PMID:24260341

Moving Speciation Genetics Forward: Modern Techniques Build on Foundational Studies in Drosophila.

PubMed

Castillo, Dean M; Barbash, Daniel A

2017-11-01

The question of how new species evolve has been examined at every level, from macroevolutionary patterns of diversification to molecular population genetic analyses of specific genomic regions between species pairs. Drosophila has been at the center of many of these research efforts. Though our understanding of the speciation process has grown considerably over the past few decades, very few genes have been identified that contribute to barriers to reproduction. The development of advanced molecular genetic and genomic methods provides promising avenues for the rapid discovery of more genes that contribute to speciation, particularly those involving prezygotic isolation. The continued expansion of tools and resources, especially for species other than Drosophila melanogaster , will be most effective when coupled with comparative approaches that reveal the genetic basis of reproductive isolation across a range of divergence times. Future research programs in Drosophila have high potential to answer long-standing questions in speciation. These include identifying the selective forces that contribute to divergence between populations and the genetic basis of traits that cause reproductive isolation. The latter can be expanded upon to understand how the genetic basis of reproductive isolation changes over time and whether certain pathways and genes are more commonly involved. Copyright © 2017 by the Genetics Society of America.

Co-evolutionary data mining for fuzzy rules: automatic fitness function creation phase space, and experiments

NASA Astrophysics Data System (ADS)

Smith, James F., III; Blank, Joseph A.

2003-03-01

An approach is being explored that involves embedding a fuzzy logic based resource manager in an electronic game environment. Game agents can function under their own autonomous logic or human control. This approach automates the data mining problem. The game automatically creates a cleansed database reflecting the domain expert's knowledge, it calls a data mining function, a genetic algorithm, for data mining of the data base as required and allows easy evaluation of the information extracted. The co-evolutionary fitness functions, chromosomes and stopping criteria for ending the game are discussed. Genetic algorithm and genetic program based data mining procedures are discussed that automatically discover new fuzzy rules and strategies. The strategy tree concept and its relationship to co-evolutionary data mining are examined as well as the associated phase space representation of fuzzy concepts. The overlap of fuzzy concepts in phase space reduces the effective strategies available to adversaries. Co-evolutionary data mining alters the geometric properties of the overlap region known as the admissible region of phase space significantly enhancing the performance of the resource manager. Procedures for validation of the information data mined are discussed and significant experimental results provided.

Resurgent vector-borne diseases as a global health problem.

PubMed Central

Gubler, D. J.

1998-01-01

Vector-borne infectious diseases are emerging or resurging as a result of changes in public health policy, insecticide and drug resistance, shift in emphasis from prevention to emergency response, demographic and societal changes, and genetic changes in pathogens. Effective prevention strategies can reverse this trend. Research on vaccines, environmentally safe insecticides, alternative approaches to vector control, and training programs for health-care workers are needed. PMID:9716967

Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming.

PubMed

Luna, Jose Maria; Pechenizkiy, Mykola; Del Jesus, Maria Jose; Ventura, Sebastian

2017-09-25

Real-world data usually comprise features whose interpretation depends on some contextual information. Such contextual-sensitive features and patterns are of high interest to be discovered and analyzed in order to obtain the right meaning. This paper formulates the problem of mining context-aware association rules, which refers to the search for associations between itemsets such that the strength of their implication depends on a contextual feature. For the discovery of this type of associations, a model that restricts the search space and includes syntax constraints by means of a grammar-based genetic programming methodology is proposed. Grammars can be considered as a useful way of introducing subjective knowledge to the pattern mining process as they are highly related to the background knowledge of the user. The performance and usefulness of the proposed approach is examined by considering synthetically generated datasets. A posteriori analysis on different domains is also carried out to demonstrate the utility of this kind of associations. For example, in educational domains, it is essential to identify and understand contextual and context-sensitive factors that affect overall and individual student behavior and performance. The results of the experiments suggest that the approach is feasible and it automatically identifies interesting context-aware associations from real-world datasets.

Genetic toxicology in the 21st century: Reflections and future ...

EPA Pesticide Factsheets

A symposium at the 40th anniversary of the Environmental Mutagen Society, held from October 24–28, 2009 in St. Louis, MO, surveyed the current status and future directions of genetic toxicology. This article summarizes the presentations and provides a perspective on the future. An abbreviated history is presented, highlighting the current standard battery of genotoxicity assays and persistent challenges. Application of computational toxicology to safety testing within a regulatory setting is discussed as a means for reducing the need for animal testing and human clinical trials, and current approaches and applications of in silico genotoxicity screening approaches across the pharmaceutical industry were surveyed and are reported here. The expanded use of toxicogenomics to illuminate mechanisms and bridge genotoxicity and carcinogenicity, and new public efforts to use high-throughput screening technologies to address lack of toxicity evaluation for the backlog of thousands of industrial chemicals in the environment are detailed. The Tox21 project involves coordinated efforts of four U.S. Government regulatory/research entities to use new and innovative assays to characterize key steps in toxicity pathways, including genotoxic and nongenotoxic mechanisms for carcinogenesis. Progress to date, highlighting preliminary test results from the National Toxicology Program is summarized. Finally, an overview is presented of ToxCast™, a related research program of the

The potential use of genetics to increase the effectiveness of treatment programs for criminal offenders.

PubMed

Beaver, Kevin M; Jackson, Dylan B; Flesher, Dillon

2014-01-01

During the past couple of decades, the amount of research examining the genetic underpinnings to antisocial behaviors, including crime, has exploded. Findings from this body of work have generated a great deal of information linking genetics to criminal involvement. As a partial result, there is now a considerable amount of interest in how these findings should be integrated into the criminal justice system. In the current paper, we outline the potential ways that genetic information can be used to increase the effectiveness of treatment programs designed to reduce recidivism among offenders. We conclude by drawing attention to how genetic information can be used by rehabilitation programs to increase program effectiveness, reduce offender recidivism rates, and enhance public safety.

Latent spatial models and sampling design for landscape genetics

USGS Publications Warehouse

Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

2016-01-01

We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

Signatures of selection in five Italian cattle breeds detected by a 54K SNP panel.

PubMed

Mancini, Giordano; Gargani, Maria; Chillemi, Giovanni; Nicolazzi, Ezequiel Luis; Marsan, Paolo Ajmone; Valentini, Alessio; Pariset, Lorraine

2014-02-01

In this study we used a medium density panel of SNP markers to perform population genetic analysis in five Italian cattle breeds. The BovineSNP50 BeadChip was used to genotype a total of 2,935 bulls of Piedmontese, Marchigiana, Italian Holstein, Italian Brown and Italian Pezzata Rossa breeds. To determine a genome-wide pattern of positive selection we mapped the F st values against genome location. The highest F st peaks were obtained on BTA6 and BTA13 where some candidate genes are located. We identified selection signatures peculiar of each breed which suggest selection for genes involved in milk or meat traits. The genetic structure was investigated by using a multidimensional scaling of the genetic distance matrix and a Bayesian approach implemented in the STRUCTURE software. The genotyping data showed a clear partitioning of the cattle genetic diversity into distinct breeds if a number of clusters equal to the number of populations were given. Assuming a lower number of clusters beef breeds group together. Both methods showed all five breeds separated in well defined clusters and the Bayesian approach assigned individuals to the breed of origin. The work is of interest not only because it enriches the knowledge on the process of evolution but also because the results generated could have implications for selective breeding programs.

Research to support sterile-male-release and genetic alteration techniques for sea lamprey control

USGS Publications Warehouse

Bergstedt, Roger A.; Twohey, Michael B.

2007-01-01

Integrated pest management of sea lampreys in the Laurentian Great Lakes has recently been enhanced by addition of a sterile-male-release program, and future developments in genetic approaches may lead to additional methods for reducing sea lamprey reproduction. We review the development, implementation, and evaluation of the sterile-male-release technique (SMRT) as it is being applied against sea lampreys in the Great Lakes, review the current understanding of SMRT efficacy, and identify additional research areas and topics that would increase either the efficacy of the SMRT or expand its geographic potential for application. Key areas for additional research are in the sterilization process, effects of skewed sex ratios on mating behavior, enhancing attractiveness of sterilized males, techniques for genetic alteration of sea lampreys, and sources of animals to enhance or expand the use of sterile lampreys.

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

Hybrid Neural-Network: Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics Developed and Demonstrated

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2002-01-01

As part of the NASA Aviation Safety Program, a unique model-based diagnostics method that employs neural networks and genetic algorithms for aircraft engine performance diagnostics has been developed and demonstrated at the NASA Glenn Research Center against a nonlinear gas turbine engine model. Neural networks are applied to estimate the internal health condition of the engine, and genetic algorithms are used for sensor fault detection, isolation, and quantification. This hybrid architecture combines the excellent nonlinear estimation capabilities of neural networks with the capability to rank the likelihood of various faults given a specific sensor suite signature. The method requires a significantly smaller data training set than a neural network approach alone does, and it performs the combined engine health monitoring objectives of performance diagnostics and sensor fault detection and isolation in the presence of nominal and degraded engine health conditions.

Where have all the tadpoles gone? Individual genetic tracking of amphibian larvae until adulthood

PubMed Central

RINGLER, EVA; MANGIONE, ROSANNA; RINGLER, MAX

2015-01-01

Reliably marking larvae and reidentifying them after metamorphosis is a challenge that has hampered studies on recruitment, dispersal, migration and survivorship of amphibians for a long time, as conventional tags are not reliably retained through metamorphosis. Molecular methods allow unique genetic fingerprints to be established for individuals. Although microsatellite markers have successfully been applied in mark–recapture studies on several animal species, they have never been previously used in amphibians to follow individuals across different life cycle stages. Here, we evaluate microsatellites for genetic across-stages mark–recapture studies in amphibians and test the suitability of available software packages for genotype matching. We sampled tadpoles of the dendrobatid frog Allobates femoralis, which we introduced on a river island in the Nature Reserve ‘Les Nouragues’ in French Guiana. In two subsequent recapture sessions, we searched for surviving juveniles and adults, respectively. All individuals were genotyped at 14 highly variable microsatellite loci, which yielded unique genetic fingerprints for all individuals. We found large differences in the identification success of the programs tested. The pairwise-relatedness-based approach, conducted with the programs kingroup or ML-Relate, performed best with our data set. Matching ventral patterns of juveniles and adult individuals acted as a control for the reliability of the genetic identification. Our results demonstrate that microsatellite markers are a highly powerful tool for studying amphibian populations on an individual basis. The ability to individually track amphibian tadpoles throughout metamorphosis until adulthood will be of substantial value for future studies on amphibian population ecology and evolution. PMID:25388775

Where have all the tadpoles gone? Individual genetic tracking of amphibian larvae until adulthood.

PubMed

Ringler, Eva; Mangione, Rosanna; Ringler, Max

2015-07-01

Reliably marking larvae and reidentifying them after metamorphosis is a challenge that has hampered studies on recruitment, dispersal, migration and survivorship of amphibians for a long time, as conventional tags are not reliably retained through metamorphosis. Molecular methods allow unique genetic fingerprints to be established for individuals. Although microsatellite markers have successfully been applied in mark-recapture studies on several animal species, they have never been previously used in amphibians to follow individuals across different life cycle stages. Here, we evaluate microsatellites for genetic across-stages mark-recapture studies in amphibians and test the suitability of available software packages for genotype matching. We sampled tadpoles of the dendrobatid frog Allobates femoralis, which we introduced on a river island in the Nature Reserve 'Les Nouragues' in French Guiana. In two subsequent recapture sessions, we searched for surviving juveniles and adults, respectively. All individuals were genotyped at 14 highly variable microsatellite loci, which yielded unique genetic fingerprints for all individuals. We found large differences in the identification success of the programs tested. The pairwise-relatedness-based approach, conducted with the programs kingroup or ML-Relate, performed best with our data set. Matching ventral patterns of juveniles and adult individuals acted as a control for the reliability of the genetic identification. Our results demonstrate that microsatellite markers are a highly powerful tool for studying amphibian populations on an individual basis. The ability to individually track amphibian tadpoles throughout metamorphosis until adulthood will be of substantial value for future studies on amphibian population ecology and evolution. © 2014 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.

Recovery of Native Genetic Background in Admixed Populations Using Haplotypes, Phenotypes, and Pedigree Information – Using Cika Cattle as a Case Breed

PubMed Central

Simčič, Mojca; Smetko, Anamarija; Sölkner, Johann; Seichter, Doris; Gorjanc, Gregor; Kompan, Dragomir; Medugorac, Ivica

2015-01-01

The aim of this study was to obtain unbiased estimates of the diversity parameters, the population history, and the degree of admixture in Cika cattle which represents the local admixed breeds at risk of extinction undergoing challenging conservation programs. Genetic analyses were performed on the genome-wide Single Nucleotide Polymorphism (SNP) Illumina Bovine SNP50 array data of 76 Cika animals and 531 animals from 14 reference populations. To obtain unbiased estimates we used short haplotypes spanning four markers instead of single SNPs to avoid an ascertainment bias of the BovineSNP50 array. Genome-wide haplotypes combined with partial pedigree and type trait classification show the potential to improve identification of purebred animals with a low degree of admixture. Phylogenetic analyses demonstrated unique genetic identity of Cika animals. Genetic distance matrix presented by rooted Neighbour-Net suggested long and broad phylogenetic connection between Cika and Pinzgauer. Unsupervised clustering performed by the admixture analysis and two-dimensional presentation of the genetic distances between individuals also suggest Cika is a distinct breed despite being similar in appearance to Pinzgauer. Animals identified as the most purebred could be used as a nucleus for a recovery of the native genetic background in the current admixed population. The results show that local well-adapted strains, which have never been intensively managed and differentiated into specific breeds, exhibit large haplotype diversity. They suggest a conservation and recovery approach that does not rely exclusively on the search for the original native genetic background but rather on the identification and removal of common introgressed haplotypes would be more powerful. Successful implementation of such an approach should be based on combining phenotype, pedigree, and genome-wide haplotype data of the breed of interest and a spectrum of reference breeds which potentially have had direct or indirect historical contribution to the genetic makeup of the breed of interest. PMID:25923207

Genetics of PCOS: A systematic bioinformatics approach to unveil the proteins responsible for PCOS.

PubMed

Panda, Pritam Kumar; Rane, Riya; Ravichandran, Rahul; Singh, Shrinkhla; Panchal, Hetalkumar

2016-06-01

Polycystic ovary syndrome (PCOS) is a hormonal imbalance in women, which causes problems during menstrual cycle and in pregnancy that sometimes results in fatality. Though the genetics of PCOS is not fully understood, early diagnosis and treatment can prevent long-term effects. In this study, we have studied the proteins involved in PCOS and the structural aspects of the proteins that are taken into consideration using computational tools. The proteins involved are modeled using Modeller 9v14 and Ab-initio programs. All the 43 proteins responsible for PCOS were subjected to phylogenetic analysis to identify the relatedness of the proteins. Further, microarray data analysis of PCOS datasets was analyzed that was downloaded from GEO datasets to find the significant protein-coding genes responsible for PCOS, which is an addition to the reported protein-coding genes. Various statistical analyses were done using R programming to get an insight into the structural aspects of PCOS that can be used as drug targets to treat PCOS and other related reproductive diseases.

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.

Multi-period response management to contaminated water distribution networks: dynamic programming versus genetic algorithms

NASA Astrophysics Data System (ADS)

Bashi-Azghadi, Seyyed Nasser; Afshar, Abbas; Afshar, Mohammad Hadi

2018-03-01

Previous studies on consequence management assume that the selected response action including valve closure and/or hydrant opening remains unchanged during the entire management period. This study presents a new embedded simulation-optimization methodology for deriving time-varying operational response actions in which the network topology may change from one stage to another. Dynamic programming (DP) and genetic algorithm (GA) are used in order to minimize selected objective functions. Two networks of small and large sizes are used in order to illustrate the performance of the proposed modelling schemes if a time-dependent consequence management strategy is to be implemented. The results show that for a small number of decision variables even in large-scale networks, DP is superior in terms of accuracy and computer runtime. However, as the number of potential actions grows, DP loses its merit over the GA approach. This study clearly proves the priority of the proposed dynamic operation strategy over the commonly used static strategy.

A new mathematical modeling for pure parsimony haplotyping problem.

PubMed

Feizabadi, R; Bagherian, M; Vaziri, H R; Salahi, M

2016-11-01

Pure parsimony haplotyping (PPH) problem is important in bioinformatics because rational haplotyping inference plays important roles in analysis of genetic data, mapping complex genetic diseases such as Alzheimer's disease, heart disorders and etc. Haplotypes and genotypes are m-length sequences. Although several integer programing models have already been presented for PPH problem, its NP-hardness characteristic resulted in ineffectiveness of those models facing the real instances especially instances with many heterozygous sites. In this paper, we assign a corresponding number to each haplotype and genotype and based on those numbers, we set a mixed integer programing model. Using numbers, instead of sequences, would lead to less complexity of the new model in comparison with previous models in a way that there are neither constraints nor variables corresponding to heterozygous nucleotide sites in it. Experimental results approve the efficiency of the new model in producing better solution in comparison to two state-of-the art haplotyping approaches. Copyright © 2016 Elsevier Inc. All rights reserved.

Discovering Link Communities in Complex Networks by an Integer Programming Model and a Genetic Algorithm

PubMed Central

Li, Zhenping; Zhang, Xiang-Sun; Wang, Rui-Sheng; Liu, Hongwei; Zhang, Shihua

2013-01-01

Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks. PMID:24386268

Artificial intelligence in peer review: How can evolutionary computation support journal editors?

PubMed Central

Fronczak, Piotr; Fronczak, Agata; Ausloos, Marcel; Nedic, Olgica

2017-01-01

With the volume of manuscripts submitted for publication growing every year, the deficiencies of peer review (e.g. long review times) are becoming more apparent. Editorial strategies, sets of guidelines designed to speed up the process and reduce editors’ workloads, are treated as trade secrets by publishing houses and are not shared publicly. To improve the effectiveness of their strategies, editors in small publishing groups are faced with undertaking an iterative trial-and-error approach. We show that Cartesian Genetic Programming, a nature-inspired evolutionary algorithm, can dramatically improve editorial strategies. The artificially evolved strategy reduced the duration of the peer review process by 30%, without increasing the pool of reviewers (in comparison to a typical human-developed strategy). Evolutionary computation has typically been used in technological processes or biological ecosystems. Our results demonstrate that genetic programs can improve real-world social systems that are usually much harder to understand and control than physical systems. PMID:28931033

Neural networks with multiple general neuron models: a hybrid computational intelligence approach using Genetic Programming.

PubMed

Barton, Alan J; Valdés, Julio J; Orchard, Robert

2009-01-01

Classical neural networks are composed of neurons whose nature is determined by a certain function (the neuron model), usually pre-specified. In this paper, a type of neural network (NN-GP) is presented in which: (i) each neuron may have its own neuron model in the form of a general function, (ii) any layout (i.e network interconnection) is possible, and (iii) no bias nodes or weights are associated to the connections, neurons or layers. The general functions associated to a neuron are learned by searching a function space. They are not provided a priori, but are rather built as part of an Evolutionary Computation process based on Genetic Programming. The resulting network solutions are evaluated based on a fitness measure, which may, for example, be based on classification or regression errors. Two real-world examples are presented to illustrate the promising behaviour on classification problems via construction of a low-dimensional representation of a high-dimensional parameter space associated to the set of all network solutions.

Novel SNP markers in InvGE and SssI genes are associated with natural variation of sugar contents and frying color in Solanum tuberosum Group Phureja.

PubMed

Duarte-Delgado, Diana; Juyó, Deissy; Gebhardt, Christiane; Sarmiento, Felipe; Mosquera-Vásquez, Teresa

2017-03-09

Potato frying color is an agronomic trait influenced by the sugar content of tubers. The candidate gene approach was employed to elucidate the molecular basis of this trait in Solanum tuberosum Group Phureja, which is mainly diploid and represents an important genetic resource for potato breeding. The objective of this research was to identify novel genetic variants related with frying quality in loci with key functions in carbohydrate metabolism, with the purpose of discovering genetic variability useful in breeding programs. Therefore, an association analysis was implemented with 109 SNP markers identified in ten candidate genes. The analyses revealed four associations in the locus InvGE coding for an apoplastic invertase and one association in the locus SssI coding for a soluble starch synthase. The SNPs SssI-C 45711901 T and InvGE-C 2475454 T were associated with sucrose content and frying color, respectively, and were not found previously in tetraploid genotypes. The rare haplotype InvGE-A 2475187 C 2475295 A 2475344 was associated with higher fructose contents. Our study allowed a more detailed analysis of the sequence variation of exon 3 from InvGE, which was not possible in previous studies because of the high frequency of insertion-deletion polymorphisms in tetraploid potatoes. The association mapping strategy using a candidate gene approach in Group Phureja allowed the identification of novel SNP markers in InvGE and SssI associated with frying color and the tuber sugar content measured by High Performance Liquid Chromatography (HPLC). These novel associations might be useful in potato breeding programs for improving quality traits and to increase crop genetic variability. The results suggest that some genes involved in the natural variation of tuber sugar content and frying color are conserved in both Phureja and tetraploid germplasm. Nevertheless, the associated variants in both types of germplasm were present in different regions of these genes. This study contributes to the understanding of the genetic architecture of tuber sugar contents and frying color at harvest in Group Phureja.

Routine human-competitive machine intelligence by means of genetic programming

NASA Astrophysics Data System (ADS)

Koza, John R.; Streeter, Matthew J.; Keane, Martin

2004-01-01

Genetic programming is a systematic method for getting computers to automatically solve a problem. Genetic programming starts from a high-level statement of what needs to be done and automatically creates a computer program to solve the problem. The paper demonstrates that genetic programming (1) now routinely delivers high-return human-competitive machine intelligence; (2) is an automated invention machine; (3) can automatically create a general solution to a problem in the form of a parameterized topology; and (4) has delivered a progression of qualitatively more substantial results in synchrony with five approximately order-of-magnitude increases in the expenditure of computer time. Recent results involving the automatic synthesis of the topology and sizing of analog electrical circuits and controllers demonstrate these points.

Influence of ethnic traditional cultures on genetic diversity of rice landraces under on-farm conservation in southwest China.

PubMed

Wang, Yanjie; Wang, Yanli; Sun, Xiaodong; Caiji, Zhuoma; Yang, Jingbiao; Cui, Di; Cao, Guilan; Ma, Xiaoding; Han, Bing; Xue, Dayuan; Han, Longzhi

2016-10-27

Crop genetic resources are important components of biodiversity. However, with the large-scale promotion of mono-cropping, genetic diversity has largely been lost. Ex-situ conservation approaches were widely used to protect traditional crop varieties worldwide. However, this method fails to maintain the dynamic evolutionary processes of crop genetic resources in their original habitats, leading to genetic diversity reduction and even loss of the capacity of resistance to new diseases and pests. Therefore, on-farm conservation has been considered a crucial complement to ex-situ conservation. This study aimed at clarifying the genetic diversity differences between ex-situ conservation and on-farm conservation and to exploring the influence of traditional cultures on genetic diversity of rice landraces under on-farm conservation. The conservation status of rice landrace varieties, including Indica and Japonica, non-glutinous rice (Oryza sativa) and glutinous rice (Oryza sativa var. glutinosa Matsum), was obtained through ethno-biology investigation method in 12 villages of ethnic groups from Guizhou, Yunnan and Guangxi provinces of China. The genetic diversity between 24 pairs of the same rice landraces from different times were compared using simple sequence repeat (SSR) molecular markers technology. The landrace paris studied were collected in 1980 and maintained ex-situ, while 2014 samples were collected on-farm in southwest of China. The results showed that many varieties of rice landraces have been preserved on-farm by local farmers for hundreds or thousands of years. The number of alleles (Na), effective number of alleles (Ne), Nei genetic diversity index (He) and Shannon information index (I) of rice landraces were significantly higher by 12.3-30.4 % under on-farm conservation than under ex-situ conservation. Compared with the ex-situ conservation approach, rice landraces under on-farm conservation programs had more alleles and higher genetic diversity. In every site we investigated, ethnic traditional cultures play a positive influence on rice landrace variety diversity and genetic diversity. Most China's rice landraces were conserved in the ethnic areas of southwest China. On-farm conservation can effectively promote the allelic variation and increase the genetic diversity of rice landraces over the past 35 years. Moreover, ethnic traditional culture practices are a crucial foundation to increase genetic diversity of rice landraces and implement on-farm conservation.

Postdoctoral training in posttraumatic stress disorder research.

PubMed

Sloan, Denise M; Vogt, Dawne; Wisco, Blair E; Keane, Terence M

2015-03-01

Postdoctoral training is increasingly common in the field of psychology. Although many individuals pursue postdoctoral training in psychology, guidelines for research training programs at this level do not exist. The rapid advances in the field, particularly with respect to genetics, neuroimaging, and data analytic approaches, require clinical scientists to possess knowledge and expertise across a broad array of areas. Postdoctoral training is often needed to acquire such a skill set. This paper describes a postdoctoral training program designed for individuals pursuing academic careers in traumatic stress disorders research. In this paper, we describe the structure of our training program, challenges we have faced during the 15 years of its existence, and how we have addressed these challenges. We conclude with a presentation of outcome data for the training program and a discussion of how training programs in other settings might be structured. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Guidelines on the use of molecular genetics in reintroduction programs

Treesearch

Michael K. Schwartz

2005-01-01

The use of molecular genetics can play a key role in reintroduction efforts. Prior to the introduction of any individuals, molecular genetics can be used to identify the most appropriate source population for the reintroduction, ensure that no relic populations exist in the reintroduction area, and guide captive breeding programs. The use of molecular genetics post-...

Constructing linkage maps in the genomics era with MapDisto 2.0.

PubMed

Heffelfinger, Christopher; Fragoso, Christopher A; Lorieux, Mathias

2017-07-15

Genotyping by sequencing (GBS) generates datasets that are challenging to handle by current genetic mapping software with graphical interface. Geneticists need new user-friendly computer programs that can analyze GBS data on desktop computers. This requires improvements in computation efficiency, both in terms of speed and use of random-access memory (RAM). MapDisto v.2.0 is a user-friendly computer program for construction of genetic linkage maps. It includes several new major features: (i) handling of very large genotyping datasets like the ones generated by GBS; (ii) direct importation and conversion of Variant Call Format (VCF) files; (iii) detection of linkage, i.e. construction of linkage groups in case of segregation distortion; (iv) data imputation on VCF files using a new approach, called LB-Impute. Features i to iv operate through inclusion of new Java modules that are used transparently by MapDisto; (v) QTL detection via a new R/qtl graphical interface. The program is available free of charge at mapdisto.free.fr. mapdisto@gmail.com. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Review of functional markers for improving cooking, eating, and the nutritional qualities of rice

PubMed Central

Lau, Wendy C. P.; Rafii, Mohd Y.; Ismail, Mohd R.; Puteh, Adam; Latif, Mohammad A.; Ramli, Asfaliza

2015-01-01

After yield, quality is one of the most important aspects of rice breeding. Preference for rice quality varies among cultures and regions; therefore, rice breeders have to tailor the quality according to the preferences of local consumers. Rice quality assessment requires routine chemical analysis procedures. The advancement of molecular marker technology has revolutionized the strategy in breeding programs. The availability of rice genome sequences and the use of forward and reverse genetics approaches facilitate gene discovery and the deciphering of gene functions. A well-characterized gene is the basis for the development of functional markers, which play an important role in plant genotyping and, in particular, marker-assisted breeding. In addition, functional markers offer advantages that counteract the limitations of random DNA markers. Some functional markers have been applied in marker-assisted breeding programs and have successfully improved rice quality to meet local consumers’ preferences. Although functional markers offer a plethora of advantages over random genetic markers, the development and application of functional markers should be conducted with care. The decreasing cost of sequencing will enable more functional markers for rice quality improvement to be developed, and application of these markers in rice quality breeding programs is highly anticipated. PMID:26528304

Advancing Pharmacogenomics Education in the Core PharmD Curriculum through Student Personal Genomic Testing

PubMed Central

Adams, Solomon M.; Anderson, Kacey B.; Coons, James C.; Smith, Randall B.; Meyer, Susan M.; Parker, Lisa S.

2016-01-01

Objective. To develop, implement, and evaluate “Test2Learn” a program to enhance pharmacogenomics education through the use of personal genomic testing (PGT) and real genetic data. Design. One hundred twenty-two second-year doctor of pharmacy (PharmD) students in a required course were offered PGT as part of a larger program approach to teach pharmacogenomics within a robust ethical framework. The program added novel learning objectives, lecture materials, analysis tools, and exercises using individual-level and population-level genetic data. Outcomes were assessed with objective measures and pre/post survey instruments. Assessment. One hundred students (82%) underwent PGT. Knowledge significantly improved on multiple assessments. Genotyped students reported a greater increase in confidence in understanding test results by the end of the course. Similarly, undergoing PGT improved student’s self-perceived ability to empathize with patients compared to those not genotyped. Most students (71%) reported feeling PGT was an important part of the course, and 60% reported they had a better understanding of pharmacogenomics specifically because of the opportunity. Conclusion. Implementation of PGT in the core pharmacy curriculum was feasible, well-received, and enhanced student learning of pharmacogenomics. PMID:26941429

Ecological speciation in the tropics: insights from comparative genetic studies in Amazonia

PubMed Central

Beheregaray, Luciano B.; Cooke, Georgina M.; Chao, Ning L.; Landguth, Erin L.

2015-01-01

Evolution creates and sustains biodiversity via adaptive changes in ecologically relevant traits. Ecologically mediated selection contributes to genetic divergence both in the presence or absence of geographic isolation between populations, and is considered an important driver of speciation. Indeed, the genetics of ecological speciation is becoming increasingly studied across a variety of taxa and environments. In this paper we review the literature of ecological speciation in the tropics. We report on low research productivity in tropical ecosystems and discuss reasons accounting for the rarity of studies. We argue for research programs that simultaneously address biogeographical and taxonomic questions in the tropics, while effectively assessing relationships between reproductive isolation and ecological divergence. To contribute toward this goal, we propose a new framework for ecological speciation that integrates information from phylogenetics, phylogeography, population genomics, and simulations in evolutionary landscape genetics (ELG). We introduce components of the framework, describe ELG simulations (a largely unexplored approach in ecological speciation), and discuss design and experimental feasibility within the context of tropical research. We then use published genetic datasets from populations of five codistributed Amazonian fish species to assess the performance of the framework in studies of tropical speciation. We suggest that these approaches can assist in distinguishing the relative contribution of natural selection from biogeographic history in the origin of biodiversity, even in complex ecosystems such as Amazonia. We also discuss on how to assess ecological speciation using ELG simulations that include selection. These integrative frameworks have considerable potential to enhance conservation management in biodiversity rich ecosystems and to complement historical biogeographic and evolutionary studies of tropical biotas. PMID:25653668

Higher criticism approach to detect rare variants using whole genome sequencing data

PubMed Central

2014-01-01

Because of low statistical power of single-variant tests for whole genome sequencing (WGS) data, the association test for variant groups is a key approach for genetic mapping. To address the features of sparse and weak genetic effects to be detected, the higher criticism (HC) approach has been proposed and theoretically has proven optimal for detecting sparse and weak genetic effects. Here we develop a strategy to apply the HC approach to WGS data that contains rare variants as the majority. By using Genetic Analysis Workshop 18 "dose" genetic data with simulated phenotypes, we assess the performance of HC under a variety of strategies for grouping variants and collapsing rare variants. The HC approach is compared with the minimal p-value method and the sequence kernel association test. The results show that the HC approach is preferred for detecting weak genetic effects. PMID:25519367

The “Genetic Program”: Behind the Genesis of an Influential Metaphor

PubMed Central

Peluffo, Alexandre E.

2015-01-01

The metaphor of the “genetic program,” indicating the genome as a set of instructions required to build a phenotype, has been very influential in biology despite various criticisms over the years. This metaphor, first published in 1961, is thought to have been invented independently in two different articles, one by Ernst Mayr and the other by François Jacob and Jacques Monod. Here, after a detailed analysis of what both parties meant by “genetic program,” I show, using unpublished archives, the strong resemblance between the ideas of Mayr and Monod and suggest that their idea of genetic program probably shares a common origin. I explore the possibility that the two men met before 1961 and also exchanged their ideas through common friends and colleagues in the field of molecular biology. Based on unpublished correspondence of Jacob and Monod, I highlight the important events that influenced the preparation of their influential paper, which introduced the concept of the genetic program. Finally, I suggest that the genetic program metaphor may have preceded both papers and that it was probably used informally before 1961. PMID:26170444

A counterfactual impact evaluation of a bilingual program on students' grade point average at a spanish university.

PubMed

Arco-Tirado, J L; Fernández-Martín, F; Ramos-García, A M; Littvay, L; Villoria, J; Naranjo, J A

2018-06-01

This observational study intends to estimate the causal effects of an English as a Medium of Instruction (EMI) program (as predictor) on students Grade Point Average (GPA) (as outcome) at a particular University in Spain by using a Counterfactual Impact Evaluation (CIE). The need to address the crucial question of causal inferences in EMI programs to produce credible evidences of successful interventions contrasts, however, with the absence of experimental or quasi-experimental research and evaluation designs in the field. CIE approach is emerging as a methodologically viable solution to bridge that gap. The program evaluated here consisted in delivering an EMI program in a Primary Education Teacher Training Degree group. After achieving balance on the observed covariates and recreating a situation that would have been expected in a randomized experiment, three matching approaches such as genetic matching, nearest neighbor matching and Coarsened Exact Matching were used to analyze observational data from a total of 1288 undergraduate students, including both treatment and control group. Results show unfavorable effects of the bilingual group treatment condition. Potential interpretations and recommendations are provided in order to strengthen future causal evidences of bilingual education programs' effectiveness in Higher Education. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

ECUT: Energy Conversion and Utilization Technologies program. Biocatalysis project

NASA Technical Reports Server (NTRS)

1990-01-01

The Biocatalysis Project is a mission-oriented, applied research and exploratory development activity directed toward resolution of the major generic technical barriers that impede the development of biologically catalyzed commercial chemical production. The approach toward achieving project objectives involves an integrated participation of Universities, Industrial Companies and Government Research Laboratories. The Project's technical activities were organized into three work elements: molecular modeling and applied genetics; bioprocess engineering; and bioprocess design and assessment.

Determinism and Underdetermination in Genetics: Implications for Students' Engagement in Argumentation and Epistemic Practices

NASA Astrophysics Data System (ADS)

Jiménez-Aleixandre, María Pilar

2014-02-01

In the last two decades science studies and science education research have shifted from an interest in products (of science or of learning), to an interest in processes and practices. The focus of this paper is on students' engagement in epistemic practices (Kelly in Teaching scientific inquiry: Recommendations for research and implementation. Sense Publishers, Rotterdam, pp 99-117, 2008), or on their practical epistemologies (Wickman in Sci Educ 88(3):325-344, 2004). In order to support these practices in genetics classrooms we need to take into account domain-specific features of the epistemology of genetics, in particular issues about determinism and underdetermination. I suggest that certain difficulties may be related to the specific nature of causality in genetics, and in particular to the correspondence between a given set of factors and a range of potential effects, rather than a single one. The paper seeks to bring together recent developments in the epistemology of biology and of genetics, on the one hand, with science education approaches about epistemic practices, on the other. The implications of these perspectives for current challenges in learning genetics are examined, focusing on students' engagement in epistemic practices, as argumentation, understood as using evidence to evaluate knowledge claims. Engaging in argumentation in genetics classrooms is intertwined with practices such as using genetics models to build explanations, or framing genetics issues in their social context. These challenges are illustrated with studies making part of our research program in the USC.

Genome-Wide Association Study of Genetic Control of Seed Fatty Acid Biosynthesis in Brassica napus

PubMed Central

Gacek, Katarzyna; Bayer, Philipp E.; Bartkowiak-Broda, Iwona; Szala, Laurencja; Bocianowski, Jan; Edwards, David; Batley, Jacqueline

2017-01-01

Fatty acids and their composition in seeds determine oil value for nutritional or industrial purposes and also affect seed germination as well as seedling establishment. To better understand the genetic basis of seed fatty acid biosynthesis in oilseed rape (Brassica napus L.) we applied a genome-wide association study, using 91,205 single nucleotide polymorphisms (SNPs) characterized across a mapping population with high-resolution skim genotyping by sequencing (SkimGBS). We identified a cluster of loci on chromosome A05 associated with oleic and linoleic seed fatty acids. The delineated genomic region contained orthologs of the Arabidopsis thaliana genes known to play a role in regulation of seed fatty acid biosynthesis such as Fatty acyl-ACP thioesterase B (FATB) and Fatty Acid Desaturase (FAD5). This approach allowed us to identify potential functional genes regulating fatty acid composition in this important oil producing crop and demonstrates that this approach can be used as a powerful tool for dissecting complex traits for B. napus improvement programs. PMID:28163710

Targeted genotyping-by-sequencing permits cost-effective identification and discrimination of pasture grass species and cultivars.

PubMed

Pembleton, Luke W; Drayton, Michelle C; Bain, Melissa; Baillie, Rebecca C; Inch, Courtney; Spangenberg, German C; Wang, Junping; Forster, John W; Cogan, Noel O I

2016-05-01

A targeted amplicon-based genotyping-by-sequencing approach has permitted cost-effective and accurate discrimination between ryegrass species (perennial, Italian and inter-species hybrid), and identification of cultivars based on bulked samples. Perennial ryegrass and Italian ryegrass are the most important temperate forage species for global agriculture, and are represented in the commercial pasture seed market by numerous cultivars each composed of multiple highly heterozygous individuals. Previous studies have identified difficulties in the use of morphophysiological criteria to discriminate between these two closely related taxa. Recently, a highly multiplexed single nucleotide polymorphism (SNP)-based genotyping assay has been developed that permits accurate differentiation between both species and cultivars of ryegrasses at the genetic level. This assay has since been further developed into an amplicon-based genotyping-by-sequencing (GBS) approach implemented on a second-generation sequencing platform, allowing accelerated throughput and ca. sixfold reduction in cost. Using the GBS approach, 63 cultivars of perennial, Italian and interspecific hybrid ryegrasses, as well as intergeneric Festulolium hybrids, were genotyped. The genetic relationships between cultivars were interpreted in terms of known breeding histories and indistinct species boundaries within the Lolium genus, as well as suitability of current cultivar registration methodologies. An example of applicability to quality assurance and control (QA/QC) of seed purity is also described. Rapid, low-cost genotypic assays provide new opportunities for breeders to more fully explore genetic diversity within breeding programs, allowing the combination of novel unique genetic backgrounds. Such tools also offer the potential to more accurately define cultivar identities, allowing protection of varieties in the commercial market and supporting processes of cultivar accreditation and quality assurance.

Evolutionary-based approaches for determining the deviatoric stress of calcareous sands

NASA Astrophysics Data System (ADS)

Shahnazari, Habib; Tutunchian, Mohammad A.; Rezvani, Reza; Valizadeh, Fatemeh

2013-01-01

Many hydrocarbon reservoirs are located near oceans which are covered by calcareous deposits. These sediments consist mainly of the remains of marine plants or animals, so calcareous soils can have a wide variety of engineering properties. Due to their local expansion and considerable differences from terrigenous soils, the evaluation of engineering behaviors of calcareous sediments has been a major concern for geotechnical engineers in recent years. Deviatoric stress is one of the most important parameters directly affecting important shearing characteristics of soils. In this study, a dataset of experimental triaxial tests was gathered from two sources. First, the data of previous experimental studies from the literature were gathered. Then, a series of triaxial tests was performed on calcareous sands of the Persian Gulf to develop the dataset. This work resulted in a large database of experimental results on the maximum deviatoric stress of different calcareous sands. To demonstrate the capabilities of evolutionary-based approaches in modeling the deviatoric stress of calcareous sands, two promising variants of genetic programming (GP), multigene genetic programming (MGP) and gene expression programming (GEP), were applied to propose new predictive models. The models' input parameters were the physical and in-situ condition properties of soil and the output was the maximum deviatoric stress (i.e., the axial-deviator stress). The results of statistical analyses indicated the robustness of these models, and a parametric study was also conducted for further verification of the models, in which the resulting trends were consistent with the results of the experimental study. Finally, the proposed models were further simplified by applying a practical geotechnical correlation.

Efficient identification and referral of low-income women at high risk for hereditary breast cancer: a practice-based approach.

PubMed

Joseph, G; Kaplan, C; Luce, J; Lee, R; Stewart, S; Guerra, C; Pasick, R

2012-01-01

Identification of low-income women with the rare but serious risk of hereditary cancer and their referral to appropriate services presents an important public health challenge. We report the results of formative research to reach thousands of women for efficient identification of those at high risk and expedient access to free genetic services. External validity is maximized by emphasizing intervention fit with the two end-user organizations who must connect to make this possible. This study phase informed the design of a subsequent randomized controlled trial. We conducted a randomized controlled pilot study (n = 38) to compare two intervention models for feasibility and impact. The main outcome was receipt of genetic counseling during a two-month intervention period. Model 1 was based on the usual outcall protocol of an academic hospital genetic risk program, and Model 2 drew on the screening and referral procedures of a statewide toll-free phone line through which large numbers of high-risk women can be identified. In Model 1, the risk program proactively calls patients to schedule genetic counseling; for Model 2, women are notified of their eligibility for counseling and make the call themselves. We also developed and pretested a family history screener for administration by phone to identify women appropriate for genetic counseling. There was no statistically significant difference in receipt of genetic counseling between women randomized to Model 1 (3/18) compared with Model 2 (3/20) during the intervention period. However, when unresponsive women in Model 2 were called after 2 months, 7 more obtained counseling; 4 women from Model 1 were also counseled after the intervention. Thus, the intervention model that closely aligned with the risk program's outcall to high-risk women was found to be feasible and brought more low-income women to free genetic counseling. Our screener was easy to administer by phone and appeared to identify high-risk callers effectively. The model and screener are now in use in the main trial to test the effectiveness of this screening and referral intervention. A validation analysis of the screener is also underway. Identification of intervention strategies and tools, and their systematic comparison for impact and efficiency in the context where they will ultimately be used are critical elements of practice-based research. Copyright © 2012 S. Karger AG, Basel.

Attaining genetic height potential: Analysis of height outcomes from the ANSWER Program in children treated with growth hormone over 5 years.

PubMed

Ross, Judith L; Lee, Peter A; Gut, Robert; Germak, John

2015-12-01

This study aimed to assess attainment of genetic height potential after long-term growth hormone (GH) treatment in GH-naïve children diagnosed with isolated growth hormone deficiency (IGHD), multiple pituitary hormone deficiency (MPHD), born small for gestational age (SGA), or idiopathic short stature (ISS) enrolled in the American Norditropin® Web-enabled Research (ANSWER) Program. Children with IGHD (n=2884), MPHD (n=200), SGA (n=481), or ISS (n=733) with baseline height standard deviation score (HSDS)≤-2 were assessed over 5 years of GH treatment for mean HSDS, change in HSDS (ΔHSDS), and corrected HSDS (HSDS-target HSDS). Mean HSDS and corrected HSDS significantly increased to close to target height across all diagnostic groups after 5 years of GH treatment (P<0.0001). ∆HSDS at year 5 increased for all groups (IGHD: 1.8; MPHD: 2.1; SGA: 1.8; ISS: 1.6). Among patients who continued GH for 5 years, mean insulin-like growth factor-I (IGF-I) SDS increased to within normal range across all groups. Body mass index (BMI) SDS remained relatively stable in all diagnostic groups. Bone age (BA) increased, and the mean BA to chronological age (BA/CA) ratio reached or approached 1 across diagnostic groups over 5 years of GH treatment. Long-term GH therapy resulted in a significant increase in mean HSDS and corrected HSDS from baseline values in all diagnostic groups. The observed increase in mean corrected HSDS is consistent with growth that approached the patients' genetic height potential, although complete height gains will be evaluated at the attainment of final height. Copyright © 2015 Elsevier Ltd. All rights reserved.

Conservation and canalization of gene expression during angiosperm diversification accompany the origin and evolution of the flower

PubMed Central

Chanderbali, André S.; Yoo, Mi-Jeong; Zahn, Laura M.; Brockington, Samuel F.; Wall, P. Kerr; Gitzendanner, Matthew A.; Albert, Victor A.; Leebens-Mack, James; Altman, Naomi S.; Ma, Hong; dePamphilis, Claude W.; Soltis, Douglas E.; Soltis, Pamela S.

2010-01-01

The origin and rapid diversification of the angiosperms (Darwin's “Abominable Mystery”) has engaged generations of researchers. Here, we examine the floral genetic programs of phylogenetically pivotal angiosperms (water lily, avocado, California poppy, and Arabidopsis) and a nonflowering seed plant (a cycad) to obtain insight into the origin and subsequent evolution of the flower. Transcriptional cascades with broadly overlapping spatial domains, resembling the hypothesized ancestral gymnosperm program, are deployed across morphologically intergrading organs in water lily and avocado flowers. In contrast, spatially discrete transcriptional programs in distinct floral organs characterize the more recently derived angiosperm lineages represented by California poppy and Arabidopsis. Deep evolutionary conservation in the genetic programs of putatively homologous floral organs traces to those operating in gymnosperm reproductive cones. Female gymnosperm cones and angiosperm carpels share conserved genetic features, which may be associated with the ovule developmental program common to both organs. However, male gymnosperm cones share genetic features with both perianth (sterile attractive and protective) organs and stamens, supporting the evolutionary origin of the floral perianth from the male genetic program of seed plants. PMID:21149731

Conservation and canalization of gene expression during angiosperm diversification accompany the origin and evolution of the flower.

PubMed

Chanderbali, André S; Yoo, Mi-Jeong; Zahn, Laura M; Brockington, Samuel F; Wall, P Kerr; Gitzendanner, Matthew A; Albert, Victor A; Leebens-Mack, James; Altman, Naomi S; Ma, Hong; dePamphilis, Claude W; Soltis, Douglas E; Soltis, Pamela S

2010-12-28

The origin and rapid diversification of the angiosperms (Darwin's "Abominable Mystery") has engaged generations of researchers. Here, we examine the floral genetic programs of phylogenetically pivotal angiosperms (water lily, avocado, California poppy, and Arabidopsis) and a nonflowering seed plant (a cycad) to obtain insight into the origin and subsequent evolution of the flower. Transcriptional cascades with broadly overlapping spatial domains, resembling the hypothesized ancestral gymnosperm program, are deployed across morphologically intergrading organs in water lily and avocado flowers. In contrast, spatially discrete transcriptional programs in distinct floral organs characterize the more recently derived angiosperm lineages represented by California poppy and Arabidopsis. Deep evolutionary conservation in the genetic programs of putatively homologous floral organs traces to those operating in gymnosperm reproductive cones. Female gymnosperm cones and angiosperm carpels share conserved genetic features, which may be associated with the ovule developmental program common to both organs. However, male gymnosperm cones share genetic features with both perianth (sterile attractive and protective) organs and stamens, supporting the evolutionary origin of the floral perianth from the male genetic program of seed plants.

Molecular Marker Systems for Oenothera Genetics

PubMed Central

Rauwolf, Uwe; Golczyk, Hieronim; Meurer, Jörg; Herrmann, Reinhold G.; Greiner, Stephan

2008-01-01

The genus Oenothera has an outstanding scientific tradition. It has been a model for studying aspects of chromosome evolution and speciation, including the impact of plastid nuclear co-evolution. A large collection of strains analyzed during a century of experimental work and unique genetic possibilities allow the exchange of genetically definable plastids, individual or multiple chromosomes, and/or entire haploid genomes (Renner complexes) between species. However, molecular genetic approaches for the genus are largely lacking. In this study, we describe the development of efficient PCR-based marker systems for both the nuclear genome and the plastome. They allow distinguishing individual chromosomes, Renner complexes, plastomes, and subplastomes. We demonstrate their application by monitoring interspecific exchanges of genomes, chromosome pairs, and/or plastids during crossing programs, e.g., to produce plastome–genome incompatible hybrids. Using an appropriate partial permanent translocation heterozygous hybrid, linkage group 7 of the molecular map could be assigned to chromosome 9·8 of the classical Oenothera map. Finally, we provide the first direct molecular evidence that homologous recombination and free segregation of chromosomes in permanent translocation heterozygous strains is suppressed. PMID:18791241

Molecular marker systems for Oenothera genetics.

PubMed

Rauwolf, Uwe; Golczyk, Hieronim; Meurer, Jörg; Herrmann, Reinhold G; Greiner, Stephan

2008-11-01

The genus Oenothera has an outstanding scientific tradition. It has been a model for studying aspects of chromosome evolution and speciation, including the impact of plastid nuclear co-evolution. A large collection of strains analyzed during a century of experimental work and unique genetic possibilities allow the exchange of genetically definable plastids, individual or multiple chromosomes, and/or entire haploid genomes (Renner complexes) between species. However, molecular genetic approaches for the genus are largely lacking. In this study, we describe the development of efficient PCR-based marker systems for both the nuclear genome and the plastome. They allow distinguishing individual chromosomes, Renner complexes, plastomes, and subplastomes. We demonstrate their application by monitoring interspecific exchanges of genomes, chromosome pairs, and/or plastids during crossing programs, e.g., to produce plastome-genome incompatible hybrids. Using an appropriate partial permanent translocation heterozygous hybrid, linkage group 7 of the molecular map could be assigned to chromosome 9.8 of the classical Oenothera map. Finally, we provide the first direct molecular evidence that homologous recombination and free segregation of chromosomes in permanent translocation heterozygous strains is suppressed.

Genetics and the unity of biology. Program

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

Not Available

1988-12-31

International Congresses of Genetics, convened just once every five years, provide a rare opportunity for overview in the field of genetic engineering. The Congress, held August 20-27, 1988 in Toronto, Canada focused on the theme Genetics and the Unity of Biology, which was chosen because the concepts of modern genetics have provided biology with a unifying theoretical structure. This program guide contains a schedule of all Congress activities and a listing of all Symposia, Workshops and Poster Sessions held.

Analyzing Population Genetics Data: A Comparison of the Software

USDA-ARS?s Scientific Manuscript database

Choosing a software program for analyzing population genetic data can be a challenge without prior knowledge of the methods used by each program. There are numerous web sites listing programs by type of data analyzed, type of analyses performed, or other criteria. Even with programs categorized in ...

Increased genetic gains in sheep, beef and dairy breeding programs from using female reproductive technologies combined with optimal contribution selection and genomic breeding values.

PubMed

Granleese, Tom; Clark, Samuel A; Swan, Andrew A; van der Werf, Julius H J

2015-09-14

Female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro embryo production and embryo transfer (JIVET) can boost rates of genetic gain but they can also increase rates of inbreeding. Inbreeding can be managed using the principles of optimal contribution selection (OCS), which maximizes genetic gain while placing a penalty on the rate of inbreeding. We evaluated the potential benefits and synergies that exist between genomic selection (GS) and reproductive technologies under OCS for sheep and cattle breeding programs. Various breeding program scenarios were simulated stochastically including: (1) a sheep breeding program for the selection of a single trait that could be measured either early or late in life; (2) a beef breeding program with an early or late trait; and (3) a dairy breeding program with a sex limited trait. OCS was applied using a range of penalties (severe to no penalty) on co-ancestry of selection candidates, with the possibility of using multiple ovulation and embryo transfer (MOET) and/or juvenile in vitro embryo production and embryo transfer (JIVET) for females. Each breeding program was simulated with and without genomic selection. All breeding programs could be penalized to result in an inbreeding rate of 1 % increase per generation. The addition of MOET to artificial insemination or natural breeding (AI/N), without the use of GS yielded an extra 25 to 60 % genetic gain. The further addition of JIVET did not yield an extra genetic gain. When GS was used, MOET and MOET + JIVET programs increased rates of genetic gain by 38 to 76 % and 51 to 81 % compared to AI/N, respectively. Large increases in genetic gain were found across species when female reproductive technologies combined with genomic selection were applied and inbreeding was managed, especially for breeding programs that focus on the selection of traits measured late in life or that are sex-limited. Optimal contribution selection was an effective tool to optimally allocate different combinations of reproductive technologies. Applying a range of penalties to co-ancestry of selection candidates allows a comprehensive exploration of the inbreeding vs. genetic gain space.

Cancer Genetics and Signaling | Center for Cancer Research

Cancer.gov

The Cancer, Genetics, and Signaling (CGS) Group at the National Cancer Institute at Frederick  offers a competitive postdoctoral training and mentoring program focusing on molecular and genetic aspects of cancer. The CGS Fellows Program is designed to attract and train exceptional postdoctoral fellows interested in pursuing independent research career tracks. CGS Fellows participate in a structured mentoring program designed for scientific and career development and transition to independent positions.

Patterns of ancestry and genetic diversity in reintroduced populations of the slimy sculpin: Implications for conservation

USGS Publications Warehouse

Huff, David D.; Miller, Loren M.; Vondracek, Bruce C.

2010-01-01

Reintroductions are a common approach for preserving intraspecific biodiversity in fragmented landscapes. However, they may exacerbate the reduction in genetic diversity initially caused by population fragmentation because the effective population size of reintroduced populations is often smaller and reintroduced populations also tend to be more geographically isolated than native populations. Mixing genetically divergent sources for reintroduction purposes is a practice intended to increase genetic diversity. We documented the outcome of reintroductions from three mixed sources on the ancestral composition and genetic variation of a North American fish, the slimy sculpin (Cottus cognatus). We used microsatellite markers to evaluate allelic richness and heterozygosity in the reintroduced populations relative to computer simulated expectations. Sculpins in reintroduced populations exhibited higher levels of heterozygosity and allelic richness than any single source, but only slightly higher than the single most genetically diverse source population. Simulations intended to mimic an ideal scenario for maximizing genetic variation in the reintroduced populations also predicted increases, but they were only moderately greater than the most variable source population. We found that a single source contributed more than the other two sources at most reintroduction sites. We urge caution when choosing whether to mix source populations in reintroduction programs. Genetic characteristics of candidate source populations should be evaluated prior to reintroduction if feasible. When combined with knowledge of the degree of genetic distinction among sources, simulations may allow the genetic diversity benefits of mixing populations to be weighed against the risks of outbreeding depression in reintroduced and nearby populations.

Patterns of ancestry and genetic diversity in reintroduced populations of the slimy sculpin: Implications for conservation

USGS Publications Warehouse

Huff, D.D.; Miller, L.M.; Vondracek, B.

2010-01-01

Reintroductions are a common approach for preserving intraspecific biodiversity in fragmented landscapes. However, they may exacerbate the reduction in genetic diversity initially caused by population fragmentation because the effective population size of reintroduced populations is often smaller and reintroduced populations also tend to be more geographically isolated than native populations. Mixing genetically divergent sources for reintroduction purposes is a practice intended to increase genetic diversity. We documented the outcome of reintroductions from three mixed sources on the ancestral composition and genetic variation of a North American fish, the slimy sculpin (Cottus cognatus). We used microsatellite markers to evaluate allelic richness and heterozygosity in the reintroduced populations relative to computer simulated expectations. Sculpins in reintroduced populations exhibited higher levels of heterozygosity and allelic richness than any single source, but only slightly higher than the single most genetically diverse source population. Simulations intended to mimic an ideal scenario for maximizing genetic variation in the reintroduced populations also predicted increases, but they were only moderately greater than the most variable source population. We found that a single source contributed more than the other two sources at most reintroduction sites. We urge caution when choosing whether to mix source populations in reintroduction programs. Genetic characteristics of candidate source populations should be evaluated prior to reintroduction if feasible. When combined with knowledge of the degree of genetic distinction among sources, simulations may allow the genetic diversity benefits of mixing populations to be weighed against the risks of outbreeding depression in reintroduced and nearby populations. ?? 2010 US Government.

No apparent reduction in schistosome burden or genetic diversity following four years of school-based mass drug administration in mwea, central kenya, a heavy transmission area.

PubMed

Lelo, Agola E; Mburu, David N; Magoma, Gabriel N; Mungai, Ben N; Kihara, Jimmy H; Mwangi, Ibrahim N; Maina, Geoffrey M; Kinuthia, Joseph M; Mutuku, Martin W; Loker, Eric S; Mkoji, Gerald M; Steinauer, Michelle L

2014-10-01

Schistosomiasis is a debilitating neglected tropical disease that infects over 200 million people worldwide. To combat this disease, in 2012, the World Health Organization announced a goal of reducing and eliminating transmission of schistosomes. Current control focuses primarily on mass drug administration (MDA). Therefore, we monitored transmission of Schistosoma mansoni via fecal egg counts and genetic markers in a typical school based MDA setting to ascertain the actual impacts of MDA on the targeted schistosome population. For 4 years, we followed 67 children enrolled in a MDA program in Kenya. Infection status and egg counts were measured each year prior to treatment. For 15 of these children, for which there was no evidence of acquired resistance, meaning they became re-infected following each treatment, we collected microsatellite genotype data from schistosomes passed in fecal samples as a representation of the force of transmission between drug treatments. We genotyped a total of 4938 parasites from these children, with an average of 329.2 parasites per child for the entire study, and an average of 82.3 parasites per child per annual examination. We compared prevalence, egg counts, and genetic measures including allelic richness, gene diversity (expected heterozygosity), adult worm burdens and effective number of breeders among time points to search for evidence for a change in transmission or schistosome populations during the MDA program. We found no evidence of reduced transmission or schistosome population decline over the course of the program. Although prevalence declined in the 67 children as it did in the overall program, reinfection rates were high, and for the 15 children studied in detail, schistosome egg counts and estimated adult worm burdens did not decline between years 1 and 4, and genetic diversity increased over the course of drug treatment. School based control programs undoubtedly improve the health of individuals; however, our data show that in an endemic area, such a program has had no obvious effect on reducing transmission or of significantly impacting the schistosome population as sampled by the children we studied in depth. Results like these, in combination with other sources of information, suggest more integrated approaches for interrupting transmission and significantly diminishing schistosome populations will be required to achieve sustainable control.

Early 20th-century research at the interfaces of genetics, development, and evolution: reflections on progress and dead ends.

PubMed

Deichmann, Ute

2011-09-01

Three early 20th-century attempts at unifying separate areas of biology, in particular development, genetics, physiology, and evolution, are compared in regard to their success and fruitfulness for further research: Jacques Loeb's reductionist project of unifying approaches by physico-chemical explanations; Richard Goldschmidt's anti-reductionist attempts to unify by integration; and Sewall Wright's combination of reductionist research and vision of hierarchical genetic systems. Loeb's program, demanding that all aspects of biology, including evolution, be studied by the methods of the experimental sciences, proved highly successful and indispensible for higher level investigations, even though evolutionary change and properties of biological systems up to now cannot be fully explained on the molecular level alone. Goldschmidt has been appraised as pioneer of physiological and developmental genetics and of a new evolutionary synthesis which transcended neo-Darwinism. However, this study concludes that his anti-reductionist attempts to integrate genetics, development and evolution have to be regarded as failures or dead ends. His grand speculations were based on the one hand on concepts and experimental systems that were too vague in order to stimulate further research, and on the other on experiments which in their core parts turned out not to be reproducible. In contrast, Sewall Wright, apart from being one of the architects of the neo-Darwinian synthesis of the 1930s, opened up new paths of testable quantitative developmental genetic investigations. He placed his research within a framework of logical reasoning, which resulted in the farsighted speculation that examinations of biological systems should be related to the regulation of hierarchical genetic subsystems, possibly providing a mechanism for development and evolution. I argue that his suggestion of basing the study of systems on clearly defined properties of the components has proved superior to Goldschmidt's approach of studying systems as a whole, and that attempts to integrate different fields at a too early stage may prove futile or worse. Copyright © 2011 Elsevier Inc. All rights reserved.

Evaluation of offspring and maternal genetic effects on disease risk using a family-based approach: the "pent" design.

PubMed

Mitchell, Laura E; Weinberg, Clarice R

2005-10-01

Diseases that develop during gestation may be influenced by the genotype of the mother and the inherited genotype of the embryo/fetus. However, given the correlation between maternal and offspring genotypes, differentiating between inherited and maternal genetic effects is not straightforward. The two-step transmission disequilibrium test was the first, family-based test proposed for the purpose of differentiating between maternal and offspring genetic effects. However, this approach, which requires data from "pents" comprising an affected child, mother, father, and maternal grandparents, provides biased tests for maternal genetic effects when the offspring genotype is associated with disease. An alternative approach based on transmissions from grandparents provides unbiased tests for maternal and offspring genetic effects but requires genotype information for paternal grandparents in addition to pents. The authors have developed two additional, pent-based approaches for the evaluation of maternal and offspring genetic effects. One approach requires the assumption of genetic mating type symmetry (pent-1), whereas the other does not (pent-2). Simulation studies demonstrate that both of these approaches provide valid estimation and testing for offspring and maternal genotypic effects. In addition, the power of the pent-1 approach is comparable with that of the approach based on data using all four grandparents.

HBC-Evo: predicting human breast cancer by exploiting amino acid sequence-based feature spaces and evolutionary ensemble system.

PubMed

Majid, Abdul; Ali, Safdar

2015-01-01

We developed genetic programming (GP)-based evolutionary ensemble system for the early diagnosis, prognosis and prediction of human breast cancer. This system has effectively exploited the diversity in feature and decision spaces. First, individual learners are trained in different feature spaces using physicochemical properties of protein amino acids. Their predictions are then stacked to develop the best solution during GP evolution process. Finally, results for HBC-Evo system are obtained with optimal threshold, which is computed using particle swarm optimization. Our novel approach has demonstrated promising results compared to state of the art approaches.

A method of evolving novel feature extraction algorithms for detecting buried objects in FLIR imagery using genetic programming

NASA Astrophysics Data System (ADS)

Paino, A.; Keller, J.; Popescu, M.; Stone, K.

2014-06-01

In this paper we present an approach that uses Genetic Programming (GP) to evolve novel feature extraction algorithms for greyscale images. Our motivation is to create an automated method of building new feature extraction algorithms for images that are competitive with commonly used human-engineered features, such as Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG). The evolved feature extraction algorithms are functions defined over the image space, and each produces a real-valued feature vector of variable length. Each evolved feature extractor breaks up the given image into a set of cells centered on every pixel, performs evolved operations on each cell, and then combines the results of those operations for every cell using an evolved operator. Using this method, the algorithm is flexible enough to reproduce both LBP and HOG features. The dataset we use to train and test our approach consists of a large number of pre-segmented image "chips" taken from a Forward Looking Infrared Imagery (FLIR) camera mounted on the hood of a moving vehicle. The goal is to classify each image chip as either containing or not containing a buried object. To this end, we define the fitness of a candidate solution as the cross-fold validation accuracy of the features generated by said candidate solution when used in conjunction with a Support Vector Machine (SVM) classifier. In order to validate our approach, we compare the classification accuracy of an SVM trained using our evolved features with the accuracy of an SVM trained using mainstream feature extraction algorithms, including LBP and HOG.

The Drosophila genome nexus: a population genomic resource of 623 Drosophila melanogaster genomes, including 197 from a single ancestral range population.

PubMed

Lack, Justin B; Cardeno, Charis M; Crepeau, Marc W; Taylor, William; Corbett-Detig, Russell B; Stevens, Kristian A; Langley, Charles H; Pool, John E

2015-04-01

Hundreds of wild-derived Drosophila melanogaster genomes have been published, but rigorous comparisons across data sets are precluded by differences in alignment methodology. The most common approach to reference-based genome assembly is a single round of alignment followed by quality filtering and variant detection. We evaluated variations and extensions of this approach and settled on an assembly strategy that utilizes two alignment programs and incorporates both substitutions and short indels to construct an updated reference for a second round of mapping prior to final variant detection. Utilizing this approach, we reassembled published D. melanogaster population genomic data sets and added unpublished genomes from several sub-Saharan populations. Most notably, we present aligned data from phase 3 of the Drosophila Population Genomics Project (DPGP3), which provides 197 genomes from a single ancestral range population of D. melanogaster (from Zambia). The large sample size, high genetic diversity, and potentially simpler demographic history of the DPGP3 sample will make this a highly valuable resource for fundamental population genetic research. The complete set of assemblies described here, termed the Drosophila Genome Nexus, presently comprises 623 consistently aligned genomes and is publicly available in multiple formats with supporting documentation and bioinformatic tools. This resource will greatly facilitate population genomic analysis in this model species by reducing the methodological differences between data sets. Copyright © 2015 by the Genetics Society of America.

Single-Step BLUP with Varying Genotyping Effort in Open-Pollinated Picea glauca.

PubMed

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

2017-03-10

Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce ( Picea glauca ) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Québec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm. Copyright © 2017 Ratcliffe et al.

The genetic basis of new treatment modalities in melanoma.

PubMed

Kunz, Manfred

2015-01-01

In recent years, intracellular signal transduction via RAS-RAF-MEK-ERK has been successfully targeted in new treatment approaches for melanoma using small molecule inhibitors against activated BRAF (V600E mutation) and activated MEK1/2. Also mutated c-KIT has been identified as a promising target. Meanwhile, evidence has been provided that combinations between BRAF inhibitors and MEK1/2 inhibitors are more promising than single-agent treatments. Moreover, new treatment algorithms favor sequential treatment using BRAF inhibitors and newly developed immunotherapies targeting common T lymphocyte antigen 4 (CTLA-4) or programmed cell death 1 (PD-1). In depth molecular analyses have uncovered new mechanisms of treatment resistance and recurrence, which may impact on future treatment decisions. Moreover, next-generation sequencing data have shown that recurrent lesions harbor specific genetic aberrations. At the same time, high throughput sequencing studies of melanoma unraveled a series of new treatment candidates for future treatment approaches such as ERBB4, GRIN2A, GRM3, and RAC1. More recent bioinformatic technologies provided genetic evidence for extensive tumor heterogeneity and tumor clonality of solid tumors, which might also be of relevance for melanoma. However, these technologies have not yet been applied to this tumor. In this review, an overview on the genetic basis of current treatment of melanoma, treatment resistance and recurrences including new treatment perspectives based on recent high-throughput sequencing data is provided. Moreover, future aspects of individualized treatment based on each patient's individual mutational landscape are discussed.

A synthetic genetic edge detection program.

PubMed

Tabor, Jeffrey J; Salis, Howard M; Simpson, Zachary Booth; Chevalier, Aaron A; Levskaya, Anselm; Marcotte, Edward M; Voigt, Christopher A; Ellington, Andrew D

2009-06-26

Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E. coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.

A Synthetic Genetic Edge Detection Program

PubMed Central

Tabor, Jeffrey J.; Salis, Howard; Simpson, Zachary B.; Chevalier, Aaron A.; Levskaya, Anselm; Marcotte, Edward M.; Voigt, Christopher A.; Ellington, Andrew D.

2009-01-01

Summary Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E.coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks. PMID:19563759

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.

Potential International Approaches to Ownership/Control of Human Genetic Resources.

PubMed

Rhodes, Catherine

2016-09-01

In its governance activities for genetic resources, the international community has adopted various approaches to their ownership, including: free access; common heritage of mankind; intellectual property rights; and state sovereign rights. They have also created systems which combine elements of these approaches. While governance of plant and animal genetic resources is well-established internationally, there has not yet been a clear approach selected for human genetic resources. Based on assessment of the goals which international governance of human genetic resources ought to serve, and the implications for how they will be accessed and utilised, it is argued that common heritage of mankind will be the most appropriate approach to adopt to their ownership/control. It does this with the aim of stimulating discussion in this area and providing a starting point for deeper consideration of how a common heritage of mankind, or similar, regime for human genetic resources would function and be implemented.

Which BRCA genetic testing programs are ready for implementation in health care? A systematic review of economic evaluations.

PubMed

D'Andrea, Elvira; Marzuillo, Carolina; De Vito, Corrado; Di Marco, Marco; Pitini, Erica; Vacchio, Maria Rosaria; Villari, Paolo

2016-12-01

There is considerable evidence regarding the efficacy and effectiveness of BRCA genetic testing programs, but whether they represent good use of financial resources is not clear. Therefore, we aimed to identify the main health-care programs for BRCA testing and to evaluate their cost-effectiveness. We performed a systematic review of full economic evaluations of health-care programs involving BRCA testing. Nine economic evaluations were included, and four main categories of BRCA testing programs were identified: (i) population-based genetic screening of individuals without cancer, either comprehensive or targeted based on ancestry; (ii) family history (FH)-based genetic screening, i.e., testing individuals without cancer but with FH suggestive of BRCA mutation; (iii) familial mutation (FM)-based genetic screening, i.e., testing individuals without cancer but with known familial BRCA mutation; and (iv) cancer-based genetic screening, i.e., testing individuals with BRCA-related cancers. Currently BRCA1/2 population-based screening represents good value for the money among Ashkenazi Jews only. FH-based screening is potentially very cost-effective, although further studies that include costs of identifying high-risk women are needed. There is no evidence of cost-effectiveness for BRCA screening of all newly diagnosed cases of breast/ovarian cancers followed by cascade testing of relatives, but programs that include tools for identifying affected women at higher risk for inherited forms are promising. Cost-effectiveness is highly sensitive to the cost of BRCA1/2 testing.Genet Med 18 12, 1171-1180.

Relieving the Bottleneck: An Investigation of Barriers to Expansion of Supervision Networks at Genetic Counseling Training Programs.

PubMed

Berg, Jordan; Hoskovec, Jennifer; Hashmi, S Shahrukh; McCarthy Veach, Patricia; Ownby, Allison; Singletary, Claire N

2018-02-01

Rapid growth in the demand for genetic counselors has led to a workforce shortage. There is a prevailing assumption that the number of training slots for genetic counseling students is linked to the availability of clinical supervisors. This study aimed to determine and compare barriers to expansion of supervision networks at genetic counseling training programs as perceived by supervisors, non-supervisors, and Program Directors. Genetic counselors were recruited via National Society of Genetic Counselors e-blast; Program Directors received personal emails. Online surveys were completed by 216 supervisors, 98 non-supervisors, and 23 Program Directors. Respondents rated impact of 35 barriers; comparisons were made using Kruskal-Wallis and Wilcoxon ranked sum tests. Half of supervisors (51%) indicated willingness to increase supervision. All non-supervisors were willing to supervise. However, all agreed that being too busy impacted ability to supervise, highlighted by supervisors' most impactful barriers: lack of time, other responsibilities, intensive nature of supervision, desire for breaks, and unfilled positions. Non-supervisors noted unique barriers: distance, institutional barriers, and non-clinical roles. Program Directors' perceptions were congruent with those of genetic counselors with three exceptions they rated as impactful: lack of money, prefer not to supervise, and never been asked. In order to expand supervision networks and provide comprehensive student experiences, the profession must examine service delivery models to increase workplace efficiency, reconsider the supervision paradigm, and redefine what constitutes a countable case or place value on non-direct patient care experiences.

Culturally relevant inquiry-based laboratory module implementations in upper-division genetics and cell biology teaching laboratories.

PubMed

Siritunga, Dimuth; Montero-Rojas, María; Carrero, Katherine; Toro, Gladys; Vélez, Ana; Carrero-Martínez, Franklin A

2011-01-01

Today, more minority students are entering undergraduate programs than ever before, but they earn only 6% of all science or engineering PhDs awarded in the United States. Many studies suggest that hands-on research activities enhance students' interest in pursuing a research career. In this paper, we present a model for the implementation of laboratory research in the undergraduate teaching laboratory using a culturally relevant approach to engage students. Laboratory modules were implemented in upper-division genetics and cell biology courses using cassava as the central theme. Students were asked to bring cassava samples from their respective towns, which allowed them to compare their field-collected samples against known lineages from agricultural stations at the end of the implementation. Assessment of content and learning perceptions revealed that our novel approach allowed students to learn while engaged in characterizing Puerto Rican cassava. In two semesters, based on the percentage of students who answered correctly in the premodule assessment for content knowledge, there was an overall improvement of 66% and 55% at the end in the genetics course and 24% and 15% in the cell biology course. Our proposed pedagogical model enhances students' professional competitiveness by providing students with valuable research skills as they work on a problem to which they can relate.

Reframing developmental biology and building evolutionary theory's new synthesis.

PubMed

Tauber, Alfred I

2010-01-01

Gilbert and Epel present a new approach to developmental biology: embryogenesis must be understood within the full context of the organism's environment. Instead of an insular embryo following a genetic blueprint, this revised program maintains that embryogenesis is subject to inputs from the environment that generate novel genetic variation with dynamic consequences for development. Beyond allelic variation of structural genes and of regulatory loci, plasticity-derived epigenetic variation completes the triad of the major types of variation required for evolution. Developmental biology and ecology, disciplines that have previously been regarded as distinct, are presented here as fully integrated under the rubric of "eco-devo," and from this perspective, which highlights how the environment not only selects variation, it helps construct it, another synthesis with evolutionary biology must also be made, "eco-evo-devo." This second integration has enormous implications for expanding evolution theory, inasmuch as the Modern Synthesis (Provine 1971), which combined classical genetics and Darwinism in the mid-20th century, did not account for the role of development in evolution. The eco-evo-devo synthesis thus portends a major theoretical inflection in evolutionary biology. Following a description of these scientific developments, comment is offered as to how this new integrated approach might be understood within the larger shifts in contemporary biology.

Culturally Relevant Inquiry-Based Laboratory Module Implementations in Upper-Division Genetics and Cell Biology Teaching Laboratories

PubMed Central

Siritunga, Dimuth; Montero-Rojas, María; Carrero, Katherine; Toro, Gladys; Vélez, Ana; Carrero-Martínez, Franklin A.

2011-01-01

Today, more minority students are entering undergraduate programs than ever before, but they earn only 6% of all science or engineering PhDs awarded in the United States. Many studies suggest that hands-on research activities enhance students’ interest in pursuing a research career. In this paper, we present a model for the implementation of laboratory research in the undergraduate teaching laboratory using a culturally relevant approach to engage students. Laboratory modules were implemented in upper-division genetics and cell biology courses using cassava as the central theme. Students were asked to bring cassava samples from their respective towns, which allowed them to compare their field-collected samples against known lineages from agricultural stations at the end of the implementation. Assessment of content and learning perceptions revealed that our novel approach allowed students to learn while engaged in characterizing Puerto Rican cassava. In two semesters, based on the percentage of students who answered correctly in the premodule assessment for content knowledge, there was an overall improvement of 66% and 55% at the end in the genetics course and 24% and 15% in the cell biology course. Our proposed pedagogical model enhances students’ professional competitiveness by providing students with valuable research skills as they work on a problem to which they can relate. PMID:21885825

Real-Time Monitoring and Analysis of Zebrafish Electrocardiogram with Anomaly Detection.

PubMed

Lenning, Michael; Fortunato, Joseph; Le, Tai; Clark, Isaac; Sherpa, Ang; Yi, Soyeon; Hofsteen, Peter; Thamilarasu, Geethapriya; Yang, Jingchun; Xu, Xiaolei; Han, Huy-Dung; Hsiai, Tzung K; Cao, Hung

2017-12-28

Heart disease is the leading cause of mortality in the U.S. with approximately 610,000 people dying every year. Effective therapies for many cardiac diseases are lacking, largely due to an incomplete understanding of their genetic basis and underlying molecular mechanisms. Zebrafish ( Danio rerio ) are an excellent model system for studying heart disease as they enable a forward genetic approach to tackle this unmet medical need. In recent years, our team has been employing electrocardiogram (ECG) as an efficient tool to study the zebrafish heart along with conventional approaches, such as immunohistochemistry, DNA and protein analyses. We have overcome various challenges in the small size and aquatic environment of zebrafish in order to obtain ECG signals with favorable signal-to-noise ratio (SNR), and high spatial and temporal resolution. In this paper, we highlight our recent efforts in zebrafish ECG acquisition with a cost-effective simplified microelectrode array (MEA) membrane providing multi-channel recording, a novel multi-chamber apparatus for simultaneous screening, and a LabVIEW program to facilitate recording and processing. We also demonstrate the use of machine learning-based programs to recognize specific ECG patterns, yielding promising results with our current limited amount of zebrafish data. Our solutions hold promise to carry out numerous studies of heart diseases, drug screening, stem cell-based therapy validation, and regenerative medicine.

Real-Time Monitoring and Analysis of Zebrafish Electrocardiogram with Anomaly Detection

PubMed Central

Lenning, Michael; Fortunato, Joseph; Le, Tai; Clark, Isaac; Sherpa, Ang; Yi, Soyeon; Hofsteen, Peter; Thamilarasu, Geethapriya; Yang, Jingchun; Xu, Xiaolei; Hsiai, Tzung K.; Cao, Hung

2017-01-01

Heart disease is the leading cause of mortality in the U.S. with approximately 610,000 people dying every year. Effective therapies for many cardiac diseases are lacking, largely due to an incomplete understanding of their genetic basis and underlying molecular mechanisms. Zebrafish (Danio rerio) are an excellent model system for studying heart disease as they enable a forward genetic approach to tackle this unmet medical need. In recent years, our team has been employing electrocardiogram (ECG) as an efficient tool to study the zebrafish heart along with conventional approaches, such as immunohistochemistry, DNA and protein analyses. We have overcome various challenges in the small size and aquatic environment of zebrafish in order to obtain ECG signals with favorable signal-to-noise ratio (SNR), and high spatial and temporal resolution. In this paper, we highlight our recent efforts in zebrafish ECG acquisition with a cost-effective simplified microelectrode array (MEA) membrane providing multi-channel recording, a novel multi-chamber apparatus for simultaneous screening, and a LabVIEW program to facilitate recording and processing. We also demonstrate the use of machine learning-based programs to recognize specific ECG patterns, yielding promising results with our current limited amount of zebrafish data. Our solutions hold promise to carry out numerous studies of heart diseases, drug screening, stem cell-based therapy validation, and regenerative medicine. PMID:29283402

Programmed Evolution for Optimization of Orthogonal Metabolic Output in Bacteria

PubMed Central

Eckdahl, Todd T.; Campbell, A. Malcolm; Heyer, Laurie J.; Poet, Jeffrey L.; Blauch, David N.; Snyder, Nicole L.; Atchley, Dustin T.; Baker, Erich J.; Brown, Micah; Brunner, Elizabeth C.; Callen, Sean A.; Campbell, Jesse S.; Carr, Caleb J.; Carr, David R.; Chadinha, Spencer A.; Chester, Grace I.; Chester, Josh; Clarkson, Ben R.; Cochran, Kelly E.; Doherty, Shannon E.; Doyle, Catherine; Dwyer, Sarah; Edlin, Linnea M.; Evans, Rebecca A.; Fluharty, Taylor; Frederick, Janna; Galeota-Sprung, Jonah; Gammon, Betsy L.; Grieshaber, Brandon; Gronniger, Jessica; Gutteridge, Katelyn; Henningsen, Joel; Isom, Bradley; Itell, Hannah L.; Keffeler, Erica C.; Lantz, Andrew J.; Lim, Jonathan N.; McGuire, Erin P.; Moore, Alexander K.; Morton, Jerrad; Nakano, Meredith; Pearson, Sara A.; Perkins, Virginia; Parrish, Phoebe; Pierson, Claire E.; Polpityaarachchige, Sachith; Quaney, Michael J.; Slattery, Abagael; Smith, Kathryn E.; Spell, Jackson; Spencer, Morgan; Taye, Telavive; Trueblood, Kamay; Vrana, Caroline J.; Whitesides, E. Tucker

2015-01-01

Current use of microbes for metabolic engineering suffers from loss of metabolic output due to natural selection. Rather than combat the evolution of bacterial populations, we chose to embrace what makes biological engineering unique among engineering fields – evolving materials. We harnessed bacteria to compute solutions to the biological problem of metabolic pathway optimization. Our approach is called Programmed Evolution to capture two concepts. First, a population of cells is programmed with DNA code to enable it to compute solutions to a chosen optimization problem. As analog computers, bacteria process known and unknown inputs and direct the output of their biochemical hardware. Second, the system employs the evolution of bacteria toward an optimal metabolic solution by imposing fitness defined by metabolic output. The current study is a proof-of-concept for Programmed Evolution applied to the optimization of a metabolic pathway for the conversion of caffeine to theophylline in E. coli. Introduced genotype variations included strength of the promoter and ribosome binding site, plasmid copy number, and chaperone proteins. We constructed 24 strains using all combinations of the genetic variables. We used a theophylline riboswitch and a tetracycline resistance gene to link theophylline production to fitness. After subjecting the mixed population to selection, we measured a change in the distribution of genotypes in the population and an increased conversion of caffeine to theophylline among the most fit strains, demonstrating Programmed Evolution. Programmed Evolution inverts the standard paradigm in metabolic engineering by harnessing evolution instead of fighting it. Our modular system enables researchers to program bacteria and use evolution to determine the combination of genetic control elements that optimizes catabolic or anabolic output and to maintain it in a population of cells. Programmed Evolution could be used for applications in energy, pharmaceuticals, chemical commodities, biomining, and bioremediation. PMID:25714374

Programmed evolution for optimization of orthogonal metabolic output in bacteria.

PubMed

Eckdahl, Todd T; Campbell, A Malcolm; Heyer, Laurie J; Poet, Jeffrey L; Blauch, David N; Snyder, Nicole L; Atchley, Dustin T; Baker, Erich J; Brown, Micah; Brunner, Elizabeth C; Callen, Sean A; Campbell, Jesse S; Carr, Caleb J; Carr, David R; Chadinha, Spencer A; Chester, Grace I; Chester, Josh; Clarkson, Ben R; Cochran, Kelly E; Doherty, Shannon E; Doyle, Catherine; Dwyer, Sarah; Edlin, Linnea M; Evans, Rebecca A; Fluharty, Taylor; Frederick, Janna; Galeota-Sprung, Jonah; Gammon, Betsy L; Grieshaber, Brandon; Gronniger, Jessica; Gutteridge, Katelyn; Henningsen, Joel; Isom, Bradley; Itell, Hannah L; Keffeler, Erica C; Lantz, Andrew J; Lim, Jonathan N; McGuire, Erin P; Moore, Alexander K; Morton, Jerrad; Nakano, Meredith; Pearson, Sara A; Perkins, Virginia; Parrish, Phoebe; Pierson, Claire E; Polpityaarachchige, Sachith; Quaney, Michael J; Slattery, Abagael; Smith, Kathryn E; Spell, Jackson; Spencer, Morgan; Taye, Telavive; Trueblood, Kamay; Vrana, Caroline J; Whitesides, E Tucker

2015-01-01

Current use of microbes for metabolic engineering suffers from loss of metabolic output due to natural selection. Rather than combat the evolution of bacterial populations, we chose to embrace what makes biological engineering unique among engineering fields - evolving materials. We harnessed bacteria to compute solutions to the biological problem of metabolic pathway optimization. Our approach is called Programmed Evolution to capture two concepts. First, a population of cells is programmed with DNA code to enable it to compute solutions to a chosen optimization problem. As analog computers, bacteria process known and unknown inputs and direct the output of their biochemical hardware. Second, the system employs the evolution of bacteria toward an optimal metabolic solution by imposing fitness defined by metabolic output. The current study is a proof-of-concept for Programmed Evolution applied to the optimization of a metabolic pathway for the conversion of caffeine to theophylline in E. coli. Introduced genotype variations included strength of the promoter and ribosome binding site, plasmid copy number, and chaperone proteins. We constructed 24 strains using all combinations of the genetic variables. We used a theophylline riboswitch and a tetracycline resistance gene to link theophylline production to fitness. After subjecting the mixed population to selection, we measured a change in the distribution of genotypes in the population and an increased conversion of caffeine to theophylline among the most fit strains, demonstrating Programmed Evolution. Programmed Evolution inverts the standard paradigm in metabolic engineering by harnessing evolution instead of fighting it. Our modular system enables researchers to program bacteria and use evolution to determine the combination of genetic control elements that optimizes catabolic or anabolic output and to maintain it in a population of cells. Programmed Evolution could be used for applications in energy, pharmaceuticals, chemical commodities, biomining, and bioremediation.

What makes community engagement effective?: Lessons from the Eliminate Dengue Program in Queensland Australia.

PubMed

Kolopack, Pamela A; Parsons, Janet A; Lavery, James V

2015-04-01

Worldwide, more than 40% of the population is at risk from dengue and recent estimates suggest that up to 390 million dengue infections are acquired every year. The Eliminate Dengue (ED) Program is investigating the use of Wolbachia-infected, transmission-compromised, mosquitoes to reduce dengue transmission. Previous introductions of genetically-modified strategies for dengue vector control have generated controversy internationally by inadequately engaging host communities. Community Engagement (CE) was a key component of the ED Program's initial open release trials in Queensland Australia. Their approach to CE was perceived as effective by the ED team's senior leadership, members of its CE team, and by its funders, but if and why this was the case was unclear. We conducted a qualitative case study of the ED Program's approach to CE to identify and critically examine its components, and to explain whether and how these efforts contributed to the support received by stakeholders. In-depth semi-structured interviews were conducted with 24 participants with a range of experiences and perspectives related to the ED Program's CE activities. Our analytic approach combined techniques of grounded theory and qualitative description. The ED Program's approach to CE reflected four foundational features: 1) enabling conditions; 2) leadership; 3) core commitments and guiding values; and 4) formative social science research. These foundations informed five key operational practices: 1) building the CE team; 2) integrating CE into management practices; 3) discerning the community of stakeholders; 4) establishing and maintaining a presence in the community; and 5) socializing the technology and research strategy. We also demonstrate how these practices contributed to stakeholders' willingness to support the trials. Our case study has identified, and explained the functional relationships among, the critical features of the ED Program's approach to CE. It has also illuminated how these features were meaningful to stakeholders and contributed to garnering support within the host communities for the open-release trials. Our findings reveal how translating ethical intentions into effective action is more socially complex than is currently reflected in the CE literature. Because our case study delineates the critical features of the ED Program's approach to CE, it can serve as a framework for other programs to follow when designing their own strategies. And because the findings outline a theory of change for CE, it can also serve as a starting point for developing an evaluation framework for CE.

SAM: The "Search and Match" Computer Program of the Escherichia coli Genetic Stock Center

ERIC Educational Resources Information Center

Bachmann, B. J.; And Others

1973-01-01

Describes a computer program used at a genetic stock center to locate particular strains of bacteria. The program can match up to 30 strain descriptions requested by a researcher with the records on file. Uses of this particular program can be made in many fields. (PS)

Genetic diversity trend in Indian rice varieties: an analysis using SSR markers.

PubMed

Singh, Nivedita; Choudhury, Debjani Roy; Tiwari, Gunjan; Singh, Amit Kumar; Kumar, Sundeep; Srinivasan, Kalyani; Tyagi, R K; Sharma, A D; Singh, N K; Singh, Rakesh

2016-09-05

The knowledge of the extent and pattern of diversity in the crop species is a prerequisite for any crop improvement as it helps breeders in deciding suitable breeding strategies for their future improvement. Rice is the main staple crop in India with the large number of varieties released every year. Studies based on the small set of rice genotypes have reported a loss in genetic diversity especially after green revolution. However, a detailed study of the trend of diversity in Indian rice varieties is lacking. SSR markers have proven to be a marker of choice for studying the genetic diversity. Therefore, the present study was undertaken with the aim to characterize and assess trends of genetic diversity in a large set of Indian rice varieties (released between 1940-2013), conserved in the National Gene Bank of India using SSR markers. A set of 729 Indian rice varieties were genotyped using 36 HvSSR markers to assess the genetic diversity and genetic relationship. A total of 112 alleles was amplified with an average of 3.11 alleles per locus with mean Polymorphic Information Content (PIC) value of 0.29. Cluster analysis grouped these varieties into two clusters whereas the model based population structure divided them into three populations. AMOVA study based on hierarchical cluster and model based approach showed 3 % and 11 % variation between the populations, respectively. Decadal analysis for gene diversity and PIC showed increasing trend from 1940 to 2005, thereafter values for both the parameters showed decreasing trend between years 2006-2013. In contrast to this, allele number demonstrated increasing trend in these varieties released and notified between1940 to 1985, it remained nearly constant during 1986 to 2005 and again showed an increasing trend. Our results demonstrated that the Indian rice varieties harbors huge amount of genetic diversity. However, the trait based improvement program in the last decades forced breeders to rely on few parents, which resulted in loss of gene diversity during 2006 to 2013. The present study indicates the need for broadening the genetic base of Indian rice varieties through the use of diverse parents in the current breeding program.

Cultural differences define diagnosis and genomic medicine practice: implications for undiagnosed diseases program in China.

PubMed

Duan, Xiaohong; Markello, Thomas; Adams, David; Toro, Camilo; Tifft, Cynthia; Gahl, William A; Boerkoel, Cornelius F

2013-09-01

Despite the current acceleration and increasing leadership of Chinese genetics research, genetics and its clinical application have largely been imported to China from the Occident. Neither genetics nor the scientific reductionism underpinning its clinical application is integral to the traditional Chinese worldview. Given that disease concepts and their incumbent diagnoses are historically derived and culturally meaningful, we hypothesize that the cultural expectations of genetic diagnoses and medical genetics practice differ between the Occident and China. Specifically, we suggest that an undiagnosed diseases program in China will differ from the recently established Undiagnosed Diseases Program at the United States National Institutes of Health; a culturally sensitive concept will integrate traditional Chinese understanding of disease with the scientific reductionism of Occidental medicine.

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

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

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

Fractional populations in multiple gene inheritance.

PubMed

Chung, Myung-Hoon; Kim, Chul Koo; Nahm, Kyun

2003-01-22

With complete knowledge of the human genome sequence, one of the most interesting tasks remaining is to understand the functions of individual genes and how they communicate. Using the information about genes (locus, allele, mutation rate, fitness, etc.), we attempt to explain population demographic data. This population evolution study could complement and enhance biologists' understanding about genes. We present a general approach to study population genetics in complex situations. In the present approach, multiple allele inheritance, multiple loci inheritance, natural selection and mutations are allowed simultaneously in order to consider a more realistic situation. A simulation program is presented so that readers can readily carry out studies with their own parameters. It is shown that the multiplicity of the loci greatly affects the demographic results of fractional population ratios. Furthermore, the study indicates that some high infant mortality rates due to congenital anomalies can be attributed to multiple loci inheritance. The simulation program can be downloaded from http://won.hongik.ac.kr/~mhchung/index_files/yapop.htm. In order to run this program, one needs Visual Studio.NET platform, which can be downloaded from http://msdn.microsoft.com/netframework/downloads/default.asp.

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.

Capturing neutral and adaptive genetic diversity for conservation in a highly structured tree species.

PubMed

Rodríguez-Quilón, Isabel; Santos-Del-Blanco, Luis; Serra-Varela, María Jesús; Koskela, Jarkko; González-Martínez, Santiago C; Alía, Ricardo

2016-10-01

Preserving intraspecific genetic diversity is essential for long-term forest sustainability in a climate change scenario. Despite that, genetic information is largely neglected in conservation planning, and how conservation units should be defined is still heatedly debated. Here, we use maritime pine (Pinus pinaster Ait.), an outcrossing long-lived tree with a highly fragmented distribution in the Mediterranean biodiversity hotspot, to prove the importance of accounting for genetic variation, of both neutral molecular markers and quantitative traits, to define useful conservation units. Six gene pools associated to distinct evolutionary histories were identified within the species using 12 microsatellites and 266 single nucleotide polymorphisms (SNPs). In addition, height and survival standing variation, their genetic control, and plasticity were assessed in a multisite clonal common garden experiment (16 544 trees). We found high levels of quantitative genetic differentiation within previously defined neutral gene pools. Subsequent cluster analysis and post hoc trait distribution comparisons allowed us to define 10 genetically homogeneous population groups with high evolutionary potential. They constitute the minimum number of units to be represented in a maritime pine dynamic conservation program. Our results uphold that the identification of conservation units below the species level should account for key neutral and adaptive components of genetic diversity, especially in species with strong population structure and complex evolutionary histories. The environmental zonation approach currently used by the pan-European genetic conservation strategy for forest trees would be largely improved by gradually integrating molecular and quantitative trait information, as data become available. © 2016 by the Ecological Society of America.

Clumpak: a program for identifying clustering modes and packaging population structure inferences across K.

PubMed

Kopelman, Naama M; Mayzel, Jonathan; Jakobsson, Mattias; Rosenberg, Noah A; Mayrose, Itay

2015-09-01

The identification of the genetic structure of populations from multilocus genotype data has become a central component of modern population-genetic data analysis. Application of model-based clustering programs often entails a number of steps, in which the user considers different modelling assumptions, compares results across different predetermined values of the number of assumed clusters (a parameter typically denoted K), examines multiple independent runs for each fixed value of K, and distinguishes among runs belonging to substantially distinct clustering solutions. Here, we present Clumpak (Cluster Markov Packager Across K), a method that automates the postprocessing of results of model-based population structure analyses. For analysing multiple independent runs at a single K value, Clumpak identifies sets of highly similar runs, separating distinct groups of runs that represent distinct modes in the space of possible solutions. This procedure, which generates a consensus solution for each distinct mode, is performed by the use of a Markov clustering algorithm that relies on a similarity matrix between replicate runs, as computed by the software Clumpp. Next, Clumpak identifies an optimal alignment of inferred clusters across different values of K, extending a similar approach implemented for a fixed K in Clumpp and simplifying the comparison of clustering results across different K values. Clumpak incorporates additional features, such as implementations of methods for choosing K and comparing solutions obtained by different programs, models, or data subsets. Clumpak, available at http://clumpak.tau.ac.il, simplifies the use of model-based analyses of population structure in population genetics and molecular ecology. © 2015 John Wiley & Sons Ltd.

Genome-wide association study (GWAS) for growth rate and age at sexual maturation in Atlantic salmon (Salmo salar).

PubMed

Gutierrez, Alejandro P; Yáñez, José M; Fukui, Steve; Swift, Bruce; Davidson, William S

2015-01-01

Early sexual maturation is considered a serious drawback for Atlantic salmon aquaculture as it retards growth, increases production times and affects flesh quality. Although both growth and sexual maturation are thought to be complex processes controlled by several genetic and environmental factors, selection for these traits has been continuously accomplished since the beginning of Atlantic salmon selective breeding programs. In this genome-wide association study (GWAS) we used a 6.5K single-nucleotide polymorphism (SNP) array to genotype ∼ 480 individuals from the Cermaq Canada broodstock program and search for SNPs associated with growth and age at sexual maturation. Using a mixed model approach we identified markers showing a significant association with growth, grilsing (early sexual maturation) and late sexual maturation. The most significant associations were found for grilsing, with markers located in Ssa10, Ssa02, Ssa13, Ssa25 and Ssa12, and for late maturation with markers located in Ssa28, Ssa01 and Ssa21. A lower level of association was detected with growth on Ssa13. Candidate genes, which were linked to these genetic markers, were identified and some of them show a direct relationship with developmental processes, especially for those in association with sexual maturation. However, the relatively low power to detect genetic markers associated with growth (days to 5 kg) in this GWAS indicates the need to use a higher density SNP array in order to overcome the low levels of linkage disequilibrium observed in Atlantic salmon before the information can be incorporated into a selective breeding program.

Cancer Genetics and Signaling | Center for Cancer Research

Cancer.gov

The Cancer, Genetics, and Signaling (CGS) Group at the National Cancer Institute at Frederick  offers a competitive postdoctoral training and mentoring program focusing on molecular and genetic aspects of cancer. The CGS Fellows Program is designed to attract and train exceptional postdoctoral fellows interested in pursuing independent research career tracks. CGS Fellows

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.

Use of qualitative environmental and phenotypic variables in the context of allele distribution models: detecting signatures of selection in the genome of Lake Victoria cichlids.

PubMed

Joost, Stéphane; Kalbermatten, Michael; Bezault, Etienne; Seehausen, Ole

2012-01-01

When searching for loci possibly under selection in the genome, an alternative to population genetics theoretical models is to establish allele distribution models (ADM) for each locus to directly correlate allelic frequencies and environmental variables such as precipitation, temperature, or sun radiation. Such an approach implementing multiple logistic regression models in parallel was implemented within a computing program named MATSAM: . Recently, this application was improved in order to support qualitative environmental predictors as well as to permit the identification of associations between genomic variation and individual phenotypes, allowing the detection of loci involved in the genetic architecture of polymorphic characters. Here, we present the corresponding methodological developments and compare the results produced by software implementing population genetics theoretical models (DFDIST: and BAYESCAN: ) and ADM (MATSAM: ) in an empirical context to detect signatures of genomic divergence associated with speciation in Lake Victoria cichlid fishes.

Genetic counseling for beta-thalassemia trait following health screening in a health maintenance organization: comparison of programmed and conventional counseling.

PubMed Central

Fisher, L; Rowley, P T; Lipkin, M

1981-01-01

Providing adequate counseling of patients identified in genetic screening programs is a major responsibility and expense. Adults in a health maintenance organization, unselected for interest, were screened for beta-thalassemia trait as part of preventive health care. Counseling was provided by either a trained physician (conventional counseling) or by a videotape containing the same information followed by an opportunity to question a trained physician (programmed counseling). Immediately before and after counseling, knowledge of thalassemia, knowledge of genetics, and mood change were assessed by questionnaire. Comparable mood changes and similar learning about thalassemia and genetics occurred with both counseling methods. Thus, as judged by immediate effects on knowledge and mood, videotaped instruction can greatly reduce professional time required for genetic counseling and facilitate the incorporation of genetic screening into primary health care. PMID:7325162

Contradictory genetic make-up of Dutch harbour porpoises: Response to van der Plas-Duivesteijn et al.

NASA Astrophysics Data System (ADS)

Kopps, Anna M.; Palsbøll, Per J.

2016-02-01

The assessment of the status of endangered species or populations typically draw generously on the plethora of population genetic software available to detect population genetic structuring. However, despite the many available analytical approaches, population genetic inference methods [of neutral genetic variation] essentially capture three basic processes; migration, random genetic drift and mutation. Consequently, different analytical approaches essentially capture the same basic process, and should yield consistent results.

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

PubMed

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

2011-03-24

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

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.

Mammalian Synthetic Biology: Engineering Biological Systems.

PubMed

Black, Joshua B; Perez-Pinera, Pablo; Gersbach, Charles A

2017-06-21

The programming of new functions into mammalian cells has tremendous application in research and medicine. Continued improvements in the capacity to sequence and synthesize DNA have rapidly increased our understanding of mechanisms of gene function and regulation on a genome-wide scale and have expanded the set of genetic components available for programming cell biology. The invention of new research tools, including targetable DNA-binding systems such as CRISPR/Cas9 and sensor-actuator devices that can recognize and respond to diverse chemical, mechanical, and optical inputs, has enabled precise control of complex cellular behaviors at unprecedented spatial and temporal resolution. These tools have been critical for the expansion of synthetic biology techniques from prokaryotic and lower eukaryotic hosts to mammalian systems. Recent progress in the development of genome and epigenome editing tools and in the engineering of designer cells with programmable genetic circuits is expanding approaches to prevent, diagnose, and treat disease and to establish personalized theranostic strategies for next-generation medicines. This review summarizes the development of these enabling technologies and their application to transforming mammalian synthetic biology into a distinct field in research and medicine.

Flow discharge prediction in compound channels using linear genetic programming

NASA Astrophysics Data System (ADS)

Azamathulla, H. Md.; Zahiri, A.

2012-08-01

SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.

Mendelian randomization with fine-mapped genetic data: Choosing from large numbers of correlated instrumental variables.

PubMed

Burgess, Stephen; Zuber, Verena; Valdes-Marquez, Elsa; Sun, Benjamin B; Hopewell, Jemma C

2017-12-01

Mendelian randomization uses genetic variants to make causal inferences about the effect of a risk factor on an outcome. With fine-mapped genetic data, there may be hundreds of genetic variants in a single gene region any of which could be used to assess this causal relationship. However, using too many genetic variants in the analysis can lead to spurious estimates and inflated Type 1 error rates. But if only a few genetic variants are used, then the majority of the data is ignored and estimates are highly sensitive to the particular choice of variants. We propose an approach based on summarized data only (genetic association and correlation estimates) that uses principal components analysis to form instruments. This approach has desirable theoretical properties: it takes the totality of data into account and does not suffer from numerical instabilities. It also has good properties in simulation studies: it is not particularly sensitive to varying the genetic variants included in the analysis or the genetic correlation matrix, and it does not have greatly inflated Type 1 error rates. Overall, the method gives estimates that are less precise than those from variable selection approaches (such as using a conditional analysis or pruning approach to select variants), but are more robust to seemingly arbitrary choices in the variable selection step. Methods are illustrated by an example using genetic associations with testosterone for 320 genetic variants to assess the effect of sex hormone related pathways on coronary artery disease risk, in which variable selection approaches give inconsistent inferences. © 2017 The Authors Genetic Epidemiology Published by Wiley Periodicals, Inc.

Consensus statement understanding health and malnutrition through a systems approach: the ENOUGH program for early life.

PubMed

Kaput, Jim; van Ommen, Ben; Kremer, Bas; Priami, Corrado; Monteiro, Jacqueline Pontes; Morine, Melissa; Pepping, Fre; Diaz, Zoey; Fenech, Michael; He, Yiwu; Albers, Ruud; Drevon, Christian A; Evelo, Chris T; Hancock, Robert E W; Ijsselmuiden, Carel; Lumey, L H; Minihane, Anne-Marie; Muller, Michael; Murgia, Chiara; Radonjic, Marijana; Sobral, Bruno; West, Keith P

2014-01-01

Nutrition research, like most biomedical disciplines, adopted and often uses experimental approaches based on Beadle and Tatum's one gene-one polypeptide hypothesis, thereby reducing biological processes to single reactions or pathways. Systems thinking is needed to understand the complexity of health and disease processes requiring measurements of physiological processes, as well as environmental and social factors, which may alter the expression of genetic information. Analysis of physiological processes with omics technologies to assess systems' responses has only become available over the past decade and remains costly. Studies of environmental and social conditions known to alter health are often not connected to biomedical research. While these facts are widely accepted, developing and conducting comprehensive research programs for health are often beyond financial and human resources of single research groups. We propose a new research program on essential nutrients for optimal underpinning of growth and health (ENOUGH) that will use systems approaches with more comprehensive measurements and biostatistical analysis of the many biological and environmental factors that influence undernutrition. Creating a knowledge base for nutrition and health is a necessary first step toward developing solutions targeted to different populations in diverse social and physical environments for the two billion undernourished people in developed and developing economies.

Selection for sow longevity.

PubMed

Serenius, T; Stalder, K J

2006-04-01

Sow longevity plays an important role in economically efficient piglet production because sow longevity is related to the number of piglets produced during its productive lifetime; however, selection for sow longevity is not commonly practiced in any pig breeding program. There is relatively little scientific literature concerning the genetic parameters (genetic variation and genetic correlations) or methods available for breeding value estimation for effective selection for sow longevity. This paper summarizes the current knowledge about the genetics of sow longevity and discusses the available breeding value estimation methods for sow longevity traits. The studies in the literature clearly indicate that sow longevity is a complex trait, and even the definition of sow longevity is variable depending on the researcher and research objective. In general, the measures and analyses of sow longevity can be divided into 1) continuous traits (e.g., productive lifetime) analyzed with proportional hazard models; and 2) more simple binary traits such as stayability until some predetermined fixed parity. Most studies have concluded that sufficient genetic variation exists for effective selection on sow longevity, and heritability estimates have ranged between 0.02 and 0.25. Moreover, sow longevity has shown to be genetically associated with prolificacy and leg conformation traits. Variable results from previous research have led to a lack of consensus among swine breeders concerning the valid methodology of estimating breeding values for longevity traits. One can not deny the superiority of survival analysis in the modeling approach of longevity data; however, multiple-trait analyses are not possible using currently available survival analysis software. Less sophisticated approaches have the advantage of evaluating multiple traits simultaneously, and thus, can use the genetic associations between sow longevity and other traits. Additional research is needed to identify the most efficient selection methods for sow longevity. Future research needs to concentrate on multiple trait analysis of sow longevity traits. Moreover, because longevity is a fitness trait, the nonadditive genetic effects (e.g., dominance) may play important role in the inheritance of sow longevity. Currently, not a single estimate for dominance variance of sow longevity could be identified from the scientific literature.

Descriptive survey of Summer Genetics Institute nurse graduates in the USA.

PubMed

Hickey, Kathleen T; Sciacca, Robert R; McCarthy, Mary S

2013-03-01

The purpose of this study was to describe the clinical, research, educational, and professional activities that nurses are engaged in following participation in a 2 month intramural genetics training program. An online survey was administered in 2010 to graduates of the program sponsored by the US National Institute of Nursing Research from 2000 to 2009, in Bethesda, Maryland, USA. The electronic, voluntary survey was sent to 189 graduates via email. The survey included demographic characteristics, educational preparation, professional roles and responsibilities, and attitudes about genetic testing and privacy issues. Of the 95 graduates responding to the survey, 74% had doctorates and 70% were advanced practice nurses. All respondents reported incorporating genetics knowledge into daily clinical, academic, or research practices since completing the program, with 72% reporting being involved in genetically-focused research (52% with research funding), 32% incorporating genetics into patient care, and 79% providing genetics education. Respondents working in a hospital setting or academic institution were more likely to desire additional training in genetics. National Institute of Nursing Research graduates have successfully integrated genomics into a variety of nursing practices. © 2012 Wiley Publishing Asia Pty Ltd.

Prediction of Scour below Flip Bucket using Soft Computing Techniques

NASA Astrophysics Data System (ADS)

Azamathulla, H. Md.; Ab Ghani, Aminuddin; Azazi Zakaria, Nor

2010-05-01

The accurate prediction of the depth of scour around hydraulic structure (trajectory spillways) has been based on the experimental studies and the equations developed are mainly empirical in nature. This paper evaluates the performance of the soft computing (intelligence) techiques, Adaptive Neuro-Fuzzy System (ANFIS) and Genetic expression Programming (GEP) approach, in prediction of scour below a flip bucket spillway. The results are very promising, which support the use of these intelligent techniques in prediction of highly non-linear scour parameters.

Genetic Evolution of Shape-Altering Programs for Supersonic Aerodynamics

NASA Technical Reports Server (NTRS)

Kennelly, Robert A., Jr.; Bencze, Daniel P. (Technical Monitor)

2002-01-01

Two constrained shape optimization problems relevant to aerodynamics are solved by genetic programming, in which a population of computer programs evolves automatically under pressure of fitness-driven reproduction and genetic crossover. Known optimal solutions are recovered using a small, naive set of elementary operations. Effectiveness is improved through use of automatically defined functions, especially when one of them is capable of a variable number of iterations, even though the test problems lack obvious exploitable regularities. An attempt at evolving new elementary operations was only partially successful.

Genetic testing for colorectal carcinoma susceptibility: focus group responses of individuals with colorectal carcinoma and first-degree relatives.

PubMed

Kinney, A Y; DeVellis, B M; Skrzynia, C; Millikan, R

2001-01-01

Colorectal carcinoma (CRC) may be the most frequent form of hereditary cancer. Genetic counseling and testing for heritable CRC is a promising approach for reducing the high incidence and mortality rates associated with the disease. Patients with CRC or those with at least one family member with the disease are the most likely persons to request or be offered genetic testing in the clinical or research setting. Currently, however, little is known about the behavioral, psychosocial, ethical, legal, and economic outcomes of CRC genetic counseling and testing. Eight focus group interviews, four for CRC patients (n = 28) and four for first-degree relatives (n = 33), were conducted to obtain insights into attitudes, beliefs, and informational needs about genetic testing for hereditary CRC. Focus group interviews revealed a general lack of knowledge about cancer genetics and genetic testing; worry about confidentiality issues; strong concern for family members, particularly children; and a need for primary care providers to be informed about these issues. Major perceived advantages of genetic testing included improving health-related decisions, guiding physicians in making recommendations for surveillance, and informing relatives about risk potential. Disadvantages included potential discrimination, adverse psychologic effects, and financial costs associated with testing. As knowledge and media coverage of genetics continue to expand, it becomes increasingly important to continue efforts on behalf of, and in partnership with, those individuals most affected by genetic testing for hereditary cancer syndromes. These findings provide data needed to develop and implement informational, educational, counseling, and research-oriented programs that are sensitive to individuals' concerns and preferences. Copyright 2001 American Cancer Society.

Effectiveness and consistency of a suite of descriptors for assessing the ecological status of seagrass meadows (Posidonia oceanica L. Delile)

NASA Astrophysics Data System (ADS)

Rotini, Alice; Belmonte, Alessandro; Barrote, Isabel; Micheli, Carla; Peirano, Andrea; Santos, Rui O.; Silva, João; Migliore, Luciana

2013-09-01

The increasing rate of human-induced environmental changes on coastal marine ecosystems has created a demand for effective descriptors, in particular for those suitable for monitoring the status of seagrass meadows. Growing evidence has supported the useful application of biochemical and genetic descriptors such as secondary metabolite synthesis, photosynthetic activity and genetic diversity. In the present study, we have investigated the effectiveness of different descriptors (traditional, biochemical and genetic) in monitoring seagrass meadow conservation status. The Posidonia oceanica meadow of Monterosso al Mare (Ligurian sea, NW Mediterranean) was subjected to the measurement of bed density, leaf biometry, total phenols, soluble protein and photosynthetic pigment content as well as to RAPD marker analysis. This suite of descriptors provided evidence of their effectiveness and convenient application as markers of the conservation status of P. oceanica and/or other seagrasses. Biochemical/genetic descriptors and those obtained by traditional methods depicted a well conserved meadow with seasonal variability and, particularly in summer, indicated a healthier condition in a portion of the bed (station C), which was in agreement with the physical and sedimentological features of the station. Our results support the usefulness of introducing biochemical and genetic approaches to seagrass monitoring programs since they are effective indicators of plant physiological stress and environmental disturbance.

Understanding GINA and How GINA Affects Nurses.

PubMed

Delk, Kayla L

2015-11-01

The Genetic Information Nondiscrimination Act (GINA) is a federal law that became fully effective in 2009 and is intended to prevent employers and health insurers from discriminating against individuals based on their genetic or family history. The article discusses the sections of GINA, what information constitutes genetic information, who enforces GINA, and scenarios in which GINA does not apply. Also discussed are the instances in which an employer may request genetic information from employees, including wellness or genetic monitoring programs. Finally, the article offers a look at how GINA affects nurses who are administering wellness or genetic monitoring programs on behalf of employers. © 2015 The Author(s).

On prediction of genetic values in marker-assisted selection.

PubMed Central

Lange, C; Whittaker, J C

2001-01-01

We suggest a new approximation for the prediction of genetic values in marker-assisted selection. The new approximation is compared to the standard approach. It is shown that the new approach will often provide substantially better prediction of genetic values; furthermore the new approximation avoids some of the known statistical problems of the standard approach. The advantages of the new approach are illustrated by a simulation study in which the new approximation outperforms both the standard approach and phenotypic selection. PMID:11729177

The Alberta Hereditary Diseases Program: a regional model for delivery of genetic services.

PubMed Central

Lowry, R B; Bowen, P

1990-01-01

Genetic counselling and related services are generally provided at major university medical centres because they are very specialized. The need for rurally based genetic services prompted the inclusion of an outreached program in the Alberta Hereditary Diseases Program (AHDP), which was established in 1979; the AHDP was designed to provide services to the entire province through two regional centres and seven outreach clinics. There is a community health nurse in almost every health unit whose duties are either totally or partially devoted to the AHDP; thus, genetic help and information are as close as a rural health unit. The AHDP is designed to provide complete clinical (diagnostic, counselling and some management) services and laboratory (cytogenetic, biochemical and molecular) services for genetic disorders. In addition, the program emphasizes education and publishes a quarterly bulletin, which is sent free of charge to all physicians, hospitals, public health units, social service units, major radio and television stations, newspapers and public libraries and to selected individuals and groups in Alberta. PMID:2302614

Assessing the Effects of Tutorial and Edutainment Software Programs on Students' Achievements, Misconceptions and Attitudes towards Biology

ERIC Educational Resources Information Center

Kara, Yilmaz; Yesilyurt, Selami

2007-01-01

The purpose of this study was to investigate the effects of tutorial and edutainment software programs related to "genetic concepts" topic on student achievements, misconceptions and attitudes. An experimental research design including the genetic concepts achievement test (GAT), the genetic concept test (GCT) and biology attitude scale…

A high-density SNP genetic linkage map for the silver-lipped pearl oyster, Pinctada maxima: a valuable resource for gene localisation and marker-assisted selection.

PubMed

Jones, David B; Jerry, Dean R; Khatkar, Mehar S; Raadsma, Herman W; Zenger, Kyall R

2013-11-20

The silver-lipped pearl oyster, Pinctada maxima, is an important tropical aquaculture species extensively farmed for the highly sought "South Sea" pearls. Traditional breeding programs have been initiated for this species in order to select for improved pearl quality, but many economic traits under selection are complex, polygenic and confounded with environmental factors, limiting the accuracy of selection. The incorporation of a marker-assisted selection (MAS) breeding approach would greatly benefit pearl breeding programs by allowing the direct selection of genes responsible for pearl quality. However, before MAS can be incorporated, substantial genomic resources such as genetic linkage maps need to be generated. The construction of a high-density genetic linkage map for P. maxima is not only essential for unravelling the genomic architecture of complex pearl quality traits, but also provides indispensable information on the genome structure of pearl oysters. A total of 1,189 informative genome-wide single nucleotide polymorphisms (SNPs) were incorporated into linkage map construction. The final linkage map consisted of 887 SNPs in 14 linkage groups, spans a total genetic distance of 831.7 centimorgans (cM), and covers an estimated 96% of the P. maxima genome. Assessment of sex-specific recombination across all linkage groups revealed limited overall heterochiasmy between the sexes (i.e. 1.15:1 F/M map length ratio). However, there were pronounced localised differences throughout the linkage groups, whereby male recombination was suppressed near the centromeres compared to female recombination, but inflated towards telomeric regions. Mean values of LD for adjacent SNP pairs suggest that a higher density of markers will be required for powerful genome-wide association studies. Finally, numerous nacre biomineralization genes were localised providing novel positional information for these genes. This high-density SNP genetic map is the first comprehensive linkage map for any pearl oyster species. It provides an essential genomic tool facilitating studies investigating the genomic architecture of complex trait variation and identifying quantitative trait loci for economically important traits useful in genetic selection programs within the P. maxima pearling industry. Furthermore, this map provides a foundation for further research aiming to improve our understanding of the dynamic process of biomineralization, and pearl oyster evolution and synteny.

Latent spatial models and sampling design for landscape genetics

Treesearch

Ephraim M. Hanks; Melvin B. Hooten; Steven T. Knick; Sara J. Oyler-McCance; Jennifer A. Fike; Todd B. Cross; Michael K. Schwartz

2016-01-01

We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial...

Population genetics of Schistosoma japonicum within the Philippines suggest high levels of transmission between humans and dogs.

PubMed

Rudge, James W; Carabin, Hélène; Balolong, Ernesto; Tallo, Veronica; Shrivastava, Jaya; Lu, Da-Bing; Basáñez, María-Gloria; Olveda, Remigio; McGarvey, Stephen T; Webster, Joanne P

2008-01-01

Schistosoma japonicum, which remains a major public health problem in the Philippines and mainland China, is the only schistosome species for which zoonotic transmission is considered important. While bovines are suspected as the main zoonotic reservoir in parts of China, the relative contributions of various non-human mammals to S. japonicum transmission in the Philippines remain to be determined. We examined the population genetics of S. japonicum in the Philippines in order to elucidate transmission patterns across host species and geographic areas. S. japonicum miracidia (hatched from eggs within fecal samples) from humans, dogs, pigs and rats, and cercariae shed from snail-intermediate hosts, were collected across two geographic areas of Samar Province. Individual isolates were then genotyped using seven multiplexed microsatellite loci. Wright's F(ST) values and phylogenetic trees calculated for parasite populations suggest a high frequency of parasite gene-flow across definitive host species, particularly between dogs and humans. Parasite genetic differentiation between areas was not evident at the definitive host level, possibly suggesting frequent import and export of infections between villages, although there was some evidence of geographic structuring at the snail-intermediate host level. These results suggest very high levels of transmission across host species, and indicate that the role of dogs should be considered when planning control programs. Furthermore, a regional approach to treatment programs is recommended where human migration is extensive.

From ecology to base pairs: nursing and genetic science.

PubMed

Williams, J K; Tripp-Reimer, T

2001-07-01

With the mapping of the human genome has come the opportunity for nursing research to explore topics of concern to the maintenance, restoration, and attainment of genetic-related health. Initially, nursing research on genetic topics originated primarily from physical anthropology and from a clinical, disease-focused perspective. Nursing research subsequently focused on psychosocial aspects of genetic conditions for individuals and their family members. As findings emerge from current human genome discovery, new programs of genetic nursing research are originating from a biobehavioral interface, ranging from the investigations of the influence of specific molecular changes on gene function to social/ethical issues of human health and disease. These initiatives reflect nursing's response to discoveries of gene mutations related to phenotypic expression in both clinical and community-based populations. Genetic research programs are needed that integrate or adapt theoretical and methodological advances in epidemiology, family systems, anthropology, and ethics with those from nursing. Research programs must address not only populations with a specific disease but also community-based genetic health care issues. As genetic health care practice evolves, so will opportunities for research by nurses who can apply genetic concepts and interventions to improve the health of the public. This article presents an analysis of the evolution of genetic nursing research and challengesfor the future.

Population genetics of commercial and feral honey bees in Western Australia.

PubMed

Chapman, Nadine C; Lim, Julianne; Oldroyd, Benjamin P

2008-04-01

Due to the introduction of exotic honey bee (Apis mellifera L.) diseases in the eastern states, the borders of the state of Western Australia were closed to the import of bees for breeding and other purposes > 25 yr ago. To provide genetically improved stock for the industry, a closed population breeding program was established that now provides stock for the majority of Western Australian beekeepers. Given concerns that inbreeding may have resulted from the closed population breeding structure, we assessed the genetic diversity within and between the breeding lines by using microsatellite and mitochondrial markers. We found that the breeding population still maintains considerable genetic diversity, despite 25 yr of selective breeding. We also investigated the genetic distance of the closed population breeding program to that of beekeepers outside of the program, and the feral Western Australian honey bee population. The feral population is genetically distinct from the closed population, but not from the genetic stock maintained by beekeepers outside of the program. The honey bees of Western Australia show three mitotypes, originating from two subspecies: Apis mellifera ligustica (mitotypes C1 and M7b) and Apis mellifera iberica (mitotype M6). Only mitotypes C1 and M6 are present in the commercial populations. The feral population contains all three mitotypes.

Simulation Approach for Timing Analysis of Genetic Logic Circuits.

PubMed

Baig, Hasan; Madsen, Jan

2017-07-21

Constructing genetic logic circuits is an application of synthetic biology in which parts of the DNA of a living cell are engineered to perform a dedicated Boolean function triggered by an appropriate concentration of certain proteins or by different genetic components. These logic circuits work in a manner similar to electronic logic circuits, but they are much more stochastic and hence much harder to characterize. In this article, we introduce an approach to analyze the threshold value and timing of genetic logic circuits. We show how this approach can be used to analyze the timing behavior of single and cascaded genetic logic circuits. We further analyze the timing sensitivity of circuits by varying the degradation rates and concentrations. Our approach can be used not only to characterize the timing behavior but also to analyze the timing constraints of cascaded genetic logic circuits, a capability that we believe will be important for design automation in synthetic biology.

Genetic and Chemical Screenings Identify HDAC3 as a Key Regulator in Hepatic Differentiation of Human Pluripotent Stem Cells.

PubMed

Li, Shuang; Li, Mushan; Liu, Xiaojian; Yang, Yuanyuan; Wei, Yuda; Chen, Yanhao; Qiu, Yan; Zhou, Tingting; Feng, Zhuanghui; Ma, Danjun; Fang, Jing; Ying, Hao; Wang, Hui; Musunuru, Kiran; Shao, Zhen; Zhao, Yongxu; Ding, Qiurong

2018-05-24

Hepatocyte-like cells (HLCs) derived from human pluripotent stem cells (hPSCs) offer a promising cell resource for disease modeling and transplantation. However, differentiated HLCs exhibit an immature phenotype and comprise a heterogeneous population. Thus, a better understanding of HLC differentiation will improve the likelihood of future application. Here, by taking advantage of CRISPR-Cas9-based genome-wide screening technology and a high-throughput hPSC screening platform with a reporter readout, we identified several potential genetic regulators of HLC differentiation. By using a chemical screening approach within our platform, we also identified compounds that can further promote HLC differentiation and preserve the characteristics of in vitro cultured primary hepatocytes. Remarkably, both screenings identified histone deacetylase 3 (HDAC3) as a key regulator in hepatic differentiation. Mechanistically, HDAC3 formed a complex with liver transcriptional factors, e.g., HNF4, and co-regulated the transcriptional program during hepatic differentiation. This study highlights a broadly useful approach for studying and optimizing hPSC differentiation. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Managing Polyploidy in Ex Situ Conservation Genetics: The Case of the Critically Endangered Adriatic Sturgeon (Acipenser naccarii)

PubMed Central

Congiu, Leonardo; Pujolar, Jose Martin; Forlani, Anna; Cenadelli, Silvia; Dupanloup, Isabelle; Barbisan, Federica; Galli, Andrea; Fontana, Francesco

2011-01-01

While the current expansion of conservation genetics enables to address more efficiently the management of threatened species, alternative methods for genetic relatedness data analysis in polyploid species are necessary. Within this framework, we present a standardized and simple protocol specifically designed for polyploid species that can facilitate management of genetic diversity, as exemplified by the ex situ conservation program for the tetraploid Adriatic sturgeon Acipenser naccarii. A critically endangered endemic species of the Adriatic Sea tributaries, its persistence is strictly linked to the ex situ conservation of a single captive broodstock currently decimated to about 25 individuals, which represents the last remaining population of Adriatic sturgeon of certain wild origin. The genetic variability of three F1 broodstocks available as future breeders was estimated based on mitochondrial and microsatellite information and compared with the variability of the parental generation. Genetic data showed that the F1 stocks have only retained part of the genetic variation present in the original stock due to the few parent pairs used as founders. This prompts for the urgent improvement of the current F1 stocks by incorporating new founders that better represent the genetic diversity available. Following parental allocation based on band sharing values, we set up a user-friendly tool for selection of candidate breeders according to relatedness between all possible parent-pairs that secures the use of non-related individuals. The approach developed here could also be applied to other endangered tetraploid sturgeon species overexploited for caviar production, particularly in regions lacking proper infrastructure and/or expertise. PMID:21483472

The current state of genetic counseling and newborn screening: an interview with Megan Tucker

PubMed Central

Tucker, Megan

2017-01-01

Megan Tucker talks to Francesca Lake, Managing Editor: A certified genetic counselor for over 10 years, Megan is currently the director of the Indiana State University Genetic Counseling Graduate Program and the Genetic Counseling Clinic at Union Hospital (Terre Haute, IN, USA). She began her career split between the Center for Prenatal Diagnosis and the Medical Genetics and Neurodevelopmental Center at St Vincent Hospital (Indianapolis, IN, USA). During this time she was instrumental in both the development of the statewide Perinatal Loss Evaluation Program and a hospital protocol to ensure collection of cord blood to allow time to effectively genetically evaluate babies. Her current clinical focus is in cancer and psychiatric genetic counseling. PMID:28883988

Solving a mathematical model integrating unequal-area facilities layout and part scheduling in a cellular manufacturing system by a genetic algorithm.

PubMed

Ebrahimi, Ahmad; Kia, Reza; Komijan, Alireza Rashidi

2016-01-01

In this article, a novel integrated mixed-integer nonlinear programming model is presented for designing a cellular manufacturing system (CMS) considering machine layout and part scheduling problems simultaneously as interrelated decisions. The integrated CMS model is formulated to incorporate several design features including part due date, material handling time, operation sequence, processing time, an intra-cell layout of unequal-area facilities, and part scheduling. The objective function is to minimize makespan, tardiness penalties, and material handling costs of inter-cell and intra-cell movements. Two numerical examples are solved by the Lingo software to illustrate the results obtained by the incorporated features. In order to assess the effects and importance of integration of machine layout and part scheduling in designing a CMS, two approaches, sequentially and concurrent are investigated and the improvement resulted from a concurrent approach is revealed. Also, due to the NP-hardness of the integrated model, an efficient genetic algorithm is designed. As a consequence, computational results of this study indicate that the best solutions found by GA are better than the solutions found by B&B in much less time for both sequential and concurrent approaches. Moreover, the comparisons between the objective function values (OFVs) obtained by sequential and concurrent approaches demonstrate that the OFV improvement is averagely around 17 % by GA and 14 % by B&B.

Genomics-based precision breeding approaches to improve drought tolerance in rice.

PubMed

Swamy, B P Mallikarjuna; Kumar, Arvind

2013-12-01

Rice (Oryza sativa L.), the major staple food crop of the world, faces a severe threat from widespread drought. The development of drought-tolerant rice varieties is considered a feasible option to counteract drought stress. The screening of rice germplasm under drought and its characterization at the morphological, genetic, and molecular levels revealed the existence of genetic variation for drought tolerance within the rice gene pool. The improvements made in managed drought screening and selection for grain yield under drought have significantly contributed to progress in drought breeding programs. The availability of rice genome sequence information, genome-wide molecular markers, and low-cost genotyping platforms now makes it possible to routinely apply marker-assisted breeding approaches to improve grain yield under drought. Grain yield QTLs with a large and consistent effect under drought have been indentified and successfully pyramided in popular rice mega-varieties. Various rice functional genomics resources, databases, tools, and recent advances in "-omics" are facilitating the characterization of genes and pathways involved in drought tolerance, providing the basis for candidate gene identification and allele mining. The transgenic approach is successful in generating drought tolerance in rice under controlled conditions, but field-level testing is necessary. Genomics-assisted drought breeding approaches hold great promise, but a well-planned integration with standardized phenotyping is highly essential to exploit their full potential. Copyright © 2013 Elsevier Inc. All rights reserved.

Processing and population genetic analysis of multigenic datasets with ProSeq3 software.

PubMed

Filatov, Dmitry A

2009-12-01

The current tendency in molecular population genetics is to use increasing numbers of genes in the analysis. Here I describe a program for handling and population genetic analysis of DNA polymorphism data collected from multiple genes. The program includes a sequence/alignment editor and an internal relational database that simplify the preparation and manipulation of multigenic DNA polymorphism datasets. The most commonly used DNA polymorphism analyses are implemented in ProSeq3, facilitating population genetic analysis of large multigenic datasets. Extensive input/output options make ProSeq3 a convenient hub for sequence data processing and analysis. The program is available free of charge from http://dps.plants.ox.ac.uk/sequencing/proseq.htm.

Quantitative trait nucleotide analysis using Bayesian model selection.

PubMed

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

2005-10-01

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

Concordant but Varied Phenotypes among Duchenne Muscular Dystrophy Patient-Specific Myoblasts Derived using a Human iPSC-Based Model.

PubMed

Choi, In Young; Lim, HoTae; Estrellas, Kenneth; Mula, Jyothi; Cohen, Tatiana V; Zhang, Yuanfan; Donnelly, Christopher J; Richard, Jean-Philippe; Kim, Yong Jun; Kim, Hyesoo; Kazuki, Yasuhiro; Oshimura, Mitsuo; Li, Hongmei Lisa; Hotta, Akitsu; Rothstein, Jeffrey; Maragakis, Nicholas; Wagner, Kathryn R; Lee, Gabsang

2016-06-07

Duchenne muscular dystrophy (DMD) remains an intractable genetic disease. Althogh there are several animal models of DMD, there is no human cell model that carries patient-specific DYSTROPHIN mutations. Here, we present a human DMD model using human induced pluripotent stem cells (hiPSCs). Our model reveals concordant disease-related phenotypes with patient-dependent variation, which are partially reversed by genetic and pharmacological approaches. Our "chemical-compound-based" strategy successfully directs hiPSCs into expandable myoblasts, which exhibit a myogenic transcriptional program, forming striated contractile myofibers and participating in muscle regeneration in vivo. DMD-hiPSC-derived myoblasts show disease-related phenotypes with patient-to-patient variability, including aberrant expression of inflammation or immune-response genes and collagens, increased BMP/TGFβ signaling, and reduced fusion competence. Furthermore, by genetic correction and pharmacological "dual-SMAD" inhibition, the DMD-hiPSC-derived myoblasts and genetically corrected isogenic myoblasts form "rescued" multi-nucleated myotubes. In conclusion, our findings demonstrate the feasibility of establishing a human "DMD-in-a-dish" model using hiPSC-based disease modeling. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Characterizing bread wheat genotypes of Pakistani origin for grain zinc biofortification potential.

PubMed

Rehman, Abdul; Farooq, Muhammad; Nawaz, Ahmad; Al-Sadi, Abdullah M; Al-Hashmi, Khalid S; Nadeem, Faisal; Ullah, Aman

2018-03-15

Zinc (Zn) is essential for all life forms and its deficiency is a major issue of malnutrition in humans. This study was carried out to characterize 28 wheat genotypes of Pakistani origin for grain zinc biofortification potential, genetic diversity and relatedness. There was low genetic differentiation among the tested genotypes. However, they differed greatly in yield-related traits, grain mineral (Zn, calcium (Ca) and protein) concentrations and Zn bioavailability. Zinc application increased the concentration of Zn in wheat grain (32.1%), embryo (19.8%), aleurone (47%) and endosperm (23.7%), with an increase in bioavailable Zn (22.2%) and a reduction in phytate concentration (6.8%). Application of Zn also enhanced grain protein and Ca concentrations. Among wheat genotypes, Blue Silver had the highest concentration of Zn in grain, embryo, aleurone and endosperm, with high bioavailable Zn, while Kohinoor-83 had low phytate concentration. Wheat genotypes of Pakistan are genetically less diverse owing to continuous focus on the development of high-yielding varieties only. Therefore genetically diverse wheat genotypes with high endospermic Zn concentration and better grain yield should be used in breeding programs approaches, aiming at improving Zn bioavailability. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Accessible Genetics Research Ethics Education (AGREE): A Web-Based Program for IRBs and Investigators

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

Sugarman, Jeremy; Lee, Linda

The primary objective of this project was to design and evaluate a series of web-based educational modules on genetics research ethics for members of Institutional Review Boards and investigators to facilitate the development and oversight of important research that is sensitive to the relevant ethical, legal and social issues. After a needs assessment was completed in March of 2003, five online educational modules on the ethics of research in genetics were developed, tested, and made available through a host website for AGREE: http://agree.mc.duke.edu/index.html. The 5 modules are: (1) Ethics and Genetics Research in Populations; (2) Ethics in Behavioral Genetics Research;more » (3) Ethical Issues in Research on Gene-Environment Interactions; (4) Ethical Issues in Reproductive Genetics Research; and (5) Ethical Issues in Diagnostic and Therapeutic Research. The development process adopted a tested approach used at Duke University School of Medicine in providing education for researchers and IRB members, supplementing it with expert input and a rigorous evaluation. The host website also included a description of the AGREE; short bios on the AGREE Investigators and Expert Advisory Panel; streaming media of selected presentations from a conference, Working at the Frontiers of Law and Science: Applications of the Human Genome held October 2-3, 2003, at the University of North Carolina at Chapel Hill; and links to online resources in genomics, research ethics, ethics in genomics research, and related organizations. The web site was active beginning with the posting of the first module and was maintained throughout the project period. We have also secured agreement to keep the site active an additional year beyond the project period. AGREE met its primary objective of creating web-based educational modules related to the ethical issues in genetics research. The modules have been disseminated widely. While it is clearly easier to judge the quality of the educational experience than to evaluate the impact of an educational program on research, the AGREE modules have been met with very positive feedback on the part of users.« less

Screening Jews and genes: a consideration of the ethics of genetic screening within the Jewish community: challenges and responses.

PubMed

Levin, M

1999-01-01

Screening for genetic disorders, particularly Tay-Sachs Disease, has been traditionally welcome by the Jewish community. I review the history of genetic screening among Jews and the views from the Jewish tradition on the subject, and then discuss ethical challenges of screening and the impact of historical memories upon future acceptance of screening programs. Some rational principles to guide future design of genetic screening programs among Jews are proposed.

Ecological genetics at the USGS National Wetlands Research Center

USGS Publications Warehouse

Travis, Steven

2006-01-01

The Ecological Genetics Program at the USGS National Wetlands Research Center (NWRC) employs state-of-the-art DNA fingerprinting technologies in characterizing critical management aspects of the population biology of species of concern (fig. 1). The overarching themes of this program have been (1) the critical role that genetic diversity plays in maintaining population viability and (2) how management strategies might incorporate genetic information in preventing the decline of desirable species or in controlling the spread of invasive species.

Directed Chemical Evolution with an Outsized Genetic Code

PubMed Central

Krusemark, Casey J.; Tilmans, Nicolas P.; Brown, Patrick O.; Harbury, Pehr B.

2016-01-01

The first demonstration that macromolecules could be evolved in a test tube was reported twenty-five years ago. That breakthrough meant that billions of years of chance discovery and refinement could be compressed into a few weeks, and provided a powerful tool that now dominates all aspects of protein engineering. A challenge has been to extend this scientific advance into synthetic chemical space: to enable the directed evolution of abiotic molecules. The problem has been tackled in many ways. These include expanding the natural genetic code to include unnatural amino acids, engineering polyketide and polypeptide synthases to produce novel products, and tagging combinatorial chemistry libraries with DNA. Importantly, there is still no small-molecule analog of directed protein evolution, i.e. a substantiated approach for optimizing complex (≥ 10^9 diversity) populations of synthetic small molecules over successive generations. We present a key advance towards this goal: a tool for genetically-programmed synthesis of small-molecule libraries from large chemical alphabets. The approach accommodates alphabets that are one to two orders of magnitude larger than any in Nature, and facilitates evolution within the chemical spaces they create. This is critical for small molecules, which are built up from numerous and highly varied chemical fragments. We report a proof-of-concept chemical evolution experiment utilizing an outsized genetic code, and demonstrate that fitness traits can be passed from an initial small-molecule population through to the great-grandchildren of that population. The results establish the practical feasibility of engineering synthetic small molecules through accelerated evolution. PMID:27508294

On Gene Concepts and Teaching Genetics: Episodes from Classical Genetics

ERIC Educational Resources Information Center

Burian, Richard M.

2013-01-01

This paper addresses the teaching of advanced high school courses or undergraduate courses for non-biology majors about genetics or history of genetics. It will probably be difficult to take the approach described here in a high school science course, although the general approach could help improve such courses. It would be ideal for a college…

A SPECTRAL GRAPH APPROACH TO DISCOVERING GENETIC ANCESTRY1

PubMed Central

Lee, Ann B.; Luca, Diana; Roeder, Kathryn

2010-01-01

Mapping human genetic variation is fundamentally interesting in fields such as anthropology and forensic inference. At the same time, patterns of genetic diversity confound efforts to determine the genetic basis of complex disease. Due to technological advances, it is now possible to measure hundreds of thousands of genetic variants per individual across the genome. Principal component analysis (PCA) is routinely used to summarize the genetic similarity between subjects. The eigenvectors are interpreted as dimensions of ancestry. We build on this idea using a spectral graph approach. In the process we draw on connections between multidimensional scaling and spectral kernel methods. Our approach, based on a spectral embedding derived from the normalized Laplacian of a graph, can produce more meaningful delineation of ancestry than by using PCA. The method is stable to outliers and can more easily incorporate different similarity measures of genetic data than PCA. We illustrate a new algorithm for genetic clustering and association analysis on a large, genetically heterogeneous sample. PMID:20689656

Genetics of steroid-resistant nephrotic syndrome: a review of mutation spectrum and suggested approach for genetic testing.

PubMed

Joshi, S; Andersen, R; Jespersen, B; Rittig, S

2013-09-01

Identification of genes, associated mutations and genotype-phenotype correlations in steroid-resistant nephrotic syndrome (SRNS) is being translated to clinical practice through genetic testing. This review provides an update on the genes and mutations associated with SRNS along with a suggested approach for genetic testing in patients with SRNS. The number of indentified genes associated with SRNS is increasing along with our understanding of their impact on treatment response and risk of recurrence. A systematic approach to genetic testing in patients with SRNS might aid the physician in selecting appropriate treatment. ©2013 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

On the path to genetic novelties: insights from programmed DNA elimination and RNA splicing.

PubMed

Catania, Francesco; Schmitz, Jürgen

2015-01-01

Understanding how genetic novelties arise is a central goal of evolutionary biology. To this end, programmed DNA elimination and RNA splicing deserve special consideration. While programmed DNA elimination reshapes genomes by eliminating chromatin during organismal development, RNA splicing rearranges genetic messages by removing intronic regions during transcription. Small RNAs help to mediate this class of sequence reorganization, which is not error-free. It is this imperfection that makes programmed DNA elimination and RNA splicing excellent candidates for generating evolutionary novelties. Leveraging a number of these two processes' mechanistic and evolutionary properties, which have been uncovered over the past years, we present recently proposed models and empirical evidence for how splicing can shape the structure of protein-coding genes in eukaryotes. We also chronicle a number of intriguing similarities between the processes of programmed DNA elimination and RNA splicing, and highlight the role that the variation in the population-genetic environment may play in shaping their target sequences. © 2015 Wiley Periodicals, Inc.

The social dynamics of genetic testing: the case of Fragile-X.

PubMed

Nelkin, D

1996-12-01

This article considers a program to screen school children for Fragile-X Syndrome as a way to explore several features of the growing practice of genetic testing in American society. These include the common practice of predictive testing in nonclinical settings; the economic, entrepreneurial, and policy interests that are driving the development of genetic screening programs; and the public support for genetic testing even when there are no effective therapeutic interventions. Drawing from research on popular images of genetics, I argue that cultural beliefs and expectations, widely conveyed through popular narratives, are encouraging the search for diagnostic information and enhancing the appeal of genetic explanations for a growing range of conditions.

Genetic and environmental influences underlying the relationship between autistic traits and temperament and character dimensions in adulthood.

PubMed

Picardi, Angelo; Fagnani, Corrado; Medda, Emanuela; Toccaceli, Virgilia; Brambilla, Paolo; Stazi, Maria Antonietta

2015-04-01

In recent years, several twin studies adopted a dimensional approach to Autism Spectrum Disorders (ASD) and estimated the contribution of genetic and environmental influences to variation in autistic traits. However, no study was performed on adults over 18 years of age and all but two studies were based on parent or teacher ratings. Also, the genetic and environmental contributions to the interplay between autistic traits and adult personality dimensions have not been investigated. A sample of 266 complete twin pairs (30% males, mean age 40 ± 12 years) drawn from the population-based Italian Twin Register was administered the Autism-Spectrum Quotient, Temperament and Character Inventory (TCI-125), and General Health Questionnaire (GHQ-12). Genetic structural equation modelling was performed with the Mx program. Estimates were adjusted for gender, age, and GHQ-12 score. Genetic factors accounted for 44% and 20%-49% of individual differences in autistic traits and TCI dimensions, respectively. Unshared environmental factors explained the remaining proportion of variance. Consistently with the notion of a personality profile in ASD characterised by obsessive temperament, autistic traits showed significant phenotypic correlations with several TCI dimensions (positive: HA; negative: NS, RD, SD, C). Genetic and unshared environmental correlations between AQ and these TCI dimensions were significant. The degree of genetic overlap was generally greater than the degree of environmental overlap. Despite some limitations, this study suggests that genetic factors contribute substantially to individual differences in autistic traits in adults, with unshared environmental influences also playing an important role. It also suggests that autistic traits and the majority of temperament and character dimensions share common genetic and environmental aetiological factors. Copyright © 2014 Elsevier Inc. All rights reserved.

Effective Population Size, Genetic Variation, and Their Relevance for Conservation: The Bighorn Sheep in Tiburon Island and Comparisons with Managed Artiodactyls

PubMed Central

Gasca-Pineda, Jaime; Cassaigne, Ivonne; Alonso, Rogelio A.; Eguiarte, Luis E.

2013-01-01

The amount of genetic diversity in a finite biological population mostly depends on the interactions among evolutionary forces and the effective population size (N e) as well as the time since population establishment. Because the N e estimation helps to explore population demographic history, and allows one to predict the behavior of genetic diversity through time, N e is a key parameter for the genetic management of small and isolated populations. Here, we explored an N e-based approach using a bighorn sheep population on Tiburon Island, Mexico (TI) as a model. We estimated the current (N crnt) and ancestral stable (N stbl) inbreeding effective population sizes as well as summary statistics to assess genetic diversity and the demographic scenarios that could explain such diversity. Then, we evaluated the feasibility of using TI as a source population for reintroduction programs. We also included data from other bighorn sheep and artiodactyl populations in the analysis to compare their inbreeding effective size estimates. The TI population showed high levels of genetic diversity with respect to other managed populations. However, our analysis suggested that TI has been under a genetic bottleneck, indicating that using individuals from this population as the only source for reintroduction could lead to a severe genetic diversity reduction. Analyses of the published data did not show a strict correlation between H E and N crnt estimates. Moreover, we detected that ancient anthropogenic and climatic pressures affected all studied populations. We conclude that the estimation of N crnt and N stbl are informative genetic diversity estimators and should be used in addition to summary statistics for conservation and population management planning. PMID:24147115

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

Cancer.gov

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

Genome-Wide Prediction of the Performance of Three-Way Hybrids in Barley.

PubMed

Li, Zuo; Philipp, Norman; Spiller, Monika; Stiewe, Gunther; Reif, Jochen C; Zhao, Yusheng

2017-03-01

Predicting the grain yield performance of three-way hybrids is challenging. Three-way crosses are relevant for hybrid breeding in barley ( L.) and maize ( L.) adapted to East Africa. The main goal of our study was to implement and evaluate genome-wide prediction approaches of the performance of three-way hybrids using data of single-cross hybrids for a scenario in which parental lines of the three-way hybrids originate from three genetically distinct subpopulations. We extended the ridge regression best linear unbiased prediction (RRBLUP) and devised a genomic selection model allowing for subpopulation-specific marker effects (GSA-RRBLUP: general and subpopulation-specific additive RRBLUP). Using an empirical barley data set, we showed that applying GSA-RRBLUP tripled the prediction ability of three-way hybrids from 0.095 to 0.308 compared with RRBLUP, modeling one additive effect for all three subpopulations. The experimental findings were further substantiated with computer simulations. Our results emphasize the potential of GSA-RRBLUP to improve genome-wide hybrid prediction of three-way hybrids for scenarios of genetically diverse parental populations. Because of the advantages of the GSA-RRBLUP model in dealing with hybrids from different parental populations, it may also be a promising approach to boost the prediction ability for hybrid breeding programs based on genetically diverse heterotic groups. Copyright © 2017 Crop Science Society of America.

Systems Genetics as a Tool to Identify Master Genetic Regulators in Complex Disease.

PubMed

Moreno-Moral, Aida; Pesce, Francesco; Behmoaras, Jacques; Petretto, Enrico

2017-01-01

Systems genetics stems from systems biology and similarly employs integrative modeling approaches to describe the perturbations and phenotypic effects observed in a complex system. However, in the case of systems genetics the main source of perturbation is naturally occurring genetic variation, which can be analyzed at the systems-level to explain the observed variation in phenotypic traits. In contrast with conventional single-variant association approaches, the success of systems genetics has been in the identification of gene networks and molecular pathways that underlie complex disease. In addition, systems genetics has proven useful in the discovery of master trans-acting genetic regulators of functional networks and pathways, which in many cases revealed unexpected gene targets for disease. Here we detail the central components of a fully integrated systems genetics approach to complex disease, starting from assessment of genetic and gene expression variation, linking DNA sequence variation to mRNA (expression QTL mapping), gene regulatory network analysis and mapping the genetic control of regulatory networks. By summarizing a few illustrative (and successful) examples, we highlight how different data-modeling strategies can be effectively integrated in a systems genetics study.

Automating the packing heuristic design process with genetic programming.

PubMed

Burke, Edmund K; Hyde, Matthew R; Kendall, Graham; Woodward, John

2012-01-01

The literature shows that one-, two-, and three-dimensional bin packing and knapsack packing are difficult problems in operational research. Many techniques, including exact, heuristic, and metaheuristic approaches, have been investigated to solve these problems and it is often not clear which method to use when presented with a new instance. This paper presents an approach which is motivated by the goal of building computer systems which can design heuristic methods. The overall aim is to explore the possibilities for automating the heuristic design process. We present a genetic programming system to automatically generate a good quality heuristic for each instance. It is not necessary to change the methodology depending on the problem type (one-, two-, or three-dimensional knapsack and bin packing problems), and it therefore has a level of generality unmatched by other systems in the literature. We carry out an extensive suite of experiments and compare with the best human designed heuristics in the literature. Note that our heuristic design methodology uses the same parameters for all the experiments. The contribution of this paper is to present a more general packing methodology than those currently available, and to show that, by using this methodology, it is possible for a computer system to design heuristics which are competitive with the human designed heuristics from the literature. This represents the first packing algorithm in the literature able to claim human competitive results in such a wide variety of packing domains.

Evaluation of a population-based approach to familial colorectal cancer.

PubMed

Parfrey, P S; Dicks, E; Parfrey, O; McNicholas, P J; Noseworthy, H; Woods, M O; Negriin, C; Green, J

2017-05-01

As Newfoundland has the highest rate of familial colorectal cancer (CRC) in the world, we started a population-based clinic to provide colonoscopic and Lynch syndrome (LS) screening recommendations to families of CRC patients based on family risk. Of 1091 incident patients 51% provided a family history. Seventy-two percent of families were at low or intermediate-low risk of CRC and colonoscopic screening recommendations were provided by letter. Twenty-eight percent were at high and intermediate-high risk and were referred to the genetic counsellor, but only 30% (N = 48) were interviewed by study end. Colonoscopy was recommended more frequently than every 5 years in 35% of families. Lower family risk was associated with older age of proband but the frequency of screening colonoscopy recommendations varied across all age groups, driven by variability in family history. Twenty-four percent had a high MMR predict score for a Lynch syndrome mutation, and 23% fulfilled the Provincial Program criteria for LS screening. A population-based approach in the provision of colonoscopic screening recommendations to families at risk of CRC was limited by the relatively low response rate. A family history first approach to the identification of LS families was inefficient. © 2016 The Authors. Clinical Genetics published by John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Estimation of genetic parameters and breeding values across challenged environments to select for robust pigs.

PubMed

Herrero-Medrano, J M; Mathur, P K; ten Napel, J; Rashidi, H; Alexandri, P; Knol, E F; Mulder, H A

2015-04-01

Robustness is an important issue in the pig production industry. Since pigs from international breeding organizations have to withstand a variety of environmental challenges, selection of pigs with the inherent ability to sustain their productivity in diverse environments may be an economically feasible approach in the livestock industry. The objective of this study was to estimate genetic parameters and breeding values across different levels of environmental challenge load. The challenge load (CL) was estimated as the reduction in reproductive performance during different weeks of a year using 925,711 farrowing records from farms distributed worldwide. A wide range of levels of challenge, from favorable to unfavorable environments, was observed among farms with high CL values being associated with confirmed situations of unfavorable environment. Genetic parameters and breeding values were estimated in high- and low-challenge environments using a bivariate analysis, as well as across increasing levels of challenge with a random regression model using Legendre polynomials. Although heritability estimates of number of pigs born alive were slightly higher in environments with extreme CL than in those with intermediate levels of CL, the heritabilities of number of piglet losses increased progressively as CL increased. Genetic correlations among environments with different levels of CL suggest that selection in environments with extremes of low or high CL would result in low response to selection. Therefore, selection programs of breeding organizations that are commonly conducted under favorable environments could have low response to selection in commercial farms that have unfavorable environmental conditions. Sows that had experienced high levels of challenge at least once during their productive life were ranked according to their EBV. The selection of pigs using EBV ignoring environmental challenges or on the basis of records from only favorable environments resulted in a sharp decline in productivity as the level of challenge increased. In contrast, selection using the random regression approach resulted in limited change in productivity with increasing levels of challenge. Hence, we demonstrate that the use of a quantitative measure of environmental CL and a random regression approach can be comprehensively combined for genetic selection of pigs with enhanced ability to maintain high productivity in harsh environments.

Genetics/genomics education for nongenetic health professionals: a systematic literature review.

PubMed

Talwar, Divya; Tseng, Tung-Sung; Foster, Margaret; Xu, Lei; Chen, Lei-Shih

2017-07-01

The completion of the Human Genome Project has enhanced avenues for disease prevention, diagnosis, and management. Owing to the shortage of genetic professionals, genetics/genomics training has been provided to nongenetic health professionals for years to establish their genomic competencies. We conducted a systematic literature review to summarize and evaluate the existing genetics/genomics education programs for nongenetic health professionals. Five electronic databases were searched from January 1990 to June 2016. Forty-four studies met our inclusion criteria. There was a growing publication trend. Program participants were mainly physicians and nurses. The curricula, which were most commonly provided face to face, included basic genetics; applied genetics/genomics; ethical, legal, and social implications of genetics/genomics; and/or genomic competencies/recommendations in particular professional fields. Only one-third of the curricula were theory-based. The majority of studies adopted a pre-/post-test design and lacked follow-up data collection. Nearly all studies reported participants' improvements in one or more of the following areas: knowledge, attitudes, skills, intention, self-efficacy, comfort level, and practice. However, most studies did not report participants' age, ethnicity, years of clinical practice, data validity, and data reliability. Many genetics/genomics education programs for nongenetic health professionals exist. Nevertheless, enhancement in methodological quality is needed to strengthen education initiatives.Genet Med advance online publication 20 October 2016.

Specimen banking of marine organisms in the United States: Current status and long-term prospective

USGS Publications Warehouse

Becker, P.R.; Wise, S.A.; Thorsteinson, L.; Koster, B.J.; Rowles, T.

1997-01-01

A major part of the activities conducted over the last decade by the National Biomonitoring Specimen Bank (NBSB) has involved the archival of marine specimens collected by ongoing environmental monitoring programs. These archived specimens include bivalves, marine sediments, and fish tissues collected by the National Status and Trends and the Exxon Valdez Oil Spill Damage Assessment programs, and marine mammal tissues collected by the Marine Mammal Health and Stranding Response Program and the Alaska Marine Mammal Tissue Archival Project. In addition to supporting these programs, the specimens have been used to investigate circumpolar patterns of chlorinated hydrocarbon concentrations, genetic separation of marine animal stocks, baseline levels of essential and nonessential elements in marine mammals, and the potential risk to human consumers in the Arctic from anthropogenic contaminants found in local subsistence foods. The NBSB specimens represent a resource that has the potential for addressing future issues of marine environmental quality and ecosystem changes through retrospective analysis; however, an ecosystem-based food web approach would maximize this potential. The current status of the NBSB activities related to the banking of marine organisms is presented and discussed, the long-term prospective of these activities is presented, and the importance of an ecosystem-based food web monitoring approach to the value of specimen banking is discussed.

Review of the algal biology program within the National Alliance for Advanced Biofuels and Bioproducts

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

Unkefer, Clifford J.; Sayre, Richard T.; Magnuson, Jon K.

In 2010,when the National Alliance for Advanced Biofuels and Bioproducts (NAABB) consortiumbegan, littlewas known about themolecular basis of algal biomass or oil production. Very fewalgal genome sequenceswere available and efforts to identify the best-producing wild species through bioprospecting approaches had largely stalled after the U.S. Department of Energy's Aquatic Species Program. This lack of knowledge included how reduced carbon was partitioned into storage products like triglycerides or starch and the role played bymetabolite remodeling in the accumulation of energy-dense storage products. Furthermore, genetic transformation and metabolic engineering approaches to improve algal biomass and oil yields were in their infancy. Genomemore » sequencing and transcriptional profiling were becoming less expensive, however; and the tools to annotate gene expression profiles under various growth and engineered conditions were just starting to be developed for algae. It was in this context that an integrated algal biology program was introduced in the NAABB to address the greatest constraints limiting algal biomass yield. This review describes the NAABB algal biology program, including hypotheses, research objectives, and strategies to move algal biology research into the twenty-first century and to realize the greatest potential of algae biomass systems to produce biofuels.« less

Review of the algal biology program within the National Alliance for Advanced Biofuels and Bioproducts

DOE PAGES

Unkefer, Clifford Jay; Sayre, Richard Thomas; Magnuson, Jon K.; ...

2016-06-21

In 2010,when the National Alliance for Advanced Biofuels and Bioproducts (NAABB) consortium began, little was known about the molecular basis of algal biomass or oil production. Very few algal genome sequences were available and efforts to identify the best-producing wild species through bioprospecting approaches had largely stalled after the U.S. Department of Energy's Aquatic Species Program. This lack of knowledge included how reduced carbon was partitioned into storage products like triglycerides or starch and the role played by metabolite remodeling in the accumulation of energy-dense storage products. Furthermore, genetic transformation and metabolic engineering approaches to improve algal biomass and oilmore » yields were in their infancy. Genome sequencing and transcriptional profiling were becoming less expensive, however; and the tools to annotate gene expression profiles under various growth and engineered conditions were just starting to be developed for algae. It was in this context that an integrated algal biology program was introduced in the NAABB to address the greatest constraints limiting algal biomass yield. Our review describes the NAABB algal biology program, including hypotheses, research objectives, and strategies to move algal biology research into the twenty-first century and to realize the greatest potential of algae biomass systems to produce biofuels.« less

Signature program: a platform of basket trials.

PubMed

Slosberg, Eric D; Kang, Barinder P; Peguero, Julio; Taylor, Matthew; Bauer, Todd M; Berry, Donald A; Braiteh, Fadi; Spira, Alexander; Meric-Bernstam, Funda; Stein, Steven; Piha-Paul, Sarina A; Salvado, August

2018-04-20

Investigating targeted therapies can be challenging due to diverse tumor mutations and slow patient accrual for clinical studies. The Signature Program is a series of 8 phase 2, agent-specific basket protocols using a rapid study start-up approach involving no predetermined study sites. Each protocol evaluated 1 agent (buparlisib, dovitinib, binimetinib, encorafenib, sonidegib, BGJ398, ceritinib, or ribociclib) in patients with solid or hematologic malignancies and an actionable mutation. The primary endpoint of each study was the clinical benefit rate (ie, complete or partial response, or stable disease) at 16 weeks. A total of 192 individual sites were opened in the United States, with a median start-up time of 3.6 weeks. The most common tumor types among the 595 treated patients were colorectal (9.2%), non-small cell lung adenocarcinoma (9.1%), and ovarian (8.4%). Frequent genetic alterations were in PIK3CA , RAS , p16 , and PTEN . Overall, 30 partial or complete responses were observed with 6 compounds in 16 tumor types. The Signature Program presents a unique and successful approach for rapid signal finding across multiple tumors and allowed various agents to be evaluated in patients with rare alterations. Incorporating these program features in conventional studies could lead to improved trial efficiencies and patient outcomes.

Review of the algal biology program within the National Alliance for Advanced Biofuels and Bioproducts

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

Unkefer, Clifford Jay; Sayre, Richard Thomas; Magnuson, Jon K.

In 2010,when the National Alliance for Advanced Biofuels and Bioproducts (NAABB) consortium began, little was known about the molecular basis of algal biomass or oil production. Very few algal genome sequences were available and efforts to identify the best-producing wild species through bioprospecting approaches had largely stalled after the U.S. Department of Energy's Aquatic Species Program. This lack of knowledge included how reduced carbon was partitioned into storage products like triglycerides or starch and the role played by metabolite remodeling in the accumulation of energy-dense storage products. Furthermore, genetic transformation and metabolic engineering approaches to improve algal biomass and oilmore » yields were in their infancy. Genome sequencing and transcriptional profiling were becoming less expensive, however; and the tools to annotate gene expression profiles under various growth and engineered conditions were just starting to be developed for algae. It was in this context that an integrated algal biology program was introduced in the NAABB to address the greatest constraints limiting algal biomass yield. Our review describes the NAABB algal biology program, including hypotheses, research objectives, and strategies to move algal biology research into the twenty-first century and to realize the greatest potential of algae biomass systems to produce biofuels.« less

Signature program: a platform of basket trials

PubMed Central

Peguero, Julio; Taylor, Matthew; Bauer, Todd M.; Berry, Donald A.; Braiteh, Fadi; Spira, Alexander; Meric-Bernstam, Funda; Stein, Steven; Piha-Paul, Sarina A.; Salvado, August

2018-01-01

Investigating targeted therapies can be challenging due to diverse tumor mutations and slow patient accrual for clinical studies. The Signature Program is a series of 8 phase 2, agent-specific basket protocols using a rapid study start-up approach involving no predetermined study sites. Each protocol evaluated 1 agent (buparlisib, dovitinib, binimetinib, encorafenib, sonidegib, BGJ398, ceritinib, or ribociclib) in patients with solid or hematologic malignancies and an actionable mutation. The primary endpoint of each study was the clinical benefit rate (ie, complete or partial response, or stable disease) at 16 weeks. A total of 192 individual sites were opened in the United States, with a median start-up time of 3.6 weeks. The most common tumor types among the 595 treated patients were colorectal (9.2%), non-small cell lung adenocarcinoma (9.1%), and ovarian (8.4%). Frequent genetic alterations were in PIK3CA, RAS, p16, and PTEN. Overall, 30 partial or complete responses were observed with 6 compounds in 16 tumor types. The Signature Program presents a unique and successful approach for rapid signal finding across multiple tumors and allowed various agents to be evaluated in patients with rare alterations. Incorporating these program features in conventional studies could lead to improved trial efficiencies and patient outcomes. PMID:29765547

Primary care providers' cancer genetic testing-related knowledge, attitudes, and communication behaviors: A systematic review and research agenda.

PubMed

Hamilton, Jada G; Abdiwahab, Ekland; Edwards, Heather M; Fang, Min-Lin; Jdayani, Andrew; Breslau, Erica S

2017-03-01

Primary care providers (PCPs) can play a critical role in helping patients receive the preventive health benefits of cancer genetic risk information. Thus, the objective of this systematic review was to identify studies of US PCPs' knowledge, attitudes, and communication-related behaviors regarding genetic tests that could inform risk-stratification approaches for breast, colorectal, and prostate cancer screening in order to describe current findings and research gaps. We conducted a systematic search of six electronic databases to identify peer-reviewed empirical articles relating to US PCPs and genetic testing for breast, colorectal, or prostate cancer published in English from 2008 to 2016. We reviewed these data and used narrative synthesis methods to integrate findings into a descriptive summary and identify research needs. We identified 27 relevant articles. Most focused on genetic testing for breast cancer (23/27) and colorectal cancer risk (12/27); only one study examined testing for prostate cancer risk. Most articles addressed descriptive research questions (24/27). Many studies (24/27) documented PCPs' knowledge, often concluding that providers' knowledge was incomplete. Studies commonly (11/27) examined PCPs' attitudes. Across studies, PCPs expressed some concerns about ethical, legal, and social implications of testing. Attitudes about the utility of clinical genetic testing, including for targeted cancer screening, were generally favorable; PCPs were more skeptical of direct-to-consumer testing. Relatively fewer studies (9/27) examined PCPs' communication practices regarding cancer genetic testing. This review indicates a need for investigators to move beyond descriptive research questions related to PCPs' knowledge and attitudes about cancer genetic testing. Research is needed to address important gaps regarding the development, testing, and implementation of innovative interventions and educational programs that can improve PCPs' genetic testing knowledge, assuage concerns about the appropriateness of cancer genetic testing, and promote open and effective patient-provider communication about genetic risk and genetic testing.

Incorporating gene-environment interaction in testing for association with rare genetic variants.

PubMed

Chen, Han; Meigs, James B; Dupuis, Josée

2014-01-01

The incorporation of gene-environment interactions could improve the ability to detect genetic associations with complex traits. For common genetic variants, single-marker interaction tests and joint tests of genetic main effects and gene-environment interaction have been well-established and used to identify novel association loci for complex diseases and continuous traits. For rare genetic variants, however, single-marker tests are severely underpowered due to the low minor allele frequency, and only a few gene-environment interaction tests have been developed. We aimed at developing powerful and computationally efficient tests for gene-environment interaction with rare variants. In this paper, we propose interaction and joint tests for testing gene-environment interaction of rare genetic variants. Our approach is a generalization of existing gene-environment interaction tests for multiple genetic variants under certain conditions. We show in our simulation studies that our interaction and joint tests have correct type I errors, and that the joint test is a powerful approach for testing genetic association, allowing for gene-environment interaction. We also illustrate our approach in a real data example from the Framingham Heart Study. Our approach can be applied to both binary and continuous traits, it is powerful and computationally efficient.

Regulation of STATs by polycystin-1 and their role in polycystic kidney disease.

PubMed

Weimbs, Thomas; Olsan, Erin E; Talbot, Jeffrey J

2013-04-01

Autosomal-dominant polycystic kidney disease (ADPKD) is a common genetic disease caused by mutations in the gene coding for polycystin-1 (PC1). PC1 can regulate STAT transcription factors by a novel, dual mechanism. STAT3 and STAT6 are aberrantly activated in renal cysts. Genetic and pharmacological approaches to inhibit STAT3 or STAT6 have led to promising results in ADPKD mouse models. Here, we review current findings that lead to a model of PC1 as a key regulator of STAT signaling in renal tubule cells. We discuss how PC1 may orchestrate appropriate epithelial responses to renal injury, and how this system may lead to aberrant STAT activation in ADPKD thereby causing inappropriate activation of tissue repair programs that culminate in renal cyst growth and fibrosis.

New biotechnological tools to accelerate scab-resistance trait transfer to apple.

PubMed

Cusin, Roberta; Revers, Luís Fernando; Maraschin, Felipe Dos Santos

2017-01-01

Apple is a fruit crop cultivated worldwide. Apple orchards are exposed to a diverse set of environmental and biological factors that affect the productivity and sustainability of the culture. Many of the efforts and costs for apple production rely on reducing the incidence of fungal diseases, and one of the main diseases is apple scab caused by the fungus Venturia inaequalis. The economic impact of scab on apple productivity has guided many breeding programs to search for cultivars resistant to apple scab. Introgression from wild relatives has been successful to some extent, and genetic engineering for resistant cultivars has even been employed. This review presents the techniques used to the present time to obtain pathogen-resistant apple cultivars and introduces new biotechnological approaches based on plant plasmids that show promising results for delivering genetic traits with a short-term perspective.

Catfish Biology and Farming.

PubMed

Dunham, Rex A; Elaswad, Ahmed

2018-02-15

This article summarizes the biology and culture of ictalurid catfish, an important commercial, aquaculture, and sport fish family in the United States. The history of the propagation as well as spawning of common catfish species in this family is reviewed, with special emphasis on channel catfish and its hybridization with blue catfish. The importance of the channel catfish female×blue catfish male hybrid, including current and future methods of hybrid catfish production, and the potential role it plays in the recovery of the US catfish industry are discussed. Recent advances in catfish culture elements, including environment, management, nutrition, feeding, disease control, culture systems, genetic improvement programs, transgenics, and the application of genome-based approaches in catfish production and welfare, are reviewed. The current status, needs, and future projections are discussed, as well as genetically modified organism developments that are changing the future.

Genome engineering in ornamental plants: Current status and future prospects.

PubMed

Kishi-Kaboshi, Mitsuko; Aida, Ryutaro; Sasaki, Katsutomo

2018-03-13

Ornamental plants, like roses, carnations, and chrysanthemums, are economically important and are sold all over the world. In addition, numerous cut and garden flowers add colors to homes and gardens. Various strategies of plant breeding have been employed to improve traits of many ornamental plants. These approaches span from conventional techniques, such as crossbreeding and mutation breeding, to genetically modified plants. Recently, genome editing has become available as an efficient means for modifying traits in plant species. Genome editing technology is useful for genetic analysis and is poised to become a common breeding method for ornamental plants. In this review, we summarize the benefits and limitations of conventional breeding techniques and genome editing methods and discuss their future potential to accelerate the rate breeding programs in ornamental plants. Copyright © 2018 Elsevier Masson SAS. 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.

A “genetics first” approach to selection

USDA-ARS?s Scientific Manuscript database

A different approach for using genomic information in genetic improvement is proposed. Past research in population genetics and animal breeding combined with information on sequence variants suggest the possibility that selection might be able to capture a portion of inbreeding and heterosis effect...

Imaging Genetics and Genomics in Psychiatry: A Critical Review of Progress and Potential.

PubMed

Bogdan, Ryan; Salmeron, Betty Jo; Carey, Caitlin E; Agrawal, Arpana; Calhoun, Vince D; Garavan, Hugh; Hariri, Ahmad R; Heinz, Andreas; Hill, Matthew N; Holmes, Andrew; Kalin, Ned H; Goldman, David

2017-08-01

Imaging genetics and genomics research has begun to provide insight into the molecular and genetic architecture of neural phenotypes and the neural mechanisms through which genetic risk for psychopathology may emerge. As it approaches its third decade, imaging genetics is confronted by many challenges, including the proliferation of studies using small sample sizes and diverse designs, limited replication, problems with harmonization of neural phenotypes for meta-analysis, unclear mechanisms, and evidence that effect sizes may be more modest than originally posited, with increasing evidence of polygenicity. These concerns have encouraged the field to grow in many new directions, including the development of consortia and large-scale data collection projects and the use of novel methods (e.g., polygenic approaches, machine learning) that enhance the quality of imaging genetic studies but also introduce new challenges. We critically review progress in imaging genetics and offer suggestions and highlight potential pitfalls of novel approaches. Ultimately, the strength of imaging genetics and genomics lies in their translational and integrative potential with other research approaches (e.g., nonhuman animal models, psychiatric genetics, pharmacologic challenge) to elucidate brain-based pathways that give rise to the vast individual differences in behavior as well as risk for psychopathology. Copyright © 2017 Society of Biological Psychiatry. All rights reserved.

Primer on Molecular Genetics; DOE Human Genome Program

DOE R&D Accomplishments Database

1992-04-01

This report is taken from the April 1992 draft of the DOE Human Genome 1991--1992 Program Report, which is expected to be published in May 1992. The primer is intended to be an introduction to basic principles of molecular genetics pertaining to the genome project. The material contained herein is not final and may be incomplete. Techniques of genetic mapping and DNA sequencing are described.

Cross-validation analysis for genetic evaluation models for ranking in endurance horses.

PubMed

García-Ballesteros, S; Varona, L; Valera, M; Gutiérrez, J P; Cervantes, I

2018-01-01

Ranking trait was used as a selection criterion for competition horses to estimate racing performance. In the literature the most common approaches to estimate breeding values are the linear or threshold statistical models. However, recent studies have shown that a Thurstonian approach was able to fix the race effect (competitive level of the horses that participate in the same race), thus suggesting a better prediction accuracy of breeding values for ranking trait. The aim of this study was to compare the predictability of linear, threshold and Thurstonian approaches for genetic evaluation of ranking in endurance horses. For this purpose, eight genetic models were used for each approach with different combinations of random effects: rider, rider-horse interaction and environmental permanent effect. All genetic models included gender, age and race as systematic effects. The database that was used contained 4065 ranking records from 966 horses and that for the pedigree contained 8733 animals (47% Arabian horses), with an estimated heritability around 0.10 for the ranking trait. The prediction ability of the models for racing performance was evaluated using a cross-validation approach. The average correlation between real and predicted performances across genetic models was around 0.25 for threshold, 0.58 for linear and 0.60 for Thurstonian approaches. Although no significant differences were found between models within approaches, the best genetic model included: the rider and rider-horse random effects for threshold, only rider and environmental permanent effects for linear approach and all random effects for Thurstonian approach. The absolute correlations of predicted breeding values among models were higher between threshold and Thurstonian: 0.90, 0.91 and 0.88 for all animals, top 20% and top 5% best animals. For rank correlations these figures were 0.85, 0.84 and 0.86. The lower values were those between linear and threshold approaches (0.65, 0.62 and 0.51). In conclusion, the Thurstonian approach is recommended for the routine genetic evaluations for ranking in endurance horses.

Inferring Causalities in Landscape Genetics: An Extension of Wright's Causal Modeling to Distance Matrices.

PubMed

Fourtune, Lisa; Prunier, Jérôme G; Paz-Vinas, Ivan; Loot, Géraldine; Veyssière, Charlotte; Blanchet, Simon

2018-04-01

Identifying landscape features that affect functional connectivity among populations is a major challenge in fundamental and applied sciences. Landscape genetics combines landscape and genetic data to address this issue, with the main objective of disentangling direct and indirect relationships among an intricate set of variables. Causal modeling has strong potential to address the complex nature of landscape genetic data sets. However, this statistical approach was not initially developed to address the pairwise distance matrices commonly used in landscape genetics. Here, we aimed to extend the applicability of two causal modeling methods-that is, maximum-likelihood path analysis and the directional separation test-by developing statistical approaches aimed at handling distance matrices and improving functional connectivity inference. Using simulations, we showed that these approaches greatly improved the robustness of the absolute (using a frequentist approach) and relative (using an information-theoretic approach) fits of the tested models. We used an empirical data set combining genetic information on a freshwater fish species (Gobio occitaniae) and detailed landscape descriptors to demonstrate the usefulness of causal modeling to identify functional connectivity in wild populations. Specifically, we demonstrated how direct and indirect relationships involving altitude, temperature, and oxygen concentration influenced within- and between-population genetic diversity of G. occitaniae.

Polyglot Programming in Applications Used for Genetic Data Analysis

PubMed Central

Nowak, Robert M.

2014-01-01

Applications used for the analysis of genetic data process large volumes of data with complex algorithms. High performance, flexibility, and a user interface with a web browser are required by these solutions, which can be achieved by using multiple programming languages. In this study, I developed a freely available framework for building software to analyze genetic data, which uses C++, Python, JavaScript, and several libraries. This system was used to build a number of genetic data processing applications and it reduced the time and costs of development. PMID:25197633

Polyglot programming in applications used for genetic data analysis.

PubMed

Nowak, Robert M

2014-01-01

Applications used for the analysis of genetic data process large volumes of data with complex algorithms. High performance, flexibility, and a user interface with a web browser are required by these solutions, which can be achieved by using multiple programming languages. In this study, I developed a freely available framework for building software to analyze genetic data, which uses C++, Python, JavaScript, and several libraries. This system was used to build a number of genetic data processing applications and it reduced the time and costs of development.

Objectives, criteria and methods for using molecular genetic data in priority setting for conservation of animal genetic resources.

PubMed

Boettcher, P J; Tixier-Boichard, M; Toro, M A; Simianer, H; Eding, H; Gandini, G; Joost, S; Garcia, D; Colli, L; Ajmone-Marsan, P

2010-05-01

The genetic diversity of the world's livestock populations is decreasing, both within and across breeds. A wide variety of factors has contributed to the loss, replacement or genetic dilution of many local breeds. Genetic variability within the more common commercial breeds has been greatly decreased by selectively intense breeding programmes. Conservation of livestock genetic variability is thus important, especially when considering possible future changes in production environments. The world has more than 7500 livestock breeds and conservation of all of them is not feasible. Therefore, prioritization is needed. The objective of this article is to review the state of the art in approaches for prioritization of breeds for conservation, particularly those approaches that consider molecular genetic information, and to identify any shortcomings that may restrict their application. The Weitzman method was among the first and most well-known approaches for utilization of molecular genetic information in conservation prioritization. This approach balances diversity and extinction probability to yield an objective measure of conservation potential. However, this approach was designed for decision making across species and measures diversity as distinctiveness. For livestock, prioritization will most commonly be performed among breeds within species, so alternatives that measure diversity as co-ancestry (i.e. also within-breed variability) have been proposed. Although these methods are technically sound, their application has generally been limited to research studies; most existing conservation programmes have effectively primarily based decisions on extinction risk. The development of user-friendly software incorporating these approaches may increase their rate of utilization.

Cluster ensemble based on Random Forests for genetic data.

PubMed

Alhusain, Luluah; Hafez, Alaaeldin M

2017-01-01

Clustering plays a crucial role in several application domains, such as bioinformatics. In bioinformatics, clustering has been extensively used as an approach for detecting interesting patterns in genetic data. One application is population structure analysis, which aims to group individuals into subpopulations based on shared genetic variations, such as single nucleotide polymorphisms. Advances in DNA sequencing technology have facilitated the obtainment of genetic datasets with exceptional sizes. Genetic data usually contain hundreds of thousands of genetic markers genotyped for thousands of individuals, making an efficient means for handling such data desirable. Random Forests (RFs) has emerged as an efficient algorithm capable of handling high-dimensional data. RFs provides a proximity measure that can capture different levels of co-occurring relationships between variables. RFs has been widely considered a supervised learning method, although it can be converted into an unsupervised learning method. Therefore, RF-derived proximity measure combined with a clustering technique may be well suited for determining the underlying structure of unlabeled data. This paper proposes, RFcluE, a cluster ensemble approach for determining the underlying structure of genetic data based on RFs. The approach comprises a cluster ensemble framework to combine multiple runs of RF clustering. Experiments were conducted on high-dimensional, real genetic dataset to evaluate the proposed approach. The experiments included an examination of the impact of parameter changes, comparing RFcluE performance against other clustering methods, and an assessment of the relationship between the diversity and quality of the ensemble and its effect on RFcluE performance. This paper proposes, RFcluE, a cluster ensemble approach based on RF clustering to address the problem of population structure analysis and demonstrate the effectiveness of the approach. The paper also illustrates that applying a cluster ensemble approach, combining multiple RF clusterings, produces more robust and higher-quality results as a consequence of feeding the ensemble with diverse views of high-dimensional genetic data obtained through bagging and random subspace, the two key features of the RF algorithm.

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.

Supply of genetic information--amount, format, and frequency.

PubMed

Misztal, I; Lawlor, T J

1999-05-01

The volume and complexity of genetic information is increasing because of new traits and better models. New traits may include reproduction, health, and carcass. More comprehensive models include the test day model in dairy cattle or a growth model in beef cattle. More complex models, which may include nonadditive effects such as inbreeding and dominance, also provide additional information. The amount of information per animal may increase drastically if DNA marker typing becomes routine and quantitative trait loci information is utilized. In many industries, evaluations are run more frequently. They result in faster genetic progress and improved management and marketing opportunities but also in extra costs and information overload. Adopting new technology and making some organizational changes can help realize all the added benefits of the improvements to the genetic evaluation systems at an acceptable cost. Continuous genetic evaluation, in which new records are accepted and breeding values are updated continuously, will relieve time pressures. An online mating system with access to both genetic and marketing information can result in mating recommendations customized for each user. Such a system could utilize inbreeding and dominance information that cannot efficiently be accommodated in the current sire summaries or off-line mating programs. The new systems will require a new organizational approach in which the task of scientists and technicians will not be simply running the evaluations but also providing the research, design, supervision, and maintenance required in the entire system of evaluation, decision making, and distribution.

Enhancing the effectiveness of biological control programs of invasive species through a more comprehensive pest management approach.

PubMed

DiTomaso, Joseph M; Van Steenwyk, Robert A; Nowierski, Robert M; Vollmer, Jennifer L; Lane, Eric; Chilton, Earl; Burch, Patrick L; Cowan, Phil E; Zimmerman, Kenneth; Dionigi, Christopher P

2017-01-01

Invasive species are one of the greatest economic and ecological threats to agriculture and natural areas in the US and the world. Among the available management tools, biological control provides one of the most economical and long-term effective strategies for managing widespread and damaging invasive species populations of nearly all taxa. However, integrating biological control programs in a more complete integrated pest management approach that utilizes increased information and communication, post-release monitoring, adaptive management practices, long-term stewardship strategies, and new and innovative ecological and genetic technologies can greatly improve the effectiveness of biological control. In addition, expanding partnerships among relevant national, regional, and local agencies, as well as academic scientists and land managers, offers far greater opportunities for long-term success in the suppression of established invasive species. In this paper we direct our recommendations to federal agencies that oversee, fund, conduct research, and develop classical biological control programs for invasive species. By incorporating these recommendations into adaptive management strategies, private and public land managers will have far greater opportunities for long-term success in suppression of established invasive species. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Genetic control of residual variance of yearling weight in Nellore beef cattle.

PubMed

Iung, L H S; Neves, H H R; Mulder, H A; Carvalheiro, R

2017-04-01

There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them. The aim of our study was to investigate the genetic heterogeneity of residual variance on yearling weight (YW; 291.15 ± 46.67) in a Nellore beef cattle population; to compare the results of the statistical approaches, the two-step approach and the double hierarchical generalized linear model (DHGLM); and to evaluate the effectiveness of power transformation to accommodate scale differences. The comparison was based on genetic parameters, accuracy of EBV for residual variance, and cross-validation to assess predictive performance of both approaches. A total of 194,628 yearling weight records from 625 sires were used in the analysis. The results supported the hypothesis of genetic heterogeneity of residual variance on YW in Nellore beef cattle and the opportunity of selection, measured through the genetic coefficient of variation of residual variance (0.10 to 0.12 for the two-step approach and 0.17 for DHGLM, using an untransformed data set). However, low estimates of genetic variance associated with positive genetic correlations between mean and residual variance (about 0.20 for two-step and 0.76 for DHGLM for an untransformed data set) limit the genetic response to selection for uniformity of production while simultaneously increasing YW itself. Moreover, large sire families are needed to obtain accurate estimates of genetic merit for residual variance, as indicated by the low heritability estimates (<0.007). Box-Cox transformation was able to decrease the dependence of the variance on the mean and decreased the estimates of genetic parameters for residual variance. The transformation reduced but did not eliminate all the genetic heterogeneity of residual variance, highlighting its presence beyond the scale effect. The DHGLM showed higher predictive ability of EBV for residual variance and therefore should be preferred over the two-step approach.

Transnational science and collaborative networks. The case of Genetics and Radiobiology in Mexico, 1950-1970.

PubMed

Barahona, Ana

2015-01-01

The transnational approach of the science and technology studies (S&TS) abandons the nation as a unit of analysis in order to understand the development of science history. It also abandons Euro-US-centred narratives in order to explain the role of international collaborative networks and the circulation of knowledge, people, artefacts and scientific practices. It is precisely under this perspective that the development of genetics and radiobiology in Mexico shall be analyzed, together with the pioneering work of the Mexican physician-turned-geneticist Alfonso León de Garay who spent two years in the Galton Laboratory in London under the supervision of Lionel Penrose. Upon his return de Garay funded the Genetics and Radiobiology Program of the National Commission of Nuclear Energy based on local needs and the aim of working beyond geographical limitations to thus facilitate the circulation of knowledge, practices and people. The three main lines of research conducted in the years after its foundation that were in line with international projects while responding to the national context were, first, cytogenetic studies of certain abnormalities, and the cytogenetics and anthropological studies of the Olympic Games held in Mexico in 1968; second, the study of the effects of radiation on hereditary material; and third, the study of population genetics in Drosophila and in Mexican indigenous groups. The program played a key role in reshaping the scientific careers of Mexican geneticists, and in transferring locally sourced research into broader networks. This case shows the importance of international collaborative networks and circulation in the constitution of national scientific elites, and also shows the national and transnational concerns that shaped local practices.

Can functional hologenomics aid tackling current challenges in plant breeding?

PubMed

Nogales, Amaia; Nobre, Tânia; Valadas, Vera; Ragonezi, Carla; Döring, Matthias; Polidoros, Alexios; Arnholdt-Schmitt, Birgit

2016-07-01

Molecular plant breeding usually overlooks the genetic variability that arises from the association of plants with endophytic microorganisms, when looking at agronomic interesting target traits. This source of variability can have crucial effects on the functionality of the organism considered as a whole (the holobiont), and therefore can be selectable in breeding programs. However, seeing the holobiont as a unit for selection and improvement in breeding programs requires novel approaches for genotyping and phenotyping. These should not focus just at the plant level, but also include the associated endophytes and their functional effects on the plant, to make effective desirable trait screenings. The present review intends to draw attention to a new research field on functional hologenomics that if associated with adequate phenotyping tools could greatly increase the efficiency of breeding programs. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Forward genetics by sequencing EMS variation-induced inbred lines

USDA-ARS?s Scientific Manuscript database

The dramatic increase in throughput of sequencing techniques enables gene cloning through pre-existing forward genetics approaches. We show that it also brings with it the potential to change the crossing designs and approach of forward genetics. To achieve this for eukaryotic organisms with complex...

A survey of application: genomics and genetic programming, a new frontier.

PubMed

Khan, Mohammad Wahab; Alam, Mansaf

2012-08-01

The aim of this paper is to provide an introduction to the rapidly developing field of genetic programming (GP). Particular emphasis is placed on the application of GP to genomics. First, the basic methodology of GP is introduced. This is followed by a review of applications in the areas of gene network inference, gene expression data analysis, SNP analysis, epistasis analysis and gene annotation. Finally this paper concluded by suggesting potential avenues of possible future research on genetic programming, opportunities to extend the technique, and areas for possible practical applications. Copyright © 2012 Elsevier Inc. All rights reserved.

Genetic assessment of a summer chum salmon metapopulation in recovery

PubMed Central

Small, Maureen P; Johnson, Thom H; Bowman, Cherril; Martinez, Edith

2014-01-01

Programs to rebuild imperiled wild fish populations often include hatchery-born fish derived from wild populations to supplement natural spawner abundance. These programs require monitoring to determine their demographic, biological, and genetic effects. In 1990s in Washington State, the Summer Chum Salmon Conservation Initiative developed a recovery program for the threatened Hood Canal summer chum salmon Evolutionarily Significant Unit (ESU) (the metapopulation) that used in-river spawners (wild fish) for each respective supplementation broodstock in six tributaries. Returning spawners (wild-born and hatchery-born) composed subsequent broodstocks, and tributary-specific supplementation was limited to three generations. We assessed impacts of the programs on neutral genetic diversity in this metapopulation using 16 microsatellite loci and a thirty-year dataset spanning before and after supplementation, roughly eight generations. Following supplementation, differentiation among subpopulations decreased (but not significantly) and isolation by distance patterns remained unchanged. There was no decline in genetic diversity in wild-born fish, but hatchery-born fish sampled in the same spawning areas had significantly lower genetic diversity and unequal family representation. Despite potential for negative effects from supplementation programs, few were detected in wild-born fish. We hypothesize that chum salmon natural history makes them less vulnerable to negative impacts from hatchery supplementation. PMID:24567747

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

PubMed

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

2010-04-01

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

Genetic screening: programs, principles, and research--thirty years later. Reviewing the recommendations of the Committee for the Study of Inborn Errors of Metabolism (SIEM).

PubMed

Simopoulos, A P

2009-01-01

Screening programs for genetic diseases and characteristics have multiplied in the last 50 years. 'Genetic Screening: Programs, Principles, and Research' is the report of the Committee for the Study of Inborn Errors of Metabolism (SIEM Committee) commissioned by the Division of Medical Sciences of the National Research Council at the National Academy of Sciences in Washington, DC, published in 1975. The report is considered a classic in the field worldwide, therefore it was thought appropriate 30 years later to present the Committee's modus operandi and bring the Committee's recommendations to the attention of those involved in genetics, including organizational, educational, legal, and research aspects of genetic screening. The Committee's report anticipated many of the legal, ethical, economic, social, medical, and policy aspects of genetic screening. The recommendations are current, and future committees should be familiar with them. In 1975 the Committee stated: 'As new screening tests are devised, they should be carefully reviewed. If the experimental rate of discovery of new genetic characteristics means an accelerating rate of appearance of new screening tests, now is the time to develop the medical and social apparatus to accommodate what later on may otherwise turn out to be unmanageable growth.' What a prophetic statement that was. If the Committee's recommendations had been implemented on time, there would be today a federal agency in existence, responsive and responsible to carry out the programs and support research on various aspects of genetic screening, including implementation of a federal law that protects consumers from discrimination by their employers and the insurance industry on the basis of genetic information. Copyright 2008 S. Karger AG, Basel.

Genome survey and high-density genetic map construction provide genomic and genetic resources for the Pacific White Shrimp Litopenaeus vannamei

PubMed Central

Yu, Yang; Zhang, Xiaojun; Yuan, Jianbo; Li, Fuhua; Chen, Xiaohan; Zhao, Yongzhen; Huang, Long; Zheng, Hongkun; Xiang, Jianhai

2015-01-01

The Pacific white shrimp Litopenaeus vannamei is the dominant crustacean species in global seafood mariculture. Understanding the genome and genetic architecture is useful for deciphering complex traits and accelerating the breeding program in shrimp. In this study, a genome survey was conducted and a high-density linkage map was constructed using a next-generation sequencing approach. The genome survey was used to identify preliminary genome characteristics and to generate a rough reference for linkage map construction. De novo SNP discovery resulted in 25,140 polymorphic markers. A total of 6,359 high-quality markers were selected for linkage map construction based on marker coverage among individuals and read depths. For the linkage map, a total of 6,146 markers spanning 4,271.43 cM were mapped to 44 sex-averaged linkage groups, with an average marker distance of 0.7 cM. An integration analysis linked 5,885 genome scaffolds and 1,504 BAC clones to the linkage map. Based on the high-density linkage map, several QTLs for body weight and body length were detected. This high-density genetic linkage map reveals basic genomic architecture and will be useful for comparative genomics research, genome assembly and genetic improvement of L. vannamei and other penaeid shrimp species. PMID:26503227

Genetic complexity of miscanthus cell wall composition and biomass quality for biofuels.

PubMed

van der Weijde, Tim; Kamei, Claire L Alvim; Severing, Edouard I; Torres, Andres F; Gomez, Leonardo D; Dolstra, Oene; Maliepaard, Chris A; McQueen-Mason, Simon J; Visser, Richard G F; Trindade, Luisa M

2017-05-25

Miscanthus sinensis is a high yielding perennial grass species with great potential as a bioenergy feedstock. One of the challenges that currently impedes commercial cellulosic biofuel production is the technical difficulty to efficiently convert lignocellulosic biomass into biofuel. The development of feedstocks with better biomass quality will improve conversion efficiency and the sustainability of the value-chain. Progress in the genetic improvement of biomass quality may be substantially expedited by the development of genetic markers associated to quality traits, which can be used in a marker-assisted selection program. To this end, a mapping population was developed by crossing two parents of contrasting cell wall composition. The performance of 182 F1 offspring individuals along with the parents was evaluated in a field trial with a randomized block design with three replicates. Plants were phenotyped for cell wall composition and conversion efficiency characters in the second and third growth season after establishment. A new SNP-based genetic map for M. sinensis was built using a genotyping-by-sequencing (GBS) approach, which resulted in 464 short-sequence uniparental markers that formed 16 linkage groups in the male map and 17 linkage groups in the female map. A total of 86 QTLs for a variety of biomass quality characteristics were identified, 20 of which were detected in both growth seasons. Twenty QTLs were directly associated to different conversion efficiency characters. Marker sequences were aligned to the sorghum reference genome to facilitate cross-species comparisons. Analyses revealed that for some traits previously identified QTLs in sorghum occurred in homologous regions on the same chromosome. In this work we report for the first time the genetic mapping of cell wall composition and bioconversion traits in the bioenergy crop miscanthus. These results are a first step towards the development of marker-assisted selection programs in miscanthus to improve biomass quality and facilitate its use as feedstock for biofuel production.

Population genetics, community of parasites, and resistance to rodenticides in an urban brown rat (Rattus norvegicus) population

PubMed Central

Gasqui, Patrick; Cosson, Jean-François; Benoît, Etienne; Lattard, Virginie; Crespin, Laurent; Lorvelec, Olivier; Pisanu, Benoît; Teynié, Alexandre; Vayssier-Taussat, Muriel; Bonnet, Sarah; Marianneau, Philippe; Lacôte, Sandra; Bourhy, Pascale; Berny, Philippe; Pavio, Nicole; Le Poder, Sophie; Gilot-Fromont, Emmanuelle; Jourdain, Elsa; Hammed, Abdessalem; Fourel, Isabelle; Chikh, Farid; Vourc’h, Gwenaël

2017-01-01

Brown rats are one of the most widespread urban species worldwide. Despite the nuisances they induce and their potential role as a zoonotic reservoir, knowledge on urban rat populations remains scarce. The main purpose of this study was to characterize an urban brown rat population from Chanteraines park (Hauts-de-Seine, France), with regards to haematology, population genetics, immunogenic diversity, resistance to anticoagulant rodenticides, and community of parasites. Haematological parameters were measured. Population genetics was investigated using 13 unlinked microsatellite loci. Immunogenic diversity was assessed for Mhc-Drb. Frequency of the Y139F mutation (conferring resistance to rodenticides) and two linked microsatellites were studied, concurrently with the presence of anticoagulant residues in the liver. Combination of microscopy and molecular methods were used to investigate the occurrence of 25 parasites. Statistical approaches were used to explore multiple parasite relationships and model parasite occurrence. Eighty-six rats were caught. The first haematological data for a wild urban R. norvegicus population was reported. Genetic results suggested high genetic diversity and connectivity between Chanteraines rats and surrounding population(s). We found a high prevalence (55.8%) of the mutation Y139F and presence of rodenticide residues in 47.7% of the sampled individuals. The parasite species richness was high (16). Seven potential zoonotic pathogens were identified, together with a surprisingly high diversity of Leptospira species (4). Chanteraines rat population is not closed, allowing gene flow and making eradication programs challenging, particularly because rodenticide resistance is highly prevalent. Parasitological results showed that co-infection is more a rule than an exception. Furthermore, the presence of several potential zoonotic pathogens, of which four Leptospira species, in this urban rat population raised its role in the maintenance and spread of these pathogens. Our findings should stimulate future discussions about the development of a long-term rat-control management program in Chanteraines urban park. PMID:28886097

Population genetics, community of parasites, and resistance to rodenticides in an urban brown rat (Rattus norvegicus) population.

PubMed

Desvars-Larrive, Amélie; Pascal, Michel; Gasqui, Patrick; Cosson, Jean-François; Benoît, Etienne; Lattard, Virginie; Crespin, Laurent; Lorvelec, Olivier; Pisanu, Benoît; Teynié, Alexandre; Vayssier-Taussat, Muriel; Bonnet, Sarah; Marianneau, Philippe; Lacôte, Sandra; Bourhy, Pascale; Berny, Philippe; Pavio, Nicole; Le Poder, Sophie; Gilot-Fromont, Emmanuelle; Jourdain, Elsa; Hammed, Abdessalem; Fourel, Isabelle; Chikh, Farid; Vourc'h, Gwenaël

2017-01-01

Brown rats are one of the most widespread urban species worldwide. Despite the nuisances they induce and their potential role as a zoonotic reservoir, knowledge on urban rat populations remains scarce. The main purpose of this study was to characterize an urban brown rat population from Chanteraines park (Hauts-de-Seine, France), with regards to haematology, population genetics, immunogenic diversity, resistance to anticoagulant rodenticides, and community of parasites. Haematological parameters were measured. Population genetics was investigated using 13 unlinked microsatellite loci. Immunogenic diversity was assessed for Mhc-Drb. Frequency of the Y139F mutation (conferring resistance to rodenticides) and two linked microsatellites were studied, concurrently with the presence of anticoagulant residues in the liver. Combination of microscopy and molecular methods were used to investigate the occurrence of 25 parasites. Statistical approaches were used to explore multiple parasite relationships and model parasite occurrence. Eighty-six rats were caught. The first haematological data for a wild urban R. norvegicus population was reported. Genetic results suggested high genetic diversity and connectivity between Chanteraines rats and surrounding population(s). We found a high prevalence (55.8%) of the mutation Y139F and presence of rodenticide residues in 47.7% of the sampled individuals. The parasite species richness was high (16). Seven potential zoonotic pathogens were identified, together with a surprisingly high diversity of Leptospira species (4). Chanteraines rat population is not closed, allowing gene flow and making eradication programs challenging, particularly because rodenticide resistance is highly prevalent. Parasitological results showed that co-infection is more a rule than an exception. Furthermore, the presence of several potential zoonotic pathogens, of which four Leptospira species, in this urban rat population raised its role in the maintenance and spread of these pathogens. Our findings should stimulate future discussions about the development of a long-term rat-control management program in Chanteraines urban park.

A second generation genetic linkage map of Japanese flounder (Paralichthys olivaceus)

PubMed Central

2010-01-01

Background Japanese flounder (Paralichthys olivaceus) is one of the most economically important marine species in Northeast Asia. Information on genetic markers associated with quantitative trait loci (QTL) can be used in breeding programs to identify and select individuals carrying desired traits. Commercial production of Japanese flounder could be increased by developing disease-resistant fish and improving commercially important traits. Previous maps have been constructed with AFLP markers and a limited number of microsatellite markers. In this study, improved genetic linkage maps are presented. In contrast with previous studies, these maps were built mainly with a large number of codominant markers so they can potentially be used to analyze different families and populations. Results Sex-specific genetic linkage maps were constructed for the Japanese flounder including a total of 1,375 markers [1,268 microsatellites, 105 single nucleotide polymorphisms (SNPs) and two genes]; 1,167 markers are linked to the male map and 1,067 markers are linked to the female map. The lengths of the male and female maps are 1,147.7 cM and 833.8 cM, respectively. Based on estimations of map lengths, the female and male maps covered 79 and 82% of the genome, respectively. Recombination ratio in the new maps revealed F:M of 1:0.7. All linkage groups in the maps presented large differences in the location of sex-specific recombination hot-spots. Conclusions The improved genetic linkage maps are very useful for QTL analyses and marker-assisted selection (MAS) breeding programs for economically important traits in Japanese flounder. In addition, SNP flanking sequences were blasted against Tetraodon nigroviridis (puffer fish) and Danio rerio (zebrafish), and synteny analysis has been carried out. The ability to detect synteny among species or genera based on homology analysis of SNP flanking sequences may provide opportunities to complement initial QTL experiments with candidate gene approaches from homologous chromosomal locations identified in related model organisms. PMID:20937088

Utilization of farm animal genetic resources in a changing agro-ecological environment in the Nordic countries.

PubMed

Kantanen, Juha; Løvendahl, Peter; Strandberg, Erling; Eythorsdottir, Emma; Li, Meng-Hua; Kettunen-Præbel, Anne; Berg, Peer; Meuwissen, Theo

2015-01-01

Livestock production is the most important component of northern European agriculture and contributes to and will be affected by climate change. Nevertheless, the role of farm animal genetic resources in the adaptation to new agro-ecological conditions and mitigation of animal production's effects on climate change has been inadequately discussed despite there being several important associations between animal genetic resources and climate change issues. The sustainability of animal production systems and future food security require access to a wide diversity of animal genetic resources. There are several genetic questions that should be considered in strategies promoting adaptation to climate change and mitigation of environmental effects of livestock production. For example, it may become important to choose among breeds and even among farm animal species according to their suitability to a future with altered production systems. Some animals with useful phenotypes and genotypes may be more useful than others in the changing environment. Robust animal breeds with the potential to adapt to new agro-ecological conditions and tolerate new diseases will be needed. The key issue in mitigation of harmful greenhouse gas effects induced by livestock production is the reduction of methane (CH4) emissions from ruminants. There are differences in CH4 emissions among breeds and among individual animals within breeds that suggest a potential for improvement in the trait through genetic selection. Characterization of breeds and individuals with modern genomic tools should be applied to identify breeds that have genetically adapted to marginal conditions and to get critical information for breeding and conservation programs for farm animal genetic resources. We conclude that phenotyping and genomic technologies and adoption of new breeding approaches, such as genomic selection introgression, will promote breeding for useful characters in livestock species.

Genetic Diversity and Population Structure of Whitebark Pine (Pinus albicaulis Engelm.) in Western North America

PubMed Central

Liu, Jun-Jun; Sniezko, Richard; Murray, Michael; Wang, Ning; Chen, Hao; Zamany, Arezoo; Sturrock, Rona N.; Savin, Douglas; Kegley, Angelia

2016-01-01

Whitebark pine (WBP, Pinus albicaulis Engelm.) is an endangered conifer species due to heavy mortality from white pine blister rust (WPBR, caused by Cronartium ribicola) and mountain pine beetle (Dendroctonus ponderosae). Information about genetic diversity and population structure is of fundamental importance for its conservation and restoration. However, current knowledge on the genetic constitution and genomic variation is still limited for WBP. In this study, an integrated genomics approach was applied to characterize seed collections from WBP breeding programs in western North America. RNA-seq analysis was used for de novo assembly of the WBP needle transcriptome, which contains 97,447 protein-coding transcripts. Within the transcriptome, single nucleotide polymorphisms (SNPs) were discovered, and more than 22,000 of them were non-synonymous SNPs (ns-SNPs). Following the annotation of genes with ns-SNPs, 216 ns-SNPs within candidate genes with putative functions in disease resistance and plant defense were selected to design SNP arrays for high-throughput genotyping. Among these SNP loci, 71 were highly polymorphic, with sufficient variation to identify a unique genotype for each of the 371 individuals originating from British Columbia (Canada), Oregon and Washington (USA). A clear genetic differentiation was evident among seed families. Analyses of genetic spatial patterns revealed varying degrees of diversity and the existence of several genetic subgroups in the WBP breeding populations. Genetic components were associated with geographic variables and phenotypic rating of WPBR disease severity across landscapes, which may facilitate further identification of WBP genotypes and gene alleles contributing to local adaptation and quantitative resistance to WPBR. The WBP genomic resources developed here provide an invaluable tool for further studies and for exploitation and utilization of the genetic diversity preserved within this endangered conifer and other five-needle pines. PMID:27992468

Utilization of farm animal genetic resources in a changing agro-ecological environment in the Nordic countries

PubMed Central

Kantanen, Juha; Løvendahl, Peter; Strandberg, Erling; Eythorsdottir, Emma; Li, Meng-Hua; Kettunen-Præbel, Anne; Berg, Peer; Meuwissen, Theo

2015-01-01

Livestock production is the most important component of northern European agriculture and contributes to and will be affected by climate change. Nevertheless, the role of farm animal genetic resources in the adaptation to new agro-ecological conditions and mitigation of animal production’s effects on climate change has been inadequately discussed despite there being several important associations between animal genetic resources and climate change issues. The sustainability of animal production systems and future food security require access to a wide diversity of animal genetic resources. There are several genetic questions that should be considered in strategies promoting adaptation to climate change and mitigation of environmental effects of livestock production. For example, it may become important to choose among breeds and even among farm animal species according to their suitability to a future with altered production systems. Some animals with useful phenotypes and genotypes may be more useful than others in the changing environment. Robust animal breeds with the potential to adapt to new agro-ecological conditions and tolerate new diseases will be needed. The key issue in mitigation of harmful greenhouse gas effects induced by livestock production is the reduction of methane (CH4) emissions from ruminants. There are differences in CH4 emissions among breeds and among individual animals within breeds that suggest a potential for improvement in the trait through genetic selection. Characterization of breeds and individuals with modern genomic tools should be applied to identify breeds that have genetically adapted to marginal conditions and to get critical information for breeding and conservation programs for farm animal genetic resources. We conclude that phenotyping and genomic technologies and adoption of new breeding approaches, such as genomic selection introgression, will promote breeding for useful characters in livestock species. PMID:25767477

Are attractors 'strange', or is life more complicated than the simple laws of physics?

PubMed

Pogun, S

2001-01-01

Interesting and intriguing questions involve complex systems whose properties cannot be explained fully by reductionist approaches. Last century was dominated by physics, and applying the simple laws of physics to biology appeared to be a practical solution to understand living organisms. However, although some attributes of living organisms involve physico-chemical properties, the genetic program and evolutionary history of complex biological systems make them unique and unpredictable. Furthermore, there are and will be 'unobservable' phenomena in biology which have to be accounted for.

Genetics and Common Disorders: Implications for Primary Care and Public Health Providers

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

McInerney, Joseph D.; Greendale, Karen; Peay, Holly L.

We developed this program for primary care providers (PCPs) and public health professionals (PHPs) who are interested in increasing their understanding of the genetics of common chronic diseases and of the implications of genetics and genomics for their fields. The program differs from virtually all previous educational efforts in genetics for health professionals in that it focuses on the genetics of common chronic disease and on the broad principles that emerge when one views disease from the perspectives of variation and individuality, which are at the heart of thinking genetically. The CD-ROM introduces users to content that will improve theirmore » understanding of topics such as: • A framework for genetics and common disease; • Basic information on genetics, genomics, genetic medicine, and public health genetics, all in the context of common chronic disease; • The status of research on genetic contributions to specific common diseases, including a review of research methods; • Genetic/environmental interaction as the new “central dogma” of public health genetics; • The importance of taking and analyzing a family history; • The likely impact of potential gene discovery and genetic testing on genetic counseling and risk assessment and on the practices of PCPs and PHPs; • Stratification of populations into low-, moderate-, and high-risk categories; • The potential role of PCPs and PHPs in identifying high-risk individuals and families, in providing limited genetics services, and in referring to clinical genetics specialists; the potential for standard referral algorithms; • Implications of genetic insights for diagnosis and treatment; • Ethical, legal, and social issues that arise from genetic testing for common chronic diseases; and • Specific prevention strategies based on understanding of genetics and genetic/ environmental interactions. The interactive content – developed by experts in genetics, primary care, and public health – is organized around two case studies designed to appeal to primary care providers (thrombophilia) and public health professionals (development of a screening grogram for colorectal cancer). NCHPEG has distributed more than 0000 copies of the CD-ROM to NCHPEG member organizations and to other organizations and individuals in response to requests. The program also is available at www.nchpeg.org.« less

Introduction to the Natural Anticipator and the Artificial Anticipator

NASA Astrophysics Data System (ADS)

Dubois, Daniel M.

2010-11-01

This short communication deals with the introduction of the concept of anticipator, which is one who anticipates, in the framework of computing anticipatory systems. The definition of anticipation deals with the concept of program. Indeed, the word program, comes from "pro-gram" meaning "to write before" by anticipation, and means a plan for the programming of a mechanism, or a sequence of coded instructions that can be inserted into a mechanism, or a sequence of coded instructions, as genes or behavioural responses, that is part of an organism. Any natural or artificial programs are thus related to anticipatory rewriting systems, as shown in this paper. All the cells in the body, and the neurons in the brain, are programmed by the anticipatory genetic code, DNA, in a low-level language with four signs. The programs in computers are also computing anticipatory systems. It will be shown, at one hand, that the genetic code DNA is a natural anticipator. As demonstrated by Nobel laureate McClintock [8], genomes are programmed. The fundamental program deals with the DNA genetic code. The properties of the DNA consist in self-replication and self-modification. The self-replicating process leads to reproduction of the species, while the self-modifying process leads to new species or evolution and adaptation in existing ones. The genetic code DNA keeps its instructions in memory in the DNA coding molecule. The genetic code DNA is a rewriting system, from DNA coding to DNA template molecule. The DNA template molecule is a rewriting system to the Messenger RNA molecule. The information is not destroyed during the execution of the rewriting program. On the other hand, it will be demonstrated that Turing machine is an artificial anticipator. The Turing machine is a rewriting system. The head reads and writes, modifying the content of the tape. The information is destroyed during the execution of the program. This is an irreversible process. The input data are lost.

A novel approach for supercapacitors degradation characterization

NASA Astrophysics Data System (ADS)

Oz, Alon; Gelman, Danny; Goren, Emanuelle; Shomrat, Neta; Baltianski, Sioma; Tsur, Yoed

2017-07-01

A novel approach to analyze electrochemical impedance spectroscopy (EIS), based on evolutionary programming, has been utilized to characterize supercapacitors operation mechanism and degradation processes. This approach poses the ability of achieving a comprehensive study of supercapacitors via solely AC measurements. Commercial supercapacitors were examined during accelerated degradation. The microstructure of the electrode-electrolyte interface changes upon degradation; electrolyte parasitic reactions yield the formation of precipitates on the porous surface, which limit the access of the electrolyte ions to the active area and thus reduces performance. EIS analysis using Impedance Spectroscopy Genetic Programming (ISGP) technique enables identifying how the changing microstructure is affecting the operation mechanism of supercapacitors, in terms of each process effective capacitance and time constant. The most affected process is the transport of electrolyte ions at the porous electrode. Their access to the whole active area is hindered, which is shown in our analysis by the decrease of the capacitance gained in the transport and the longer time it takes to penetrate the entire pores depth. Early failure detection is also demonstrated, in a way not readily possible via conventional indicators. ISGP advanced analysis method has been verified using conventional and proven techniques: cyclic voltammetry and post mortem measurements.

MACARON: A python framework to identify and re-annotate multi-base affected codons in whole genome/exome sequence data.

PubMed

Khan, Waqasuddin; Saripella, Ganapathi Varma-; Ludwig, Thomas; Cuppens, Tania; Thibord, Florian; Génin, Emmanuelle; Deleuze, Jean-Francois; Trégouët, David-Alexandre

2018-05-03

Predicted deleteriousness of coding variants is a frequently used criterion to filter out variants detected in next-generation sequencing projects and to select candidates impacting on the risk of human diseases. Most available dedicated tools implement a base-to-base annotation approach that could be biased in presence of several variants in the same genetic codon. We here proposed the MACARON program that, from a standard VCF file, identifies, re-annotates and predicts the amino acid change resulting from multiple single nucleotide variants (SNVs) within the same genetic codon. Applied to the whole exome dataset of 573 individuals, MACARON identifies 114 situations where multiple SNVs within a genetic codon induce an amino acid change that is different from those predicted by standard single SNV annotation tool. Such events are not uncommon and deserve to be studied in sequencing projects with inconclusive findings. MACARON is written in python with codes available on the GENMED website (www.genmed.fr). david-alexandre.tregouet@inserm.fr. Supplementary data are available at Bioinformatics online.

Epigenetics and Epigenomics of Plants.

PubMed

Yadav, Chandra Bhan; Pandey, Garima; Muthamilarasan, Mehanathan; Prasad, Manoj

2018-01-23

The genetic material DNA in association with histone proteins forms the complex structure called chromatin, which is prone to undergo modification through certain epigenetic mechanisms including cytosine DNA methylation, histone modifications, and small RNA-mediated methylation. Alterations in chromatin structure lead to inaccessibility of genomic DNA to various regulatory proteins such as transcription factors, which eventually modulates gene expression. Advancements in high-throughput sequencing technologies have provided the opportunity to study the epigenetic mechanisms at genome-wide levels. Epigenomic studies using high-throughput technologies will widen the understanding of mechanisms as well as functions of regulatory pathways in plant genomes, which will further help in manipulating these pathways using genetic and biochemical approaches. This technology could be a potential research tool for displaying the systematic associations of genetic and epigenetic variations, especially in terms of cytosine methylation onto the genomic region in a specific cell or tissue. A comprehensive study of plant populations to correlate genotype to epigenotype and to phenotype, and also the study of methyl quantitative trait loci (QTL) or epiGWAS, is possible by using high-throughput sequencing methods, which will further accelerate molecular breeding programs for crop improvement. Graphical Abstract.

Genomic alterations and molecular subtypes of gastric cancers in Asians.

PubMed

Ye, Xiang S; Yu, Chunping; Aggarwal, Amit; Reinhard, Christoph

2016-05-09

Gastric cancer (GC) is a highly heterogenic disease, and it is the second leading cause of cancer death in the world. Common chemotherapies are not very effective for GC, which often presents as an advanced or metastatic disease at diagnosis. Treatment options are limited, and the prognosis for advanced GCs is poor. The landscape of genomic alterations in GCs has recently been characterized by several international cancer genome programs, including studies that focused exclusively on GCs in Asians. These studies identified major recurrent driver mutations and provided new insights into the mutational heterogeneity and genetic profiles of GCs. An analysis of gene expression data by the Asian Cancer Research Group (ACRG) further uncovered four distinct molecular subtypes with well-defined clinical features and their intersections with actionable genetic alterations to which targeted therapeutic agents are either already available or under clinical development. In this article, we review the ACRG GC project. We also discuss the implications of the genetic and molecular findings from various GC genomic studies with respect to developing more precise diagnoses and treatment approaches for GCs.

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

PubMed Central

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

2015-01-01

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

Psychological Aspects of Genetic Approach to Teaching Mathematics

ERIC Educational Resources Information Center

Safuanov, Ildar S.

2004-01-01

In this theoretical essay the psychological aspects of genetic approach to teaching mathematics (mainly at universities) are discussed. Analysis of the history and modern state of genetic teaching shows that its psychological aspects may be explained using both Vygotskian and Piagetian frameworks. Experience of practice of mathematical education…

Improving Metabolic and Cardiovascular Health at an Early Psychosis Intervention Program in Vancouver, Canada

PubMed Central

Fredrikson, Diane H.; Boyda, Heidi N.; Tse, Lurdes; Whitney, Zachary; Pattison, Mark A.; Ott, Fred J.; Hansen, Laura; Barr, Alasdair M.

2014-01-01

Psychotic disorders most commonly appear during the late teenage years and early adulthood. A focused and rapid clinical response by an integrated health team can help to improve the quality of life of the patient, leading to a better long-term prognosis. The Vancouver Coastal Health early psychosis intervention program covers a catchment area of approximately 800,000 people in the cities of Vancouver and Richmond, Canada. The program provides a multidisciplinary approach to supporting patients under the age of 30 who have recently experienced first-break psychosis. The program addresses the needs of the treatment environment, medication, and psychological therapies. A critical part of this support includes a program to specifically improve patients’ physical health. Physical health needs are addressed through a two-pronged, parallel approach. Patients receive routine metabolic health assessments during their first year in the program, where standard metabolic parameters are recorded. Based on the results of clinical interviews and laboratory tests, specific actionable interventions are recommended. The second key strategy is a program that promotes healthy lifestyle goal development. Patients work closely with occupational therapists to develop goals to improve cardiometabolic health. These programs are supported by an active research environment, where patients are able to engage in studies with a focus on improving their physical health. These studies include a longitudinal evaluation of the effects of integrated health coaching on maintaining cardiometabolic health in patients recently admitted to the program, as well as a clinical study that evaluates the effects of low versus higher metabolic risk antipsychotic drugs on central adiposity. An additional pharmacogenomic study is helping to identify genetic variants that may predict cardiometabolic changes following treatment with antipsychotic drugs. PMID:25249985

Unraveling the Tangled Skein: The Evolution of Transcriptional Regulatory Networks in Development.

PubMed

Rebeiz, Mark; Patel, Nipam H; Hinman, Veronica F

2015-01-01

The molecular and genetic basis for the evolution of anatomical diversity is a major question that has inspired evolutionary and developmental biologists for decades. Because morphology takes form during development, a true comprehension of how anatomical structures evolve requires an understanding of the evolutionary events that alter developmental genetic programs. Vast gene regulatory networks (GRNs) that connect transcription factors to their target regulatory sequences control gene expression in time and space and therefore determine the tissue-specific genetic programs that shape morphological structures. In recent years, many new examples have greatly advanced our understanding of the genetic alterations that modify GRNs to generate newly evolved morphologies. Here, we review several aspects of GRN evolution, including their deep preservation, their mechanisms of alteration, and how they originate to generate novel developmental programs.

Are hotspots of evolutionary potential adequately protected in southern California?

USGS Publications Warehouse

Vandergast, A.G.; Bohonak, A.J.; Hathaway, S.A.; Boys, J.; Fisher, R.N.

2008-01-01

Reserves are often designed to protect rare habitats, or "typical" exemplars of ecoregions and geomorphic provinces. This approach focuses on current patterns of organismal and ecosystem-level biodiversity, but typically ignores the evolutionary processes that control the gain and loss of biodiversity at these and other levels (e.g., genetic, ecological). In order to include evolutionary processes in conservation planning efforts, their spatial components must first be identified and mapped. We describe a GIS-based approach for explicitly mapping patterns of genetic divergence and diversity for multiple species (a "multi-species genetic landscape"). Using this approach, we analyzed mitochondrial DNA datasets from 21 vertebrate and invertebrate species in southern California to identify areas with common phylogeographic breaks and high intrapopulation diversity. The result is an evolutionary framework for southern California within which patterns of genetic diversity can be analyzed in the context of historical processes, future evolutionary potential and current reserve design. Our multi-species genetic landscapes pinpoint six hotspots where interpopulation genetic divergence is consistently high, five evolutionary hotspots within which genetic connectivity is high, and three hotspots where intrapopulation genetic diversity is high. These 14 hotspots can be grouped into eight geographic areas, of which five largely are unprotected at this time. The multi-species genetic landscape approach may provide an avenue to readily incorporate measures of evolutionary process into GIS-based systematic conservation assessment and land-use planning.

From phenotyping towards breeding strategies: using in vivo indicator traits and genetic markers to improve meat quality in an endangered pig breed.

PubMed

Biermann, A D M; Yin, T; König von Borstel, U U; Rübesam, K; Kuhn, B; König, S

2015-06-01

In endangered and local pig breeds of small population sizes, production has to focus on alternative niche markets with an emphasis on specific product and meat quality traits to achieve economic competiveness. For designing breeding strategies on meat quality, an adequate performance testing scheme focussing on phenotyped selection candidates is required. For the endangered German pig breed 'Bunte Bentheimer' (BB), no breeding program has been designed until now, and no performance testing scheme has been implemented. For local breeds, mainly reared in small-scale production systems, a performance test based on in vivo indicator traits might be a promising alternative in order to increase genetic gain for meat quality traits. Hence, the main objective of this study was to design and evaluate breeding strategies for the improvement of meat quality within the BB breed using in vivo indicator traits and genetic markers. The in vivo indicator trait was backfat thickness measured by ultrasound (BFiv), and genetic markers were allele variants at the ryanodine receptor 1 (RYR1) locus. In total, 1116 records of production and meat quality traits were collected, including 613 in vivo ultrasound measurements and 713 carcass and meat quality records. Additionally, 700 pigs were genotyped at the RYR1 locus. Data were used (1) to estimate genetic (co)variance components for production and meat quality traits, (2) to estimate allele substitution effects at the RYR1 locus using a selective genotyping approach and (3) to evaluate breeding strategies on meat quality by combining results from quantitative-genetic and molecular-genetic approaches. Heritability for the production trait BFiv was 0.27, and 0.48 for backfat thickness measured on carcass. Estimated heritabilities for meat quality traits ranged from 0.14 for meat brightness to 0.78 for the intramuscular fat content (IMF). Genetic correlations between BFiv and IMF were higher than estimates based on carcass backfat measurements (0.39 v. 0.25). The presence of the unfavorable n allele was associated with increased electric conductivity, paler meat and higher drip loss. The allele substitution effect on IMF was unfavorable, indicating lower IMF when the n allele is present. A breeding strategy including the phenotype (BFiv) combined with genetic marker information at the RYR1 locus from the selection candidate, resulted in a 20% increase in accuracy and selection response when compared with a breeding strategy without genetic marker information.

Developing Novel Therapeutic Approaches in Small Cell Lung Carcinoma Using Genetically Engineered Mouse Models and Human Circulating Tumor Cells

DTIC Science & Technology

2014-10-01

AD_________________ Award Number: W81XWH-13-1-0325 TITLE: Developing Novel Therapeutic Approaches in Small Cell Lung Carcinoma Using ...Genetically Engineered Mouse Models and Human Circulating Tumor Cells PRINCIPAL INVESTIGATOR: Jeffrey Engelman MD PhD CONTRACTING ORGANIZATION ...Novel Therapeutic Approaches in Small Cell Lung 5a. CONTRACT NUMBER W81XWH-13-1-0325 Carcinoma Using Genetically Engineered Mouse Models and 5b

Impact of computer-assisted data collection, evaluation and management on the cancer genetic counselor's time providing patient care.

PubMed

Cohen, Stephanie A; McIlvried, Dawn E

2011-06-01

Cancer genetic counseling sessions traditionally encompass collecting medical and family history information, evaluating that information for the likelihood of a genetic predisposition for a hereditary cancer syndrome, conveying that information to the patient, offering genetic testing when appropriate, obtaining consent and subsequently documenting the encounter with a clinic note and pedigree. Software programs exist to collect family and medical history information electronically, intending to improve efficiency and simplicity of collecting, managing and storing this data. This study compares the genetic counselor's time spent in cancer genetic counseling tasks in a traditional model and one using computer-assisted data collection, which is then used to generate a pedigree, risk assessment and consult note. Genetic counselor time spent collecting family and medical history and providing face-to-face counseling for a new patient session decreased from an average of 85-69 min when using the computer-assisted data collection. However, there was no statistically significant change in overall genetic counselor time on all aspects of the genetic counseling process, due to an increased amount of time spent generating an electronic pedigree and consult note. Improvements in the computer program's technical design would potentially minimize data manipulation. Certain aspects of this program, such as electronic collection of family history and risk assessment, appear effective in improving cancer genetic counseling efficiency while others, such as generating an electronic pedigree and consult note, do not.

Genetics objective structured clinical exams at the Maimonides Infants & Children's Hospital of Brooklyn, New York.

PubMed

Altshuler, Lisa; Kachur, Elizabeth; Krinshpun, Shifra; Sullivan, Deborah

2008-11-01

In 2003, the Maimonides Infants & Children's Hospital received a Title VII Residency Training in Primary Care grant to integrate genetic-specific competencies into postgraduate pediatrics education. As part of that endeavor, mandatory yearly genetics objective structured clinical exams (OSCEs) were instituted for third-year residents. This article reports on the first three years of experience with this innovative educational tool.After an overview of genetic concepts, dysmorphology, and communication styles, residents complete a five-station OSCE and receive feedback from standardized patients and from the faculty who observe them. After this clinical exercise, the residents participate in a small-group debriefing session to share strategies for effective communication and clinical case management and to discuss the ethical issues that arise with these genetic cases.In three years, 60 residents have completed the genetics OSCE program. Evaluation data demonstrate that the program has been effective in both introducing genetic-specific challenges and assessing residents' clinical skills. It has helped trainees self-identify both strengths and further training needs. Pre- and postsurveys among the trainees show increased comfort levels in performing 5 of 12 genetic-related clinical tasks.We conclude that genetics OSCEs are an enriching educational tool. Merely providing trainees and practicing physicians with the latest scientific information is unlikely to prepare them for counseling patients about complex genetic issues. Developing proficiency requires focused practice and effective feedback.This article is part of a theme issue of Academic Medicine on the Title VII health professions training programs.

Genetic programming assisted stochastic optimization strategies for optimization of glucose to gluconic acid fermentation.

PubMed

Cheema, Jitender Jit Singh; Sankpal, Narendra V; Tambe, Sanjeev S; Kulkarni, Bhaskar D

2002-01-01

This article presents two hybrid strategies for the modeling and optimization of the glucose to gluconic acid batch bioprocess. In the hybrid approaches, first a novel artificial intelligence formalism, namely, genetic programming (GP), is used to develop a process model solely from the historic process input-output data. In the next step, the input space of the GP-based model, representing process operating conditions, is optimized using two stochastic optimization (SO) formalisms, viz., genetic algorithms (GAs) and simultaneous perturbation stochastic approximation (SPSA). These SO formalisms possess certain unique advantages over the commonly used gradient-based optimization techniques. The principal advantage of the GP-GA and GP-SPSA hybrid techniques is that process modeling and optimization can be performed exclusively from the process input-output data without invoking the detailed knowledge of the process phenomenology. The GP-GA and GP-SPSA techniques have been employed for modeling and optimization of the glucose to gluconic acid bioprocess, and the optimized process operating conditions obtained thereby have been compared with those obtained using two other hybrid modeling-optimization paradigms integrating artificial neural networks (ANNs) and GA/SPSA formalisms. Finally, the overall optimized operating conditions given by the GP-GA method, when verified experimentally resulted in a significant improvement in the gluconic acid yield. The hybrid strategies presented here are generic in nature and can be employed for modeling and optimization of a wide variety of batch and continuous bioprocesses.

Programming cells by multiplex genome engineering and accelerated evolution.

PubMed

Wang, Harris H; Isaacs, Farren J; Carr, Peter A; Sun, Zachary Z; Xu, George; Forest, Craig R; Church, George M

2009-08-13

The breadth of genomic diversity found among organisms in nature allows populations to adapt to diverse environments. However, genomic diversity is difficult to generate in the laboratory and new phenotypes do not easily arise on practical timescales. Although in vitro and directed evolution methods have created genetic variants with usefully altered phenotypes, these methods are limited to laborious and serial manipulation of single genes and are not used for parallel and continuous directed evolution of gene networks or genomes. Here, we describe multiplex automated genome engineering (MAGE) for large-scale programming and evolution of cells. MAGE simultaneously targets many locations on the chromosome for modification in a single cell or across a population of cells, thus producing combinatorial genomic diversity. Because the process is cyclical and scalable, we constructed prototype devices that automate the MAGE technology to facilitate rapid and continuous generation of a diverse set of genetic changes (mismatches, insertions, deletions). We applied MAGE to optimize the 1-deoxy-D-xylulose-5-phosphate (DXP) biosynthesis pathway in Escherichia coli to overproduce the industrially important isoprenoid lycopene. Twenty-four genetic components in the DXP pathway were modified simultaneously using a complex pool of synthetic DNA, creating over 4.3 billion combinatorial genomic variants per day. We isolated variants with more than fivefold increase in lycopene production within 3 days, a significant improvement over existing metabolic engineering techniques. Our multiplex approach embraces engineering in the context of evolution by expediting the design and evolution of organisms with new and improved properties.

Population Genetics of Schistosoma japonicum within the Philippines Suggest High Levels of Transmission between Humans and Dogs

PubMed Central

Rudge, James W.; Carabin, Hélène; Balolong, Ernesto; Tallo, Veronica; Shrivastava, Jaya; Lu, Da-Bing; Basáñez, María-Gloria; Olveda, Remigio; McGarvey, Stephen T.; Webster, Joanne P.

2008-01-01

Background Schistosoma japonicum, which remains a major public health problem in the Philippines and mainland China, is the only schistosome species for which zoonotic transmission is considered important. While bovines are suspected as the main zoonotic reservoir in parts of China, the relative contributions of various non-human mammals to S. japonicum transmission in the Philippines remain to be determined. We examined the population genetics of S. japonicum in the Philippines in order to elucidate transmission patterns across host species and geographic areas. Methodology/Principal Findings S. japonicum miracidia (hatched from eggs within fecal samples) from humans, dogs, pigs and rats, and cercariae shed from snail-intermediate hosts, were collected across two geographic areas of Samar Province. Individual isolates were then genotyped using seven multiplexed microsatellite loci. Wright's FST values and phylogenetic trees calculated for parasite populations suggest a high frequency of parasite gene-flow across definitive host species, particularly between dogs and humans. Parasite genetic differentiation between areas was not evident at the definitive host level, possibly suggesting frequent import and export of infections between villages, although there was some evidence of geographic structuring at the snail–intermediate host level. Conclusions/Significance These results suggest very high levels of transmission across host species, and indicate that the role of dogs should be considered when planning control programs. Furthermore, a regional approach to treatment programs is recommended where human migration is extensive. PMID:19030225

Landscape genetics of raccoons (Procyon lotor) associated with ridges and valleys of Pennsylvania: implications for oral rabies vaccination programs.

PubMed

Root, J Jeffrey; Puskas, Robert B; Fischer, Justin W; Swope, Craig B; Neubaum, Melissa A; Reeder, Serena A; Piaggio, Antoinette J

2009-12-01

Raccoons are the reservoir for the raccoon rabies virus variant in the United States. To combat this threat, oral rabies vaccination (ORV) programs are conducted in many eastern states. To aid in these efforts, the genetic structure of raccoons (Procyon lotor) was assessed in southwestern Pennsylvania to determine if select geographic features (i.e., ridges and valleys) serve as corridors or hindrances to raccoon gene flow (e.g., movement) and, therefore, rabies virus trafficking in this physiographic region. Raccoon DNA samples (n = 185) were collected from one ridge site and two adjacent valleys in southwestern Pennsylvania (Westmoreland, Cambria, Fayette, and Somerset counties). Raccoon genetic structure within and among these study sites was characterized at nine microsatellite loci. Results indicated that there was little population subdivision among any sites sampled. Furthermore, analyses using a model-based clustering approach indicated one essentially panmictic population was present among all the raccoons sampled over a reasonably broad geographic area (e.g., sites up to 36 km apart). However, a signature of isolation by distance was detected, suggesting that widths of ORV zones are critical for success. Combined, these data indicate that geographic features within this landscape influence raccoon gene flow only to a limited extent, suggesting that ridges of this physiographic system will not provide substantial long-term natural barriers to rabies virus trafficking. These results may be of value for future ORV efforts in Pennsylvania and other eastern states with similar landscapes.

Association Study Reveals Novel Genes Related to Yield and Quality of Fruit in Cape Gooseberry (Physalis peruviana L.).

PubMed

García-Arias, Francy L; Osorio-Guarín, Jaime A; Núñez Zarantes, Victor M

2018-01-01

Association mapping has been proposed as an efficient approach to assist plant breeding programs to investigate the genetic basis of agronomic traits. In this study, we evaluated 18 traits related to yield, (FWP, NF, FWI, and FWII), fruit size-shape (FP, FA, MW, WMH, MH, HMW, DI, FSI, FSII, OVO, OBO), and fruit quality (FIR, CF, and SST), in a diverse collection of 100 accessions of Physalis peruviana including wild, landraces, and anther culture derived lines. We identified seven accessions with suitable traits: fruit weight per plant (FWP) > 7,000 g/plant and cracked fruits (CF) < 4%, to be used as parents in cape gooseberry breeding program. In addition, the accessions were also characterized using Genotyping By Sequencing (GBS). We discovered 27,982 and 36,142 informative SNP markers based on the alignment against the two cape gooseberry references transcriptomes. Besides, 30,344 SNPs were identified based on alignment to the tomato reference genome. Genetic structure analysis showed that the population could be divided into two or three sub-groups, corresponding to landraces-anther culture and wild accessions for K = 2 and wild, landraces, and anther culture plants for K = 3. Association analysis was carried out using a Mixed Linear Model (MLM) and 34 SNP markers were significantly associated. These results reveal the basis of the genetic control of important agronomic traits and may facilitate marker-based breeding in P. peruviana .

Association Study Reveals Novel Genes Related to Yield and Quality of Fruit in Cape Gooseberry (Physalis peruviana L.)

PubMed Central

García-Arias, Francy L.; Osorio-Guarín, Jaime A.; Núñez Zarantes, Victor M.

2018-01-01

Association mapping has been proposed as an efficient approach to assist plant breeding programs to investigate the genetic basis of agronomic traits. In this study, we evaluated 18 traits related to yield, (FWP, NF, FWI, and FWII), fruit size-shape (FP, FA, MW, WMH, MH, HMW, DI, FSI, FSII, OVO, OBO), and fruit quality (FIR, CF, and SST), in a diverse collection of 100 accessions of Physalis peruviana including wild, landraces, and anther culture derived lines. We identified seven accessions with suitable traits: fruit weight per plant (FWP) > 7,000 g/plant and cracked fruits (CF) < 4%, to be used as parents in cape gooseberry breeding program. In addition, the accessions were also characterized using Genotyping By Sequencing (GBS). We discovered 27,982 and 36,142 informative SNP markers based on the alignment against the two cape gooseberry references transcriptomes. Besides, 30,344 SNPs were identified based on alignment to the tomato reference genome. Genetic structure analysis showed that the population could be divided into two or three sub-groups, corresponding to landraces-anther culture and wild accessions for K = 2 and wild, landraces, and anther culture plants for K = 3. Association analysis was carried out using a Mixed Linear Model (MLM) and 34 SNP markers were significantly associated. These results reveal the basis of the genetic control of important agronomic traits and may facilitate marker-based breeding in P. peruviana. PMID:29616069

Development of CACTA transposon derived SCAR markers and their use in population structure analysis in Zea mays.

PubMed

Roy, Neha Samir; Park, Kyong-Cheul; Lee, Sung-Il; Im, Min-Ji; Ramekar, Rahul Vasudeo; Kim, Nam-Soo

2018-02-01

Molecular marker technologies have proven to be an important breakthrough for genetic studies, construction of linkage maps and population genetics analysis. Transposable elements (TEs) constitute major fractions of repetitive sequences in plants and offer a wide range of possible areas to be explored as molecular markers. Sequence characterized amplified region (SCAR) marker development provides us with a simple and time saving alternative approach for marker development. We employed the CACTA-TD to develop SCARs and then integrated them into linkage map and used them for population structure and genetic diversity analysis of corn inbred population. A total of 108 dominant SCAR markers were designed out of which, 32 were successfully integrated in to the linkage map of maize RIL population and the remaining were added to a physical map for references to check the distribution throughout all chromosomes. Moreover, 76 polymorphic SCARs were used for diversity analysis of corn accessions being used in Korean corn breeding program. The overall average polymorphic information content (PIC) was 0.34, expected heterozygosity was 0.324 and Shannon's information index was 0.491 with a percentage of polymorphism of 98.67%. Further analysis by associating with desirable traits may also provide some accurate trait specific tagged SCAR markers. TE linked SCARs can provide an added level of polymorphism as well as improved discriminating ability and therefore can be useful in further breeding programs to develop high yielding germplasm.

User-centered design of multi-gene sequencing panel reports for clinicians.

PubMed

Cutting, Elizabeth; Banchero, Meghan; Beitelshees, Amber L; Cimino, James J; Fiol, Guilherme Del; Gurses, Ayse P; Hoffman, Mark A; Jeng, Linda Jo Bone; Kawamoto, Kensaku; Kelemen, Mark; Pincus, Harold Alan; Shuldiner, Alan R; Williams, Marc S; Pollin, Toni I; Overby, Casey Lynnette

2016-10-01

The objective of this study was to develop a high-fidelity prototype for delivering multi-gene sequencing panel (GS) reports to clinicians that simulates the user experience of a final application. The delivery and use of GS reports can occur within complex and high-paced healthcare environments. We employ a user-centered software design approach in a focus group setting in order to facilitate gathering rich contextual information from a diverse group of stakeholders potentially impacted by the delivery of GS reports relevant to two precision medicine programs at the University of Maryland Medical Center. Responses from focus group sessions were transcribed, coded and analyzed by two team members. Notification mechanisms and information resources preferred by participants from our first phase of focus groups were incorporated into scenarios and the design of a software prototype for delivering GS reports. The goal of our second phase of focus group, to gain input on the prototype software design, was accomplished through conducting task walkthroughs with GS reporting scenarios. Preferences for notification, content and consultation from genetics specialists appeared to depend upon familiarity with scenarios for ordering and delivering GS reports. Despite familiarity with some aspects of the scenarios we proposed, many of our participants agreed that they would likely seek consultation from a genetics specialist after viewing the test reports. In addition, participants offered design and content recommendations. Findings illustrated a need to support customized notification approaches, user-specific information, and access to genetics specialists with GS reports. These design principles can be incorporated into software applications that deliver GS reports. Our user-centered approach to conduct this assessment and the specific input we received from clinicians may also be relevant to others working on similar projects. Copyright © 2016 Elsevier Inc. All rights reserved.

Use of genetic programming, logistic regression, and artificial neural nets to predict readmission after coronary artery bypass surgery.

PubMed

Engoren, Milo; Habib, Robert H; Dooner, John J; Schwann, Thomas A

2013-08-01

As many as 14 % of patients undergoing coronary artery bypass surgery are readmitted within 30 days. Readmission is usually the result of morbidity and may lead to death. The purpose of this study is to develop and compare statistical and genetic programming models to predict readmission. Patients were divided into separate Construction and Validation populations. Using 88 variables, logistic regression, genetic programs, and artificial neural nets were used to develop predictive models. Models were first constructed and tested on the Construction populations, then validated on the Validation population. Areas under the receiver operator characteristic curves (AU ROC) were used to compare the models. Two hundred and two patients (7.6 %) in the 2,644 patient Construction group and 216 (8.0 %) of the 2,711 patient Validation group were re-admitted within 30 days of CABG surgery. Logistic regression predicted readmission with AU ROC = .675 ± .021 in the Construction group. Genetic programs significantly improved the accuracy, AU ROC = .767 ± .001, p < .001). Artificial neural nets were less accurate with AU ROC = 0.597 ± .001 in the Construction group. Predictive accuracy of all three techniques fell in the Validation group. However, the accuracy of genetic programming (AU ROC = .654 ± .001) was still trivially but statistically non-significantly better than that of the logistic regression (AU ROC = .644 ± .020, p = .61). Genetic programming and logistic regression provide alternative methods to predict readmission that are similarly accurate.

National Newborn Screening and Genetics Resource Center

MedlinePlus

... GENERAL INFORMATION Conditions Screened by US Programs General Resources Genetics Birth Defects Hearing Screening FOR PROFESSIONALS ACT Sheets(ACMG) General Resources Newborn Screening Genetics Birth Defects FOR FAMILIES FAQs ...

Historical changes in population structure during rice breeding programs in the northern limits of rice cultivation.

PubMed

Shinada, Hiroshi; Yamamoto, Toshio; Yamamoto, Eiji; Hori, Kiyosumi; Yonemaru, Junichi; Matsuba, Shuichi; Fujino, Kenji

2014-04-01

The rice local population was clearly differentiated into six groups over the 100-year history of rice breeding programs in the northern limit of rice cultivation over the world. Genetic improvements in plant breeding programs in local regions have led to the development of new cultivars with specific agronomic traits under environmental conditions and generated the unique genetic structures of local populations. Understanding historical changes in genome structures and phenotypic characteristics within local populations may be useful for identifying profitable genes and/or genetic resources and the creation of new gene combinations in plant breeding programs. In the present study, historical changes were elucidated in genome structures and phenotypic characteristics during 100-year rice breeding programs in Hokkaido, the northern limit of rice cultivation in the world. We selected 63 rice cultivars to represent the historical diversity of this local population from landraces to the current breeding lines. The results of the phylogenetic analysis demonstrated that these cultivars clearly differentiated into six groups over the history of rice breeding programs. Significant differences among these groups were detected in five of the seven traits, indicating that the differentiation of the Hokkaido rice population into these groups was correlated with these phenotypic changes. These results demonstrated that breeding practices in Hokkaido have created new genetic structures for adaptability to specific environmental conditions and breeding objectives. They also provide a new strategy for rice breeding programs in which such unique genes in local populations in the world can explore the genetic potentials of the local populations.

High genetic diversity of Jatropha curcas assessed by ISSR.

PubMed

Díaz, B G; Argollo, D M; Franco, M C; Nucci, S M; Siqueira, W J; de Laat, D M; Colombo, C A

2017-05-31

Jatropha curcas L. is a highly promising oilseed for sustainable production of biofuels and bio-kerosene due to its high oil content and excellent quality. However, it is a perennial and incipiently domesticated species with none stable cultivar created until now despite genetic breeding programs in progress in several countries. Knowledge of the genetic structure and diversity of the species is a necessary step for breeding programs. The molecular marker can be used as a tool for speed up the process. This study was carried out to assess genetic diversity of a germplasm bank represented by J. curcas accessions from different provenance beside interspecific hybrid and backcrosses generated by IAC breeding programs using inter-simple sequence repeat markers. The molecular study revealed 271 bands of which 98.9% were polymorphic with an average of 22.7 polymorphic bands per primer. Genetic diversity of the germplasm evaluated was slightly higher than other germplasm around the world and ranged from 0.55 to 0.86 with an average of 0.59 (Jaccard index). Cluster analysis (UPGMA) revealed no clear grouping as to the geographical origin of accessions, consistent with genetic structure analysis using the Structure software. For diversity analysis between groups, accessions were divided into eight groups by origin. Nei's genetic distance between groups was 0.14. The results showed the importance of Mexican accessions, congeneric wild species, and interspecific hybrids for conservation and development of new genotypes in breeding programs.

Systems biology: A tool for charting the antiviral landscape.

PubMed

Bowen, James R; Ferris, Martin T; Suthar, Mehul S

2016-06-15

The host antiviral programs that are initiated following viral infection form a dynamic and complex web of responses that we have collectively termed as "the antiviral landscape". Conventional approaches to studying antiviral responses have primarily used reductionist systems to assess the function of a single or a limited subset of molecules. Systems biology is a holistic approach that considers the entire system as a whole, rather than individual components or molecules. Systems biology based approaches facilitate an unbiased and comprehensive analysis of the antiviral landscape, while allowing for the discovery of emergent properties that are missed by conventional approaches. The antiviral landscape can be viewed as a hierarchy of complexity, beginning at the whole organism level and progressing downward to isolated tissues, populations of cells, and single cells. In this review, we will discuss how systems biology has been applied to better understand the antiviral landscape at each of these layers. At the organismal level, the Collaborative Cross is an invaluable genetic resource for assessing how genetic diversity influences the antiviral response. Whole tissue and isolated bulk cell transcriptomics serves as a critical tool for the comprehensive analysis of antiviral responses at both the tissue and cellular levels of complexity. Finally, new techniques in single cell analysis are emerging tools that will revolutionize our understanding of how individual cells within a bulk infected cell population contribute to the overall antiviral landscape. Copyright © 2016 Elsevier B.V. All rights reserved.

Learning directed acyclic graphs from large-scale genomics data.

PubMed

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

2017-09-20

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

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

Nurses' knowledge and educational needs regarding genetics.

PubMed

Seven, Memnun; Akyüz, Aygül; Elbüken, Burcu; Skirton, Heather; Öztürk, Hatice

2015-03-01

Nurses now require a basic knowledge of genetics to provide patient care in a range of settings. To determine Turkish registered nurses' current knowledge and educational needs in relation to genetics. A descriptive, cross-sectional study. Turkish registered nurses working in a university hospital in Turkey were recruited. All registered nurses were invited to participate and 175 completed the study. The survey instrument, basic knowledge of health genetics, confidence in knowledge and the nurses' need for genetics education were used to collect data. The majority (81.1%, n=142) of participants indicated that genetics was not taught during their degree program, although 53.1% to 96% of respondents felt confident in defining different genetic concepts. The average genetics knowledge score was 6.89±1.99 of a possible 11 (range 0-11). The majority (70.3%) expressed a strong wish to attend a continuing nursing education program in genetics. The study shows that although Turkish nurses are not sufficiently knowledgeable to apply genetics in practice, they are willing to have more education to support their care of patients. Nurses need to have more education related to genetics in accordance with advances in human genetics to optimize health care. Copyright © 2014 Elsevier Ltd. All rights reserved.

Assessment of Genetic and Molecular Approaches for the Prediction of Wheat Quality

USDA-ARS?s Scientific Manuscript database

Assessment of genetic and molecular approaches for the prediction of wheat quality. R.A. Graybosch, USDA-ARS, Lincoln, NE, U.S.A. Over the past four decades, the field of plant breeding and genetics has been revolutionized by technological advances in the areas of DNA manipulation and evaluation. Fo...

Genetic polymorphisms to predict gains in maximal O2 uptake and knee peak torque after a high intensity training program in humans.

PubMed

Yoo, Jinho; Kim, Bo-Hyung; Kim, Soo-Hwan; Kim, Yangseok; Yim, Sung-Vin

2016-05-01

The study aimed to identify single nucleotide polymorphisms (SNPs) that significantly influenced the level of improvement of two kinds of training responses, including maximal O2 uptake (V'O2max) and knee peak torque of healthy adults participating in the high intensity training (HIT) program. The study also aimed to use these SNPs to develop prediction models for individual training responses. 79 Healthy volunteers participated in the HIT program. A genome-wide association study, based on 2,391,739 SNPs, was performed to identify SNPs that were significantly associated with gains in V'O2max and knee peak torque, following 9 weeks of the HIT program. To predict two training responses, two independent SNPs sets were determined using linear regression and iterative binary logistic regression analysis. False discovery rate analysis and permutation tests were performed to avoid false-positive findings. To predict gains in V'O2max, 7 SNPs were identified. These SNPs accounted for 26.0 % of the variance in the increment of V'O2max, and discriminated the subjects into three subgroups, non-responders, medium responders, and high responders, with prediction accuracy of 86.1 %. For the knee peak torque, 6 SNPs were identified, and accounted for 27.5 % of the variance in the increment of knee peak torque. The prediction accuracy discriminating the subjects into the three subgroups was estimated as 77.2 %. Novel SNPs found in this study could explain, and predict inter-individual variability in gains of V'O2max, and knee peak torque. Furthermore, with these genetic markers, a methodology suggested in this study provides a sound approach for the personalized training program.

Genetic diversity and differentiation in Prunus species (Rosaceae) using chloroplast and mitochondrial DNA CAPS markers.

PubMed

Ben Mustapha, S; Ben Tamarzizt, H; Baraket, G; Abdallah, D; Salhi Hannachi, A

2015-04-27

Chloroplast (cpDNA) and mitochondrial DNA (mtDNA) were analyzed to establish genetic relationships among Tunisian plum cultivars using the polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) technique. Two mtDNA regions (nad 1 b/c and nad 4 1/2) and a cpDNA region (trnL-trnF) were amplified and digested using restriction enzymes. Seventy and six polymorphic sites were revealed in cpDNA and mtDNA, respectively. As a consequence, cpDNA appears to be more polymorphic than mtDNA. The unweighted pair group method with arithmetic mean (UPGMA) dendrogram showed that accessions were distributed independently of their geographical origin, and introduced and local cultivars appear to be closely related. Both UPGMA and principal component analysis grouped Tunisian plum accessions into similar clusters. The analysis of the pooled sequences allowed the detection of 17 chlorotypes and 12 mitotypes. The unique haplotypes detected for cultivars are valuable for management and preservation of the plum local resources. From this study, PCR-RFLP analysis appears to be a useful approach to detect and identify cytoplasmic variation in plum trees. Our results also provide useful information for the management of genetic resources and to establish a program to improve the genetic resources available for plums.

New biotechnological tools to accelerate scab-resistance trait transfer to apple

PubMed Central

Cusin, Roberta; Revers, Luís Fernando; Maraschin, Felipe dos Santos

2017-01-01

Abstract Apple is a fruit crop cultivated worldwide. Apple orchards are exposed to a diverse set of environmental and biological factors that affect the productivity and sustainability of the culture. Many of the efforts and costs for apple production rely on reducing the incidence of fungal diseases, and one of the main diseases is apple scab caused by the fungus Venturia inaequalis. The economic impact of scab on apple productivity has guided many breeding programs to search for cultivars resistant to apple scab. Introgression from wild relatives has been successful to some extent, and genetic engineering for resistant cultivars has even been employed. This review presents the techniques used to the present time to obtain pathogen-resistant apple cultivars and introduces new biotechnological approaches based on plant plasmids that show promising results for delivering genetic traits with a short-term perspective. PMID:28199444

Automated Design of Quantum Circuits

NASA Technical Reports Server (NTRS)

Williams, Colin P.; Gray, Alexander G.

2000-01-01

In order to design a quantum circuit that performs a desired quantum computation, it is necessary to find a decomposition of the unitary matrix that represents that computation in terms of a sequence of quantum gate operations. To date, such designs have either been found by hand or by exhaustive enumeration of all possible circuit topologies. In this paper we propose an automated approach to quantum circuit design using search heuristics based on principles abstracted from evolutionary genetics, i.e. using a genetic programming algorithm adapted specially for this problem. We demonstrate the method on the task of discovering quantum circuit designs for quantum teleportation. We show that to find a given known circuit design (one which was hand-crafted by a human), the method considers roughly an order of magnitude fewer designs than naive enumeration. In addition, the method finds novel circuit designs superior to those previously known.

Molecular mechanisms of induced pluripotency.

PubMed

Kulcenty, Katarzyna; Wróblewska, Joanna; Mazurek, Sylwia; Liszewska, Ewa; Jaworski, Jacek

2015-01-01

Growing knowledge concerning transcriptional control of cellular pluripotency has led to the discovery that the fate of differentiated cells can be reversed, which has resulted in the generation, by means of genetic manipulation, of induced pluripotent stem cells. Overexpression of just four pluripotency-related transcription factors, namely Oct3/4, Sox2, Klf4, and c-Myc (Yamanaka factors, OKSM), in fibroblasts appears sufficient to produce this new cell type. Currently, we know that these factors induce several changes in genetic program of differentiated cells that can be divided in two general phases: the initial one is stochastic, and the subsequent one is highly hierarchical and organised. This review briefly discusses the molecular events leading to induction of pluripotency in response to forced presence of OKSM factors in somatic cells. We also discuss other reprogramming strategies used thus far as well as the advantages and disadvantages of laboratory approaches towards pluripotency induction in different cell types.

Parallel tagged next-generation sequencing on pooled samples - a new approach for population genetics in ecology and conservation.

PubMed

Zavodna, Monika; Grueber, Catherine E; Gemmell, Neil J

2013-01-01

Next-generation sequencing (NGS) on pooled samples has already been broadly applied in human medical diagnostics and plant and animal breeding. However, thus far it has been only sparingly employed in ecology and conservation, where it may serve as a useful diagnostic tool for rapid assessment of species genetic diversity and structure at the population level. Here we undertake a comprehensive evaluation of the accuracy, practicality and limitations of parallel tagged amplicon NGS on pooled population samples for estimating species population diversity and structure. We obtained 16S and Cyt b data from 20 populations of Leiopelma hochstetteri, a frog species of conservation concern in New Zealand, using two approaches - parallel tagged NGS on pooled population samples and individual Sanger sequenced samples. Data from each approach were then used to estimate two standard population genetic parameters, nucleotide diversity (π) and population differentiation (FST), that enable population genetic inference in a species conservation context. We found a positive correlation between our two approaches for population genetic estimates, showing that the pooled population NGS approach is a reliable, rapid and appropriate method for population genetic inference in an ecological and conservation context. Our experimental design also allowed us to identify both the strengths and weaknesses of the pooled population NGS approach and outline some guidelines and suggestions that might be considered when planning future projects.

Influence of Genetic Counseling Graduate Program Websites on Student Application Decisions.

PubMed

Ivan, Kristina M; Hassed, Susan; Darden, Alix G; Aston, Christopher E; Guy, Carrie

2017-12-01

This study investigated how genetic counseling educational program websites affect application decisions via an online survey sent to current students and recent graduates. Program leadership: directors, assistant directors, associate directors, were also surveyed to determine where their opinions coincided or differed from those reported by students and recent graduates. Chi square analysis and t-tests were used to determine significance of results. A two-sample t-test was used to compare factors students identified as important on a 5-point Likert scale with those identified by directors. Thematic analysis revealed three major themes students consider important for program websites: easy navigation, website content, and website impression. Directors were interested in how prospective students use their program website and what information they found most useful. Students indicated there were specific programs they chose not to apply to due to the difficulty of using the website for that program. Directors significantly underestimated how important information about application requirements was to students in making application decisions. The information reported herein will help individual genetic counseling graduate programs improve website functionality and retain interested applicants.

CAR T-cell immunotherapy: The path from the by-road to the freeway?

PubMed

Whilding, Lynsey M; Maher, John

2015-12-01

Chimeric antigen receptors are genetically encoded artificial fusion molecules that can re-program the specificity of peripheral blood polyclonal T-cells against a selected cell surface target. Unparallelled clinical efficacy has recently been demonstrated using this approach to treat patients with refractory B-cell malignancy. However, the approach is technically challenging and can elicit severe toxicity in patients. Moreover, solid tumours have largely proven refractory to this approach. In this review, we describe the important structural features of CARs and how this may influence function. Emerging clinical experience is summarized in both solid tumours and haematological malignancies. Finally, we consider the particular challenges imposed by solid tumours to the successful development of CAR T-cell immunotherapy, together with a number of innovative strategies that have been developed in an effort to reverse the balance in favour of therapeutic benefit. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

Connecting the dots between genes, biochemistry, and disease susceptibility: systems biology modeling in human genetics.

PubMed

Moore, Jason H; Boczko, Erik M; Summar, Marshall L

2005-02-01

Understanding how DNA sequence variations impact human health through a hierarchy of biochemical and physiological systems is expected to improve the diagnosis, prevention, and treatment of common, complex human diseases. We have previously developed a hierarchical dynamic systems approach based on Petri nets for generating biochemical network models that are consistent with genetic models of disease susceptibility. This modeling approach uses an evolutionary computation approach called grammatical evolution as a search strategy for optimal Petri net models. We have previously demonstrated that this approach routinely identifies biochemical network models that are consistent with a variety of genetic models in which disease susceptibility is determined by nonlinear interactions between two or more DNA sequence variations. We review here this approach and then discuss how it can be used to model biochemical and metabolic data in the context of genetic studies of human disease susceptibility.

Programming languages for circuit design.

PubMed

Pedersen, Michael; Yordanov, Boyan

2015-01-01

This chapter provides an overview of a programming language for Genetic Engineering of Cells (GEC). A GEC program specifies a genetic circuit at a high level of abstraction through constraints on otherwise unspecified DNA parts. The GEC compiler then selects parts which satisfy the constraints from a given parts database. GEC further provides more conventional programming language constructs for abstraction, e.g., through modularity. The GEC language and compiler is available through a Web tool which also provides functionality, e.g., for simulation of designed circuits.

Integrative Approaches to Understanding the Pathogenic Role of Genetic Variation in Rheumatic Diseases.

PubMed

Laufer, Vincent A; Chen, Jake Y; Langefeld, Carl D; Bridges, S Louis

2017-08-01

The use of high-throughput omics may help to understand the contribution of genetic variants to the pathogenesis of rheumatic diseases. We discuss the concept of missing heritability: that genetic variants do not explain the heritability of rheumatoid arthritis and related rheumatologic conditions. In addition to an overview of how integrative data analysis can lead to novel insights into mechanisms of rheumatic diseases, we describe statistical approaches to prioritizing genetic variants for future functional analyses. We illustrate how analyses of large datasets provide hope for improved approaches to the diagnosis, treatment, and prevention of rheumatic diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Cancer heterogeneity: origins and implications for genetic association studies

PubMed Central

Urbach, Davnah; Lupien, Mathieu; Karagas, Margaret R.; Moore, Jason H.

2012-01-01

Genetic association studies have become standard approaches to characterize the genetic and epigenetic variability associated with cancer development, including predispositions and mutations. However, the bewildering genetic and phenotypic heterogeneity inherent in cancer both magnifies the conceptual and methodological problems associated with these approaches and renders the translation of available genetic information into a knowledge that is both biologically sound and clinically relevant difficult. Here, we elaborate on the underlying causes of this complexity, illustrate why it represents a challenge for genetic association studies, and briefly discuss how it can be reconciled with the ultimate goal of identifying targetable disease pathways and successfully treating individual patients. PMID:22858414

Genetic heterogeneity in autism: From single gene to a pathway perspective.

PubMed

An, Joon Yong; Claudianos, Charles

2016-09-01

The extreme genetic heterogeneity of autism spectrum disorder (ASD) represents a major challenge. Recent advances in genetic screening and systems biology approaches have extended our knowledge of the genetic etiology of ASD. In this review, we discuss the paradigm shift from a single gene causation model to pathway perturbation model as a guide to better understand the pathophysiology of ASD. We discuss recent genetic findings obtained through next-generation sequencing (NGS) and examine various integrative analyses using systems biology and complex networks approaches that identify convergent patterns of genetic elements associated with ASD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Drug discovery and development for rare genetic disorders.

PubMed

Sun, Wei; Zheng, Wei; Simeonov, Anton

2017-09-01

Approximately 7,000 rare diseases affect millions of individuals in the United States. Although rare diseases taken together have an enormous impact, there is a significant gap between basic research and clinical interventions. Opportunities now exist to accelerate drug development for the treatment of rare diseases. Disease foundations and research centers worldwide focus on better understanding rare disorders. Here, the state-of-the-art drug discovery strategies for small molecules and biological approaches for orphan diseases are reviewed. Rare diseases are usually genetic diseases; hence, employing pharmacogenetics to develop treatments and using whole genome sequencing to identify the etiologies for such diseases are appropriate strategies to exploit. Beginning with high throughput screening of small molecules, the benefits and challenges of target-based and phenotypic screens are discussed. Explanations and examples of drug repurposing are given; drug repurposing as an approach to quickly move programs to clinical trials is evaluated. Consideration is given to the category of biologics which include gene therapy, recombinant proteins, and autologous transplants. Disease models, including animal models and induced pluripotent stem cells (iPSCs) derived from patients, are surveyed. Finally, the role of biomarkers in drug discovery and development, as well as clinical trials, is elucidated. © 2017 Wiley Periodicals, Inc.

Mammalian monogamy is not controlled by a single gene

PubMed Central

Fink, Sabine; Excoffier, Laurent; Heckel, Gerald

2006-01-01

Complex social behavior in Microtus voles and other mammals has been postulated to be under the direct genetic control of a single locus: the arginine vasopressin 1a receptor (avpr1a) gene. Using a phylogenetic approach, we show that a repetitive element in the promoter region of avpr1a, which reportedly causes social monogamy, is actually widespread in nonmonogamous Microtus and other rodents. There was no evidence for intraspecific polymorphism in regard to the presence or absence of the repetitive element. Among 25 rodent species studied, the element was absent in only two closely related nonmonogamous species, indicating that this absence is certainly the result of an evolutionarily recent loss. Our analyses further demonstrate that the repetitive structures upstream of the avpr1a gene in humans and primates, which have been associated with social bonding, are evolutionarily distinct from those in rodents. Our evolutionary approach reveals that monogamy in rodents is not controlled by a single polymorphism in the promoter region of the avpr1a gene. We thus resolve the contradiction between the claims for an evolutionarily conserved genetic programming of social behavior in mammals and the vast evidence for highly complex and flexible mating systems. PMID:16832060

Teaching Molecular Biology with Microcomputers.

ERIC Educational Resources Information Center

Reiss, Rebecca; Jameson, David

1984-01-01

Describes a series of computer programs that use simulation and gaming techniques to present the basic principles of the central dogma of molecular genetics, mutation, and the genetic code. A history of discoveries in molecular biology is presented and the evolution of these computer assisted instructional programs is described. (MBR)

[Risk/protective factors and prevention programs for drug dependence in Peru].

PubMed

Cabanillas-Rojas, William

2012-03-01

Risk/ protective factors (RPF) are main elements for the analysis, understanding and formulation of answers for the prevention of drug dependences. The objective of this article is to present a literature review about the RPF and their implications in the design of preventive programs. It will focus on individual (genetic aspects, early experiences and psicosocial skills), family (parental control and monitoring, permissiveness, parenting styles), peer (group pressure and social norms) and communitarian (disorganization) RPF. On the other hand, the need of incorporating a multifactor conceptual framework for the preventive approach to drug dependences, articulating the intervention spaces (school, family and community), assuming and evolving perspective allowing the implementations of sustained actions is evidenced. On top, the implications for future research and public policy formulation are discussed.

Postdoctoral Fellow | Center for Cancer Research

Cancer.gov

The Genetics of Cancer Susceptibility Section in the Mouse Cancer Genetics Program at NCI is seeking a highly motivated postdoctoral researcher to identify novel genetic interactors of BRCA2 using CRISPR-based genetic screen in mouse embryonic stem cells and perform functional studies in mouse models.

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

USDA-ARS?s Scientific Manuscript database

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

Quality assurance and quality improvement in U.S. clinical molecular genetic laboratories.

PubMed

Chen, Bin; Richards, C Sue; Wilson, Jean Amos; Lyon, Elaine

2011-04-01

A robust quality-assurance program is essential for laboratories that perform molecular genetic testing to maintain high-quality testing and be able to address challenges associated with performance or delivery of testing services as the use of molecular genetic tests continues to expand in clinical and public health practice. This unit discusses quality-assurance and quality-improvement considerations that are critical for molecular genetic testing performed for heritable diseases and conditions. Specific discussion is provided on applying regulatory standards and best practices in establishing/verifying test performance, ensuring quality of the total testing process, monitoring and maintaining personnel competency, and continuing quality improvement. The unit provides a practical reference for laboratory professionals to use in recognizing and addressing essential quality-assurance issues in human molecular genetic testing. It should also provide useful information for genetics researchers, trainees, and fellows in human genetics training programs, as well as others who are interested in quality assurance and quality improvement for molecular genetic testing. 2011 by John Wiley & Sons, Inc.

Anaerobic Catabolism of Aromatic Compounds: a Genetic and Genomic View

PubMed Central

Carmona, Manuel; Zamarro, María Teresa; Blázquez, Blas; Durante-Rodríguez, Gonzalo; Juárez, Javier F.; Valderrama, J. Andrés; Barragán, María J. L.; García, José Luis; Díaz, Eduardo

2009-01-01

Summary: Aromatic compounds belong to one of the most widely distributed classes of organic compounds in nature, and a significant number of xenobiotics belong to this family of compounds. Since many habitats containing large amounts of aromatic compounds are often anoxic, the anaerobic catabolism of aromatic compounds by microorganisms becomes crucial in biogeochemical cycles and in the sustainable development of the biosphere. The mineralization of aromatic compounds by facultative or obligate anaerobic bacteria can be coupled to anaerobic respiration with a variety of electron acceptors as well as to fermentation and anoxygenic photosynthesis. Since the redox potential of the electron-accepting system dictates the degradative strategy, there is wide biochemical diversity among anaerobic aromatic degraders. However, the genetic determinants of all these processes and the mechanisms involved in their regulation are much less studied. This review focuses on the recent findings that standard molecular biology approaches together with new high-throughput technologies (e.g., genome sequencing, transcriptomics, proteomics, and metagenomics) have provided regarding the genetics, regulation, ecophysiology, and evolution of anaerobic aromatic degradation pathways. These studies revealed that the anaerobic catabolism of aromatic compounds is more diverse and widespread than previously thought, and the complex metabolic and stress programs associated with the use of aromatic compounds under anaerobic conditions are starting to be unraveled. Anaerobic biotransformation processes based on unprecedented enzymes and pathways with novel metabolic capabilities, as well as the design of novel regulatory circuits and catabolic networks of great biotechnological potential in synthetic biology, are now feasible to approach. PMID:19258534

Addressing consumer grievances in medicine: policies and practices of newborn screening programs in the United States.

PubMed

Natowicz, Marvin R; Hiller, Elaine H

2002-01-01

Newborn screening programs collectively administer the largest genetic testing initiative in the United States. The redress of grievances is an important mechanism for consumers to provide input into clinical and public health programs. In this study, we evaluated mechanisms for addressing consumer grievances in newborn screening programs. To do this, we surveyed all 50 state plus the District of Columbia newborn screening programs by questionnaire regarding protocols for receipt and redress of problems reported by parents of newborns and ascertained the existence and nature of complaints and how complaints were documented and addressed. Pertinent state and federal legislation and regulation were also reviewed. Six of 49 newborn screening programs reported having formal policies for handling consumer grievances. Four states reported having pertinent legislation or regulation. Thirty-eight of 49 states reported having received complaints from 1993 to 1995. Thirteen of 49 newborn screening programs reported that they actively seek feedback from consumers. Consumer grievances ranged from minor complaints to potentially life-threatening concerns. In general, complaints are managed on an ad hoc basis; formal policies are typically lacking. As newborn screening programs affect a vast number of Americans, a proactive and comprehensive approach, including solicitation of consumer feedback, could benefit both newborn screening programs and the public served by them.

Genetic Toxicology in the 21st Century: Reflections and Future Directions

PubMed Central

Mahadevan, Brinda; Snyder, Ronald D.; Waters, Michael D.; Benz, R. Daniel; Kemper, Raymond A.; Tice, Raymond R.; Richard, Ann M.

2011-01-01

A symposium at the 40th anniversary of the Environmental Mutagen Society, held from October 24–28, 2009 in St. Louis, MO, surveyed the current status and future directions of genetic toxicology. This article summarizes the presentations and provides a perspective on the future. An abbreviated history is presented, highlighting the current standard battery of genotoxicity assays and persistent challenges. Application of computational toxicology to safety testing within a regulatory setting is discussed as a means for reducing the need for animal testing and human clinical trials, and current approaches and applications of in silico genotoxicity screening approaches across the pharmaceutical industry were surveyed and are reported here. The expanded use of toxicogenomics to illuminate mechanisms and bridge genotoxicity and carcinogenicity, and new public efforts to use high-throughput screening technologies to address lack of toxicity evaluation for the backlog of thousands of industrial chemicals in the environment are detailed. The Tox21 project involves coordinated efforts of four U.S. Government regulatory/research entities to use new and innovative assays to characterize key steps in toxicity pathways, including genotoxic and nongenotoxic mechanisms for carcinogenesis. Progress to date, highlighting preliminary test results from the National Toxicology Program is summarized. Finally, an overview is presented of ToxCast™, a related research program of the U.S. Environmental Protection Agency, using a broad array of high throughput and high content technologies for toxicity profiling of environmental chemicals, and computational toxicology modeling. Progress and challenges, including the pressing need to incorporate metabolic activation capability, are summarized. PMID:21538556

On safari to Random Jungle: a fast implementation of Random Forests for high-dimensional data

PubMed Central

Schwarz, Daniel F.; König, Inke R.; Ziegler, Andreas

2010-01-01

Motivation: Genome-wide association (GWA) studies have proven to be a successful approach for helping unravel the genetic basis of complex genetic diseases. However, the identified associations are not well suited for disease prediction, and only a modest portion of the heritability can be explained for most diseases, such as Type 2 diabetes or Crohn's disease. This may partly be due to the low power of standard statistical approaches to detect gene–gene and gene–environment interactions when small marginal effects are present. A promising alternative is Random Forests, which have already been successfully applied in candidate gene analyses. Important single nucleotide polymorphisms are detected by permutation importance measures. To this day, the application to GWA data was highly cumbersome with existing implementations because of the high computational burden. Results: Here, we present the new freely available software package Random Jungle (RJ), which facilitates the rapid analysis of GWA data. The program yields valid results and computes up to 159 times faster than the fastest alternative implementation, while still maintaining all options of other programs. Specifically, it offers the different permutation importance measures available. It includes new options such as the backward elimination method. We illustrate the application of RJ to a GWA of Crohn's disease. The most important single nucleotide polymorphisms (SNPs) validate recent findings in the literature and reveal potential interactions. Availability: The RJ software package is freely available at http://www.randomjungle.org Contact: inke.koenig@imbs.uni-luebeck.de; ziegler@imbs.uni-luebeck.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20505004

Food control and a citizen science approach for improving teaching of Genetics in universities.

PubMed

Borrell, Y J; Muñoz-Colmenero, A M; Dopico, E; Miralles, L; Garcia-Vazquez, E

2016-09-10

A Citizen Science approach was implemented in the laboratory practices of Genetics at the University of Oviedo, related with the engaging topic of Food Control. Real samples of food products consumed by students at home (students as samplers) were employed as teaching material in three different courses of Genetics during the academic year 2014-2015: Experimental Methods in Food Production (MBTA) (Master level), and Applied Molecular Biology (BMA) and Conservation Genetics and Breeding (COMGE) (Bachelor/Degree level). Molecular genetics based on PCR amplification of DNA markers was employed for species identification of 22 seafood products in COMGE and MBTA, and for detection of genetically modified (GM) maize from nine products in BMA. In total six seafood products incorrectly labeled (27%), and two undeclared GM maize (22%) were found. A post-Laboratory survey was applied for assessing the efficacy of the approach for improving motivation in the Laboratory Practices of Genetics. Results confirmed that students that worked on their own samples from local markets were significantly more motivated and better evaluated their Genetic laboratory practices than control students (χ(2)  = 12.11 p = 0.033). Our results suggest that citizen science approaches could not be only useful for improving teaching of Genetics in universities but also to incorporate students and citizens as active agents in food control. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(5):450-462, 2016. © 2016 The International Union of Biochemistry and Molecular Biology.

Genetics of Resistant Hypertension: the Missing Heritability and Opportunities.

PubMed

Teixeira, Samantha K; Pereira, Alexandre C; Krieger, Jose E

2018-05-19

Blood pressure regulation in humans has long been known to be a genetically determined trait. The identification of causal genetic modulators for this trait has been unfulfilling at the least. Despite the recent advances of genome-wide genetic studies, loci associated with hypertension or blood pressure still explain a very low percentage of the overall variation of blood pressure in the general population. This has precluded the translation of discoveries in the genetics of human hypertension to clinical use. Here, we propose the combined use of resistant hypertension as a trait for mapping genetic determinants in humans and the integration of new large-scale technologies to approach in model systems the multidimensional nature of the problem. New large-scale efforts in the genetic and genomic arenas are paving the way for an increased and granular understanding of genetic determinants of hypertension. New technologies for whole genome sequence and large-scale forward genetic screens can help prioritize gene and gene-pathways for downstream characterization and large-scale population studies, and guided pharmacological design can be used to drive discoveries to the translational application through better risk stratification and new therapeutic approaches. Although significant challenges remain in the mapping and identification of genetic determinants of hypertension, new large-scale technological approaches have been proposed to surpass some of the shortcomings that have limited progress in the area for the last three decades. The incorporation of these technologies to hypertension research may significantly help in the understanding of inter-individual blood pressure variation and the deployment of new phenotyping and treatment approaches for the condition.

Genetic diversity and differentiation of exotic and American commercial cattle breeds raised in Brazil.

PubMed

Brasil, B S A F; Coelho, E G A; Drummond, M G; Oliveira, D A A

2013-11-18

The Brazilian cattle population is mainly composed of breeds of zebuine origin and their American derivatives. Comprehensive knowledge about the genetic diversity of these populations is fundamental for animal breeding programs and the conservation of genetic resources. This study aimed to assess the phylogenetic relationships, levels of genetic diversity, and patterns of taurine/zebuine admixture among 9 commercial cattle breeds raised in Brazil. Analysis of DNA polymorphisms was performed on 2965 animals using the 11 microsatellite markers recommended by the International Society of Animal Genetics. High genetic diversity was detected in all breeds, even though significant inbreeding was observed within some. Differences among the breeds accounted for 14.72% of the total genetic variability, and genetic differentiation was higher among taurine than among zebuine cattle. Of note, Nelore cattle presented with high levels of admixture, which is consistent with the history of frequent gene flow during the establishment of this breed in Brazil. Furthermore, significant genetic variability was partitioned within the commercial cattle breeds formed in America, which, therefore, comprise important resources of genetic diversity in the tropics. The genetic characterization of these important Brazilian breeds may now facilitate the development of management and breeding programs for these populations.

Genetic Testing: How Genetics and Genomics Can Affect Healthcare Disparities
.

PubMed

Allen, Deborah

2018-02-01

Advances in oncology care have transformed treatment approaches as genetics and genomics analyses promote implementation of personalized medicine. Genetics and genomics research in TP53 have demonstrated that some mutations are prevalent in minority populations. This has implications on personalized treatment approaches, particularly in early disease stages. The purpose of this article is to describe oncology nurses' role in applying these findings in practice to reduce disparities observed in cancer and survivorship care.
.

Privacy preserving protocol for detecting genetic relatives using rare variants.

PubMed

Hormozdiari, Farhad; Joo, Jong Wha J; Wadia, Akshay; Guan, Feng; Ostrosky, Rafail; Sahai, Amit; Eskin, Eleazar

2014-06-15

High-throughput sequencing technologies have impacted many areas of genetic research. One such area is the identification of relatives from genetic data. The standard approach for the identification of genetic relatives collects the genomic data of all individuals and stores it in a database. Then, each pair of individuals is compared to detect the set of genetic relatives, and the matched individuals are informed. The main drawback of this approach is the requirement of sharing your genetic data with a trusted third party to perform the relatedness test. In this work, we propose a secure protocol to detect the genetic relatives from sequencing data while not exposing any information about their genomes. We assume that individuals have access to their genome sequences but do not want to share their genomes with anyone else. Unlike previous approaches, our approach uses both common and rare variants which provide the ability to detect much more distant relationships securely. We use a simulated data generated from the 1000 genomes data and illustrate that we can easily detect up to fifth degree cousins which was not possible using the existing methods. We also show in the 1000 genomes data with cryptic relationships that our method can detect these individuals. The software is freely available for download at http://genetics.cs.ucla.edu/crypto/. © The Author 2014. Published by Oxford University Press.

Comparison of weighting approaches for genetic risk scores in gene-environment interaction studies.

PubMed

Hüls, Anke; Krämer, Ursula; Carlsten, Christopher; Schikowski, Tamara; Ickstadt, Katja; Schwender, Holger

2017-12-16

Weighted genetic risk scores (GRS), defined as weighted sums of risk alleles of single nucleotide polymorphisms (SNPs), are statistically powerful for detection gene-environment (GxE) interactions. To assign weights, the gold standard is to use external weights from an independent study. However, appropriate external weights are not always available. In such situations and in the presence of predominant marginal genetic effects, we have shown in a previous study that GRS with internal weights from marginal genetic effects ("GRS-marginal-internal") are a powerful and reliable alternative to single SNP approaches or the use of unweighted GRS. However, this approach might not be appropriate for detecting predominant interactions, i.e. interactions showing an effect stronger than the marginal genetic effect. In this paper, we present a weighting approach for such predominant interactions ("GRS-interaction-training") in which parts of the data are used to estimate the weights from the interaction terms and the remaining data are used to determine the GRS. We conducted a simulation study for the detection of GxE interactions in which we evaluated power, type I error and sign-misspecification. We compared this new weighting approach to the GRS-marginal-internal approach and to GRS with external weights. Our simulation study showed that in the absence of external weights and with predominant interaction effects, the highest power was reached with the GRS-interaction-training approach. If marginal genetic effects were predominant, the GRS-marginal-internal approach was more appropriate. Furthermore, the power to detect interactions reached by the GRS-interaction-training approach was only slightly lower than the power achieved by GRS with external weights. The power of the GRS-interaction-training approach was confirmed in a real data application to the Traffic, Asthma and Genetics (TAG) Study (N = 4465 observations). When appropriate external weights are unavailable, we recommend to use internal weights from the study population itself to construct weighted GRS for GxE interaction studies. If the SNPs were chosen because a strong marginal genetic effect was hypothesized, GRS-marginal-internal should be used. If the SNPs were chosen because of their collective impact on the biological mechanisms mediating the environmental effect (hypothesis of predominant interactions) GRS-interaction-training should be applied.

Integrated Module and Gene-Specific Regulatory Inference Implicates Upstream Signaling Networks

PubMed Central

Roy, Sushmita; Lagree, Stephen; Hou, Zhonggang; Thomson, James A.; Stewart, Ron; Gasch, Audrey P.

2013-01-01

Regulatory networks that control gene expression are important in diverse biological contexts including stress response and development. Each gene's regulatory program is determined by module-level regulation (e.g. co-regulation via the same signaling system), as well as gene-specific determinants that can fine-tune expression. We present a novel approach, Modular regulatory network learning with per gene information (MERLIN), that infers regulatory programs for individual genes while probabilistically constraining these programs to reveal module-level organization of regulatory networks. Using edge-, regulator- and module-based comparisons of simulated networks of known ground truth, we find MERLIN reconstructs regulatory programs of individual genes as well or better than existing approaches of network reconstruction, while additionally identifying modular organization of the regulatory networks. We use MERLIN to dissect global transcriptional behavior in two biological contexts: yeast stress response and human embryonic stem cell differentiation. Regulatory modules inferred by MERLIN capture co-regulatory relationships between signaling proteins and downstream transcription factors thereby revealing the upstream signaling systems controlling transcriptional responses. The inferred networks are enriched for regulators with genetic or physical interactions, supporting the inference, and identify modules of functionally related genes bound by the same transcriptional regulators. Our method combines the strengths of per-gene and per-module methods to reveal new insights into transcriptional regulation in stress and development. PMID:24146602

Comparative Approaches to Genetic Discrimination: Chasing Shadows?

PubMed

Joly, Yann; Feze, Ida Ngueng; Song, Lingqiao; Knoppers, Bartha M

2017-05-01

Genetic discrimination (GD) is one of the most pervasive issues associated with genetic research and its large-scale implementation. An increasing number of countries have adopted public policies to address this issue. Our research presents a worldwide comparative review and typology of these approaches. We conclude with suggestions for public policy development. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inferences of Recent and Ancient Human Population History Using Genetic and Non-Genetic Data

ERIC Educational Resources Information Center

Kitchen, Andrew

2008-01-01

I have adopted complementary approaches to inferring human demographic history utilizing human and non-human genetic data as well as cultural data. These complementary approaches form an interdisciplinary perspective that allows one to make inferences of human history at varying timescales, from the events that occurred tens of thousands of years…

Food Control and a Citizen Science Approach for Improving Teaching of Genetics in Universities

ERIC Educational Resources Information Center

Borrell, Y. J.; Muñoz-Colmenero, A. M.; Dopico, E.; Miralles, L.; Garcia-Vazquez, E.

2016-01-01

A Citizen Science approach was implemented in the laboratory practices of Genetics at the University of Oviedo, related with the engaging topic of Food Control. Real samples of food products consumed by students at home ("students as samplers") were employed as teaching material in three different courses of Genetics during the academic…

USDA forest service southern region – It’s all about GRITS

Treesearch

Barbara S. Crane; Kevin M. Potter

2017-01-01

Genetic resource management programs across the U.S. Department of Agriculture Forest Service (USDA FS) play a key role in supporting successful land management activities. The programs are responsible for developing and providing plant material for revegetation, seed management guidelines, emergency fire recovery assistance, genetic conservation strategies, climate...

A Microcomputer Exercise on Genetic Transcription and Translation.

ERIC Educational Resources Information Center

Meisenheimer, John L.

1985-01-01

Describes a microcomputer program (written for the Apple II+) which can serve as a lecture demonstration aid in explaining genetic transcription and translation. The program provides unemotional information on student errors, thus serving as a review drill to supplement the classroom. Student participation and instructor options are discussed. (DH)

Initial experiences utilizing exotic landrace germplasm in an upland cotton breeding program

USDA-ARS?s Scientific Manuscript database

A critical objective of plant breeding programs is accessing new sources of genetic variation. In upland cotton, one of the relatively untapped sources of genetic variation is maintained in the USDA-ARS cotton germplasm collection and is the exotic landrace collection. Photoperiod sensitivity is a m...

Information Business: Applying Infometry (Informational Geometry) in Cognitive Coordination and Genetic Programming for Electronic Information Packaging and Marketing.

ERIC Educational Resources Information Center

Tsai, Bor-sheng

1994-01-01

Describes the use of infometry, or informational geometry, to meet the challenges of information service businesses. Highlights include theoretical models for cognitive coordination and genetic programming; electronic information packaging; marketing electronic information products, including cost-benefit analyses; and recapitalization, including…

Genetics in Relation to Biology.

ERIC Educational Resources Information Center

Stewart, J. Bird

1987-01-01

Claims that most instruction dealing with genetics is limited to sex education and personal hygiene. Suggests that the biology curriculum should begin to deal with other issues related to genetics, including genetic normality, prenatal diagnoses, race, and intelligence. Predicts these topics will begin to appear in British examination programs.…

Application of Genetic/Genomic Approaches to Allergic Disorders

PubMed Central

Baye, Tesfaye M.; Martin, Lisa J.; Khurana Hershey, Gurjit K.

2010-01-01

Completion of the human genome project and rapid progress in genetics and bioinformatics have enabled the development of large public databases, which include genetic and genomic data linked to clinical health data. With the massive amount of information available, clinicians and researchers have the unique opportunity to complement and integrate their daily practice with the existing resources to clarify the underlying etiology of complex phenotypes such as allergic diseases. The genome itself is now often utilized as a starting point for many studies and multiple innovative approaches have emerged applying genetic/genomic strategies to key questions in the field of allergy and immunology. There have been several successes, which have uncovered new insights into the biologic underpinnings of allergic disorders. Herein, we will provide an in depth review of genomic approaches to identifying genes and biologic networks involved in allergic diseases. We will discuss genetic and phenotypic variation, statistical approaches for gene discovery, public databases, functional genomics, clinical implications, and the challenges that remain. PMID:20638111

Genetic approaches for the study of PTSD: Advances and challenges

PubMed Central

Banerjee, Sunayana B.; Morrison, Filomene G.; Ressler, Kerry J.

2017-01-01

Post-traumatic stress disorder (PTSD) is a highly debilitating stress and anxiety-related disorder that occurs in response to specific trauma or abuse. Genetic risk factors may account for up to 30–40% of the heritability of PTSD. Understanding the gene pathways that are associated with PTSD, and how those genes interact with the fear and stress circuitry to mediate risk and resilience for PTSD will enable the development of targeted therapies to prevent the occurrence of or decrease the severity of this complex multi-gene disorder. This review will summarize recent research on genetic approaches to understanding PTSD risk and resilience in human populations, including candidate genes and their epigenetic modifications, genome-wide association studies and neural imaging genetics approaches. Despite challenges faced within this field of study such as inconsistent results and replications, genetic approaches still offer exciting opportunities for the identification and development of novel therapeutic targets and therapies in the future. PMID:28242325

An integrative, translational approach to understanding rare and orphan genetically based diseases

PubMed Central

Hoehndorf, Robert; Schofield, Paul N.; Gkoutos, Georgios V.

2013-01-01

PhenomeNet is an approach for integrating phenotypes across species and identifying candidate genes for genetic diseases based on the similarity between a disease and animal model phenotypes. In contrast to ‘guilt-by-association’ approaches, PhenomeNet relies exclusively on the comparison of phenotypes to suggest candidate genes, and can, therefore, be applied to study the molecular basis of rare and orphan diseases for which the molecular basis is unknown. In addition to disease phenotypes from the Online Mendelian Inheritance in Man (OMIM) database, we have now integrated the clinical signs from Orphanet into PhenomeNet. We demonstrate that our approach can efficiently identify known candidate genes for genetic diseases in Orphanet and OMIM. Furthermore, we find evidence that mutations in the HIP1 gene might cause Bassoe syndrome, a rare disorder with unknown genetic aetiology. Our results demonstrate that integration and computational analysis of human disease and animal model phenotypes using PhenomeNet has the potential to reveal novel insights into the pathobiology underlying genetic diseases. PMID:23853703

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

Waters, M.D.; Stack, H.F.; Garrett, N.E.

A graphic approach, terms a Genetic Activity Profile (GAP), was developed to display a matrix of data on the genetic and related effects of selected chemical agents. The profiles provide a visual overview of the quantitative (doses) and qualitative (test results) data for each chemical. Either the lowest effective dose or highest ineffective dose is recorded for each agent and bioassay. Up to 200 different test systems are represented across the GAP. Bioassay systems are organized according to the phylogeny of the test organisms and the end points of genetic activity. The methodology for producing and evaluating genetic activity profilemore » was developed in collaboration with the International Agency for Research on Cancer (IARC). Data on individual chemicals were compiles by IARC and by the US Environmental Protection Agency (EPA). Data are available on 343 compounds selected from volumes 1-53 of the IARC Monographs and on 115 compounds identified as Superfund Priority Substances. Software to display the GAPs on an IBM-compatible personal computer is available from the authors. Structurally similar compounds frequently display qualitatively and quantitatively similar profiles of genetic activity. Through examination of the patterns of GAPs of pairs and groups of chemicals, it is possible to make more informed decisions regarding the selection of test batteries to be used in evaluation of chemical analogs. GAPs provided useful data for development of weight-of-evidence hazard ranking schemes. Also, some knowledge of the potential genetic activity of complex environmental mixtures may be gained from an assessment of the genetic activity profiles of component chemicals. The fundamental techniques and computer programs devised for the GAP database may be used to develop similar databases in other disciplines. 36 refs., 2 figs.« less

Population Genetics of Plasmodium vivax in Four Rural Communities in Central Vietnam

PubMed Central

Hong, Nguyen Van; Delgado-Ratto, Christopher; Thanh, Pham Vinh; Van den Eede, Peter; Guetens, Pieter; Binh, Nguyen Thi Huong; Phuc, Bui Quang; Duong, Tran Thanh; Van Geertruyden, Jean Pierre; D’Alessandro, Umberto; Erhart, Annette; Rosanas-Urgell, Anna

2016-01-01

Background The burden of malaria in Vietnam has drastically reduced, prompting the National Malaria Control Program to officially engage in elimination efforts. Plasmodium vivax is becoming increasingly prevalent, remaining a major problem in the country's central and southern provinces. A better understanding of P. vivax genetic diversity and structure of local parasite populations will provide baseline data for the evaluation and improvement of current efforts for control and elimination. The aim of this study was to examine the population genetics and structure of P. vivax isolates from four communities in Tra Leng commune, Nam Tra My district in Quang Nam, Central Vietnam. Methodology/Principal Findings P. vivax mono infections collected from 234 individuals between April 2009 and December 2010 were successfully analyzed using a panel of 14 microsatellite markers. Isolates displayed moderate genetic diversity (He = 0.68), with no significant differences between study communities. Polyclonal infections were frequent (71.4%) with a mean multiplicity of infection of 1.91 isolates/person. Low but significant genetic differentiation (FST value from -0.05 to 0.18) was observed between the community across the river and the other communities. Strong linkage disequilibrium (IAS = 0.113, p < 0.001) was detected across all communities, suggesting gene flow within and among them. Using multiple approaches, 101 haplotypes were grouped into two genetic clusters, while 60.4% of haplotypes were admixed. Conclusions/Significance In this area of Central Vietnam, where malaria transmission has decreased significantly over the past decade, there was moderate genetic diversity and high occurrence of polyclonal infections. Local human populations have frequent social and economic interactions that facilitate gene flow and inbreeding among parasite populations, while decreasing population structure. Findings provide important information on parasites populations circulating in the study area and are relevant to current malaria elimination efforts. PMID:26872387

Integrating Genetics and Social Science: Genetic Risk Scores

PubMed Central

Belsky, Daniel W.; Israel, Salomon

2014-01-01

The sequencing of the human genome and the advent of low-cost genome-wide assays that generate millions of observations of individual genomes in a matter of hours constitute a disruptive innovation for social science. Many public-use social science datasets have or will soon add genome-wide genetic data. With these new data come technical challenges, but also new possibilities. Among these, the lowest hanging fruit and the most potentially disruptive to existing research programs is the ability to measure previously invisible contours of health and disease risk within populations. In this article, we outline why now is the time for social scientists to bring genetics into their research programs. We discuss how to select genetic variants to study. We explain how the polygenic architecture of complex traits and the low penetrance of individual genetic loci pose challenges to research integrating genetics and social science. We introduce genetic risk scores as a method of addressing these challenges and provide guidance on how genetic risk scores can be constructed. We conclude by outlining research questions that are ripe for social science inquiry. PMID:25343363

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

PubMed

Sherer, Eric A; Sale, Mark E; Pollock, Bruce G; Belani, Chandra P; Egorin, Merrill J; Ivy, Percy S; Lieberman, Jeffrey A; Manuck, Stephen B; Marder, Stephen R; Muldoon, Matthew F; Scher, Howard I; Solit, David B; Bies, Robert R

2012-08-01

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data.

Development and pilot evaluation of novel genetic educational materials designed for an underserved patient population.

PubMed

Lubitz, Rebecca Jean; Komaromy, Miriam; Crawford, Beth; Beattie, Mary; Lee, Robin; Luce, Judith; Ziegler, John

2007-01-01

Genetic counseling for BRCA1 and BRCA2 mutations involves teaching about hereditary cancer, genetics and risk, subjects that are difficult to grasp and are routinely misunderstood. Supported by a grant from the Avon Foundation, the UCSF Cancer Risk Program started the first genetic testing and counseling service for a population of traditionally underserved women of varied ethnic and social backgrounds at the San Francisco General Hospital (SFGH). Informed by educational theory and clinical experience, we devised and piloted two simplified explanations of heredity and genetic risk, with the aim of uncovering how to best communicate genetics and risk to this underserved population. A "conventional" version comprised pictures of genes, pedigrees, and quantitative representations of risk. A "colloquial" pictorial version used an analogy of the "information book" of genes, family stories and vignettes, and visual representations of risk, without using scientific words such as genes or chromosomes. A verbal narrative accompanied each picture. We presented these modules to four focus groups of five to eight women recruited from the SFGH Family Practice Clinic. Overall, women preferred a picture-based approach and commented that additional text would have been distracting. The majority of women preferred the colloquial version because it was easier to understand and better conveyed a sense of comfort and hope. We conclude that simplicity, analogies, and familiarity support comprehension while vignettes, family stories, and photos of real people provide comfort and hope. These elements may promote understanding of complex scientific topics in healthcare, particularly when communicating with patients who come from disadvantaged backgrounds.

A mutational approach for the detection of genetic factors affecting seed size in maize.

PubMed

Sangiorgio, Stefano; Carabelli, Laura; Gabotti, Damiano; Manzotti, Priscilla Sofia; Persico, Martina; Consonni, Gabriella; Gavazzi, Giuseppe

2016-12-01

Genes influencing seed size. The designation emp (empty pericarp) refers to a group of defective kernel mutants that exhibit a drastic reduction in endosperm tissue production. They allow the isolation of genes controlling seed development and affecting seed size. Nine independently isolated emp mutants have been analyzed in this study and in all cases longitudinal sections of mature seeds revealed the absence of morphogenesis in the embryo proper, an observation that correlates with their failure to germinate. Complementation tests with the nine emp mutants, crossed inter se in all pairwise combinations, identified complementing and non-complementing pairs in the F 1 progenies. Data were then validated in the F 2 /F 3 generations. Mutant chromosomal location was also established. Overall our study has identified two novel emp genes and a novel allele at the previously identified emp4 gene. The introgression of single emp mutants in a different genetic background revealed the existence of a cryptic genetic variation (CGV) recognizable as a variable increase in the endosperm tissue. The unmasking of CGV by introducing single mutants in different genetic backgrounds is the result of the interaction of the emp mutants with a suppressor that has no obvious phenotype of its own and is present in the genetic background of the inbred lines into which the emp mutants were transferred. On the basis of these results, emp mutants could be used as tools for the detection of genetic factors that enhance the amount of endosperm tissue in the maize kernel and which could thus become valuable targets to exploit in future breeding programs.

CDFISH: an individual-based, spatially-explicit, landscape genetics simulator for aquatic species in complex riverscapes

USGS Publications Warehouse

Erin L. Landguth,; Muhlfeld, Clint C.; Luikart, Gordon

2012-01-01

We introduce Cost Distance FISHeries (CDFISH), a simulator of population genetics and connectivity in complex riverscapes for a wide range of environmental scenarios of aquatic organisms. The spatially-explicit program implements individual-based genetic modeling with Mendelian inheritance and k-allele mutation on a riverscape with resistance to movement. The program simulates individuals in subpopulations through time employing user-defined functions of individual migration, reproduction, mortality, and dispersal through straying on a continuous resistance surface.

Genetic Testing Integration Panels (GTIPs): A novel approach for considering integration of direct-to-consumer and other new genetic tests into patient care

PubMed Central

Uhlmann, Wendy R.; Sharp, Richard R.

2014-01-01

There has been a dramatic increase in the number of genetic tests available but few tests have practice guidelines. In addition, many tests have become available outside of genetics clinics through direct-to-consumer (DTC) companies and several offer tests not considered standard of care. To address several practical challenges associated with the rapid introduction of clinical and DTC genetic tests, we propose that genetic counselors and geneticists organize expert panels in their institutions to discuss the integration of new tests into patient care. We propose the establishment of Genetic Testing Integration Panels (GTIPs) to bring together local experts in medical genetics, genetic counseling, bioethics and law, health communication and clinical laboratory genetics. We describe key features of this approach and consider some of the potential advantages and limitations of using a GTIP to address the many clinical challenges raised by rapidly emerging clinical and DTC genetic tests. PMID:22246561

Contemporary Genetics for Gender Researchers: Not Your Grandma's Genetics Anymore

ERIC Educational Resources Information Center

Salk, Rachel H.; Hyde, Janet S.

2012-01-01

Over the past century, much of genetics was deterministic, and feminist researchers framed justified criticisms of genetics research. However, over the past two decades, genetics research has evolved remarkably and has moved far from earlier deterministic approaches. Our article provides a brief primer on modern genetics, emphasizing contemporary…

Genetically-Based Biologic Technologies. Biology and Human Welfare.

ERIC Educational Resources Information Center

Mayer, William V.; McInerney, Joseph D.

The purpose of this six-part booklet is to review the current status of genetically-based biologic technologies and to suggest how information about these technologies can be inserted into existing educational programs. Topic areas included in the six parts are: (1) genetically-based technologies in the curriculum; (2) genetic technologies…

MCMC multilocus lod scores: application of a new approach.

PubMed

George, Andrew W; Wijsman, Ellen M; Thompson, Elizabeth A

2005-01-01

On extended pedigrees with extensive missing data, the calculation of multilocus likelihoods for linkage analysis is often beyond the computational bounds of exact methods. Growing interest therefore surrounds the implementation of Monte Carlo estimation methods. In this paper, we demonstrate the speed and accuracy of a new Markov chain Monte Carlo method for the estimation of linkage likelihoods through an analysis of real data from a study of early-onset Alzheimer's disease. For those data sets where comparison with exact analysis is possible, we achieved up to a 100-fold increase in speed. Our approach is implemented in the program lm_bayes within the framework of the freely available MORGAN 2.6 package for Monte Carlo genetic analysis (http://www.stat.washington.edu/thompson/Genepi/MORGAN/Morgan.shtml).

Novel perspectives for the engineering of abiotic stress tolerance in plants.

PubMed

Cabello, Julieta V; Lodeyro, Anabella F; Zurbriggen, Matias D

2014-04-01

Adverse environmental conditions pose serious limitations to agricultural production. Classical biotechnological approaches towards increasing abiotic stress tolerance focus on boosting plant endogenous defence mechanisms. However, overexpression of regulatory elements or effectors is usually accompanied by growth handicap and yield penalties due to crosstalk between developmental and stress-response networks. Herein we offer an overview on novel strategies with the potential to overcome these limitations based on the engineering of regulatory systems involved in the fine-tuning of the plant response to environmental hardships, including post-translational modifications, small RNAs, epigenetic control of gene expression and hormonal networks. The development and application of plant synthetic biology tools and approaches will add new functionalities and perspectives to genetic engineering programs for enhancing abiotic stress tolerance. Copyright © 2013 Elsevier Ltd. All rights reserved.

An Efficient Rank Based Approach for Closest String and Closest Substring

PubMed Central

2012-01-01

This paper aims to present a new genetic approach that uses rank distance for solving two known NP-hard problems, and to compare rank distance with other distance measures for strings. The two NP-hard problems we are trying to solve are closest string and closest substring. For each problem we build a genetic algorithm and we describe the genetic operations involved. Both genetic algorithms use a fitness function based on rank distance. We compare our algorithms with other genetic algorithms that use different distance measures, such as Hamming distance or Levenshtein distance, on real DNA sequences. Our experiments show that the genetic algorithms based on rank distance have the best results. PMID:22675483

Generalizing genetical genomics: getting added value from environmental perturbation.

PubMed

Li, Yang; Breitling, Rainer; Jansen, Ritsert C

2008-10-01

Genetical genomics is a useful approach for studying the effect of genetic perturbations on biological systems at the molecular level. However, molecular networks depend on the environmental conditions and, thus, a comprehensive understanding of biological systems requires studying them across multiple environments. We propose a generalization of genetical genomics, which combines genetic and sensibly chosen environmental perturbations, to study the plasticity of molecular networks. This strategy forms a crucial step toward understanding why individuals respond differently to drugs, toxins, pathogens, nutrients and other environmental influences. Here we outline a strategy for selecting and allocating individuals to particular treatments, and we discuss the promises and pitfalls of the generalized genetical genomics approach.

Systems genetics approaches to understand complex traits

PubMed Central

Civelek, Mete; Lusis, Aldons J.

2014-01-01

Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. PMID:24296534

Dynamic traffic assignment : genetic algorithms approach

DOT National Transportation Integrated Search

1997-01-01

Real-time route guidance is a promising approach to alleviating congestion on the nations highways. A dynamic traffic assignment model is central to the development of guidance strategies. The artificial intelligence technique of genetic algorithm...

Feature extraction from multiple data sources using genetic programming

NASA Astrophysics Data System (ADS)

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

2002-08-01

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

Applications of genetic programming in cancer research.

PubMed

Worzel, William P; Yu, Jianjun; Almal, Arpit A; Chinnaiyan, Arul M

2009-02-01

The theory of Darwinian evolution is the fundamental keystones of modern biology. Late in the last century, computer scientists began adapting its principles, in particular natural selection, to complex computational challenges, leading to the emergence of evolutionary algorithms. The conceptual model of selective pressure and recombination in evolutionary algorithms allow scientists to efficiently search high dimensional space for solutions to complex problems. In the last decade, genetic programming has been developed and extensively applied for analysis of molecular data to classify cancer subtypes and characterize the mechanisms of cancer pathogenesis and development. This article reviews current successes using genetic programming and discusses its potential impact in cancer research and treatment in the near future.

Initialization Method for Grammar-Guided Genetic Programming

NASA Astrophysics Data System (ADS)

García-Arnau, M.; Manrique, D.; Ríos, J.; Rodríguez-Patón, A.

This paper proposes a new tree-generation algorithm for grammarguided genetic programming that includes a parameter to control the maximum size of the trees to be generated. An important feature of this algorithm is that the initial populations generated are adequately distributed in terms of tree size and distribution within the search space. Consequently, genetic programming systems starting from the initial populations generated by the proposed method have a higher convergence speed. Two different problems have been chosen to carry out the experiments: a laboratory test involving searching for arithmetical equalities and the real-world task of breast cancer prognosis. In both problems, comparisons have been made to another five important initialization methods.

Genetic conservation and paddlefish propagation

USGS Publications Warehouse

Sloss, Brian L.; Klumb, Robert A.; Heist, Edward J.

2009-01-01

The conservation of genetic diversity of our natural resources is overwhelmingly one of the central foci of 21st century management practices. Three recommendations related to the conservation of paddlefish Polyodon spathula genetic diversity are to (1) identify genetic diversity at both nuclear and mitochondrial DNA loci using a suggested list of 20 sampling locations, (2) use genetic diversity estimates to develop genetic management units, and (3) identify broodstock sources to minimize effects of supplemental stocking on the genetic integrity of native paddlefish populations. We review previous genetic work on paddlefish and described key principles and concepts associated with maintaining genetic diversity within and among paddlefish populations and also present a genetic case study of current paddlefish propagation at the U.S. Fish and Wildlife Service Gavins Point National Fish Hatchery. This study confirmed that three potential sources of broodfish were genetically indistinguishable at the loci examined, allowing the management agencies cooperating on this program flexibility in sampling gametes. This study also showed significant bias in the hatchery occurred in terms of male reproductive contribution, which resulted in a shift in the genetic diversity of progeny compared to the broodfish. This shift was shown to result from differential male contributions, partially attributed to the mode of egg fertilization. Genetic insights enable implementation of a paddlefish propagation program within an adaptive management strategy that conserves inherent genetic diversity while achieving demographic goals.

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 Genetics of Obsessive-Compulsive Disorder and Tourette Syndrome: An Epidemiological and Pathway-Based Approach for Gene Discovery

ERIC Educational Resources Information Center

Grados, Marco A.

2010-01-01

Objective: To provide a contemporary perspective on genetic discovery methods applied to obsessive-compulsive disorder (OCD) and Tourette syndrome (TS). Method: A review of research trends in genetics research in OCD and TS is conducted, with emphasis on novel approaches. Results: Genome-wide association studies (GWAS) are now in progress in OCD…

Genetic surgery - a right strategy to attack cancer.

PubMed

Sverdlov, Eugene D

2011-12-01

The approaches now united under the term "gene therapy" can be divided into two broad strategies: (1) strategy using the ideology of molecular targeted therapy, but with genes in the role of agents targeted at certain molecular component(s) or pathways presumably crucial for cancer maintenance; (ii) strategy aimed at the destruction of tumors as a whole exploiting the features shared by all cancers, for example relatively fast mitotic cell division. While the first strategy is "true" gene therapy, the second one, as e.g. suicide gene therapy, is more like genetic surgery, when a surgeon just cuts off a tumor being not interested in subtle genetic mechanisms of cancer emergence and progression. This approach inherits the ideology of chemotherapy but escapes its severe toxic effects due to intracellular formation of toxic agents. Genetic surgery seems to be the most appropriate approach to combat cancer, and its simplicity is paradoxically adequate to the super-complexity of tumors. The review consists of three parts: (i) analysis of the reasons of tumor supercomplexity and fatally inevitable failure of molecular targeted therapy, (ii) general principles of the genetic surgery strategy, and (iii) examples of genetic surgery approaches with analysis of their drawbacks and the ways for their improvement.

Post-genomic behavioral genetics: From revolution to routine.

PubMed

Ashbrook, D G; Mulligan, M K; Williams, R W

2018-03-01

What was once expensive and revolutionary-full-genome sequence-is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Women's Health Initiative (www.whi.org), the Million Veterans Program (www. va.gov/MVP), the 100 000 Genomes Project (genomicsengland.co.uk) and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro- and behavioral genetics, and sample sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequences of this new affordability of massive omics datasets: (1) it is now far more practical to explore genetic modulation of behavioral differences and the key role of gene-by-environment interactions. Researchers are already doing the hard part-the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors. © 2017 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Genetically based location from triploid populations and gene ontology of a 3.3-mb genome region linked to Alternaria brown spot resistance in citrus reveal clusters of resistance genes.

PubMed

Cuenca, José; Aleza, Pablo; Vicent, Antonio; Brunel, Dominique; Ollitrault, Patrick; Navarro, Luis

2013-01-01

Genetic analysis of phenotypical traits and marker-trait association in polyploid species is generally considered as a challenge. In the present work, different approaches were combined taking advantage of the particular genetic structures of 2n gametes resulting from second division restitution (SDR) to map a genome region linked to Alternaria brown spot (ABS) resistance in triploid citrus progeny. ABS in citrus is a serious disease caused by the tangerine pathotype of the fungus Alternaria alternata. This pathogen produces ACT-toxin, which induces necrotic lesions on fruit and young leaves, defoliation and fruit drop in susceptible genotypes. It is a strong concern for triploid breeding programs aiming to produce seedless mandarin cultivars. The monolocus dominant inheritance of susceptibility, proposed on the basis of diploid population studies, was corroborated in triploid progeny. Bulk segregant analysis coupled with genome scan using a large set of genetically mapped SNP markers and targeted genetic mapping by half tetrad analysis, using SSR and SNP markers, allowed locating a 3.3 Mb genomic region linked to ABS resistance near the centromere of chromosome III. Clusters of resistance genes were identified by gene ontology analysis of this genomic region. Some of these genes are good candidates to control the dominant susceptibility to the ACT-toxin. SSR and SNP markers were developed for efficient early marker-assisted selection of ABS resistant hybrids.

Molecular concept in human oral cancer.

PubMed

Krishna, Akhilesh; Singh, Shraddha; Kumar, Vijay; Pal, U S

2015-01-01

The incidence of oral cancer remains high in both Asian and Western countries. Several risk factors associated with development of oral cancer are now well-known, including tobacco chewing, smoking, and alcohol consumption. Cancerous risk factors may cause many genetic events through chromosomal alteration or mutations in genetic material and lead to progression and development of oral cancer through histological progress, carcinogenesis. Oral squamous carcinogenesis is a multistep process in which multiple genetic events occur that alter the normal functions of proto-oncogenes/oncogenes and tumor suppressor genes. Furthermore, these gene alterations can deregulate the normal activity such as increase in the production of growth factors (transforming growth factor-α [TGF-α], TGF-β, platelet-derived growth factor, etc.) or numbers of cell surface receptors (epidermal growth factor receptor, G-protein-coupled receptor, etc.), enhanced intracellular messenger signaling and mutated production of transcription factors (ras gene family, c-myc gene) which results disturb to tightly regulated signaling pathways of normal cell. Several oncogenes and tumor suppressor genes have been implicated in oral cancer especially cyclin family, ras, PRAD-1, cyclin-dependent kinase inhibitors, p53 and RB1. Viral infections, particularly with oncogenic human papilloma virus subtype (16 and 18) and Epstein-Barr virus have tumorigenic effect on oral epithelia. Worldwide, this is an urgent need to initiate oral cancer research programs at molecular and genetic level which investigates the causes of genetic and molecular defect, responsible for malignancy. This approach may lead to development of target dependent tumor-specific drugs and appropriate gene therapy.

Molecular concept in human oral cancer

PubMed Central

Krishna, Akhilesh; Singh, Shraddha; Kumar, Vijay; Pal, U. S.

2015-01-01

The incidence of oral cancer remains high in both Asian and Western countries. Several risk factors associated with development of oral cancer are now well-known, including tobacco chewing, smoking, and alcohol consumption. Cancerous risk factors may cause many genetic events through chromosomal alteration or mutations in genetic material and lead to progression and development of oral cancer through histological progress, carcinogenesis. Oral squamous carcinogenesis is a multistep process in which multiple genetic events occur that alter the normal functions of proto-oncogenes/oncogenes and tumor suppressor genes. Furthermore, these gene alterations can deregulate the normal activity such as increase in the production of growth factors (transforming growth factor-α [TGF-α], TGF-β, platelet-derived growth factor, etc.) or numbers of cell surface receptors (epidermal growth factor receptor, G-protein-coupled receptor, etc.), enhanced intracellular messenger signaling and mutated production of transcription factors (ras gene family, c-myc gene) which results disturb to tightly regulated signaling pathways of normal cell. Several oncogenes and tumor suppressor genes have been implicated in oral cancer especially cyclin family, ras, PRAD-1, cyclin-dependent kinase inhibitors, p53 and RB1. Viral infections, particularly with oncogenic human papilloma virus subtype (16 and 18) and Epstein-Barr virus have tumorigenic effect on oral epithelia. Worldwide, this is an urgent need to initiate oral cancer research programs at molecular and genetic level which investigates the causes of genetic and molecular defect, responsible for malignancy. This approach may lead to development of target dependent tumor-specific drugs and appropriate gene therapy. PMID:26668446

Genetically Based Location from Triploid Populations and Gene Ontology of a 3.3-Mb Genome Region Linked to Alternaria Brown Spot Resistance in Citrus Reveal Clusters of Resistance Genes

PubMed Central

Cuenca, José; Aleza, Pablo; Vicent, Antonio; Brunel, Dominique; Ollitrault, Patrick; Navarro, Luis

2013-01-01

Genetic analysis of phenotypical traits and marker-trait association in polyploid species is generally considered as a challenge. In the present work, different approaches were combined taking advantage of the particular genetic structures of 2n gametes resulting from second division restitution (SDR) to map a genome region linked to Alternaria brown spot (ABS) resistance in triploid citrus progeny. ABS in citrus is a serious disease caused by the tangerine pathotype of the fungus Alternaria alternata. This pathogen produces ACT-toxin, which induces necrotic lesions on fruit and young leaves, defoliation and fruit drop in susceptible genotypes. It is a strong concern for triploid breeding programs aiming to produce seedless mandarin cultivars. The monolocus dominant inheritance of susceptibility, proposed on the basis of diploid population studies, was corroborated in triploid progeny. Bulk segregant analysis coupled with genome scan using a large set of genetically mapped SNP markers and targeted genetic mapping by half tetrad analysis, using SSR and SNP markers, allowed locating a 3.3 Mb genomic region linked to ABS resistance near the centromere of chromosome III. Clusters of resistance genes were identified by gene ontology analysis of this genomic region. Some of these genes are good candidates to control the dominant susceptibility to the ACT-toxin. SSR and SNP markers were developed for efficient early marker-assisted selection of ABS resistant hybrids. PMID:24116149

Insulin and IGF1 Receptors Are Essential for XX and XY Gonadal Differentiation and Adrenal Development in Mice

PubMed Central

Romero, Yannick; Conne, Béatrice; Truong, Vy; Papaioannou, Marilena D.; Schaad, Olivier; Docquier, Mylène; Herrera, Pedro Luis; Wilhelm, Dagmar; Nef, Serge

2013-01-01

Mouse sex determination provides an attractive model to study how regulatory genetic networks and signaling pathways control cell specification and cell fate decisions. This study characterizes in detail the essential role played by the insulin receptor (INSR) and the IGF type I receptor (IGF1R) in adrenogenital development and primary sex determination. Constitutive ablation of insulin/IGF signaling pathway led to reduced proliferation rate of somatic progenitor cells in both XX and XY gonads prior to sex determination together with the downregulation of hundreds of genes associated with the adrenal, testicular, and ovarian genetic programs. These findings indicate that prior to sex determination somatic progenitors in Insr;Igf1r mutant gonads are not lineage primed and thus incapable of upregulating/repressing the male and female genetic programs required for cell fate restriction. In consequence, embryos lacking functional insulin/IGF signaling exhibit (i) complete agenesis of the adrenal cortex, (ii) embryonic XY gonadal sex reversal, with a delay of Sry upregulation and the subsequent failure of the testicular genetic program, and (iii) a delay in ovarian differentiation so that Insr;Igf1r mutant gonads, irrespective of genetic sex, remained in an extended undifferentiated state, before the ovarian differentiation program ultimately is initiated at around E16.5. PMID:23300479

Genetic characterization of Russian honey bee stock selected for improved resistance to Varroa destructor.

PubMed

Bourgeois, A Lelania; Rinderer, Thomas E

2009-06-01

Maintenance of genetic diversity among breeding lines is important in selective breeding and stock management. The Russian Honey Bee Breeding Program has strived to maintain high levels of heterozygosity among its breeding lines since its inception in 1997. After numerous rounds of selection for resistance to tracheal and varroa mites and improved honey production, 18 lines were selected as the core of the program. These lines were grouped into three breeding blocks that were crossbred to improve overall heterozygosity levels of the population. Microsatellite DNA data demonstrated that the program has been successful. Heterozygosity and allelic richness values are high and there are no indications of inbreeding among the three blocks. There were significant levels of genetic structure measured among the three blocks. Block C was genetically distinct from both blocks A and B (F(ST) = 0.0238), whereas blocks A and B did not differ from each other (F(ST) = 0.0074). The same pattern was seen for genic (based on numbers of alleles) differentiation. Genetic distance, as measured by chord distance, indicates that all of the 18 lines are equally distant, with minimal clustering. The data indicate that the overall design of the breeding program has been successful in maintaining high levels of diversity and avoiding problems associated with inbreeding.

Genetic Counseling Graduate Student Debt: Impact on Program, Career and Life Choices

PubMed Central

Kuhl, Ashley; Reiser, Catherine; Eickhoff, Jens; Petty, Elizabeth M

2015-01-01

The cost of education is rising, increasing student financial aid and debt for students pursuing higher education. A few studies have assessed the impact of student debt in medicine, physical therapy and social work, but little is known about the impact of student debt on genetic counseling students and graduates. To address this gap in knowledge, a web-based study of 408 recent alumni of genetic counseling programs in North America was conducted to assess the impact of student debt on program, career and life choices. Over half (63%; n=256/408) of the participants reported that loans were extremely important in their ability to attend their training program, with most using subsidized loans no longer available to current graduate students. While participants were generally satisfied with their genetic counseling education, 83% (n=282/342) of participants with student debt reported feeling burdened by their debt, which had a median of $40,000-$50,000. This debt is relatively close to the median starting salary reported by survey participants ($45,000-$50,000), breaching the “20-10 rule” that states student debt should not exceed 20% of annual net income. In response to this critical issue, we propose recommendations for the genetic counseling field that may help alleviate student debt impact and burden. PMID:24578121

A Model Program for Translational Medicine in Epilepsy Genetics

PubMed Central

Smith, Lacey A.; Ullmann, Jeremy F. P.; Olson, Heather E.; El Achkar, Christelle M.; Truglio, Gessica; Kelly, McKenna; Rosen-Sheidley, Beth; Poduri, Annapurna

2017-01-01

Recent technological advances in gene sequencing have led to a rapid increase in gene discovery in epilepsy. However, the ability to assess pathogenicity of variants, provide functional analysis, and develop targeted therapies has not kept pace with rapid advances in sequencing technology. Thus, although clinical genetic testing may lead to a specific molecular diagnosis for some patients, test results often lead to more questions than answers. As the field begins to focus on therapeutic applications of genetic diagnoses using precision medicine, developing processes that offer more than equivocal test results is essential. The success of precision medicine in epilepsy relies on establishing a correct genetic diagnosis, analyzing functional consequences of genetic variants, screening potential therapeutics in the preclinical laboratory setting, and initiating targeted therapy trials for patients. We describe the structure of a comprehensive, pediatric Epilepsy Genetics Program that can serve as a model for translational medicine in epilepsy. PMID:28056630

Convergent functional genomics in addiction research - a translational approach to study candidate genes and gene networks.

PubMed

Spanagel, Rainer

2013-01-01

Convergent functional genomics (CFG) is a translational methodology that integrates in a Bayesian fashion multiple lines of evidence from studies in human and animal models to get a better understanding of the genetics of a disease or pathological behavior. Here the integration of data sets that derive from forward genetics in animals and genetic association studies including genome wide association studies (GWAS) in humans is described for addictive behavior. The aim of forward genetics in animals and association studies in humans is to identify mutations (e.g. SNPs) that produce a certain phenotype; i.e. "from phenotype to genotype". Most powerful in terms of forward genetics is combined quantitative trait loci (QTL) analysis and gene expression profiling in recombinant inbreed rodent lines or genetically selected animals for a specific phenotype, e.g. high vs. low drug consumption. By Bayesian scoring genomic information from forward genetics in animals is then combined with human GWAS data on a similar addiction-relevant phenotype. This integrative approach generates a robust candidate gene list that has to be functionally validated by means of reverse genetics in animals; i.e. "from genotype to phenotype". It is proposed that studying addiction relevant phenotypes and endophenotypes by this CFG approach will allow a better determination of the genetics of addictive behavior.

BAC-end sequence-based SNPs and Bin mapping for rapid integration of physical and genetic maps in apple.

PubMed

Han, Yuepeng; Chagné, David; Gasic, Ksenija; Rikkerink, Erik H A; Beever, Jonathan E; Gardiner, Susan E; Korban, Schuyler S

2009-03-01

A genome-wide BAC physical map of the apple, Malus x domestica Borkh., has been recently developed. Here, we report on integrating the physical and genetic maps of the apple using a SNP-based approach in conjunction with bin mapping. Briefly, BAC clones located at ends of BAC contigs were selected, and sequenced at both ends. The BAC end sequences (BESs) were used to identify candidate SNPs. Subsequently, these candidate SNPs were genetically mapped using a bin mapping strategy for the purpose of mapping the physical onto the genetic map. Using this approach, 52 (23%) out of 228 BESs tested were successfully exploited to develop SNPs. These SNPs anchored 51 contigs, spanning approximately 37 Mb in cumulative physical length, onto 14 linkage groups. The reliability of the integration of the physical and genetic maps using this SNP-based strategy is described, and the results confirm the feasibility of this approach to construct an integrated physical and genetic maps for apple.

Recent molecular genetic studies and methodological issues in suicide research.

PubMed

Tsai, Shih-Jen; Hong, Chen-Jee; Liou, Ying-Jay

2011-06-01

Suicide behavior (SB) spans a spectrum ranging from suicidal ideation to suicide attempts and completed suicide. Strong evidence suggests a genetic susceptibility to SB, including familial heritability and common occurrence in twins. This review addresses recent molecular genetic studies in SB that include case-control association, genome gene-expression microarray, and genome-wide association (GWA). This work also reviews epigenetics in SB and pharmacogenetic studies of antidepressant-induced suicide. SB fulfills criteria for a complex genetic phenotype in which environmental factors interact with multiple genes to influence susceptibility. So far, case-control association approaches are still the mainstream in SB genetic studies, although whole genome gene-expression microarray and GWA studies have begun to emerge in recent years. Genetic association studies have suggested several genes (e.g., serotonin transporter, tryptophan hydroxylase 2, and brain-derived neurotrophic factor) related to SB, but not all reports support these findings. The case-control approach while useful is limited by present knowledge of disease pathophysiology. Genome-wide studies of gene expression and genetic variation are not constrained by our limited knowledge. However, the explanatory power and path to clinical translation of risk estimates for common variants reported in genome-wide association studies remain unclear because of the presence of rare and structural genetic variation. As whole genome sequencing becomes increasingly widespread, available genomic information will no longer be the limiting factor in applying genetics to clinical medicine. These approaches provide exciting new avenues to identify new candidate genes for SB genetic studies. The other limitation of genetic association is the lack of a consistent definition of the SB phenotype among studies, an inconsistency that hampers the comparability of the studies and data pooling. In summary, SB involves multiple genes interacting with non-genetic factors. A better understanding of the SB genes by combining whole genome approaches with case-control association studies, may potentially lead to developing effective screening, prevention, and management of SB. Copyright © 2010 Elsevier Inc. All rights reserved.

Molecular characterization of high performance inbred lines of Brazilian common beans.

PubMed

Cardoso, P C B; Veiga, M M; de Menezes, I P P; Valdisser, P A M R; Borba, T C O; Melo, L C; Del Peloso, M J; Brondani, C; Vianello, R P

2013-02-06

The identification of germplasm genetic variability in breeding programs of the common bean (Phaseolus vulgaris) is essential for determining the potential of each combination of parent plants to obtain superior genotypes. The present study aimed to estimated the extent of genetic diversity in 172 lineages and cultivars of the common bean by integrating five tests of value for cultivation and use (VCU) that were conducted over the last eight years by the breeding program of Embrapa Arroz e Feijão in Brazil. Nine multilocus genotyping systems composed of 36 fluorescent microsatellite markers distributed across 11 different chromosomes of the common bean were used, of which 24 were polymorphic in all trials. One hundred and eighty-seven alleles were identified, with an average of 7.79 alleles per locus and an average gene diversity of 0.65. The combined probability of identity for all loci was 1.32 x 10(-16). Lineages that are more genetically divergent between the selection cycles were identified, allowing the breeding program to develop a crossbreed between elite genotypes with a low degree of genetic relatedness. HE values ranged from 0.31 to 0.63, with a large reduction in the genetic base over successive selection cycles. The test showed a significant degree of differentiation (FST = 0.159). Private alleles (26%) were identified and can be directly incorporated into the gene pool of cultivated germplasm, thereby contributing effectively to the expansion of genetic diversity in this bean-breeding program.

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

PubMed

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

2016-04-01

Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition's modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of prior conditions. The method is implemented in the software NetStruct (available at https://giligreenbaum.wordpress.com/software/). Copyright © 2016 by the Genetics Society of America.

Ancient deuterostome origins of vertebrate brain signalling centres.

PubMed

Pani, Ariel M; Mullarkey, Erin E; Aronowicz, Jochanan; Assimacopoulos, Stavroula; Grove, Elizabeth A; Lowe, Christopher J

2012-03-14

Neuroectodermal signalling centres induce and pattern many novel vertebrate brain structures but are absent, or divergent, in invertebrate chordates. This has led to the idea that signalling-centre genetic programs were first assembled in stem vertebrates and potentially drove morphological innovations of the brain. However, this scenario presumes that extant cephalochordates accurately represent ancestral chordate characters, which has not been tested using close chordate outgroups. Here we report that genetic programs homologous to three vertebrate signalling centres-the anterior neural ridge, zona limitans intrathalamica and isthmic organizer-are present in the hemichordate Saccoglossus kowalevskii. Fgf8/17/18 (a single gene homologous to vertebrate Fgf8, Fgf17 and Fgf18), sfrp1/5, hh and wnt1 are expressed in vertebrate-like arrangements in hemichordate ectoderm, and homologous genetic mechanisms regulate ectodermal patterning in both animals. We propose that these genetic programs were components of an unexpectedly complex, ancient genetic regulatory scaffold for deuterostome body patterning that degenerated in amphioxus and ascidians, but was retained to pattern divergent structures in hemichordates and vertebrates. © 2012 Macmillan Publishers Limited. All rights reserved

Social Science Methods for Twins Data: Integrating Causality, Endowments and Heritability

PubMed Central

Kohler, Hans-Peter; Behrman, Jere R.; Schnittker, Jason

2011-01-01

Twins have been extensively used in economics, sociology and behavioral genetics to investigate the role of genetic endowments on a broad range of social, demographic and economic outcomes. However, the focus in these literatures has been distinct: the economic literature has been primarily concerned with the need to control for unobserved endowments—including as an important subset, genetic endowments—in analyses that attempt to establish the impact of one variable, often schooling, on a variety of economic, demographic and health outcomes. Behavioral genetic analyses have mostly been concerned with decomposing the variation in the outcomes of interest into genetic, shared environmental and non-shared environmental components, with recent multivariate analyses investigating the contributions of genes and the environment to the correlation and causation between variables. Despite the fact that twins studies and the recognition of the role of endowments are central to both of these literatures, they have mostly evolved independently. In this paper we develop formally the relationship between the economic and behavioral genetic approaches to the analyses of twins, and we develop an integrative approach that combines the identification of causal effects, which dominates the economic literature, with the decomposition of variances and covariances into genetic and environmental factors that is the primary goal of behavioral genetic approaches. We apply this integrative ACE-β approach to an illustrative investigation of the impact of schooling on several demographic outcomes such as fertility and nuptiality and health. PMID:21845929

The inclusion of ADA-SCID in expanded newborn screening by tandem mass spectrometry.

PubMed

la Marca, Giancarlo; Giocaliere, Elisa; Malvagia, Sabrina; Funghini, Silvia; Ombrone, Daniela; Della Bona, Maria Luisa; Canessa, Clementina; Lippi, Francesca; Romano, Francesca; Guerrini, Renzo; Resti, Massimo; Azzari, Chiara

2014-01-01

Severe combined immunodeficiency due to adenosine-deaminase defect (ADA-SCID) is usually deadly in childhood because of severe recurrent infections. When clinical diagnosis is done, permanent damages due to infections or metabolite accumulation are often present. Gene therapy, bone marrow transplantation or enzyme replacement therapy may be effective if started early. The aim of this study was to set-up a robust method suitable for screening with a minimized preparation process and with inexpensive running costs, for diagnosing ADA-SCID by tandem mass spectrometry. ADA-SCID satisfies all the criteria for inclusion in a newborn screening program. We describe a protocol revised to incorporate adenosine and 2-deoxyadenosine testing into an expanded newborn screening program. We assessed the effectiveness of this approach testing dried blood spots from 4 genetically confirmed early-onset and 5 delayed-onset ADA-SCID patients. Reference values were established on 50,000 healthy newborns (deoxyadenosine <0.09μmol/L, adenosine <1.61μmol/L). We also developed a second tier test to distinguish true positives from false positives and improve the positive predictive value of an initial abnormal result. In the first 18 months, the pilot project has identified a newborn with a genetically confirmed defect in adenosine deaminase (ADA) gene. The results show that the method having great simplicity, low cost and low process preparations can be fully applicable to a mass screening program. Copyright © 2013 Elsevier B.V. All rights reserved.

Recursive Directional Ligation Approach for Cloning Recombinant Spider Silks.

PubMed

Dinjaski, Nina; Huang, Wenwen; Kaplan, David L

2018-01-01

Recent advances in genetic engineering have provided a route to produce various types of recombinant spider silks. Different cloning strategies have been applied to achieve this goal (e.g., concatemerization, step-by-step ligation, recursive directional ligation). Here we describe recursive directional ligation as an approach that allows for facile modularity and control over the size of the genetic cassettes. This approach is based on sequential ligation of genetic cassettes (monomers) where the junctions between them are formed without interrupting key gene sequences with additional base pairs.

Comparative Effectiveness of Context-Based and Traditional Approaches in Teaching Genetics: Student Views and Achievement

ERIC Educational Resources Information Center

Kazeni, Monde; Onwu, Gilbert

2013-01-01

The study aimed to determine the comparative effectiveness of context-based and traditional teaching approaches in enhancing student achievement in genetics, problem-solving, science inquiry and decision-making skills, and attitude towards the study of life sciences. A mixed method but essentially quantitative research approach involving a…

The Sociopolitical Importance of Genetic, Phenomenological Approaches to Science Teaching and Learning

ERIC Educational Resources Information Center

Bazzul, Jesse

2015-01-01

This article discusses Wolff-Michael Roth's theoretical framework for a phenomenological, genetic approach to science teaching and learning based on the work of Edmund Husserl. This approach advocates the inclusion of student lifeworlds in science education and underlines the importance of thinking about subjectivity in both science and science…

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

PubMed Central

Lathrop, G M; Lalouel, J M

1984-01-01

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

Proceedings of the symposium on isozymes of North American forest trees and forest insects; July 27, 1979; Berkeley, California

Treesearch

M. Thompson Conkle

1981-01-01

These 10 symposium papers discuss gene resource management, basic genetics, genetic variation between and within tree species, genetic variability and growth, comparisons of tree life history characteristics, genetic variation in forest insects, breeding systems, and applied uses of isozymes in breeding programs.

Genetic Variation Among Open-Pollinated Progeny of Eastern Cottonwood

Treesearch

R. E. Farmer

1970-01-01

Improvement programs in eastern cottonwood (Populus deltoides Bartr.) are most frequently designed to produce genetically superior clones for direct commercial use. This paper describes a progeny test to assess genetic variability on which selection might be based.

Genetic analysis of individual origins supports isolation of grizzly bears in the Greater Yellowstone Ecosystem

USGS Publications Warehouse

Haroldson, Mark A.; Schwartz, Charles; Kendall, Katherine C.; Gunther, Kerry A.; Moody, David S.; Frey, Kevin L.; Paetkau, David

2010-01-01

The Greater Yellowstone Ecosystem (GYE) supports the southernmost of the 2 largest remaining grizzly bear (Ursus arctos) populations in the contiguous United States. Since the mid-1980s, this population has increased in numbers and expanded in range. However, concerns for its long-term genetic health remain because of its presumed continued isolation. To test the power of genetic methods for detecting immigrants, we generated 16-locus microsatellite genotypes for 424 individual grizzly bears sampled in the GYE during 1983–2007. Genotyping success was high (90%) and varied by sample type, with poorest success (40%) for hair collected from mortalities found ≥1 day after death. Years of storage did not affect genotyping success. Observed heterozygosity was 0.60, with a mean of 5.2 alleles/marker. We used factorial correspondence analysis (Program GENETIX) and Bayesian clustering (Program STRUCTURE) to compare 424 GYE genotypes with 601 existing genotypes from grizzly bears sampled in the Northern Continental Divide Ecosystem (NCDE) (FST  =  0.096 between GYE and NCDE). These methods correctly classified all sampled individuals to their population of origin, providing no evidence of natural movement between the GYE and NCDE. Analysis of 500 simulated first-generation crosses suggested that over 95% of such bears would also be detectable using our 16-locus data set. Our approach provides a practical method for detecting immigration in the GYE grizzly population. We discuss estimates for the proportion of the GYE population sampled and prospects for natural immigration into the GYE.

Early identification and high-risk strategies for bipolar disorder.

PubMed

Correll, Christoph U; Penzner, Julie B; Lencz, Todd; Auther, Andrea; Smith, Christopher W; Malhotra, Anil K; Kane, John M; Cornblatt, Barbara A

2007-06-01

To describe and compare the relative merits of different identification strategies for individuals at risk for bipolar disorder (BPD). Selective review of data that support early identification in BPD, with a particular focus on emerging clinical high-risk strategies. Early detection of individuals at risk for BPD can utilize genetic, endophenotypic and clinical methods. Most published work focuses on genetic familial endophenotypic risk markers for BPD. However, despite encouraging results, problems with specificity and sensitivity limit the application of these data to early prevention programs. In addition, offspring studies of BPD patients systematically exclude the majority of subjects without a first-degree bipolar relative. On the other hand, emerging work in the clinical-high-risk arena has already produced encouraging results. Although still preliminary, the identification of individuals in subsyndromal or attenuated symptom 'prodromal' stages of BPD seems to be an under-researched area that holds considerable promise deserving increased attention. Required next steps include the development of rating tools for attenuated and subsyndromal manic and depressive symptoms and of prodromal criteria that will allow prodromal symptomatology to be systematically studied in patients with recent-onset bipolar, as well as in prospective population-based phenomenology trials and attenuated symptom-based high-risk studies. Given the current limitations of each early identification method, combining clinical, endophenotypic and genetic strategies will increase prediction accuracy. Since reliable biological markers for BPD have not been established and since most patients with BPD lack a first-degree relative with this disorder, clinical high-risk approaches have great potential to inform early identification and intervention programs.

Creation of a National, At-home Model for Ashkenazi Jewish Carrier Screening.

PubMed

Grinzaid, Karen Arnovitz; Page, Patricia Zartman; Denton, Jessica Johnson; Ginsberg, Jessica

2015-06-01

Ethnicity-based carrier screening for the Ashkenazi Jewish population has been available and encouraged by advocacy and community groups since the early 1970's. Both the American College of Medical Genetics and the American Congress of Obstetricians and Gynecologists recommend carrier screening for this population (Obstetrics and Gynecology, 114(4), 950-953, 2009; Genetics in Medicine, 10(1), 55-56, 2008). While many physicians inquire about ethnic background and offer appropriate carrier screening, studies show that a gap remains in implementing recommendations (Genetic testing and molecular biomarkers, 2011). In addition, education and outreach efforts targeting Jewish communities have had limited success in reaching this at-risk population. Despite efforts by the medical and Jewish communities, many Jews of reproductive age are not aware of screening, and remain at risk for having children with preventable diseases. Reaching this population, preferably pre-conception, and facilitating access to screening is critically important. To address this need, genetic counselors at Emory University developed JScreen, a national Jewish genetic disease screening program. The program includes a national marketing and PR campaign, online education, at-home saliva-based screening, post-test genetic counseling via telephone or secure video conferencing, and referrals for face-to-face genetic counseling as needed. Our goals are to create a successful education and screening program for this population and to develop a model that could potentially be used for other at-risk populations.

The Genetic Blues: Understanding Genetic Principles Using a Practical Approach and a Historical Perspective.

ERIC Educational Resources Information Center

Mysliwiec, Tami H.

2003-01-01

Incorporates history and genetics to explain how genetic traits are passed on to the next generation by focusing on methemoglobinemia, a rare genetic disease, and discusses how oxygen is carried by hemoglobin. Includes individual pedigree analysis and class pedigree analysis. (YDS)

COMPLEXO: identifying the missing heritability of breast cancer via next generation collaboration.

PubMed

Southey, Melissa C; Park, Daniel J; Nguyen-Dumont, Tu; Campbell, Ian; Thompson, Ella; Trainer, Alison H; Chenevix-Trench, Georgia; Simard, Jacques; Dumont, Martine; Soucy, Penny; Thomassen, Mads; Jønson, Lars; Pedersen, Inge S; Hansen, Thomas Vo; Nevanlinna, Heli; Khan, Sofia; Sinilnikova, Olga; Mazoyer, Sylvie; Lesueur, Fabienne; Damiola, Francesca; Schmutzler, Rita; Meindl, Alfons; Hahnen, Eric; Dufault, Michael R; Chris Chan, Tl; Kwong, Ava; Barkardóttir, Rosa; Radice, Paolo; Peterlongo, Paolo; Devilee, Peter; Hilbers, Florentine; Benitez, Javier; Kvist, Anders; Törngren, Therese; Easton, Douglas; Hunter, David; Lindstrom, Sara; Kraft, Peter; Zheng, Wei; Gao, Yu-Tang; Long, Jirong; Ramus, Susan; Feng, Bing-Jian; Weitzel, Jeffrey N; Nathanson, Katherine; Offit, Kenneth; Joseph, Vijai; Robson, Mark; Schrader, Kasmintan; Wang, San; Kim, Yeong C; Lynch, Henry; Snyder, Carrie; Tavtigian, Sean; Neuhausen, Susan; Couch, Fergus J; Goldgar, David E

2013-06-21

Linkage analysis, positional cloning, candidate gene mutation scanning and genome-wide association study approaches have all contributed significantly to our understanding of the underlying genetic architecture of breast cancer. Taken together, these approaches have identified genetic variation that explains approximately 30% of the overall familial risk of breast cancer, implying that more, and likely rarer, genetic susceptibility alleles remain to be discovered.

Argo_CUDA: Exhaustive GPU based approach for motif discovery in large DNA datasets.

PubMed

Vishnevsky, Oleg V; Bocharnikov, Andrey V; Kolchanov, Nikolay A

2018-02-01

The development of chromatin immunoprecipitation sequencing (ChIP-seq) technology has revolutionized the genetic analysis of the basic mechanisms underlying transcription regulation and led to accumulation of information about a huge amount of DNA sequences. There are a lot of web services which are currently available for de novo motif discovery in datasets containing information about DNA/protein binding. An enormous motif diversity makes their finding challenging. In order to avoid the difficulties, researchers use different stochastic approaches. Unfortunately, the efficiency of the motif discovery programs dramatically declines with the query set size increase. This leads to the fact that only a fraction of top "peak" ChIP-Seq segments can be analyzed or the area of analysis should be narrowed. Thus, the motif discovery in massive datasets remains a challenging issue. Argo_Compute Unified Device Architecture (CUDA) web service is designed to process the massive DNA data. It is a program for the detection of degenerate oligonucleotide motifs of fixed length written in 15-letter IUPAC code. Argo_CUDA is a full-exhaustive approach based on the high-performance GPU technologies. Compared with the existing motif discovery web services, Argo_CUDA shows good prediction quality on simulated sets. The analysis of ChIP-Seq sequences revealed the motifs which correspond to known transcription factor binding sites.

Rapid identification of kidney cyst mutations by whole exome sequencing in zebrafish

PubMed Central

Ryan, Sean; Willer, Jason; Marjoram, Lindsay; Bagwell, Jennifer; Mankiewicz, Jamie; Leshchiner, Ignaty; Goessling, Wolfram; Bagnat, Michel; Katsanis, Nicholas

2013-01-01

Forward genetic approaches in zebrafish have provided invaluable information about developmental processes. However, the relative difficulty of mapping and isolating mutations has limited the number of new genetic screens. Recent improvements in the annotation of the zebrafish genome coupled to a reduction in sequencing costs prompted the development of whole genome and RNA sequencing approaches for gene discovery. Here we describe a whole exome sequencing (WES) approach that allows rapid and cost-effective identification of mutations. We used our WES methodology to isolate four mutations that cause kidney cysts; we identified novel alleles in two ciliary genes as well as two novel mutants. The WES approach described here does not require specialized infrastructure or training and is therefore widely accessible. This methodology should thus help facilitate genetic screens and expedite the identification of mutants that can inform basic biological processes and the causality of genetic disorders in humans. PMID:24130329