Genetic privacy in sports: clearing the hurdles.

PubMed

Callier, Shawneequa

2012-12-01

As genomic medicine continues to advance and inform clinical care, knowledge gained is likely to influence sports medicine and training practices. Susceptibility to injury, sudden cardiac failure, and other serious conditions may one day be tackled on a subclinical level through genetic testing programs. In addition, athletes may increasingly consider using genetic testing services to maximize their performance potential. This paper assesses the role of privacy and genetic discrimination laws that would apply to athletes who engage in genetic testing and the limits of these protections.

Genetic conservation in applied tree breeding programs.

Treesearch

R. Johnson; B. St. Clair; S. Lipow

2001-01-01

This paper reviews how population size and structure impacts the maintenance of genetic variation in breeding and gene resource populations. We discuss appropriate population sizes for low frequency alleles and point out some examples of low frequency alleles in the literature. Development of appropriate breeding populations and gene resource populations are discussed...

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.

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.

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.

Microchip capillary gel electrophoresis using programmed field strength gradients for the ultra-fast analysis of genetically modified organisms in soybeans.

PubMed

Kim, Yun-Jeong; Chae, Joon-Seok; Chang, Jun Keun; Kang, Seong Ho

2005-08-12

We have developed a novel method for the ultra-fast analysis of genetically modified organisms (GMOs) in soybeans by microchip capillary gel electrophoresis (MCGE) using programmed field strength gradients (PFSG) in a conventional glass double-T microchip. Under the programmed electric field strength and 0.3% poly(ethylene oxide) sieving matrix, the GMO in soybeans was analyzed within only 11 s of the microchip. The MCGE-PFSG method was a program that changes the electric field strength during GMO analysis, and was also applied to the ultra-fast analysis of PCR products. Compared to MCGE using a conventional and constantly applied electric field, the MCGE-PFSG analysis generated faster results without the loss of resolving power and reproducibility for specific DNA fragments (100- and 250-bp DNA) of GM-soybeans. The MCGE-PFSG technique may prove to be a new tool in the GMO analysis due to its speed, simplicity, and high efficiency.

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.

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.

Mendelian Genetics: Paradigm, Conjecture, or Research Program.

ERIC Educational Resources Information Center

Oldham, V.; Brouwer, W.

1984-01-01

Applies Kuhn's model of the structure of scientific revolutions, Popper's hypothetic-deductive model of science, and Lakatos' methodology of competing research programs to a historical biological episode. Suggests using Kuhn's model (emphasizing the nonrational basis of science) and Popper's model (emphasizing the rational basis of science) in…

Somatic embryogenesis tissue culture for applying varietal forestry to conifer species

Treesearch

Steven C. Grossnickle; John Pait

2008-01-01

The use of tree improvement practices to enhance the genetic characteristics of planted seedlings is a forestry practice that consistently shows a high return on investment by increasing yields obtained from planted forests. The use of improved seeds is an effective way of bringing genetic improvement to forest regeneration programs. Seed orchards are currently used to...

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.

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

PubMed

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

2003-05-01

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

Senior Computational Scientist | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) pursues independent, multidisciplinary research in basic and applied molecular biology, immunology, retrovirology, cancer biology, and human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick National Laboratory for Cancer Research (FNLCR). The Cancer & Inflammation Program (CIP),

Applying Medical Anthropology: Developing Diabetes Education and Prevention Programs in American Indian Cultures.

ERIC Educational Resources Information Center

Olson, Brooke

1999-01-01

Medical anthropology provides a broader contextual framework for understanding complex causal factors associated with diabetes among American Indians and how to minimize these factors in education/treatment programs. Discusses historical, epidemiological, and genetic considerations in American Indian diabetes; cultural factors related to foods,…

Secretary | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) pursues independent, multidisciplinary research programs in basic or applied molecular biology, immunology, retrovirology, cancer biology, or human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick national Laboratory for Cancer Research (FNLCR). The BSP Office provides

A Parallel Genetic Algorithm for Automated Electronic Circuit Design

NASA Technical Reports Server (NTRS)

Lohn, Jason D.; Colombano, Silvano P.; Haith, Gary L.; Stassinopoulos, Dimitris; Norvig, Peter (Technical Monitor)

2000-01-01

We describe a parallel genetic algorithm (GA) that automatically generates circuit designs using evolutionary search. A circuit-construction programming language is introduced and we show how evolution can generate practical analog circuit designs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. We present experimental results as applied to analog filter and amplifier design tasks.

Index-in-retrospect and breeding objectives characterizing genetic improvement programs for South African Nguni cattle

USDA-ARS?s Scientific Manuscript database

The objective of the current study was to describe the historical selection applied to Nguni cattle in South Africa. Index-in-retrospect methods were applied to data originating from the National Beef Cattle Improvement Scheme. Data used were estimated breeding values (EBV) for animals born during t...

Genetic programming based ensemble system for microarray data classification.

PubMed

Liu, Kun-Hong; Tong, Muchenxuan; Xie, Shu-Tong; Yee Ng, Vincent To

2015-01-01

Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP) based new ensemble system (named GPES), which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved.

Genetic Programming Based Ensemble System for Microarray Data Classification

PubMed Central

Liu, Kun-Hong; Tong, Muchenxuan; Xie, Shu-Tong; Yee Ng, Vincent To

2015-01-01

Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP) based new ensemble system (named GPES), which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved. PMID:25810748

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.

Postdoctoral Fellows | Center for Cancer Research

Cancer.gov

The Oncogenomics section of the Genetics Branch is a multidisciplinary and interdisciplinary translational research programmatic effort with the goal of utilizing genomics to develop novel immunotherapies for cancer. Our group is applying high throughput applied genomics methods including single cell RNAseq, single cell TCR sequencing, DNA sequencing, CRISPR/Cas9, bioinformatics combined with T cell based therapeutics to identify and develop novel immunotherapeutics for human cancer. We work with other investigators within the intramural program as well as industrial and pharmaceutical partners to rapidly translate our findings to the clinic. The program takes advantage of the uniqueness of the National Cancer Institute, (NCI), Center for Cancer Research (CCR) intramural program in that it spans high-risk basic discovery research in immunology, genomics and tumor biology, through preclinical translational research, to paradigm-shifting clinical trials. The position is available immediately. The appointment duration is up to 5 years. Stipends are commensurate with education and experience. Additional information can be found on Dr. Khan’s profile page: https://ccr.cancer.gov/Genetics-Branch/javed-khan

Tipping Points in Seaweed Genetic Engineering: Scaling Up Opportunities in the Next Decade

PubMed Central

Lin, Hanzhi; Qin, Song

2014-01-01

Seaweed genetic engineering is a transgenic expression system with unique features compared with those of heterotrophic prokaryotes and higher plants. This study discusses several newly sequenced seaweed nuclear genomes and the necessity that research on vector design should consider endogenous promoters, codon optimization, and gene copy number. Seaweed viruses and artificial transposons can be applied as transformation methods after acquiring a comprehensive understanding of the mechanism of viral infections in seaweeds and transposon patterns in seaweed genomes. After cultivating transgenic algal cells and tissues in a photobioreactor, a biosafety assessment of genetically modified (GM) seaweeds must be conducted before open-sea application. We propose a set of programs for the evaluation of gene flow from GM seaweeds to local/geographical environments. The effective implementation of such programs requires fundamentally systematic and interdisciplinary studies on algal physiology and genetics, marine hydrology, reproductive biology, and ecology. PMID:24857961

Tipping points in seaweed genetic engineering: scaling up opportunities in the next decade.

PubMed

Lin, Hanzhi; Qin, Song

2014-05-22

Seaweed genetic engineering is a transgenic expression system with unique features compared with those of heterotrophic prokaryotes and higher plants. This study discusses several newly sequenced seaweed nuclear genomes and the necessity that research on vector design should consider endogenous promoters, codon optimization, and gene copy number. Seaweed viruses and artificial transposons can be applied as transformation methods after acquiring a comprehensive understanding of the mechanism of viral infections in seaweeds and transposon patterns in seaweed genomes. After cultivating transgenic algal cells and tissues in a photobioreactor, a biosafety assessment of genetically modified (GM) seaweeds must be conducted before open-sea application. We propose a set of programs for the evaluation of gene flow from GM seaweeds to local/geographical environments. The effective implementation of such programs requires fundamentally systematic and interdisciplinary studies on algal physiology and genetics, marine hydrology, reproductive biology, and ecology.

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.

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.

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

NASA Technical Reports Server (NTRS)

Mog, Robert A.

1999-01-01

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

Genetic programs constructed from layered logic gates in single cells

PubMed Central

Moon, Tae Seok; Lou, Chunbo; Tamsir, Alvin; Stanton, Brynne C.; Voigt, Christopher A.

2014-01-01

Genetic programs function to integrate environmental sensors, implement signal processing algorithms and control expression dynamics1. These programs consist of integrated genetic circuits that individually implement operations ranging from digital logic to dynamic circuits2–6, and they have been used in various cellular engineering applications, including the implementation of process control in metabolic networks and the coordination of spatial differentiation in artificial tissues. A key limitation is that the circuits are based on biochemical interactions occurring in the confined volume of the cell, so the size of programs has been limited to a few circuits1,7. Here we apply part mining and directed evolution to build a set of transcriptional AND gates in Escherichia coli. Each AND gate integrates two promoter inputs and controls one promoter output. This allows the gates to be layered by having the output promoter of an upstream circuit serve as the input promoter for a downstream circuit. Each gate consists of a transcription factor that requires a second chaperone protein to activate the output promoter. Multiple activator–chaperone pairs are identified from type III secretion pathways in different strains of bacteria. Directed evolution is applied to increase the dynamic range and orthogonality of the circuits. These gates are connected in different permutations to form programs, the largest of which is a 4-input AND gate that consists of 3 circuits that integrate 4 inducible systems, thus requiring 11 regulatory proteins. Measuring the performance of individual gates is sufficient to capture the behaviour of the complete program. Errors in the output due to delays (faults), a common problem for layered circuits, are not observed. This work demonstrates the successful layering of orthogonal logic gates, a design strategy that could enable the construction of large, integrated circuits in single cells. PMID:23041931

Genetic architecture of sex determination in fish: applications to sex ratio control in aquaculture

PubMed Central

Martínez, Paulino; Viñas, Ana M.; Sánchez, Laura; Díaz, Noelia; Ribas, Laia; Piferrer, Francesc

2014-01-01

Controlling the sex ratio is essential in finfish farming. A balanced sex ratio is usually good for broodstock management, since it enables to develop appropriate breeding schemes. However, in some species the production of monosex populations is desirable because the existence of sexual dimorphism, primarily in growth or first time of sexual maturation, but also in color or shape, can render one sex more valuable. The knowledge of the genetic architecture of sex determination (SD) is convenient for controlling sex ratio and for the implementation of breeding programs. Unlike mammals and birds, which show highly conserved master genes that control a conserved genetic network responsible for gonad differentiation (GD), a huge diversity of SD mechanisms has been reported in fish. Despite theory predictions, more than one gene is in many cases involved in fish SD and genetic differences have been observed in the GD network. Environmental factors also play a relevant role and epigenetic mechanisms are becoming increasingly recognized for the establishment and maintenance of the GD pathways. Although major genetic factors are frequently involved in fish SD, these observations strongly suggest that SD in this group resembles a complex trait. Accordingly, the application of quantitative genetics combined with genomic tools is desirable to address its study and in fact, when applied, it has frequently demonstrated a multigene trait interacting with environmental factors in model and cultured fish species. This scenario has notable implications for aquaculture and, depending upon the species, from chromosome manipulation or environmental control techniques up to classical selection or marker assisted selection programs, are being applied. In this review, we selected four relevant species or fish groups to illustrate this diversity and hence the technologies that can be used by the industry for the control of sex ratio: turbot and European sea bass, two reference species of the European aquaculture, and salmonids and tilapia, representing the fish for which there are well established breeding programs. PMID:25324858

[The haplomatch program for comparing Y-chromosome STR-haplotypes and its application to the analysis of the origin of Don Cossacks].

PubMed

Chukhryaeva, M I; Ivanov, I O; Frolova, S A; Koshel, S M; Utevska, O M; Skhalyakho, R A; Agdzhoyan, A T; Bogunov, Yu V; Balanovska, E V; Balanovsky, O P

2016-05-01

STR haplotypes of the Y chromosome are widely used as effective genetic markers in studies of human populations and in forensic DNA analysis. The task often arises to compare the spectrum of haplotypes in individuals or entire populations. Performing this task manually is too laborious and thus unrealistic. We propose an algorithm for counting similarity between STR haplotypes. This algorithm is suitable for massive analyses of samples. It is implemented in the computer program Haplomatch, which makes it possible to find haplotypes that differ from the target haplotype by 0, 1, 2, 3, or more mutational steps. The program may operate in two modes: comparison of individuals and comparison of populations. Flexibility of the program (the possibility of using any external database), its usability (MS Excel spreadsheets are used), and the capability of being applied to other chromosomes and other species could make this software a new useful tool in population genetics and forensic and genealogical studies. The Haplomatch software is freely available on our website www.genofond.ru. The program is applied to studying the gene pool of Cossacks. Experimental analysis of Y-chromosomal diversity in a representative set (N = 131) of Upper Don Cossacks is performed. Analysis of the STR haplotypes detects genetic proximity of Cossacks to East Slavic populations (in particular, to Southern and Central Russians, as well as to Ukrainians), which confirms the hypothesis of the origin of the Cossacks mainly due to immigration from Russia and Ukraine. Also, a small genetic influence of Turkicspeaking Nogais is found, probably caused by their occurrence in the Don Voisko as part of the Tatar layer. No similarities between haplotype spectra of Cossacks and Caucasus populations are found. This case study demonstrates the effectiveness of the Haplomatch software in analyzing large sets of STR haplotypes.

Graph Structured Program Evolution: Evolution of Loop Structures

NASA Astrophysics Data System (ADS)

Shirakawa, Shinichi; Nagao, Tomoharu

Recently, numerous automatic programming techniques have been developed and applied in various fields. A typical example is genetic programming (GP), and various extensions and representations of GP have been proposed thus far. Complex programs and hand-written programs, however, may contain several loops and handle multiple data types. In this chapter, we propose a new method called Graph Structured Program Evolution (GRAPE). The representation of GRAPE is a graph structure; therefore, it can represent branches and loops using this structure. Each programis constructed as an arbitrary directed graph of nodes and a data set. The GRAPE program handles multiple data types using the data set for each type, and the genotype of GRAPE takes the form of a linear string of integers. We apply GRAPE to three test problems, factorial, exponentiation, and list sorting, and demonstrate that the optimum solution in each problem is obtained by the GRAPE system.

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

TIP: protein backtranslation aided by genetic algorithms.

PubMed

Moreira, Andrés; Maass, Alejandro

2004-09-01

Several applications require the backtranslation of a protein sequence into a nucleic acid sequence. The degeneracy of the genetic code makes this process ambiguous; moreover, not every translation is equally viable. The usual answer is to mimic the codon usage of the target species; however, this does not capture all the relevant features of the 'genomic styles' from different taxa. The program TIP ' Traducción Inversa de Proteínas') applies genetic algorithms to improve the backtranslation, by minimizing the difference of some coding statistics with respect to their average value in the target. http://www.cmm.uchile.cl/genoma/tip/

Competency-Based Education for the Molecular Genetic Pathology Fellow

PubMed Central

Talbert, Michael L.; Dunn, S. Terence; Hunt, Jennifer; Hillyard, David R.; Mirza, Imran; Nowak, Jan A.; Van Deerlin, Vivianna; Vnencak-Jones, Cindy L.

2009-01-01

The following report represents guidelines for competency-based fellowship training in Molecular Genetic Pathology (MGP) developed by the Association for Molecular Pathology Training and Education Committee and Directors of MGP Programs in the United States. The goals of the effort were to describe each of the Accreditation Council for Graduate Medical Education competencies as they apply to MGP fellowship training, provide a summary of goals and objectives, and recommend assessment tools. These guidelines are particularly pertinent to MGP training, which is a relatively new specialty that operates within a rapidly changing scientific and technological arena. It is hoped that this document will provide additional material for directors of existing MGP programs to consider for improvement of program objectives and enhancement of evaluation tools already in place. In addition, the guidelines should provide a valuable framework for the development of new MGP programs. PMID:19797613

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.

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.

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

Estimation of the genetic diversity in tetraploid alfalfa populations based on RAPD markers for breeding purposes.

PubMed

Nagl, Nevena; Taski-Ajdukovic, Ksenija; Barac, Goran; Baburski, Aleksandar; Seccareccia, Ivana; Milic, Dragan; Katic, Slobodan

2011-01-01

Alfalfa is an autotetraploid, allogamous and heterozygous forage legume, whose varieties are synthetic populations. Due to the complex nature of the species, information about genetic diversity of germplasm used in any alfalfa breeding program is most beneficial. The genetic diversity of five alfalfa varieties, involved in progeny tests at Institute of Field and Vegetable Crops, was characterized based on RAPD markers. A total of 60 primers were screened, out of which 17 were selected for the analysis of genetic diversity. A total of 156 polymorphic bands were generated, with 10.6 bands per primer. Number and percentage of polymorphic loci, effective number of alleles, expected heterozygosity and Shannon's information index were used to estimate genetic variation. Variety Zuzana had the highest values for all tested parameters, exhibiting the highest level of variation, whereas variety RSI 20 exhibited the lowest. Analysis of molecular variance (AMOVA) showed that 88.39% of the total genetic variation was attributed to intra-varietal variance. The cluster analysis for individual samples and varieties revealed differences in their population structures: variety Zuzana showed a very high level of genetic variation, Banat and Ghareh were divided in subpopulations, while Pecy and RSI 20 were relatively uniform. Ways of exploiting the investigated germplasm in the breeding programs are suggested in this paper, depending on their population structure and diversity. The RAPD analysis shows potential to be applied in analysis of parental populations in semi-hybrid alfalfa breeding program in both, development of new homogenous germplasm, and identification of promising, complementary germplasm.

Registration of USDA-UTWH-102 winter hardy orchardgrass germplasm

USDA-ARS?s Scientific Manuscript database

The USDA-ARS announces the release of USDA-UTWG-102 orchardgrass (Dactylis glomerata L.) (Reg. No., PI) germplasm. USDA-UTWH-102 possesses increased winter hardiness and provides utility to applied orchardgrass breeding and genetic programs. USDA-UTWH-102 is a 24 clone synthetic derived from orchard...

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.

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.

Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection

NASA Astrophysics Data System (ADS)

Kashid, S. S.; Ghosh, Subimal; Maity, Rajib

2010-12-01

SummarySimultaneous variations in weather and climate over widely separated regions are commonly known as "hydroclimatic teleconnections". Rainfall and runoff patterns, over continents, are found to be significantly teleconnected, with large-scale circulation patterns, through such hydroclimatic teleconnections. Though such teleconnections exist in nature, it is very difficult to model them, due to their inherent complexity. Statistical techniques and Artificial Intelligence (AI) tools gain popularity in modeling hydroclimatic teleconnection, based on their ability, in capturing the complicated relationship between the predictors (e.g. sea surface temperatures) and predictand (e.g., rainfall). Genetic Programming is such an AI tool, which is capable of capturing nonlinear relationship, between predictor and predictand, due to its flexible functional structure. In the present study, gridded multi-site weekly rainfall is predicted from El Niño Southern Oscillation (ENSO) indices, Equatorial Indian Ocean Oscillation (EQUINOO) indices, Outgoing Longwave Radiation (OLR) and lag rainfall at grid points, over the catchment, using Genetic Programming. The predicted rainfall is further used in a Genetic Programming model to predict streamflows. The model is applied for weekly forecasting of streamflow in Mahanadi River, India, and satisfactory performance is observed.

Prediction of cancer class with majority voting genetic programming classifier using gene expression data.

PubMed

Paul, Topon Kumar; Iba, Hitoshi

2009-01-01

In order to get a better understanding of different types of cancers and to find the possible biomarkers for diseases, recently, many researchers are analyzing the gene expression data using various machine learning techniques. However, due to a very small number of training samples compared to the huge number of genes and class imbalance, most of these methods suffer from overfitting. In this paper, we present a majority voting genetic programming classifier (MVGPC) for the classification of microarray data. Instead of a single rule or a single set of rules, we evolve multiple rules with genetic programming (GP) and then apply those rules to test samples to determine their labels with majority voting technique. By performing experiments on four different public cancer data sets, including multiclass data sets, we have found that the test accuracies of MVGPC are better than those of other methods, including AdaBoost with GP. Moreover, some of the more frequently occurring genes in the classification rules are known to be associated with the types of cancers being studied in this paper.

Telegenetics: application of a tele-education program in genetic syndromes for Brazilian students

PubMed Central

MAXIMINO, Luciana Paula; PICOLINI-PEREIRA, Mirela Machado; CARVALHO, José Luiz Brito

2014-01-01

With the high occurrence of genetic anomalies in Brazil and the manifestations of communication disorders associated with these conditions, the development of educative actions that comprise these illnesses can bring unique benefits in the identification and appropriate treatment of these clinical pictures. Objective The aim of this study was to develop and analyze an educational program in genetic syndromes for elementary students applied in two Brazilian states, using an Interactive Tele-education model. Material and Methods The study was carried out in 4 schools: two in the state of São Paulo, Southeast Region, Brazil, and two in the state of Amazonas, North Region, Brazil. Forty-five students, both genders, aged between 13 and 14 years, of the 9th grade of the basic education of both public and private system, were divided into two groups: 21 of São Paulo Group (SPG) and 24 of Amazonas Group (AMG). The educational program lasted about 3 months and was divided into two stages including both classroom and distance activities on genetic syndromes. The classroom activity was carried out separately in each school, with expository lessons, graphs and audiovisual contents. In the activity at a distance the educational content was presented to students by means of the Interactive Tele-education model. In this stage, the students had access a Cybertutor, using the Young Doctor Project methodology. In order to measure the effectiveness of the educational program, the Problem Situation Questionnaire (PSQ) and the Web Site Motivational Analysis Checklist adapted (FPM) were used. Results The program developed was effective for knowledge acquisition in 80% of the groups. FPM showed a high satisfaction index from the participants in relation to the Interactive Tele-education, evaluating the program as "awesome course". No statistically significant differences between the groups regarding type of school or state were observed. Conclusion Thus, the Tele-Education Program can be used as a tool for educational purposes in genetic syndromes of other populations, in several regions of Brazil. PMID:25591016

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.

Ethical Dilemmas for Oocyte Donations: Slippery Slope for Conflicts of Interest.

PubMed

Tulay, Pinar

2016-01-01

Oocyte donations have increased with improvements in oocyte cryopreservation procedures in recent years. Women with medical conditions that require chemotherapy or radiotherapy have begun to opt for oocyte cryo¬preservation prior to their treatment or to enroll in an oocyte donation program. Alternatively, some women apply for "third-party" oocyte donation programs for nonmedical reasons such as delayed childbearing. Although society seems to accept oocyte donations for medical reasons, it appears that there are still some moral issues surrounding nonmedical oocyte donations. In this review, the ethical aspects of oocyte donations and donors' perspectives are discussed. With developing technologies, the genetic screening of donors has expanded to include diseases. This review explores the ethical issues involved in genetic screening of gamete donors.

Multitask visual learning using genetic programming.

PubMed

Jaśkowski, Wojciech; Krawiec, Krzysztof; Wieloch, Bartosz

2008-01-01

We propose a multitask learning method of visual concepts within the genetic programming (GP) framework. Each GP individual is composed of several trees that process visual primitives derived from input images. Two trees solve two different visual tasks and are allowed to share knowledge with each other by commonly calling the remaining GP trees (subfunctions) included in the same individual. The performance of a particular tree is measured by its ability to reproduce the shapes contained in the training images. We apply this method to visual learning tasks of recognizing simple shapes and compare it to a reference method. The experimental verification demonstrates that such multitask learning often leads to performance improvements in one or both solved tasks, without extra computational effort.

Relations of mitochondrial genetic variants to measures of vascular function.

PubMed

Fetterman, Jessica L; Liu, Chunyu; Mitchell, Gary F; Vasan, Ramachandran S; Benjamin, Emelia J; Vita, Joseph A; Hamburg, Naomi M; Levy, Daniel

2018-05-01

Mitochondrial genetic variation with resultant alterations in oxidative phosphorylation may influence vascular function and contribute to cardiovascular disease susceptibility. We assessed relations of peptide-encoding variants in the mitochondrial genome with measures of vascular function in Framingham Heart Study participants. Of 258 variants assessed, 40 were predicted to have functional consequences by bioinformatics programs. A maternal pattern of heritability was estimated to contribute to the variability of aortic stiffness. A putative association with a microvascular function measure was identified that requires replication. The methods we have developed can be applied to assess the relations of mitochondrial genetic variation to other phenotypes. Copyright © 2017 Elsevier B.V. and Mitochondria Research Society. All rights reserved.

A serious gaming/immersion environment to teach clinical cancer genetics.

PubMed

Nosek, Thomas M; Cohen, Mark; Matthews, Anne; Papp, Klara; Wolf, Nancy; Wrenn, Gregg; Sher, Andrew; Coulter, Kenneth; Martin, Jessica; Wiesner, Georgia L

2007-01-01

We are creating an interactive, simulated "Cancer Genetics Tower" for the self-paced learning of Clinical Cancer Genetics by medical students (go to: http://casemed.case.edu/cancergenetics). The environment uses gaming theory to engage the students into achieving specific learning objectives. The first few levels contain virtual laboratories where students achieve the basic underpinnings of Cancer Genetics. The next levels apply these principles to clinical practice. A virtual attending physician and four virtual patients, available for questioning through virtual video conferencing, enrich each floor. The pinnacle clinical simulation challenges the learner to integrate all information and demonstrate mastery, thus "winning" the game. A pilot test of the program by 17 medical students yielded very favorable feedback; the students found the Tower a "great way to teach", it held their attention, and it made learning fun. A majority of the students preferred the Tower over other resources to learn Cancer Genetics.

Current seed orchard techniques and innovations

Treesearch

Lawrence K. Miller; Jeffrey DeBell

2013-01-01

As applied forest tree improvement programs in the US Northwest move forward into the third cycle, seed orchards remain as the primary source of genetically improved forest tree seed used for reforestation. The vast majority of seed orchards in this region are coastal Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), consistent with the high economic importance of...

LPmerge: an R package for merging genetic maps by linear programming.

PubMed

Endelman, Jeffrey B; Plomion, Christophe

2014-06-01

Consensus genetic maps constructed from multiple populations are an important resource for both basic and applied research, including genome-wide association analysis, genome sequence assembly and studies of evolution. The LPmerge software uses linear programming to efficiently minimize the mean absolute error between the consensus map and the linkage maps from each population. This minimization is performed subject to linear inequality constraints that ensure the ordering of the markers in the linkage maps is preserved. When marker order is inconsistent between linkage maps, a minimum set of ordinal constraints is deleted to resolve the conflicts. LPmerge is on CRAN at http://cran.r-project.org/web/packages/LPmerge. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Modelling the effect of structural QSAR parameters on skin penetration using genetic programming

NASA Astrophysics Data System (ADS)

Chung, K. K.; Do, D. Q.

2010-09-01

In order to model relationships between chemical structures and biological effects in quantitative structure-activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data.

Sterility and Sexual Competitiveness of Tapachula-7 Anastrepha ludens Males Irradiated at Different Doses.

PubMed

Orozco-Dávila, Dina; Adriano-Anaya, Maria de Lourdes; Quintero-Fong, Luis; Salvador-Figueroa, Miguel

2015-01-01

A genetic sexing strain of Anastrepha ludens (Loew), Tapachula-7, was developed by the Mexican Program Against Fruit Flies to produce and release only males in programs where the sterile insect technique (SIT) is applied. Currently, breeding are found at a massive scale, and it is necessary to determine the optimum irradiation dose that releases sterile males with minimum damage to their sexual competitiveness. Under laboratory and field conditions, we evaluated the effects of gamma irradiation at doses of 0, 20, 40, 60 and 80 Gy on the sexual competitiveness of males, the induction of sterility in wild females and offspring survivorship. The results of the study indicate that irradiation doses have a significant effect on the sexual behavior of males. A reduction of mating capacity was inversely proportional to the irradiation dose of males. It is estimated that a dose of 60 Gy can induce more than 99% sterility in wild females. In all treatments, the degree of offspring fertility was correlated with the irradiation dose of the parents. In conclusion, the results of the study indicate that a dose of 60 Gy can be applied in sterile insect technique release programs. The application of this dose in the new genetic sexing strain of A. ludens is discussed.

Sterility and Sexual Competitiveness of Tapachula-7 Anastrepha ludens Males Irradiated at Different Doses

PubMed Central

Orozco-Dávila, Dina; Adriano-Anaya, Maria de Lourdes; Quintero-Fong, Luis; Salvador-Figueroa, Miguel

2015-01-01

A genetic sexing strain of Anastrepha ludens (Loew), Tapachula-7, was developed by the Mexican Program Against Fruit Flies to produce and release only males in programs where the sterile insect technique (SIT) is applied. Currently, breeding are found at a massive scale, and it is necessary to determine the optimum irradiation dose that releases sterile males with minimum damage to their sexual competitiveness. Under laboratory and field conditions, we evaluated the effects of gamma irradiation at doses of 0, 20, 40, 60 and 80 Gy on the sexual competitiveness of males, the induction of sterility in wild females and offspring survivorship. The results of the study indicate that irradiation doses have a significant effect on the sexual behavior of males. A reduction of mating capacity was inversely proportional to the irradiation dose of males. It is estimated that a dose of 60 Gy can induce more than 99% sterility in wild females. In all treatments, the degree of offspring fertility was correlated with the irradiation dose of the parents. In conclusion, the results of the study indicate that a dose of 60 Gy can be applied in sterile insect technique release programs. The application of this dose in the new genetic sexing strain of A. ludens is discussed. PMID:26274926

Catalysis and biocatalysis program

NASA Technical Reports Server (NTRS)

1991-01-01

The annual report presents the fiscal year (FY) 1990 research activities and accomplishments for the Catalysis and Biocatalysis Program of the Advanced Industrial Concepts Division (AICD), Office of Industrial Technologies of the Department of Energy (DOE). The mission of the AICD is to create a balanced program of high risk, long term, directed interdisciplinary research and development that will improve energy efficiency and enhance fuel flexibility in the industrial sector. The Catalysis and Biocatalysis Program's technical activities were organized into five work elements: the Molecular Modeling and Catalysis by Design element; the Applied Microbiology and Genetics element; the Bioprocess Engineering element; the Separations and Novel Chemical Processes element; and the Process Design and Analysis element.

Evolution and coevolution of developmental programs

NASA Astrophysics Data System (ADS)

Jacob, Christian

1999-09-01

The developmental processes of single organisms, such as growth and structure formation, can be described by parallel rewrite systems in the form of Lindenmayer systems, which also allow one to generate geometrical structures in 3D space using turtle interpretation. We present examples of L-systems for growth programs of plant-like structures. Evolution-based programming techniques are applied to design L-systems by Genetic L-system Programming (GLP), demonstrating how developmental programs for plants, exhibiting specific morphogenetic properties can be interactively bred or automatically evolved. Finally, we demonstrate coevolutionary effects among plant populations consisting of different species, interacting with each other, competing for resources like sunlight and nutrients, and evolving successful reproduction strategies in their specific environments.

Molecular markers: a potential resource for ginger genetic diversity studies.

PubMed

Ismail, Nor Asiah; Rafii, M Y; Mahmud, T M M; Hanafi, M M; Miah, Gous

2016-12-01

Ginger is an economically important and valuable plant around the world. Ginger is used as a food, spice, condiment, medicine and ornament. There is available information on biochemical aspects of ginger, but few studies have been reported on its molecular aspects. The main objective of this review is to accumulate the available molecular marker information and its application in diverse ginger studies. This review article was prepared by combing material from published articles and our own research. Molecular markers allow the identification and characterization of plant genotypes through direct access to hereditary material. In crop species, molecular markers are applied in different aspects and are useful in breeding programs. In ginger, molecular markers are commonly used to identify genetic variation and classify the relatedness among varieties, accessions, and species. Consequently, it provides important input in determining resourceful management strategies for ginger improvement programs. Alternatively, a molecular marker could function as a harmonizing tool for documenting species. This review highlights the application of molecular markers (isozyme, RAPD, AFLP, SSR, ISSR and others such as RFLP, SCAR, NBS and SNP) in genetic diversity studies of ginger species. Some insights on the advantages of the markers are discussed. The detection of genetic variation among promising cultivars of ginger has significance for ginger improvement programs. This update of recent literature will help researchers and students select the appropriate molecular markers for ginger-related research.

Take Russia to 'task' on bioweapons transparency.

PubMed

Zilinskas, Raymond A

2012-06-06

In the run-up to his reelection, Russian president Vladimir Putin outlined 28 tasks to be undertaken by his administration, including one that commanded the development of weapons based on “genetic principles.” Political pressure must be applied by governments and professional societies to ensure that there is not a modern reincarnation of the Soviet biological warfare program.

Forensic assays of ricin: development of snp assays to generate precise genetic signatures for mixed genotypes found in ricin preparations

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

Jackson, Paul J.; Hill, Karen K.

2009-11-09

The results outlined in this report provide the information for needed to apply a SNP-based forensic analysis to diverse ricin preparations. The same methods could be useful in castor breeding programs that seek to reduce or eliminate ricin in oil-producing R. communis cultivars.

Reactions of female cheetahs (Acinonyx jubatus) to urine volatiles from males of varying genetic distance.

PubMed

Mossotti, Regina H; Baskir, Eli A; Kozlowski, Corinne P; Franklin, Ashley D; Feldhamer, George A; Asa, Cheryl S

2018-06-13

Understanding the factors used by female cheetahs (Acinonyx jubatus) to make mate choice decisions could benefit zoo breeding programs, which currently assign mates based primarily on genetic distance. Because transporting animals between institutions is costly and can be stressful, females are often limited in the number of males available for mating. One solution would be to determine if an easily transported substance could be used to gauge interest by a female to a potential mate. Here, we investigate female interest in urine samples from males of different genetic distances. Twelve females at five institutions were offered scents from 17 males of varying genetic relatedness in a pair-wise choice paradigm. Behavioral responses of the females were recorded to determine preference. Results showed that females spent more time sniffing and in proximity to scents from the most distantly related males, but female response was not influenced by male urine testosterone concentration, female parity, age, or estrous cycling. Further research will be necessary to determine whether a female's interest in male urine translates to mate preference and acceptance before this technique can be applied to zoo breeding programs. © 2018 Wiley Periodicals, Inc.

Genetic considerations for mollusk production in aquaculture: current state of knowledge

PubMed Central

Astorga, Marcela P.

2014-01-01

In 2012, world mollusk production in aquaculture reached a volume of 15,171,000 tons, representing 23% of total aquaculture production and positioning mollusks as the second most important category of aquaculture products (fishes are the first). Clams and oysters are the mollusk species with the highest production levels, followed in descending order by mussels, scallops, and abalones. In view of the increasing importance attached to genetic information on aquaculture, which can help with good maintenance and thus the sustainability of production, the present work offers a review of the state of knowledge on genetic and genomic information about mollusks produced in aquaculture. The analysis was applied to mollusks which are of importance for aquaculture, with emphasis on the 5 species with the highest production levels. According to FAO, these are: Japanese clam Ruditapes philippinarum; Pacific oyster Crassostrea gigas; Chilean mussel Mytilus chilensis; Blood clam Anadara granosa and Chinese clam Sinonovacula constricta. To date, the genomes of 5 species of mollusks have been sequenced, only one of which, Crassostrea gigas, coincides with the species with the greatest production in aquaculture. Another important species whose genome has been sequenced is Mytilus galloprovincialis, which is the second most important mussel in aquaculture production, after M. chilensis. Few genetic improvement programs have been reported in comparison with the number reported in fish species. The most commonly investigated species are oysters, with at least 5 genetic improvement programs reported, followed by abalones with 2 programs and mussels with one. The results of this work will establish the current situation with respect to the genetics of mollusks which are of importance for aquaculture production, in order to assist future decisions to ensure the sustainability of these resources. PMID:25540651

Phenological mismatch and the effectiveness of assisted gene flow.

PubMed

Wadgymar, Susana M; Weis, Arthur E

2017-06-01

The persistence of narrowly adapted species under climate change will depend on their ability to migrate apace with their historical climatic envelope or to adapt in place to maintain fitness. This second path to persistence can only occur if there is sufficient genetic variance for response to new selection regimes. Inadequate levels of genetic variation can be remedied through assisted gene flow (AGF), that is the intentional introduction of individuals genetically adapted to localities with historic climates similar to the current or future climate experienced by the resident population. However, the timing of reproduction is frequently adapted to local conditions. Phenological mismatch between residents and migrants can reduce resident × migrant mating frequencies, slowing the introgression of migrant alleles into the resident genetic background and impeding evolutionary rescue efforts. Focusing on plants, we devised a method to estimate the frequency of resident × migrant matings based on flowering schedules and applied it in an experiment that mimicked the first generation of an AGF program with Chamaecrista fasciculata, a prairie annual, under current and expected future temperature regimes. Phenological mismatch reduced the potential for resident × migrant matings by 40-90%, regardless of thermal treatment. The most successful migrant sires were the most resident like in their flowering time, further biasing the genetic admixture between resident and migrant populations. Other loci contributing to local adaptation-heat-tolerance genes, for instance-may be in linkage disequilibrium with phenology when residents and migrants are combined into a single mating pool. Thus, introgression of potentially adaptive migrant alleles into the resident genetic background is slowed when selection acts against migrant phenology. Successful AGF programs may require sustained high immigration rates or preliminary breeding programs when phenologically matched migrant source populations are unavailable. © 2016 Society for Conservation Biology.

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.

Senior Computational Scientist | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) pursues independent, multidisciplinary research in basic and applied molecular biology, immunology, retrovirology, cancer biology, and human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick National Laboratory for Cancer Research (FNLCR). The Cancer & Inflammation Program (CIP), Basic Science Program, HLA Immunogenetics Section, under the leadership of Dr. Mary Carrington, studies the influence of human leukocyte antigens (HLA) and specific KIR/HLA genotypes on risk of and outcomes to infection, cancer, autoimmune disease, and maternal-fetal disease. Recent studies have focused on the impact of HLA gene expression in disease, the molecular mechanism regulating expression levels, and the functional basis for the effect of differential expression on disease outcome. The lab’s further focus is on the genetic basis for resistance/susceptibility to disease conferred by immunogenetic variation. KEY ROLES/RESPONSIBILITIES The Senior Computational Scientist will provide research support to the CIP-BSP-HLA Immunogenetics Section performing bio-statistical design, analysis and reporting of research projects conducted in the lab. This individual will be involved in the implementation of statistical models and data preparation. Successful candidate should have 5 or more years of competent, innovative biostatistics/bioinformatics research experience, beyond doctoral training Considerable experience with statistical software, such as SAS, R and S-Plus Sound knowledge, and demonstrated experience of theoretical and applied statistics Write program code to analyze data using statistical analysis software Contribute to the interpretation and publication of research results

A multi-product green supply chain under government supervision with price and demand uncertainty

NASA Astrophysics Data System (ADS)

Hafezalkotob, Ashkan; Zamani, Soma

2018-05-01

In this paper, a bi-level game-theoretic model is proposed to investigate the effects of governmental financial intervention on green supply chain. This problem is formulated as a bi-level program for a green supply chain that produces various products with different environmental pollution levels. The problem is also regard uncertainties in market demand and sale price of raw materials and products. The model is further transformed into a single-level nonlinear programming problem by replacing the lower-level optimization problem with its Karush-Kuhn-Tucker optimality conditions. Genetic algorithm is applied as a solution methodology to solve nonlinear programming model. Finally, to investigate the validity of the proposed method, the computational results obtained through genetic algorithm are compared with global optimal solution attained by enumerative method. Analytical results indicate that the proposed GA offers better solutions in large size problems. Also, we conclude that financial intervention by government consists of green taxation and subsidization is an effective method to stabilize green supply chain members' performance.

Considering genetic characteristics in German Holstein breeding programs.

PubMed

Segelke, D; Täubert, H; Reinhardt, F; Thaller, G

2016-01-01

Recently, several research groups have demonstrated that several haplotypes may cause embryonic loss in the homozygous state. Up to now, carriers of genetic disorders were often excluded from mating, resulting in a decrease of genetic gain and a reduced number of sires available for the breeding program. Ongoing research is very likely to identify additional genetic defects causing embryonic loss and calf mortality by genotyping a large proportion of the female cattle population and sequencing key ancestors. Hence, a clear demand is present to develop a method combining selection against recessive defects (e.g., Holstein haplotypes HH1-HH5) with selection for economically beneficial traits (e.g., polled) for mating decisions. Our proposed method is a genetic index that accounts for the allele frequencies in the population and the economic value of the genetic characteristic without excluding carriers from breeding schemes. Fertility phenotypes from routine genetic evaluations were used to determine the economic value per embryo lost. Previous research has shown that embryo loss caused by HH1 and HH2 occurs later than the loss for HH3, HH4, and HH5. Therefore, an economic value of € 97 was used against HH1 and HH2 and € 70 against HH3, HH4, and HH5. For polled, € 7 per polled calf was considered. Minor allele frequencies of the defects ranged between 0.8 and 3.3%. The polled allele has a frequency of 4.1% in the German Holstein population. A genomic breeding program was simulated to study the effect of changing the selection criteria from assortative mating based on breeding values to selecting the females using the genetic index. Selection for a genetic index on the female path is a useful method to control the allele frequencies by reducing undesirable alleles and simultaneously increasing economical beneficial characteristics maintaining most of the genetic gain in production and functional traits. Additionally, we applied the genetic index to real data and found a decrease of the genetic trend for the birth years 1990 to 2006. Since 2010 the genetic index has increased due to a strong increase in the polled frequency. However, further investigation is needed to better understand the biology to determine the correct time of embryo loss and the economic value of fertility disorders. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genetics for the Human Race

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

Myles Axton; Francis Collins; Charles Rotimi

2004-11-01

This supplement has its origins on May 15, 2003, when the National Human Genome Center at Howard University held a small but important workshop in Washington DC. The workshop, Human Genome Variation and 'Race', and this special issue of Nature Genetics were proposed by scientists at Howard University and financially supported by the Genome Programs of the US Department of Energy, through its Office of Science; the Irving Harris Foundation; the National Institutes of Health, through the National Human Genome Research Institute; and Howard University. As summarized by Francis Collins, director of the National Human Genome Research Institute, the workshopmore » focused on several key questions: ''What does the current body of scientific information say about the connections among race, ethnicity, genetics and health? What remains unknown? What additional research is needed? How can this information be applied to benefit human health? How might this information be applied in nonmedical settings? How can we adopt policies that will achieve beneficial societal outcomes?'' This supplement, supported by the Department of Energy through a grant to Howard University, contains articles based on the presentations at this workshop.« less

A Parallel Genetic Algorithm for Automated Electronic Circuit Design

NASA Technical Reports Server (NTRS)

Long, Jason D.; Colombano, Silvano P.; Haith, Gary L.; Stassinopoulos, Dimitris

2000-01-01

Parallelized versions of genetic algorithms (GAs) are popular primarily for three reasons: the GA is an inherently parallel algorithm, typical GA applications are very compute intensive, and powerful computing platforms, especially Beowulf-style computing clusters, are becoming more affordable and easier to implement. In addition, the low communication bandwidth required allows the use of inexpensive networking hardware such as standard office ethernet. In this paper we describe a parallel GA and its use in automated high-level circuit design. Genetic algorithms are a type of trial-and-error search technique that are guided by principles of Darwinian evolution. Just as the genetic material of two living organisms can intermix to produce offspring that are better adapted to their environment, GAs expose genetic material, frequently strings of 1s and Os, to the forces of artificial evolution: selection, mutation, recombination, etc. GAs start with a pool of randomly-generated candidate solutions which are then tested and scored with respect to their utility. Solutions are then bred by probabilistically selecting high quality parents and recombining their genetic representations to produce offspring solutions. Offspring are typically subjected to a small amount of random mutation. After a pool of offspring is produced, this process iterates until a satisfactory solution is found or an iteration limit is reached. Genetic algorithms have been applied to a wide variety of problems in many fields, including chemistry, biology, and many engineering disciplines. There are many styles of parallelism used in implementing parallel GAs. One such method is called the master-slave or processor farm approach. In this technique, slave nodes are used solely to compute fitness evaluations (the most time consuming part). The master processor collects fitness scores from the nodes and performs the genetic operators (selection, reproduction, variation, etc.). Because of dependency issues in the GA, it is possible to have idle processors. However, as long as the load at each processing node is similar, the processors are kept busy nearly all of the time. In applying GAs to circuit design, a suitable genetic representation 'is that of a circuit-construction program. We discuss one such circuit-construction programming language and show how evolution can generate useful analog circuit designs. This language has the desirable property that virtually all sets of combinations of primitives result in valid circuit graphs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. Using a parallel genetic algorithm and circuit simulation software, we present experimental results as applied to three analog filter and two amplifier design tasks. For example, a figure shows an 85 dB amplifier design evolved by our system, and another figure shows the performance of that circuit (gain and frequency response). In all tasks, our system is able to generate circuits that achieve the target specifications.

Making Human Beings Human: Bioecological Perspectives on Human Development. The SAGE Program on Applied Developmental Science

ERIC Educational Resources Information Center

Bronfenbrenner, Urie, Ed.

2004-01-01

To a greater extent than any other species, human beings create the environments that, in turn, shape their own development. This book endeavors to demonstrate that human beings can also develop those environments to optimize their most constructive genetic potentials. What makes human beings human, therefore, is both the potential to shape their…

Registration of N6002 soybean germplasm with enhanced yield derived from Japanese cultivars Fukuyutaka and Nakasennari and elevated seed protein content

USDA-ARS?s Scientific Manuscript database

This release is part of a continuing effort to broaden the genetic base of applied North American soybean [Glycine max L. (Merr.)] breeding programs. N6002 was cooperatively developed and released by the USDA-ARS and the North Carolina Agricultural Research Service in September 2014 as a convention...

Applications of population genetics to animal breeding, from wright, fisher and lush to genomic prediction.

PubMed

Hill, William G

2014-01-01

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives' performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher's infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with "genomic selection" is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas.

A Double-Deck Elevator Group Supervisory Control System with Destination Floor Guidance System Using Genetic Network Programming

NASA Astrophysics Data System (ADS)

Yu, Lu; Zhou, Jin; Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu; Markon, Sandor

The Elevator Group Supervisory Control Systems (EGSCS) are the control systems that systematically manage three or more elevators in order to efficiently transport the passengers in buildings. Double-deck elevators, where two elevators are connected with each other, serve passengers at two consecutive floors simultaneously. Double-deck Elevator systems (DDES) become more complex in their behavior than conventional single-deck elevator systems (SDES). Recently, Artificial Intelligence (AI) technology has been used in such complex systems. Genetic Network Programming (GNP), a graph-based evolutionary method, has been applied to EGSCS and its advantages are shown in some papers. GNP can obtain the strategy of a new hall call assignment to the optimal elevator when it performs crossover and mutation operations to judgment nodes and processing nodes. Meanwhile, Destination Floor Guidance System (DFGS) is installed in DDES, so that passengers can also input their destinations at elevator halls. In this paper, we have applied GNP to DDES and compared DFGS with normal systems. The waiting time and traveling time of DFGS are all improved because of getting more information from DFGS. The simulations showed the effectiveness of the double-deck elevators with DFGS in different building traffics.

Empirical valence bond models for reactive potential energy surfaces: a parallel multilevel genetic program approach.

PubMed

Bellucci, Michael A; Coker, David F

2011-07-28

We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent. © 2011 American Institute of Physics

The eminent need for an academic program in universities to teach nanomedicine.

PubMed

Vélez, Juan Manuel; Vélez, Juan Jesus

2011-01-01

Nanomedicine is on the cutting edge of technology applied to medical and biological sciences. Nanodevices, nanomaterials, nanoinstruments, nanotechnologies, and nanotechniques (laboratory methods and procedures) are important for the modern practice of medicine and essential for research that could stimulate the discovery of new medical advances. Accordingly, there is an eminent need for implementing an academic program in universities to teach this indispensable and pragmatic discipline, especially in the departments of graduate studies and research in the areas of pharmacology, genetic engineering, proteomics, and molecular and cellular biology.

Mendelian genetics: Paradigm, conjecture, or research program

NASA Astrophysics Data System (ADS)

Oldham, V.; Brouwer, W.

Kuhn's model of the structure of scientific revolutions, Popper's hypothetic-deductive model of science, and Lakatos's methodology of competing research programs are applied to a historical episode in biology. Each of these three models offers a different explanatory system for the development, neglect, and eventual acceptance of Mendel's paradigm of inheritance. The authors conclude that both rational and nonrational criteria play an important role during times of crisis in science, when different research programs compete for acceptance. It is suggested that Kuhn's model, emphasizing the nonrational basis of science, and Popper's model, emphasizing the rational basis of science, can be used fruitfully in high school science courses.

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.

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.

Farm-by-farm analysis of microsatellite, mtDNA and SNP genotype data reveals inbreeding and crossbreeding as threats to the survival of a native Spanish pig breed.

PubMed

Herrero-Medrano, J M; Megens, H J; Crooijmans, R P; Abellaneda, J M; Ramis, G

2013-06-01

The Chato Murciano (CM), a pig breed from the Murcia region in the southeastern region of Spain, is a good model for endangered livestock populations. The remaining populations are bred on approximately 15 small farms, and no herdbook exists. To assess the genetic threats to the integrity and survival of the CM breed, and to aid in designing a conservation program, three genetic marker systems - microsatellites, SNPs and mtDNA - were applied across the majority of the total breeding stock. In addition, mtDNA and SNPs were genotyped in breeds that likely contributed genetically to the current CM gene pool. The analyses revealed the levels of genetic diversity within the range of other European local breeds (H(e) = 0.53). However, when the eight farms that rear at least 10 CM pigs were independently analyzed, high levels of inbreeding were found in some. Despite the evidence for recent crossbreeding with commercial breeds on a few farms, the entire breeding stock remains readily identifiable as CM, facilitating the design of traceability assays. The genetic management of the breed is consistent with farm size, farm owner and presence of other pig breeds on the farm, demonstrating the highly ad hoc nature of current CM breeding. The results of genetic diversity and substructure of the entire breed, as well as admixture and crossbreeding obtained in the present study, provide a benchmark to develop future conservation strategies. Furthermore, this study demonstrates that identifying farm-based practices and farm-based breeding stocks can aid in the design of a sustainable breeding program for minority breeds. © 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.

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.

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.

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.

50 CFR 224.101 - Enumeration of endangered marine and anadromous species.

Code of Federal Regulations, 2012 CFR

2012-10-01

... institutions) and which are identified as fish belonging to the NYB DPS based on genetics analyses, previously... genetics analyses, previously applied tags, previously applied marks, or documentation to verify that the... Carolina DPS based on genetics analyses, previously applied tags, previously applied marks, or...

50 CFR 224.101 - Enumeration of endangered marine and anadromous species.

Code of Federal Regulations, 2013 CFR

2013-10-01

... institutions) and which are identified as fish belonging to the NYB DPS based on genetics analyses, previously... genetics analyses, previously applied tags, previously applied marks, or documentation to verify that the... Carolina DPS based on genetics analyses, previously applied tags, previously applied marks, or...

Real Time Updating Genetic Network Programming for Adapting to the Change of Stock Prices

NASA Astrophysics Data System (ADS)

Chen, Yan; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

The key in stock trading model is to take the right actions for trading at the right time, primarily based on the accurate forecast of future stock trends. Since an effective trading with given information of stock prices needs an intelligent strategy for the decision making, we applied Genetic Network Programming (GNP) to creating a stock trading model. In this paper, we propose a new method called Real Time Updating Genetic Network Programming (RTU-GNP) for adapting to the change of stock prices. There are three important points in this paper: First, the RTU-GNP method makes a stock trading decision considering both the recommendable information of technical indices and the candlestick charts according to the real time stock prices. Second, we combine RTU-GNP with a Sarsa learning algorithm to create the programs efficiently. Also, sub-nodes are introduced in each judgment and processing node to determine appropriate actions (buying/selling) and to select appropriate stock price information depending on the situation. Third, a Real Time Updating system has been firstly introduced in our paper considering the change of the trend of stock prices. The experimental results on the Japanese stock market show that the trading model with the proposed RTU-GNP method outperforms other models without real time updating. We also compared the experimental results using the proposed method with Buy&Hold method to confirm its effectiveness, and it is clarified that the proposed trading model can obtain much higher profits than Buy&Hold method.

Genomic diversity and population structure of three autochthonous Greek sheep breeds assessed with genome-wide DNA arrays.

PubMed

Michailidou, S; Tsangaris, G; Fthenakis, G C; Tzora, A; Skoufos, I; Karkabounas, S C; Banos, G; Argiriou, A; Arsenos, G

2018-06-01

In the present study, genome-wide genotyping was applied to characterize the genetic diversity and population structure of three autochthonous Greek breeds: Boutsko, Karagouniko and Chios. Dairy sheep are among the most significant livestock species in Greece numbering approximately 9 million animals which are characterized by large phenotypic variation and reared under various farming systems. A total of 96 animals were genotyped with the Illumina's OvineSNP50K microarray beadchip, to study the population structure of the breeds and develop a specialized panel of single-nucleotide polymorphisms (SNPs), which could distinguish one breed from the others. Quality control on the dataset resulted in 46,125 SNPs, which were used to evaluate the genetic structure of the breeds. Population structure was assessed through principal component analysis (PCA) and admixture analysis, whereas inbreeding was estimated based on runs of homozygosity (ROHs) coefficients, genomic relationship matrix inbreeding coefficients (F GRM ) and patterns of linkage disequilibrium (LD). Associations between SNPs and breeds were analyzed with different inheritance models, to identify SNPs that distinguish among the breeds. Results showed high levels of genetic heterogeneity in the three breeds. Genetic distances among breeds were modest, despite their different ancestries. Chios and Karagouniko breeds were more genetically related to each other compared to Boutsko. Analysis revealed 3802 candidate SNPs that can be used to identify two-breed crosses and purebred animals. The present study provides, for the first time, data on the genetic background of three Greek indigenous dairy sheep breeds as well as a specialized marker panel that can be applied for traceability purposes as well as targeted genetic improvement schemes and conservation programs.

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

Geographic strain differentiation of Schistosoma japonicum in the Philippines using microsatellite markers

PubMed Central

Moendeg, Kharleezelle J.; Angeles, Jose Ma M.; Nakao, Ryo; Leonardo, Lydia R.; Fontanilla, Ian Kendrich C.; Goto, Yasuyuki; Kirinoki, Masashi; Villacorte, Elena A.; Rivera, Pilarita T.; Inoue, Noboru; Chigusa, Yuichi

2017-01-01

Background Microsatellites have been found to be useful in determining genetic diversities of various medically-important parasites which can be used as basis for an effective disease management and control program. In Asia and Africa, the identification of different geographical strains of Schistosoma japonicum, S. haematobium and S. mansoni as determined through microsatellites could pave the way for a better understanding of the transmission epidemiology of the parasite. Thus, the present study aims to apply microsatellite markers in analyzing the populations of S. japonicum from different endemic areas in the Philippines for possible strain differentiation. Methodology/ Principal findings Experimental mice were infected using the cercariae of S. japonicum collected from infected Oncomelania hupensis quadrasi snails in seven endemic municipalities. Adult worms were harvested from infected mice after 45 days of infection and their DNA analyzed against ten previously characterized microsatellite loci. High genetic diversity was observed in areas with high endemicity. The degree of genetic differentiation of the parasite population between endemic areas varies. Geographical separation was considered as one of the factors accounting for the observed difference between populations. Two subgroups have been observed in one of the study sites, suggesting that co-infection with several genotypes of the parasite might be present in the population. Clustering analysis showed no particular spatial structuring between parasite populations from different endemic areas. This result could possibly suggest varying degrees of effects of the ongoing control programs and the existing gene flow in the populations, which might be attributed to migration and active movement of infected hosts from one endemic area to another. Conclusions/ Significance Based on the results of the study, it is reasonable to conclude that genetic diversity could be one possible criterion to assess the infection status in highly endemic areas. Genetic surveillance using microsatellites is therefore important to predict the ongoing gene flow and degree of genetic diversity, which indirectly reflects the success of the control program in schistosomiasis-endemic areas. PMID:28692692

Regulations Under the Americans With Disabilities Act; Genetic Information Nondiscrimination Act. Final rule.

PubMed

2016-05-17

The Equal Employment Opportunity Commission (EEOC or Commission) is issuing its final rule to amend the regulations and interpretive guidance implementing Title I of the Americans with Disabilities Act (ADA) to provide guidance on the extent to which employers may use incentives to encourage employees to participate in wellness programs that ask them to respond to disability-related inquiries and/or undergo medical examinations. This rule applies to all wellness programs that include disability-related inquiries and/or medical examinations whether they are offered only to employees enrolled in an employer-sponsored group health plan, offered to all employees regardless of whether they are enrolled in such a plan, or offered as a benefit of employment by employers that do not sponsor a group health plan or group health insurance. Published elsewhere in this issue of the Federal Register, the EEOC also issued a final rule to amend the regulations implementing Title II of the Genetic Information Nondiscrimination Act (GINA) that addresses the extent to which employers may offer incentives for an employee's spouse to participate in a wellness program.

Genetic and environmental bases of the interplay between magical ideation and personality.

PubMed

Brambilla, Paolo; Fagnani, Corrado; Cecchetto, Filippo; Medda, Emanuela; Bellani, Marcella; Salemi, Miriam; Picardi, Angelo; Stazi, Maria Antonietta

2014-02-28

Sub-threshold psychotic symptoms are quite commonly present in general population. Among these, Magical Ideation (MI) has been proved to be a valid predictor of psychosis. However, the genetic and environmental influences on the interplay between MI and personality have not fully been explored. A total of 534 adult twins from the population-based Italian Twin Register were assessed for MI using the MI Scale (MIS) and for personality with the temperament and character inventory (TCI). A Multivariate Cholesky model was applied with Mx statistical program. The best-fitting model showed that additive genetic and unshared environmental factors explain approximately the same proportion of variance in MI, whereas a less strong genetic influence on personality traits emerged. Relevant correlations between MI and specific personality traits (novelty seeking, cooperativeness, self-directedness, self-transcendence) were found, suggesting shared influences for MI and these traits. Both genetic and environmental factors explained these correlations, with genetic factors playing a predominant role. Moderate-to-substantial genetic effects on MI and personality were found. Shared genetic and environmental effects underlie the phenotypic correlation between MI (psychosis-proneness) and personality traits, i.e. self-directedness (negative association) and self-transcendence (positive association), potentially representing predictive markers of psychosis liability related to schizotypy and personality. © 2013 Published by Elsevier Ireland Ltd.

Comparative Analysis of Neural Network Training Methods in Real-time Radiotherapy.

PubMed

Nouri, S; Hosseini Pooya, S M; Soltani Nabipour, J

2017-03-01

The motions of body and tumor in some regions such as chest during radiotherapy treatments are one of the major concerns protecting normal tissues against high doses. By using real-time radiotherapy technique, it is possible to increase the accuracy of delivered dose to the tumor region by means of tracing markers on the body of patients. This study evaluates the accuracy of some artificial intelligence methods including neural network and those of combination with genetic algorithm as well as particle swarm optimization (PSO) estimating tumor positions in real-time radiotherapy. One hundred recorded signals of three external markers were used as input data. The signals from 3 markers thorough 10 breathing cycles of a patient treated via a cyber-knife for a lung tumor were used as data input. Then, neural network method and its combination with genetic or PSO algorithms were applied determining the tumor locations using MATLAB© software program. The accuracies were obtained 0.8%, 12% and 14% in neural network, genetic and particle swarm optimization algorithms, respectively. The internal target volume (ITV) should be determined based on the applied neural network algorithm on training steps.

Improved genetic algorithm for the protein folding problem by use of a Cartesian combination operator.

PubMed Central

Rabow, A. A.; Scheraga, H. A.

1996-01-01

We have devised a Cartesian combination operator and coding scheme for improving the performance of genetic algorithms applied to the protein folding problem. The genetic coding consists of the C alpha Cartesian coordinates of the protein chain. The recombination of the genes of the parents is accomplished by: (1) a rigid superposition of one parent chain on the other, to make the relation of Cartesian coordinates meaningful, then, (2) the chains of the children are formed through a linear combination of the coordinates of their parents. The children produced with this Cartesian combination operator scheme have similar topology and retain the long-range contacts of their parents. The new scheme is significantly more efficient than the standard genetic algorithm methods for locating low-energy conformations of proteins. The considerable superiority of genetic algorithms over Monte Carlo optimization methods is also demonstrated. We have also devised a new dynamic programming lattice fitting procedure for use with the Cartesian combination operator method. The procedure finds excellent fits of real-space chains to the lattice while satisfying bond-length, bond-angle, and overlap constraints. PMID:8880904

Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations.

PubMed

Wang, D; Salah El-Basyoni, I; Stephen Baenziger, P; Crossa, J; Eskridge, K M; Dweikat, I

2012-11-01

Though epistasis has long been postulated to have a critical role in genetic regulation of important pathways as well as provide a major source of variation in the process of speciation, the importance of epistasis for genomic selection in the context of plant breeding is still being debated. In this paper, we report the results on the prediction of genetic values with epistatic effects for 280 accessions in the Nebraska Wheat Breeding Program using adaptive mixed least absolute shrinkage and selection operator (LASSO). The development of adaptive mixed LASSO, originally designed for association mapping, for the context of genomic selection is reported. The results show that adaptive mixed LASSO can be successfully applied to the prediction of genetic values while incorporating both marker main effects and epistatic effects. Especially, the prediction accuracy is substantially improved by the inclusion of two-locus epistatic effects (more than onefold in some cases as measured by cross-validation correlation coefficient), which is observed for multiple traits and planting locations. This points to significant potential in using non-additive genetic effects for genomic selection in crop breeding practices.

Applications of Population Genetics to Animal Breeding, from Wright, Fisher and Lush to Genomic Prediction

PubMed Central

Hill, William G.

2014-01-01

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives’ performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher’s infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with “genomic selection” is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas. PMID:24395822

Strategies for Selecting Crosses Using Genomic Prediction in Two Wheat Breeding Programs.

PubMed

Lado, Bettina; Battenfield, Sarah; Guzmán, Carlos; Quincke, Martín; Singh, Ravi P; Dreisigacker, Susanne; Peña, R Javier; Fritz, Allan; Silva, Paula; Poland, Jesse; Gutiérrez, Lucía

2017-07-01

The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The aim of this study was to compare the best crosses predicted using combinations of mid-parent value and variance prediction accounting for linkage disequilibrium (V) or assuming linkage equilibrium (V). After predicting the mean and the variance of each cross, we selected crosses based on mid-parent value, the top 10% of the progeny, and weighted mean and variance within progenies for grain yield, grain protein content, mixing time, and loaf volume in two applied wheat ( L.) breeding programs: Instituto Nacional de Investigación Agropecuaria (INIA) Uruguay and CIMMYT Mexico. Although the variance of the progeny is important to increase the chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses drove the genetic gain but the variance of the progeny had a small impact on genetic gain for grain yield. However, the relative importance of the variance of the progeny was larger for quality traits. Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses. Copyright © 2017 Crop Science Society of America.

Drag reduction of a car model by linear genetic programming control

NASA Astrophysics Data System (ADS)

Li, Ruiying; Noack, Bernd R.; Cordier, Laurent; Borée, Jacques; Harambat, Fabien

2017-08-01

We investigate open- and closed-loop active control for aerodynamic drag reduction of a car model. Turbulent flow around a blunt-edged Ahmed body is examined at ReH≈ 3× 105 based on body height. The actuation is performed with pulsed jets at all trailing edges (multiple inputs) combined with a Coanda deflection surface. The flow is monitored with 16 pressure sensors distributed at the rear side (multiple outputs). We apply a recently developed model-free control strategy building on genetic programming in Dracopoulos and Kent (Neural Comput Appl 6:214-228, 1997) and Gautier et al. (J Fluid Mech 770:424-441, 2015). The optimized control laws comprise periodic forcing, multi-frequency forcing and sensor-based feedback including also time-history information feedback and combinations thereof. Key enabler is linear genetic programming (LGP) as powerful regression technique for optimizing the multiple-input multiple-output control laws. The proposed LGP control can select the best open- or closed-loop control in an unsupervised manner. Approximately 33% base pressure recovery associated with 22% drag reduction is achieved in all considered classes of control laws. Intriguingly, the feedback actuation emulates periodic high-frequency forcing. In addition, the control identified automatically the only sensor which listens to high-frequency flow components with good signal to noise ratio. Our control strategy is, in principle, applicable to all multiple actuators and sensors experiments.

DNA linkage studies of degenerative retinal diseases.

PubMed

Daiger, S P; Heckenlively, J R; Lewis, R A; Pelias, M Z

1987-01-01

DNA linkage studies of human genetic diseases have led to rapid characterization of a number of otherwise intractable disease loci. Detection of a linked DNA marker, the first step in "reverse genetics", has permitted cloning of the genes for Duchenne muscular dystrophy, retinoblastoma and chronic granulomatosis disease, among others. Thus, the case for applying these techniques to retinitis pigmentosa and related diseases, and the urgency in capitalizing on molecular developments, is justified and compelling. The first major success regarding RP was in demonstrating linkage of the DNA marker DXS7 (L1.28) to XRP. For autosomal forms of the disease, conventional linkage studies have provided tentative evidence for linkage of ADRP to the Rh blood group on chromosome lp and for linkage of Usher's syndrome to Gc and 4q. These provisional assignments are, at least, an important starting point for DNA analysis. The Support Program for DNA Linkage Studies of Degenerative Retinal Diseases was established to provide access for the scientific community to appropriate families, using the resources of the Human Genetic Mutant Cell Repository to prepare, store and distribute lymphoblast lines. To date, two extensive, well-characterized families are included in the program: the autosomal dominant RP family UCLA-RP01, and the Usher's syndrome families LSU-US01. It is highly likely that rapid progress will be made in mapping and characterizing the inherited retinal dystrophies. We believe the support program will facilitate this progress.

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.

Flexible ligand docking using a genetic algorithm

NASA Astrophysics Data System (ADS)

Oshiro, C. M.; Kuntz, I. D.; Dixon, J. Scott

1995-04-01

Two computational techniques have been developed to explore the orientational and conformational space of a flexible ligand within an enzyme. Both methods use the Genetic Algorithm (GA) to generate conformationally flexible ligands in conjunction with algorithms from the DOCK suite of programs to characterize the receptor site. The methods are applied to three enzyme-ligand complexes: dihydrofolate reductase-methotrexate, thymidylate synthase-phenolpthalein and HIV protease-thioketal haloperidol. Conformations and orientations close to the crystallographically determined structures are obtained, as well as alternative structures with low energy. The potential for the GA method to screen a database of compounds is also examined. A collection of ligands is evaluated simultaneously, rather than docking the ligands individually into the enzyme.

A theoretical comparison of evolutionary algorithms and simulated annealing

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

Hart, W.E.

1995-08-28

This paper theoretically compares the performance of simulated annealing and evolutionary algorithms. Our main result is that under mild conditions a wide variety of evolutionary algorithms can be shown to have greater performance than simulated annealing after a sufficiently large number of function evaluations. This class of EAs includes variants of evolutionary strategie and evolutionary programming, the canonical genetic algorithm, as well as a variety of genetic algorithms that have been applied to combinatorial optimization problems. The proof of this result is based on a performance analysis of a very general class of stochastic optimization algorithms, which has implications formore » the performance of a variety of other optimization algorithm.« less

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

Fragman: an R package for fragment analysis.

PubMed

Covarrubias-Pazaran, Giovanny; Diaz-Garcia, Luis; Schlautman, Brandon; Salazar, Walter; Zalapa, Juan

2016-04-21

Determination of microsatellite lengths or other DNA fragment types is an important initial component of many genetic studies such as mutation detection, linkage and quantitative trait loci (QTL) mapping, genetic diversity, pedigree analysis, and detection of heterozygosity. A handful of commercial and freely available software programs exist for fragment analysis; however, most of them are platform dependent and lack high-throughput applicability. We present the R package Fragman to serve as a freely available and platform independent resource for automatic scoring of DNA fragment lengths diversity panels and biparental populations. The program analyzes DNA fragment lengths generated in Applied Biosystems® (ABI) either manually or automatically by providing panels or bins. The package contains additional tools for converting the allele calls to GenAlEx, JoinMap® and OneMap software formats mainly used for genetic diversity and generating linkage maps in plant and animal populations. Easy plotting functions and multiplexing friendly capabilities are some of the strengths of this R package. Fragment analysis using a unique set of cranberry (Vaccinium macrocarpon) genotypes based on microsatellite markers is used to highlight the capabilities of Fragman. Fragman is a valuable new tool for genetic analysis. The package produces equivalent results to other popular software for fragment analysis while possessing unique advantages and the possibility of automation for high-throughput experiments by exploiting the power of R.

Solving deterministic non-linear programming problem using Hopfield artificial neural network and genetic programming techniques

NASA Astrophysics Data System (ADS)

Vasant, P.; Ganesan, T.; Elamvazuthi, I.

2012-11-01

A fairly reasonable result was obtained for non-linear engineering problems using the optimization techniques such as neural network, genetic algorithms, and fuzzy logic independently in the past. Increasingly, hybrid techniques are being used to solve the non-linear problems to obtain better output. This paper discusses the use of neuro-genetic hybrid technique to optimize the geological structure mapping which is known as seismic survey. It involves the minimization of objective function subject to the requirement of geophysical and operational constraints. In this work, the optimization was initially performed using genetic programming, and followed by hybrid neuro-genetic programming approaches. Comparative studies and analysis were then carried out on the optimized results. The results indicate that the hybrid neuro-genetic hybrid technique produced better results compared to the stand-alone genetic programming method.

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.

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.

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.

Optimizing the creation of base populations for aquaculture breeding programs using phenotypic and genomic data and its consequences on genetic progress.

PubMed

Fernández, Jesús; Toro, Miguel Á; Sonesson, Anna K; Villanueva, Beatriz

2014-01-01

The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in the initial founders. Traditionally, base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and, therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during 10 generations of phenotypic selection applied in the subsequent breeding program.

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.

Discovering Knowledge from Noisy Databases Using Genetic Programming.

ERIC Educational Resources Information Center

Wong, Man Leung; Leung, Kwong Sak; Cheng, Jack C. Y.

2000-01-01

Presents a framework that combines Genetic Programming and Inductive Logic Programming, two approaches in data mining, to induce knowledge from noisy databases. The framework is based on a formalism of logic grammars and is implemented as a data mining system called LOGENPRO (Logic Grammar-based Genetic Programming System). (Contains 34…

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 demographic and genetic effects of a sterilant applied to wild horse mares

USGS Publications Warehouse

Roelle, James E.; Oyler-McCance, Sara J.

2015-01-01

Wild horse populations on western ranges can increase rapidly, resulting in the need for the Bureau of Land Management (BLM) to remove animals in order to protect the habitat that horses share with numerous other species. As an alternative to removals, BLM has sought to develop a long-term, perhaps even permanent, contraceptive to aid in reducing population growth rates. With long-term (perhaps even permanent) efficacy of contraception, however, comes increased concern about the genetic health of populations and about the potential for local extirpation. We used simulation modeling to examine the potential demographic and genetic consequences of applying a mare sterilant to wild horse populations. Using the VORTEX software package, we modeled the potential effects of a sterilant on 70 simulated populations having different initial sizes (7 values), growth rates (5 values), and genetic diversity (2 values). For each population, we varied the treatment rate of mares from 0 to 100 percent in increments of 10 percent. For each combination of these treatment levels, we ran 100 stochastic simulations, and we present the results in the form of tables and graphs showing mean population size after 20 years, mean number of removals after 20 years, mean probability of extirpation after 50 years, and mean heterozygosity after 50 years. By choosing one or two combinations of initial population size, population growth rate, and genetic diversity that best represent a herd of interest, a manager can assess the likely effects of a contraceptive program by examining the output tables and graphs representing the selected conditions.

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.

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…

75 FR 38611 - Child Support Enforcement Program; Intergovernmental Child Support

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-02

...This rule revises Federal requirements for establishing and enforcing intergovernmental support obligations in Child Support Enforcement (IV-D) program cases receiving services under title IV-D of the Social Security Act (the Act). This final rule revises previous interstate requirements to apply to case processing in all intergovernmental cases; requires the responding State IV-D agency to pay the cost of genetic testing; clarifies responsibility for determining in which State tribunal a controlling order determination is made where multiple support orders exist; recognizes and incorporates electronic communication advancements; and makes conforming changes to the Federal substantial compliance audit and State self-assessment requirements.

Establishing a Program for Individuals at High Risk for Breast Cancer

PubMed Central

Cadiz, Fernando; Kuerer, Henry M.; Puga, Julio; Camacho, Jamile; Cunill, Eduardo; Arun, Banu

2013-01-01

Our need to create a program for individuals at high risk for breast cancer development led us to research the available data on such programs. In this paper, we summarize our findings and our thinking process as we developed our own program. Breast cancer incidence is increasing worldwide. Even though there are known risk factors for breast cancer development, approximately 60% of patients with breast cancer have no known risk factor, although this situation will probably change with further research, especially in genetics. For patients with risk factors based on personal or family history, different models are available for assessing and quantifying risk. Assignment of risk levels permits tailored screening and risk reduction strategies. Potential benefits of specialized programs for women with high breast cancer risk include more cost -effective interventions as a result of patient stratification on the basis of risk; generation of valuable data to advance science; and differentiation of breast programs from other breast cancer units, which can result in increased revenue that can be directed to further improvements in patient care. Guidelines for care of patients at high risk for breast cancer are available from various groups. However, running a high-risk breast program involves much more than applying a guideline. Each high-risk program needs to be designed by its institution with consideration of local resources and country legislation, especially related to genetic issues. Development of a successful high-risk program includes identifying strengths, weaknesses, opportunities, and threats; developing a promotion plan; choosing a risk assessment tool; defining “high risk”; and planning screening and risk reduction strategies for the specific population served by the program. The information in this article may be useful for other institutions considering creation of programs for patients with high breast cancer risk. PMID:23833688

Proposed low-cost premarital screening program for prevention of sickle cell and thalassemia in Yemen

PubMed Central

Al-Nood, Hafiz; Al-Hadi, Abdulrahman

2013-01-01

In Yemen, the prevalence of sickle cell trait and β-thalassemia trait are high. The aim of this premarital program is to identify sickle cell and thalassemia carrier couples in Yemen before completing marriages proposal, in order to prevent affected birth. This can be achieved by applying a low-cost premarital screening program using simple blood tests compatible with the limited health resources of the country. If microcytosis or positive sickle cell is found in both or one partner has microcytosis and the other has positive sickle cell, so their children at high risk of having sickle cell or/and thalassemia diseases. Carrier couples will be referred to genetic counseling. The outcomes of this preventive program are predicted to decrease the incidence of affected birth and reduce the health burden of these disorders. The success of this program also requires governmental, educational and religious supports. PMID:25003062

Comparative Transcriptome of Wild Type and Selected Strains of the Microalgae Tisochrysis lutea Provides Insights into the Genetic Basis, Lipid Metabolism and the Life Cycle

PubMed Central

Carrier, Gregory; Garnier, Matthieu; Le Cunff, Loïc; Bougaran, Gaël; Probert, Ian; De Vargas, Colomban; Corre, Erwan; Cadoret, Jean-Paul; Saint-Jean, Bruno

2014-01-01

The applied exploitation of microalgae cultures has to date almost exclusively involved the use of wild type strains, deposited over decades in dedicated culture collections. Concomitantly, the concept of improving algae with selection programs for particular specific purposes is slowly emerging. Studying since a decade an economically and ecologically important haptophyte Tisochrysis lutea (Tiso), we took advantage of the availability of wild type (Tiso-Wt) and selected (Tiso-S2M2) strains to conduct a molecular variations study. This endeavour presented substantial challenges: the genome assembly was not yet available, the life cycle unknown and genetic diversity of Tiso-Wt poorly documented. This study brings the first molecular data in order to set up a selection strategy for that microalgae. Following high-throughput Illumina sequencing, transcriptomes of Tiso-Wt and Tiso-S2M2 were de novo assembled and annotated. Genetic diversity between both strains was analyzed and revealed a clear conservation, while a comparison of transcriptomes allowed identification of polymorphisms resulting from the selection program. Of 34,374 transcripts, 291 were differentially expressed and 165 contained positional polymorphisms (SNP, Indel). We focused on lipid over-accumulation of the Tiso-S2M2 strain and 8 candidate genes were identified by combining analysis of positional polymorphism, differential expression levels, selection signature and by study of putative gene function. Moreover, genetic analysis also suggests the existence of a sexual cycle and genetic recombination in Tisochrysis lutea. PMID:24489800

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.

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.

The Spring of Systems Biology-Driven Breeding.

PubMed

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

2018-05-12

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

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

Education and certification of genetic counselors.

PubMed

Katsichti, L; Hadzipetros-Bardanis, M; Bartsocas, C S

1999-01-01

Genetic counseling is defined by the American Society of Human Genetics as a communication process which deals with the human problems associated with the occurrence, or risk of occurrence, of a genetic disorder in a family. The first graduate program (Master's degree) in genetic counseling started in 1969 at Sarah Lawrence College, NY, USA, while in 1979 the National Society of Genetic Counseling (NSGC) was established. Today, there are 29 programs in U.S.A. offering a Master's degree in Genetic Counseling, five programs in Canada, one in Mexico, one in England and one in S. Africa. Most of these graduate programs offer two year training, consisting of graduate courses, seminars, research and practical training. Emphasis is given in human physiology, biochemistry, clinical genetics, cytogenetics, molecular and biochemical genetics, population genetics and statistics, prenatal diagnosis, teratology and genetic counseling in relation to psychosocial and ethical issues. Certification for eligible candidates is available through the American Board of Medical Genetics (ABMG). Requirements for certification include a master's degree in human genetics, training at sites accredited by the ABMG, documentation of genetic counseling experience, evidence of continuing education and successful completion of a comprehensive ABMG certification examination. As professionals, genetic counselors should maintain expertise, should insure mechanisms for professional advancement and should always maintain the ability to approach their patients.

Genetic parameters for uniformity of harvest weight and body size traits in the GIFT strain of Nile tilapia.

PubMed

Marjanovic, Jovana; Mulder, Han A; Khaw, Hooi L; Bijma, Piter

2016-06-10

Animal breeding programs have been very successful in improving the mean levels of traits through selection. However, in recent decades, reducing the variability of trait levels between individuals has become a highly desirable objective. Reaching this objective through genetic selection requires that there is genetic variation in the variability of trait levels, a phenomenon known as genetic heterogeneity of environmental (residual) variance. The aim of our study was to investigate the potential for genetic improvement of uniformity of harvest weight and body size traits (length, depth, and width) in the genetically improved farmed tilapia (GIFT) strain. In order to quantify the genetic variation in uniformity of traits and estimate the genetic correlations between level and variance of the traits, double hierarchical generalized linear models were applied to individual trait values. Our results showed substantial genetic variation in uniformity of all analyzed traits, with genetic coefficients of variation for residual variance ranging from 39 to 58 %. Genetic correlation between trait level and variance was strongly positive for harvest weight (0.60 ± 0.09), moderate and positive for body depth (0.37 ± 0.13), but not significantly different from 0 for body length and width. Our results on the genetic variation in uniformity of harvest weight and body size traits show good prospects for the genetic improvement of uniformity in the GIFT strain. A high and positive genetic correlation was estimated between level and variance of harvest weight, which suggests that selection for heavier fish will also result in more variation in harvest weight. Simultaneous improvement of harvest weight and its uniformity will thus require index selection.

A Model Framework to Estimate Impact and Cost of Genetics-Based Sterile Insect Methods for Dengue Vector Control

PubMed Central

Alphey, Nina; Alphey, Luke; Bonsall, Michael B.

2011-01-01

Vector-borne diseases impose enormous health and economic burdens and additional methods to control vector populations are clearly needed. The Sterile Insect Technique (SIT) has been successful against agricultural pests, but is not in large-scale use for suppressing or eliminating mosquito populations. Genetic RIDL technology (Release of Insects carrying a Dominant Lethal) is a proposed modification that involves releasing insects that are homozygous for a repressible dominant lethal genetic construct rather than being sterilized by irradiation, and could potentially overcome some technical difficulties with the conventional SIT technology. Using the arboviral disease dengue as an example, we combine vector population dynamics and epidemiological models to explore the effect of a program of RIDL releases on disease transmission. We use these to derive a preliminary estimate of the potential cost-effectiveness of vector control by applying estimates of the costs of SIT. We predict that this genetic control strategy could eliminate dengue rapidly from a human community, and at lower expense (approximately US$ 2∼30 per case averted) than the direct and indirect costs of disease (mean US$ 86–190 per case of dengue). The theoretical framework has wider potential use; by appropriately adapting or replacing each component of the framework (entomological, epidemiological, vector control bio-economics and health economics), it could be applied to other vector-borne diseases or vector control strategies and extended to include other health interventions. PMID:21998654

Assessing the impact of natural service bulls and genotype by environment interactions on genetic gain and inbreeding in organic dairy cattle genomic breeding programs.

PubMed

Yin, T; Wensch-Dorendorf, M; Simianer, H; Swalve, H H; König, S

2014-06-01

The objective of the present study was to compare genetic gain and inbreeding coefficients of dairy cattle in organic breeding program designs by applying stochastic simulations. Evaluated breeding strategies were: (i) selecting bulls from conventional breeding programs, and taking into account genotype by environment (G×E) interactions, (ii) selecting genotyped bulls within the organic environment for artificial insemination (AI) programs and (iii) selecting genotyped natural service bulls within organic herds. The simulated conventional population comprised 148 800 cows from 2976 herds with an average herd size of 50 cows per herd, and 1200 cows were assigned to 60 organic herds. In a young bull program, selection criteria of young bulls in both production systems (conventional and organic) were either 'conventional' estimated breeding values (EBV) or genomic estimated breeding values (GEBV) for two traits with low (h 2=0.05) and moderate heritability (h 2=0.30). GEBV were calculated for different accuracies (r mg), and G×E interactions were considered by modifying originally simulated true breeding values in the range from r g=0.5 to 1.0. For both traits (h 2=0.05 and 0.30) and r mg⩾0.8, genomic selection of bulls directly in the organic population and using selected bulls via AI revealed higher genetic gain than selecting young bulls in the larger conventional population based on EBV; also without the existence of G×E interactions. Only for pronounced G×E interactions (r g=0.5), and for highly accurate GEBV for natural service bulls (r mg>0.9), results suggests the use of genotyped organic natural service bulls instead of implementing an AI program. Inbreeding coefficients of selected bulls and their offspring were generally lower when basing selection decisions for young bulls on GEBV compared with selection strategies based on pedigree indices.

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.

Applying Quantitative Genetic Methods to Primate Social Behavior

PubMed Central

Brent, Lauren J. N.

2013-01-01

Increasingly, behavioral ecologists have applied quantitative genetic methods to investigate the evolution of behaviors in wild animal populations. The promise of quantitative genetics in unmanaged populations opens the door for simultaneous analysis of inheritance, phenotypic plasticity, and patterns of selection on behavioral phenotypes all within the same study. In this article, we describe how quantitative genetic techniques provide studies of the evolution of behavior with information that is unique and valuable. We outline technical obstacles for applying quantitative genetic techniques that are of particular relevance to studies of behavior in primates, especially those living in noncaptive populations, e.g., the need for pedigree information, non-Gaussian phenotypes, and demonstrate how many of these barriers are now surmountable. We illustrate this by applying recent quantitative genetic methods to spatial proximity data, a simple and widely collected primate social behavior, from adult rhesus macaques on Cayo Santiago. Our analysis shows that proximity measures are consistent across repeated measurements on individuals (repeatable) and that kin have similar mean measurements (heritable). Quantitative genetics may hold lessons of considerable importance for studies of primate behavior, even those without a specific genetic focus. PMID:24659839

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.

Comparative genomic analysis of Lactobacillus plantarum ZJ316 reveals its genetic adaptation and potential probiotic profiles* #

PubMed Central

Li, Ping; Li, Xuan; Gu, Qing; Lou, Xiu-yu; Zhang, Xiao-mei; Song, Da-feng; Zhang, Chen

2016-01-01

Objective: In previous studies, Lactobacillus plantarum ZJ316 showed probiotic properties, such as antimicrobial activity against various pathogens and the capacity to significantly improve pig growth and pork quality. The purpose of this study was to reveal the genes potentially related to its genetic adaptation and probiotic profiles based on comparative genomic analysis. Methods: The genome sequence of L. plantarum ZJ316 was compared with those of eight L. plantarum strains deposited in GenBank. BLASTN, Mauve, and MUMmer programs were used for genome alignment and comparison. CRISPRFinder was applied for searching the clustered regularly interspaced short palindromic repeats (CRISPRs). Results: We identified genes that encode proteins related to genetic adaptation and probiotic profiles, including carbohydrate transport and metabolism, proteolytic enzyme systems and amino acid biosynthesis, CRISPR adaptive immunity, stress responses, bile salt resistance, ability to adhere to the host intestinal wall, exopolysaccharide (EPS) biosynthesis, and bacteriocin biosynthesis. Conclusions: Comparative characterization of the L. plantarum ZJ316 genome provided the genetic basis for further elucidating the functional mechanisms of its probiotic properties. ZJ316 could be considered a potential probiotic candidate. PMID:27487802

Comparative genomic analysis of Lactobacillus plantarum ZJ316 reveals its genetic adaptation and potential probiotic profiles.

PubMed

Li, Ping; Li, Xuan; Gu, Qing; Lou, Xiu-Yu; Zhang, Xiao-Mei; Song, Da-Feng; Zhang, Chen

2016-08-01

In previous studies, Lactobacillus plantarum ZJ316 showed probiotic properties, such as antimicrobial activity against various pathogens and the capacity to significantly improve pig growth and pork quality. The purpose of this study was to reveal the genes potentially related to its genetic adaptation and probiotic profiles based on comparative genomic analysis. The genome sequence of L. plantarum ZJ316 was compared with those of eight L. plantarum strains deposited in GenBank. BLASTN, Mauve, and MUMmer programs were used for genome alignment and comparison. CRISPRFinder was applied for searching the clustered regularly interspaced short palindromic repeats (CRISPRs). We identified genes that encode proteins related to genetic adaptation and probiotic profiles, including carbohydrate transport and metabolism, proteolytic enzyme systems and amino acid biosynthesis, CRISPR adaptive immunity, stress responses, bile salt resistance, ability to adhere to the host intestinal wall, exopolysaccharide (EPS) biosynthesis, and bacteriocin biosynthesis. Comparative characterization of the L. plantarum ZJ316 genome provided the genetic basis for further elucidating the functional mechanisms of its probiotic properties. ZJ316 could be considered a potential probiotic candidate.

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.

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.

Portfolio optimization by using linear programing models based on genetic algorithm

NASA Astrophysics Data System (ADS)

Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.

2018-01-01

In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.

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

Morphology versus DNA barcoding: two sides of the same coin. A case study of Ceutorhynchus erysimi and C. contractus identification.

PubMed

Stepanović, Svetlana; Kosovac, Andrea; Krstić, Oliver; Jović, Jelena; Toševski, Ivo

2016-08-01

Genotyping of 2 well-known weevil species from the genus Ceutorhynchus (Coleoptera: Curculionidae) distributed in west Palearctic, C. erysimi and C. contractus, revealed phenotype versus genotype inconsistencies in a set of 56 specimens (25 C. erysimi and 31 C. contractus) collected from 25 locations in Serbia and Montenegro. An analysis of the mitochondrial cytochrome oxidase subunit I gene (COI), widely used as a barcoding region, and a nuclear gene, elongation factor-1α (EF-1α), revealed stable genetic divergence among these species. The average uncorrected pairwise distances for the COI and EF-1α genes were 3.8%, and 1.3%, respectively, indicating 2 genetically well-segregated species. However, the genetic data were not congruent with the phenotypic characteristics of the studied specimens. In the first place, C. erysimi genotypes were attached to specimens with phenotypic characteristics of C. contractus. Species-specific PCR-RFLP assays for the barcoding gene COI were applied for the molecular identification of 101 additional specimens of both morphospecies (33 C. erysimi and 68 C. contractus) and were found to confirm this incongruity. The discrepancy between the genetic and morphological data raises the question of the accuracy of using a barcoding approach, as it may result in misleading conclusions about the taxonomic position of the studied organism. Additionally, the typological species concept shows considerable weakness when genetic data are not supported with phenotypic characteristics as in case of asymmetric introgression, which may cause certain problems, especially in applied studies such as biological control programs in which the biological properties of the studied organisms are the main focus. © 2015 Institute of Zoology, Chinese Academy of Sciences.

A Tri-part Model for Genetics Literacy: Exploring Undergraduate Student Reasoning About Authentic Genetics Dilemmas

NASA Astrophysics Data System (ADS)

Shea, Nicole A.; Duncan, Ravit Golan; Stephenson, Celeste

2015-08-01

Genetics literacy is becoming increasingly important as advancements in our application of genetic technologies such as stem cell research, cloning, and genetic screening become more prevalent. Very few studies examine how genetics literacy is applied when reasoning about authentic genetic dilemmas. However, there is evidence that situational features of a reasoning task may influence how students apply content knowledge as they generate and support arguments. Understanding how students apply content knowledge to reason about authentic and complex issues is important for considering instructional practices that best support student thinking and reasoning. In this conceptual report, we present a tri-part model for genetics literacy that embodies the relationships between content knowledge use, argumentation quality, and the role of situational features in reasoning to support genetics literacy. Using illustrative examples from an interview study with early career undergraduate students majoring in the biological sciences and late career undergraduate students majoring in genetics, we provide insights into undergraduate student reasoning about complex genetics issues and discuss implications for teaching and learning. We further discuss the need for research about how the tri-part model of genetics literacy can be used to explore students' thinking and reasoning abilities in genetics.

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)

[The application of gene expression programming in the diagnosis of heart disease].

PubMed

Dai, Wenbin; Zhang, Yuntao; Gao, Xingyu

2009-02-01

GEP (Gene expression programming) is a new genetic algorithm, and it has been proved to be excellent in function finding. In this paper, for the purpose of setting up a diagnostic model, GEP is used to deal with the data of heart disease. Eight variables, Sex, Chest pain, Blood pressure, Angina, Peak, Slope, Colored vessels and Thal, are picked out of thirteen variables to form a classified function. This function is used to predict a forecasting set of 100 samples, and the accuracy is 87%. Other algorithms such as SVM (Support vector machine) are applied to the same data and the forecasting results show that GEP is better than other algorithms.

Application of evolutionary computation in ECAD problems

NASA Astrophysics Data System (ADS)

Lee, Dae-Hyun; Hwang, Seung H.

1998-10-01

Design of modern electronic system is a complicated task which demands the use of computer- aided design (CAD) tools. Since a lot of problems in ECAD are combinatorial optimization problems, evolutionary computations such as genetic algorithms and evolutionary programming have been widely employed to solve those problems. We have applied evolutionary computation techniques to solve ECAD problems such as technology mapping, microcode-bit optimization, data path ordering and peak power estimation, where their benefits are well observed. This paper presents experiences and discusses issues in those applications.

Exploring the Role of Genetic Modifiers in DNA Repair and Breast Cancer

DTIC Science & Technology

2013-09-01

GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER E-Mail: 5f. WORK UNIT NUMBER 7. PERFORMING...detailed in the Statement of Work for this training grant . I have applied for and received a no-cost extension (Amendment P00001, 24-Aug-2012...Date In Year 1 of this grant I successfully constructed a yeast tel1∆ ∆ genome-wide double-deletion library that was screened for sensitivity to

Determination of Genetic Structure and Signatures of Selection in Three Strains of Tanzania Shorthorn Zebu, Boran and Friesian Cattle by Genome-Wide SNP Analyses

PubMed Central

Msalya, George; Kim, Eui-Soo; Laisser, Emmanuel L. K.; Kipanyula, Maulilio J.; Karimuribo, Esron D.; Kusiluka, Lughano J. M.; Chenyambuga, Sebastian W.; Rothschild, Max F.

2017-01-01

Background More than 90 percent of cattle in Tanzania belong to the indigenous Tanzania Short Horn Zebu (TSZ) population which has been classified into 12 strains based on historical evidence, morphological characteristics, and geographic distribution. However, specific genetic information of each TSZ population has been lacking and has caused difficulties in designing programs such as selection, crossbreeding, breed improvement or conservation. This study was designed to evaluate the genetic structure, assess genetic relationships, and to identify signatures of selection among cattle of Tanzania with the main goal of understanding genetic relationship, variation and uniqueness among them. Methodology/Principal findings The Illumina Bos indicus SNP 80K BeadChip was used to genotype genome wide SNPs in 168 DNA samples obtained from three strains of TSZ cattle namely Maasai, Tarime and Sukuma as well as two comparative breeds; Boran and Friesian. Population structure and signatures of selection were examined using principal component analysis (PCA), admixture analysis, pairwise distances (FST), integrated haplotype score (iHS), identical by state (IBS) and runs of homozygosity (ROH). There was a low level of inbreeding (F~0.01) in the TSZ population compared to the Boran and Friesian breeds. The analyses of FST, IBS and admixture identified no considerable differentiation between TSZ trains. Importantly, common ancestry in Boran and TSZ were revealed based on admixture and IBD, implying gene flow between two populations. In addition, Friesian ancestry was found in Boran. A few common significant iHS were detected, which may reflect influence of recent selection in each breed or strain. Conclusions Population admixture and selection signatures could be applied to develop conservation plan of TSZ cattle as well as future breeding programs in East African cattle. PMID:28129396

Optimal Refueling Pattern Search for a CANDU Reactor Using a Genetic Algorithm

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

Quang Binh, DO; Gyuhong, ROH; Hangbok, CHOI

2006-07-01

This paper presents the results from the application of genetic algorithms to a refueling optimization of a Canada deuterium uranium (CANDU) reactor. This work aims at making a mathematical model of the refueling optimization problem including the objective function and constraints and developing a method based on genetic algorithms to solve the problem. The model of the optimization problem and the proposed method comply with the key features of the refueling strategy of the CANDU reactor which adopts an on-power refueling operation. In this study, a genetic algorithm combined with an elitism strategy was used to automatically search for themore » refueling patterns. The objective of the optimization was to maximize the discharge burn-up of the refueling bundles, minimize the maximum channel power, or minimize the maximum change in the zone controller unit (ZCU) water levels. A combination of these objectives was also investigated. The constraints include the discharge burn-up, maximum channel power, maximum bundle power, channel power peaking factor and the ZCU water level. A refueling pattern that represents the refueling rate and channels was coded by a one-dimensional binary chromosome, which is a string of binary numbers 0 and 1. A computer program was developed in FORTRAN 90 running on an HP 9000 workstation to conduct the search for the optimal refueling patterns for a CANDU reactor at the equilibrium state. The results showed that it was possible to apply genetic algorithms to automatically search for the refueling channels of the CANDU reactor. The optimal refueling patterns were compared with the solutions obtained from the AUTOREFUEL program and the results were consistent with each other. (authors)« less

There is room for selection in a small local pig breed when using optimum contribution selection: a simulation study.

PubMed

Gourdine, J L; Sørensen, A C; Rydhmer, L

2012-01-01

Selection progress must be carefully balanced against the conservation of genetic variation in small populations of local breeds. Well-defined breeding programs with specified selection traits are rare in local pig breeds. Given the small population size, the focus is often on the management of genetic diversity. However, in local breeds, optimum contribution selection can be applied to control the rate of inbreeding and to avoid reduced performance in traits with high market value. The aim of this study was to assess the extent to which a breeding program aiming for improved product quality in a small local breed would be feasible. We used stochastic simulations to compare 25 scenarios. The scenarios differed in size of population, selection intensity of boars, type of selection (random selection, truncation selection based on BLUP breeding values, or optimum contribution selection based on BLUP breeding values), and heritability of the selection trait. It was assumed that the local breed is used in an extensive system for a high-meat-quality market. The simulations showed that in the smallest population (300 female reproducers), inbreeding increased by 0.8% when selection was performed at random. With optimum contribution selection, genetic progress can be achieved that is almost as great as that with truncation selection based on BLUP breeding values (0.2 to 0.5 vs. 0.3 to 0.5 genetic SD, P < 0.05), but at a considerably decreased rate of inbreeding (0.7 to 1.2 vs. 2.3 to 5.7%, P < 0.01). This confirmation of the potential utilization of OCS even in small populations is important in the context of sustainable management and the use of animal genetic resources.

Applied reproductive technologies and genetic resource banking for amphibian conservation.

PubMed

Kouba, Andrew J; Vance, Carrie K

2009-01-01

As amphibian populations continue to decline, both government and non-government organisations are establishing captive assurance colonies to secure populations deemed at risk of extinction if left in the wild. For the most part, little is known about the nutritional ecology, reproductive biology or husbandry needs of the animals placed into captive breeding programs. Because of this lack of knowledge, conservation biologists are currently facing the difficult task of maintaining and reproducing these species. Academic and zoo scientists are beginning to examine different technologies for maintaining the genetic diversity of founder populations brought out of the wild before the animals become extinct from rapidly spreading epizootic diseases. One such technology is genetic resource banking and applied reproductive technologies for species that are difficult to reproduce reliably in captivity. Significant advances have been made in the last decade for amphibian assisted reproduction including the use of exogenous hormones for induction of spermiation and ovulation, in vitro fertilisation, short-term cold storage of gametes and long-term cryopreservation of spermatozoa. These scientific breakthroughs for a select few species will no doubt serve as models for future assisted breeding protocols and the increasing number of amphibians requiring conservation intervention. However, the development of specialised assisted breeding protocols that can be applied to many different families of amphibians will likely require species-specific modifications considering their wide range of reproductive modes. The purpose of this review is to summarise the current state of knowledge in the area of assisted reproduction technologies and gene banking for the conservation of amphibians.

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

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

Adaptable Constrained Genetic Programming: Extensions and Applications

NASA Technical Reports Server (NTRS)

Janikow, Cezary Z.

2005-01-01

An evolutionary algorithm applies evolution-based principles to problem solving. To solve a problem, the user defines the space of potential solutions, the representation space. Sample solutions are encoded in a chromosome-like structure. The algorithm maintains a population of such samples, which undergo simulated evolution by means of mutation, crossover, and survival of the fittest principles. Genetic Programming (GP) uses tree-like chromosomes, providing very rich representation suitable for many problems of interest. GP has been successfully applied to a number of practical problems such as learning Boolean functions and designing hardware circuits. To apply GP to a problem, the user needs to define the actual representation space, by defining the atomic functions and terminals labeling the actual trees. The sufficiency principle requires that the label set be sufficient to build the desired solution trees. The closure principle allows the labels to mix in any arity-consistent manner. To satisfy both principles, the user is often forced to provide a large label set, with ad hoc interpretations or penalties to deal with undesired local contexts. This unfortunately enlarges the actual representation space, and thus usually slows down the search. In the past few years, three different methodologies have been proposed to allow the user to alleviate the closure principle by providing means to define, and to process, constraints on mixing the labels in the trees. Last summer we proposed a new methodology to further alleviate the problem by discovering local heuristics for building quality solution trees. A pilot system was implemented last summer and tested throughout the year. This summer we have implemented a new revision, and produced a User's Manual so that the pilot system can be made available to other practitioners and researchers. We have also designed, and partly implemented, a larger system capable of dealing with much more powerful heuristics.

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.

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

NASA Astrophysics Data System (ADS)

Krajíček, Jiří

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

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.

Genetic engineering of cyanobacteria as biodiesel feedstock.

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

Ruffing, Anne.; Trahan, Christine Alexandra; Jones, Howland D. T.

2013-01-01

Algal biofuels are a renewable energy source with the potential to replace conventional petroleum-based fuels, while simultaneously reducing greenhouse gas emissions. The economic feasibility of commercial algal fuel production, however, is limited by low productivity of the natural algal strains. The project described in this SAND report addresses this low algal productivity by genetically engineering cyanobacteria (i.e. blue-green algae) to produce free fatty acids as fuel precursors. The engineered strains were characterized using Sandias unique imaging capabilities along with cutting-edge RNA-seq technology. These tools are applied to identify additional genetic targets for improving fuel production in cyanobacteria. This proof-of-concept studymore » demonstrates successful fuel production from engineered cyanobacteria, identifies potential limitations, and investigates several strategies to overcome these limitations. This project was funded from FY10-FY13 through the President Harry S. Truman Fellowship in National Security Science and Engineering, a program sponsored by the LDRD office at Sandia National Laboratories.« less

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.

Implementation and utilization of genetic testing in personalized medicine

PubMed Central

Abul-Husn, Noura S; Owusu Obeng, Aniwaa; Sanderson, Saskia C; Gottesman, Omri; Scott, Stuart A

2014-01-01

Clinical genetic testing began over 30 years ago with the availability of mutation detection for sickle cell disease diagnosis. Since then, the field has dramatically transformed to include gene sequencing, high-throughput targeted genotyping, prenatal mutation detection, preimplantation genetic diagnosis, population-based carrier screening, and now genome-wide analyses using microarrays and next-generation sequencing. Despite these significant advances in molecular technologies and testing capabilities, clinical genetics laboratories historically have been centered on mutation detection for Mendelian disorders. However, the ongoing identification of deoxyribonucleic acid (DNA) sequence variants associated with common diseases prompted the availability of testing for personal disease risk estimation, and created commercial opportunities for direct-to-consumer genetic testing companies that assay these variants. This germline genetic risk, in conjunction with other clinical, family, and demographic variables, are the key components of the personalized medicine paradigm, which aims to apply personal genomic and other relevant data into a patient’s clinical assessment to more precisely guide medical management. However, genetic testing for disease risk estimation is an ongoing topic of debate, largely due to inconsistencies in the results, concerns over clinical validity and utility, and the variable mode of delivery when returning genetic results to patients in the absence of traditional counseling. A related class of genetic testing with analogous issues of clinical utility and acceptance is pharmacogenetic testing, which interrogates sequence variants implicated in interindividual drug response variability. Although clinical pharmacogenetic testing has not previously been widely adopted, advances in rapid turnaround time genetic testing technology and the recent implementation of preemptive genotyping programs at selected medical centers suggest that personalized medicine through pharmacogenetics is now a reality. This review aims to summarize the current state of implementing genetic testing for personalized medicine, with an emphasis on clinical pharmacogenetic testing. PMID:25206309

Online Learning of Genetic Network Programming and its Application to Prisoner’s Dilemma Game

NASA Astrophysics Data System (ADS)

Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

A new evolutionary model with the network structure named Genetic Network Programming (GNP) has been proposed recently. GNP, that is, an expansion of GA and GP, represents solutions as a network structure and evolves it by using “offline learning (selection, mutation, crossover)”. GNP can memorize the past action sequences in the network flow, so it can deal with Partially Observable Markov Decision Process (POMDP) well. In this paper, in order to improve the ability of GNP, Q learning (an off-policy TD control algorithm) that is one of the famous online methods is introduced for online learning of GNP. Q learning is suitable for GNP because (1) in reinforcement learning, the rewards an agent will get in the future can be estimated, (2) TD control doesn’t need much memory and can learn quickly, and (3) off-policy is suitable in order to search for an optimal solution independently of the policy. Finally, in the simulations, online learning of GNP is applied to a player for “Prisoner’s dilemma game” and its ability for online adaptation is confirmed.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

[The practice and discussion of the physical knowledge stepping into genetics teaching].

PubMed

Luo, Shen; Luo, Peigao

2014-09-01

Genetics, one of the core courses of biological field, play a key role in biology teaching and research. In fact, there exists high similarity between many genetic knowledge and physical knowledge. Due to strong abstract of genetic contents and the weak basis of genetics, some students lack of interests to study genetics. How to apply the strong physical knowledge which students had been learned in the middle school in genetics teaching is worthwhile for genetics teachers. In this paper, we would like to introduce an infiltrative teaching model on applying physical knowledge into genetic contents by establishing the intrinsic logistic relationship between physical knowledge and genetic knowledge. This teaching model could help students more deeply understand genetic knowledge and enhance students' self-studying ability as well as creating ability.

Newborn screening in Victoria: a case study of tissue banking regulation.

PubMed

Lawson, Charles

2008-12-01

The regulation of human tissue collections is increasingly important in maintaining public trust (and legitimacy) for critical practices and resources directed to public health programs and research. This article examines the governance arrangements applying to VCGS Ltd (under its various incarnations as "Genetic Health Services Victoria", "VCGS Pathology", and so on) and the existing collection of population-wide blood samples maintained on newborn screening cards (or Guthrie cards) in Victoria. The analyses reveal a complex web of regulations (and possibly even no regulation) and the limited role of significant statutory schemes that are generally assumed to apply to human tissue collections and the data and information derived from those materials. The article argues that, without a clear regulatory framework (and in particular meaningful consent), there is likely to be a decline in public trust (and legitimacy) with a consequent decreased participation in what is a public health program with immediate and quantifiable benefits and a valuable research resource for the future.

A graph-based evolutionary algorithm: Genetic Network Programming (GNP) and its extension using reinforcement learning.

PubMed

Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu

2007-01-01

This paper proposes a graph-based evolutionary algorithm called Genetic Network Programming (GNP). Our goal is to develop GNP, which can deal with dynamic environments efficiently and effectively, based on the distinguished expression ability of the graph (network) structure. The characteristics of GNP are as follows. 1) GNP programs are composed of a number of nodes which execute simple judgment/processing, and these nodes are connected by directed links to each other. 2) The graph structure enables GNP to re-use nodes, thus the structure can be very compact. 3) The node transition of GNP is executed according to its node connections without any terminal nodes, thus the past history of the node transition affects the current node to be used and this characteristic works as an implicit memory function. These structural characteristics are useful for dealing with dynamic environments. Furthermore, we propose an extended algorithm, "GNP with Reinforcement Learning (GNPRL)" which combines evolution and reinforcement learning in order to create effective graph structures and obtain better results in dynamic environments. In this paper, we applied GNP to the problem of determining agents' behavior to evaluate its effectiveness. Tileworld was used as the simulation environment. The results show some advantages for GNP over conventional methods.

Fuzzy multiobjective models for optimal operation of a hydropower system

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

Large-scale SNP discovery and construction of a high-density genetic map of Colossoma macropomum through genotyping-by-sequencing

PubMed Central

Nunes, José de Ribamar da Silva; Liu, Shikai; Pértille, Fábio; Perazza, Caio Augusto; Villela, Priscilla Marqui Schmidt; de Almeida-Val, Vera Maria Fonseca; Hilsdorf, Alexandre Wagner Silva; Liu, Zhanjiang; Coutinho, Luiz Lehmann

2017-01-01

Colossoma macropomum, or tambaqui, is the largest native Characiform species found in the Amazon and Orinoco river basins, yet few resources for genetic studies and the genetic improvement of tambaqui exist. In this study, we identified a large number of single-nucleotide polymorphisms (SNPs) for tambaqui and constructed a high-resolution genetic linkage map from a full-sib family of 124 individuals and their parents using the genotyping by sequencing method. In all, 68,584 SNPs were initially identified using minimum minor allele frequency (MAF) of 5%. Filtering parameters were used to select high-quality markers for linkage analysis. We selected 7,734 SNPs for linkage mapping, resulting in 27 linkage groups with a minimum logarithm of odds (LOD) of 8 and maximum recombination fraction of 0.35. The final genetic map contains 7,192 successfully mapped markers that span a total of 2,811 cM, with an average marker interval of 0.39 cM. Comparative genomic analysis between tambaqui and zebrafish revealed variable levels of genomic conservation across the 27 linkage groups which allowed for functional SNP annotations. The large-scale SNP discovery obtained here, allowed us to build a high-density linkage map in tambaqui, which will be useful to enhance genetic studies that can be applied in breeding programs. PMID:28387238

Genetic relationship between growth and reproductive traits in Nellore cattle.

PubMed

Santana, M L; Eler, J P; Ferraz, J B S; Mattos, E C

2012-04-01

The objective of this study was to evaluate the genetic relationship between postweaning weight gain (PWG), heifer pregnancy (HP), scrotal circumference (SC) at 18 months of age, stayability at 6 years of age (STAY) and finishing visual score at 18 months of age (PREC), and to determine the potential of these traits as selection criteria for the genetic improvement of growth and reproduction in Nellore cattle. The HP was defined as the observation that a heifer conceived and remained pregnant, which was assessed by rectal palpation at 60 days. The STAY was defined as whether or not a cow calved every year up to the age of 6 years, given that she was provided the opportunity to breed. The Bayesian linear-threshold analysis via the Gibbs sampler was used to estimate the variance and covariance components applying a multitrait model. Posterior mean estimates of direct heritability were 0.15 ± 0.00, 0.42 ± 0.02, 0.49 ± 0.01, 0.11 ± 0.01 and 0.19 ± 0.00 for PWG, HP, SC, STAY and PREC, respectively. The genetic correlations between traits ranged from 0.17 to 0.62. The traits studied generally have potential for use as selection criteria in genetic breeding programs. The genetic correlations between all traits show that selection for one of these traits does not imply the loss of the others.

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.

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-...

Research Associate | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) at the Frederick National Laboratory for Cancer Research (FNLCR) pursues independent, multidisciplinary research programs in basic or applied molecular biology, immunology, retrovirology, cancer biology or human genetics. As part of the BSP, the Microbiome and Genetics Core (the Core) characterizes microbiomes by next-generation sequencing to determine their composition and variation, as influenced by immune, genetic, and host health factors. The Core provides support across a spectrum of processes, from nucleic acid isolation through bioinformatics and statistical analysis. KEY ROLES/RESPONSIBILITIES The Research Associate II will provide support in the areas of automated isolation, preparation, PCR and sequencing of DNA on next generation platforms (Illumina MiSeq and NextSeq). An opportunity exists to join the Core’s team of highly trained experimentalists and bioinformaticians working to characterize microbiome samples. The following represent requirements of the position: A minimum of five (5) years related of biomedical experience. Experience with high-throughput nucleic acid (DNA/RNA) extraction. Experience in performing PCR amplification (including quantitative real-time PCR). Experience or familiarity with robotic liquid handling protocols (especially on the Eppendorf epMotion 5073 or 5075 platforms). Experience in operating and maintaining benchtop Illumina sequencers (MiSeq and NextSeq). Ability to evaluate experimental quality and to troubleshoot molecular biology protocols. Experience with sample tracking, inventory management and biobanking. Ability to operate and communicate effectively in a team-oriented work environment.

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

Multiple Models for Rosaceae Genomics[OA

PubMed Central

Shulaev, Vladimir; Korban, Schuyler S.; Sosinski, Bryon; Abbott, Albert G.; Aldwinckle, Herb S.; Folta, Kevin M.; Iezzoni, Amy; Main, Dorrie; Arús, Pere; Dandekar, Abhaya M.; Lewers, Kim; Brown, Susan K.; Davis, Thomas M.; Gardiner, Susan E.; Potter, Daniel; Veilleux, Richard E.

2008-01-01

The plant family Rosaceae consists of over 100 genera and 3,000 species that include many important fruit, nut, ornamental, and wood crops. Members of this family provide high-value nutritional foods and contribute desirable aesthetic and industrial products. Most rosaceous crops have been enhanced by human intervention through sexual hybridization, asexual propagation, and genetic improvement since ancient times, 4,000 to 5,000 B.C. Modern breeding programs have contributed to the selection and release of numerous cultivars having significant economic impact on the U.S. and world markets. In recent years, the Rosaceae community, both in the United States and internationally, has benefited from newfound organization and collaboration that have hastened progress in developing genetic and genomic resources for representative crops such as apple (Malus spp.), peach (Prunus spp.), and strawberry (Fragaria spp.). These resources, including expressed sequence tags, bacterial artificial chromosome libraries, physical and genetic maps, and molecular markers, combined with genetic transformation protocols and bioinformatics tools, have rendered various rosaceous crops highly amenable to comparative and functional genomics studies. This report serves as a synopsis of the resources and initiatives of the Rosaceae community, recent developments in Rosaceae genomics, and plans to apply newly accumulated knowledge and resources toward breeding and crop improvement. PMID:18487361

Genetic profile of scrapie codons 146, 211 and 222 in the PRNP gene locus in three breeds of dairy goats.

PubMed

Vouraki, Sotiria; Gelasakis, Athanasios I; Alexandri, Panoraia; Boukouvala, Evridiki; Ekateriniadou, Loukia V; Banos, Georgios; Arsenos, Georgios

2018-01-01

Polymorphisms at PRNP gene locus have been associated with resistance against classical scrapie in goats. Genetic selection on this gene within appropriate breeding programs may contribute to the control of the disease. The present study characterized the genetic profile of codons 146, 211 and 222 in three dairy goat breeds in Greece. A total of 766 dairy goats from seven farms were used. Animals belonged to two indigenous Greek, Eghoria (n = 264) and Skopelos (n = 287) and a foreign breed, Damascus (n = 215). Genomic DNA was extracted from blood samples from individual animals. Polymorphisms were detected in these codons using Real-Time PCR analysis and four different Custom TaqMan® SNP Genotyping Assays. Genotypic, allelic and haplotypic frequencies were calculated based on individual animal genotypes. Chi-square tests were used to examine Hardy-Weinberg equilibrium state and compare genotypic distribution across breeds. Genetic distances among the three breeds, and between these and 30 breeds reared in other countries were estimated based on haplotypic frequencies using fixation index FST with Arlequin v3.1 software; a Neighbor-Joining tree was created using PHYLIP package v3.695. Level of statistical significance was set at P = 0.01. All scrapie resistance-associated alleles (146S, 146D, 211Q and 222K) were detected in the studied population. Significant frequency differences were observed between the indigenous Greek and Damascus breeds. Alleles 222K and 146S had the highest frequency in the two indigenous and the Damascus breed, respectively (ca. 6.0%). The studied breeds shared similar haplotypic frequencies with most South Italian and Turkish breeds but differed significantly from North-Western European, Far East and some USA goat breeds. Results suggest there is adequate variation in the PRNP gene locus to support breeding programs for enhanced scrapie resistance in goats reared in Greece. Genetic comparisons among goat breeds indicate that separate breeding programs should apply to the two indigenous and the imported Damascus breeds.

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.

Interview: Professor Andrew Feinberg speaks to Epigenomics.

PubMed

Feinberg, Andrew

2009-10-01

Andrew Feinberg studied mathematics and humanities at Yale University (CT, USA) in the Directed Studies honors program, and he received his BA (1973) and MD (1976) from the accelerated medical program at Johns Hopkins University (MD, USA), as well as an MPH from Johns Hopkins (1981). He performed a postdoctoral fellowship in developmental biology at the University of California, San Diego (UCSD, CA, USA), clinical training in medicine and medical genetics at the University of Pennsylvania (PA, USA) and genetics research with Bert Vogelstein at Johns Hopkins, discovering altered DNA methylation in human cancer. Dr Feinberg continued to perform seminal work in cancer epigenetics as a Howard Hughes investigator at the University of Michigan (MI, USA), discovering human imprinted genes and loss of imprinting in cancer, and the molecular basis of Beckwith-Wiedemann syndrome. He returned to John Hopkins in 1994 as King Fahd Professor of Medicine, Molecular Biology & Genetics and Oncology, and he holds an Adjunct Professorship at the Karolinska Institute in Sweden. Dr Feinberg is Director of the Center for Epigenetics, a National Human Genome Research Institute-designated Center of Excellence in Genome Sciences. The Center is pioneering genome-scale tools in molecular, statistical and epidemiological epigenetics, and is applying them to the study of cancer, neuropsychiatric disease and aging. As part of the center, Dr Feinberg has organized a highly innovative program to bring gifted minority high-school students into genetics and genomics. Dr Feinberg has also invented a number of widely used molecular tools, including random priming. His honors include election to the American Society for Clinical Investigation, the Association of American Physicians, the Institute of Medicine of the National Academy of Sciences, and the American Academy of Arts and Sciences, as well as membership on the ISI most-cited authors list, a MERIT Award of the National Cancer Institute, a Doctor of Philosophy (Hon. Caus.) from Uppsala University (Sweden), and the President's Diversity Recognition Award of Johns Hopkins University.

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

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.

Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

PubMed

Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

2017-11-01

Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes

PubMed Central

2013-01-01

Motivation Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. Results We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. Availability The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana. PMID:24564704

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes.

PubMed

Wang, Yue; Goh, Wilson; Wong, Limsoon; Montana, Giovanni

2013-01-01

Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana.

Automated Discovery of Functional Generality of Human Gene Expression Programs

PubMed Central

Gerber, Georg K; Dowell, Robin D; Jaakkola, Tommi S; Gifford, David K

2007-01-01

An important research problem in computational biology is the identification of expression programs, sets of co-expressed genes orchestrating normal or pathological processes, and the characterization of the functional breadth of these programs. The use of human expression data compendia for discovery of such programs presents several challenges including cellular inhomogeneity within samples, genetic and environmental variation across samples, uncertainty in the numbers of programs and sample populations, and temporal behavior. We developed GeneProgram, a new unsupervised computational framework based on Hierarchical Dirichlet Processes that addresses each of the above challenges. GeneProgram uses expression data to simultaneously organize tissues into groups and genes into overlapping programs with consistent temporal behavior, to produce maps of expression programs, which are sorted by generality scores that exploit the automatically learned groupings. Using synthetic and real gene expression data, we showed that GeneProgram outperformed several popular expression analysis methods. We applied GeneProgram to a compendium of 62 short time-series gene expression datasets exploring the responses of human cells to infectious agents and immune-modulating molecules. GeneProgram produced a map of 104 expression programs, a substantial number of which were significantly enriched for genes involved in key signaling pathways and/or bound by NF-κB transcription factors in genome-wide experiments. Further, GeneProgram discovered expression programs that appear to implicate surprising signaling pathways or receptor types in the response to infection, including Wnt signaling and neurotransmitter receptors. We believe the discovered map of expression programs involved in the response to infection will be useful for guiding future biological experiments; genes from programs with low generality scores might serve as new drug targets that exhibit minimal “cross-talk,” and genes from high generality programs may maintain common physiological responses that go awry in disease states. Further, our method is multipurpose, and can be applied readily to novel compendia of biological data. PMID:17696603

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.

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 ...

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.

Genetic programming and serial processing for time series classification.

PubMed

Alfaro-Cid, Eva; Sharman, Ken; Esparcia-Alcázar, Anna I

2014-01-01

This work describes an approach devised by the authors for time series classification. In our approach genetic programming is used in combination with a serial processing of data, where the last output is the result of the classification. The use of genetic programming for classification, although still a field where more research in needed, is not new. However, the application of genetic programming to classification tasks is normally done by considering the input data as a feature vector. That is, to the best of our knowledge, there are not examples in the genetic programming literature of approaches where the time series data are processed serially and the last output is considered as the classification result. The serial processing approach presented here fills a gap in the existing literature. This approach was tested in three different problems. Two of them are real world problems whose data were gathered for online or conference competitions. As there are published results of these two problems this gives us the chance to compare the performance of our approach against top performing methods. The serial processing of data in combination with genetic programming obtained competitive results in both competitions, showing its potential for solving time series classification problems. The main advantage of our serial processing approach is that it can easily handle very large datasets.

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.

Teaching Applied Genetics and Molecular Biology to Agriculture Engineers. Application of the European Credit Transfer System

ERIC Educational Resources Information Center

Weiss, J.; Egea-Cortines, M.

2008-01-01

We have been teaching applied molecular genetics to engineers and adapted the teaching methodology to the European Credit Transfer System. We teach core principles of genetics that are universal and form the conceptual basis of most molecular technologies. The course then teaches widely used techniques and finally shows how different techniques…

Review of Current Conservation Genetic Analyses of Northeast Pacific Sharks.

PubMed

Larson, Shawn E; Daly-Engel, Toby S; Phillips, Nicole M

Conservation genetics is an applied science that utilizes molecular tools to help solve problems in species conservation and management. It is an interdisciplinary specialty in which scientists apply the study of genetics in conjunction with traditional ecological fieldwork and other techniques to explore molecular variation, population boundaries, and evolutionary relationships with the goal of enabling resource managers to better protect biodiversity and identify unique populations. Several shark species in the northeast Pacific (NEP) have been studied using conservation genetics techniques, which are discussed here. The primary methods employed to study population genetics of sharks have historically been nuclear microsatellites and mitochondrial (mt) DNA. These markers have been used to assess genetic diversity, mating systems, parentage, relatedness, and genetically distinct populations to inform management decisions. Novel approaches in conservation genetics, including next-generation DNA and RNA sequencing, environmental DNA (eDNA), and epigenetics are just beginning to be applied to elasmobranch evolution, physiology, and ecology. Here, we review the methods and results of past studies, explore future directions for shark conservation genetics, and discuss the implications of molecular research and techniques for the long-term management of shark populations in the NEP. © 2017 Elsevier Ltd. All rights reserved.

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data.

PubMed

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S; Windus, Theresa L; Dick-Perez, Marilu

2017-03-27

A newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides, important for metal extraction chemistry, are parametrized using ParFit. ParFit is in an open source program available for free on GitHub ( https://github.com/fzahari/ParFit ).

Inclusion Criteria for NCI Cancer Genetics Services Directory

Cancer.gov

Professionals who provide services related to cancer genetics (cancer risk assessment, genetic counseling, genetic susceptibility testing, and others) must meet these criteria before applying to be listed in the National Cancer Institute's Cancer Genetics Services Directory.

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.

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.

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.

Summary of the National Toxicology Program benzidine dye initiative.

PubMed Central

Morgan, D L; Dunnick, J K; Goehl, T; Jokinen, M P; Matthews, H B; Zeiger, E; Mennear, J H

1994-01-01

The benzidine dye initiative is a research program established by the National Toxicology Program to generate an integrated body of scientific information regarding the potential health risks associated with exposure to benzidine- and benzidine-congener-derived dyes. Because an in-depth evaluation of each of the hundreds of benzidine-congener-derived dyes was considered impractical, the research program was designed to study the metabolism and disposition, genetic toxicity, and in vivo toxicity and carcinogenicity of two primary benzidine congeners, 3,3'-dimethylbenzidine and 3,3'-dimethoxybenzidine, and a select group of prototypical dyes derived from those amines. It was anticipated that by applying the basic information generated in these extensive studies, it would be possible to make regulatory decisions about other dyes after conducting only a minimal number of experiments such as studies of disposition and metabolism, and in vitro mutagenicity. This paper summarizes the results of studies conducted to evaluate the metabolism, disposition, mutagenicity, toxicity, and carcinogenicity of representative benzidine congeners and derived dyes. PMID:7925189

A novel program to design siRNAs simultaneously effective to highly variable virus genomes.

PubMed

Lee, Hui Sun; Ahn, Jeonghyun; Jun, Eun Jung; Yang, Sanghwa; Joo, Chul Hyun; Kim, Yoo Kyum; Lee, Heuiran

2009-07-10

A major concern of antiviral therapy using small interfering RNAs (siRNAs) targeting RNA viral genome is high sequence diversity and mutation rate due to genetic instability. To overcome this problem, it is indispensable to design siRNAs targeting highly conserved regions. We thus designed CAPSID (Convenient Application Program for siRNA Design), a novel bioinformatics program to identify siRNAs targeting highly conserved regions within RNA viral genomes. From a set of input RNAs of diverse sequences, CAPSID rapidly searches conserved patterns and suggests highly potent siRNA candidates in a hierarchical manner. To validate the usefulness of this novel program, we investigated the antiviral potency of universal siRNA for various Human enterovirus B (HEB) serotypes. Assessment of antiviral efficacy using Hela cells, clearly demonstrates that HEB-specific siRNAs exhibit protective effects against all HEBs examined. These findings strongly indicate that CAPSID can be applied to select universal antiviral siRNAs against highly divergent viral genomes.

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)

Layout design-based research on optimization and assessment method for shipbuilding workshop

NASA Astrophysics Data System (ADS)

Liu, Yang; Meng, Mei; Liu, Shuang

2013-06-01

The research study proposes to examine a three-dimensional visualization program, emphasizing on improving genetic algorithms through the optimization of a layout design-based standard and discrete shipbuilding workshop. By utilizing a steel processing workshop as an example, the principle of minimum logistic costs will be implemented to obtain an ideological equipment layout, and a mathematical model. The objectiveness is to minimize the total necessary distance traveled between machines. An improved control operator is implemented to improve the iterative efficiency of the genetic algorithm, and yield relevant parameters. The Computer Aided Tri-Dimensional Interface Application (CATIA) software is applied to establish the manufacturing resource base and parametric model of the steel processing workshop. Based on the results of optimized planar logistics, a visual parametric model of the steel processing workshop is constructed, and qualitative and quantitative adjustments then are applied to the model. The method for evaluating the results of the layout is subsequently established through the utilization of AHP. In order to provide a mode of reference to the optimization and layout of the digitalized production workshop, the optimized discrete production workshop will possess a certain level of practical significance.

Genetic algorithm dynamics on a rugged landscape

NASA Astrophysics Data System (ADS)

Bornholdt, Stefan

1998-04-01

The genetic algorithm is an optimization procedure motivated by biological evolution and is successfully applied to optimization problems in different areas. A statistical mechanics model for its dynamics is proposed based on the parent-child fitness correlation of the genetic operators, making it applicable to general fitness landscapes. It is compared to a recent model based on a maximum entropy ansatz. Finally it is applied to modeling the dynamics of a genetic algorithm on the rugged fitness landscape of the NK model.

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

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.

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.

HIPAA's Individual Right of Access to Genomic Data: Reconciling Safety and Civil Rights.

PubMed

Evans, Barbara J

2018-01-04

In 2014, the United States granted individuals a right of access to their own laboratory test results, including genomic data. Many observers feel that this right is in tension with regulatory and bioethical standards designed to protect the safety of people who undergo genomic testing. This commentary attributes this tension to growing pains within an expanding federal regulatory program for genetic and genomic testing. The Genetic Information Nondiscrimination Act of 2008 expanded the regulatory agenda to encompass civil rights and consumer safety. The individual access right, as it applies to genomic data, is best understood as a civil-rights regulation. Competing regulatory objectives-safety and civil rights-were not successfully integrated during the initial rollout of genomic civil-rights regulations after 2008. Federal law clarifies how to prioritize safety and civil rights when the two come into conflict, although with careful policy design, the two need not collide. This commentary opens a dialog about possible solutions to advance safety and civil rights together. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

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.

A Tri-Part Model for Genetics Literacy: Exploring Undergraduate Student Reasoning about Authentic Genetics Dilemmas

ERIC Educational Resources Information Center

Shea, Nicole A.; Duncan, Ravit Golan; Stephenson, Celeste

2015-01-01

Genetics literacy is becoming increasingly important as advancements in our application of genetic technologies such as stem cell research, cloning, and genetic screening become more prevalent. Very few studies examine how genetics literacy is applied when reasoning about authentic genetic dilemmas. However, there is evidence that situational…

Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

PubMed Central

Molla-Alizadeh-Zavardehi, S.; Tavakkoli-Moghaddam, R.; Lotfi, F. Hosseinzadeh

2014-01-01

This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms. PMID:24883359

A binary genetic programing model for teleconnection identification between global sea surface temperature and local maximum monthly rainfall events

NASA Astrophysics Data System (ADS)

Danandeh Mehr, Ali; Nourani, Vahid; Hrnjica, Bahrudin; Molajou, Amir

2017-12-01

The effectiveness of genetic programming (GP) for solving regression problems in hydrology has been recognized in recent studies. However, its capability to solve classification problems has not been sufficiently explored so far. This study develops and applies a novel classification-forecasting model, namely Binary GP (BGP), for teleconnection studies between sea surface temperature (SST) variations and maximum monthly rainfall (MMR) events. The BGP integrates certain types of data pre-processing and post-processing methods with conventional GP engine to enhance its ability to solve both regression and classification problems simultaneously. The model was trained and tested using SST series of Black Sea, Mediterranean Sea, and Red Sea as potential predictors as well as classified MMR events at two locations in Iran as predictand. Skill of the model was measured in regard to different rainfall thresholds and SST lags and compared to that of the hybrid decision tree-association rule (DTAR) model available in the literature. The results indicated that the proposed model can identify potential teleconnection signals of surrounding seas beneficial to long-term forecasting of the occurrence of the classified MMR events.

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

PubMed

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

2004-11-01

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

A CAL Program to Teach the Basic Principles of Genetic Engineering--A Change from the Traditional Approach.

ERIC Educational Resources Information Center

Dewhurst, D. G.; And Others

1989-01-01

An interactive computer-assisted learning program written for the BBC microcomputer to teach the basic principles of genetic engineering is described. Discussed are the hardware requirements software, use of the program, and assessment. (Author/CW)

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

Experimental design for estimating unknown groundwater pumping using genetic algorithm and reduced order model

NASA Astrophysics Data System (ADS)

Ushijima, Timothy T.; Yeh, William W.-G.

2013-10-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.

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

Do-it-yourself statistics: A computer-assisted likelihood approach to analysis of data from genetic crosses.

PubMed Central

Robbins, L G

2000-01-01

Graduate school programs in genetics have become so full that courses in statistics have often been eliminated. In addition, typical introductory statistics courses for the "statistics user" rather than the nascent statistician are laden with methods for analysis of measured variables while genetic data are most often discrete numbers. These courses are often seen by students and genetics professors alike as largely irrelevant cookbook courses. The powerful methods of likelihood analysis, although commonly employed in human genetics, are much less often used in other areas of genetics, even though current computational tools make this approach readily accessible. This article introduces the MLIKELY.PAS computer program and the logic of do-it-yourself maximum-likelihood statistics. The program itself, course materials, and expanded discussions of some examples that are only summarized here are available at http://www.unisi. it/ricerca/dip/bio_evol/sitomlikely/mlikely.h tml. PMID:10628965

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

A hybrid intelligent algorithm for portfolio selection problem with fuzzy returns

NASA Astrophysics Data System (ADS)

Li, Xiang; Zhang, Yang; Wong, Hau-San; Qin, Zhongfeng

2009-11-01

Portfolio selection theory with fuzzy returns has been well developed and widely applied. Within the framework of credibility theory, several fuzzy portfolio selection models have been proposed such as mean-variance model, entropy optimization model, chance constrained programming model and so on. In order to solve these nonlinear optimization models, a hybrid intelligent algorithm is designed by integrating simulated annealing algorithm, neural network and fuzzy simulation techniques, where the neural network is used to approximate the expected value and variance for fuzzy returns and the fuzzy simulation is used to generate the training data for neural network. Since these models are used to be solved by genetic algorithm, some comparisons between the hybrid intelligent algorithm and genetic algorithm are given in terms of numerical examples, which imply that the hybrid intelligent algorithm is robust and more effective. In particular, it reduces the running time significantly for large size problems.

ANT: Software for Generating and Evaluating Degenerate Codons for Natural and Expanded Genetic Codes.

PubMed

Engqvist, Martin K M; Nielsen, Jens

2015-08-21

The Ambiguous Nucleotide Tool (ANT) is a desktop application that generates and evaluates degenerate codons. Degenerate codons are used to represent DNA positions that have multiple possible nucleotide alternatives. This is useful for protein engineering and directed evolution, where primers specified with degenerate codons are used as a basis for generating libraries of protein sequences. ANT is intuitive and can be used in a graphical user interface or by interacting with the code through a defined application programming interface. ANT comes with full support for nonstandard, user-defined, or expanded genetic codes (translation tables), which is important because synthetic biology is being applied to an ever widening range of natural and engineered organisms. The Python source code for ANT is freely distributed so that it may be used without restriction, modified, and incorporated in other software or custom data pipelines.

Development of Web-Based Menu Planning Support System and its Solution Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Kashima, Tomoko; Matsumoto, Shimpei; Ishii, Hiroaki

2009-10-01

Recently lifestyle-related diseases have become an object of public concern, while at the same time people are being more health conscious. As an essential factor for causing the lifestyle-related diseases, we assume that the knowledge circulation on dietary habits is still insufficient. This paper focuses on everyday meals close to our life and proposes a well-balanced menu planning system as a preventive measure of lifestyle-related diseases. The system is developed by using a Web-based frontend and it provides multi-user services and menu information sharing capabilities like social networking services (SNS). The system is implemented on a Web server running Apache (HTTP server software), MySQL (database management system), and PHP (scripting language for dynamic Web pages). For the menu planning, a genetic algorithm is applied by understanding this problem as multidimensional 0-1 integer programming.

Genetic Structure and Molecular Diversity of Cacao Plants Established as Local Varieties for More than Two Centuries: The Genetic History of Cacao Plantations in Bahia, Brazil.

PubMed

Santos, Elisa S L; Cerqueira-Silva, Carlos Bernard M; Mori, Gustavo M; Ahnert, Dário; Mello, Durval L N; Pires, José Luis; Corrêa, Ronan X; de Souza, Anete P

2015-01-01

Bahia is the most important cacao-producing state in Brazil, which is currently the sixth-largest country worldwide to produce cacao seeds. In the eighteenth century, the Comum, Pará and Maranhão varieties of cacao were introduced into southern Bahia, and their descendants, which are called 'Bahian cacao' or local Bahian varieties, have been cultivated for over 200 years. Comum plants have been used to start plantations in African countries and extended as far as countries in South Asia and Oceania. In Brazil, two sets of clones selected from Bahian varieties and their mutants, the Agronomic Institute of East (SIAL) and Bahian Cacao Institute (SIC) series, represent the diversity of Bahian cacao in germplasm banks. Because the genetic diversity of Bahian varieties, which is essential for breeding programs, remains unknown, the objective of this work was to assess the genetic structure and diversity of local Bahian varieties collected from farms and germplasm banks. To this end, 30 simple sequence repeat (SSR) markers were used to genotype 279 cacao plants from germplasm and local farms. The results facilitated the identification of 219 cacao plants of Bahian origin, and 51 of these were SIAL or SIC clones. Bahian cacao showed low genetic diversity. It could be verified that SIC and SIAL clones do not represent the true diversity of Bahian cacao, with the greatest amount of diversity found in cacao trees on the farms. Thus, a core collection to aid in prioritizing the plants to be sampled for Bahian cacao diversity is suggested. These results provide information that can be used to conserve Bahian cacao plants and applied in breeding programs to obtain more productive Bahian cacao with superior quality and tolerance to major diseases in tropical cacao plantations worldwide.

Genetic Structure and Molecular Diversity of Cacao Plants Established as Local Varieties for More than Two Centuries: The Genetic History of Cacao Plantations in Bahia, Brazil

PubMed Central

Santos, Elisa S. L.; Cerqueira-Silva, Carlos Bernard M.; Mori, Gustavo M.; Ahnert, Dário; Mello, Durval L. N.; Pires, José Luis; Corrêa, Ronan X.; de Souza, Anete P.

2015-01-01

Bahia is the most important cacao-producing state in Brazil, which is currently the sixth-largest country worldwide to produce cacao seeds. In the eighteenth century, the Comum, Pará and Maranhão varieties of cacao were introduced into southern Bahia, and their descendants, which are called ‘Bahian cacao’ or local Bahian varieties, have been cultivated for over 200 years. Comum plants have been used to start plantations in African countries and extended as far as countries in South Asia and Oceania. In Brazil, two sets of clones selected from Bahian varieties and their mutants, the Agronomic Institute of East (SIAL) and Bahian Cacao Institute (SIC) series, represent the diversity of Bahian cacao in germplasm banks. Because the genetic diversity of Bahian varieties, which is essential for breeding programs, remains unknown, the objective of this work was to assess the genetic structure and diversity of local Bahian varieties collected from farms and germplasm banks. To this end, 30 simple sequence repeat (SSR) markers were used to genotype 279 cacao plants from germplasm and local farms. The results facilitated the identification of 219 cacao plants of Bahian origin, and 51 of these were SIAL or SIC clones. Bahian cacao showed low genetic diversity. It could be verified that SIC and SIAL clones do not represent the true diversity of Bahian cacao, with the greatest amount of diversity found in cacao trees on the farms. Thus, a core collection to aid in prioritizing the plants to be sampled for Bahian cacao diversity is suggested. These results provide information that can be used to conserve Bahian cacao plants and applied in breeding programs to obtain more productive Bahian cacao with superior quality and tolerance to major diseases in tropical cacao plantations worldwide. PMID:26675449

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.

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data

DOE PAGES

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S.; ...

2017-02-23

Here, a newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides,more » important for metal extraction chemistry, are parametrized using ParFit.« less

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data

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

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S.

Here, a newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides,more » important for metal extraction chemistry, are parametrized using ParFit.« less

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.

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.

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.

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.

How Genetics Might Affect Real Property Rights: Currents in Contemporary Bioethics.

PubMed

Rothstein, Mark A; Rothstein, Laura

2016-03-01

New developments in genetics could affect a variety of real property rights. Mortgage lenders, mortgage insurers, real estate sellers, senior living centers, retirement communities, or other parties in residential real estate transactions begin requiring predictive genetic information as part of the application process. One likely use would be by retirement communities to learn an individual's genetic risk for Alzheimer's disease. The federal Fair Housing Act prohibits discrimination based on disability, but it is not clear that it would apply to genetic risk assessments. Only California law explicitly applies to this situation and there have been no reported cases. © 2016 American Society of Law, Medicine & Ethics.

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

A Web-Based Genetic Polymorphism Learning Approach for High School Students and Science Teachers

ERIC Educational Resources Information Center

Amenkhienan, Ehichoya; Smith, Edward J.

2006-01-01

Variation and polymorphism are concepts that are central to genetics and genomics, primary biological disciplines in which high school students and undergraduates require a solid foundation. From 1998 through 2002, a web-based genetics education program was developed for high school teachers and students. The program included an exercise on using…

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…

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.

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

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.

Artificial intelligence programming with LabVIEW: genetic algorithms for instrumentation control and optimization.

PubMed

Moore, J H

1995-06-01

A genetic algorithm for instrumentation control and optimization was developed using the LabVIEW graphical programming environment. The usefulness of this methodology for the optimization of a closed loop control instrument is demonstrated with minimal complexity and the programming is presented in detail to facilitate its adaptation to other LabVIEW applications. Closed loop control instruments have variety of applications in the biomedical sciences including the regulation of physiological processes such as blood pressure. The program presented here should provide a useful starting point for those wishing to incorporate genetic algorithm approaches to LabVIEW mediated optimization of closed loop control instruments.

From Data to Equations: Inferring the Laws governing Saturn's Ring Temperature

NASA Astrophysics Data System (ADS)

Altobelli, N.; Lopez-Paz, D.; Spilker, L.; Pilorz, S.

2011-10-01

Six years after Saturn Orbit Insertion (SOI), the Composite Infrared Spectrometer (CIRS) on-board the Cassini Spacecraft has been performing a thermal mapping of Saturn's main rings, by measuring the thermal radiance in the far-infrared ( [10-600] cm-1 ) for different viewing geometries. So far, more than 2.5 millions individual spectra have been recorded, from Saturn's northern winter solstice till Saturn's northern spring. We present a first attempt of treating the data set globally by applying numerical data mining techniques inherited from the field of artificial intelligence, such as neural networks and genetic programing.

[Direct genetic manipulation and criminal code in Venezuela: absolute criminal law void?].

PubMed

Cermeño Zambrano, Fernando G De J

2002-01-01

The judicial regulation of genetic biotechnology applied to the human genome is of big relevance currently in Venezuela due to the drafting of an innovative bioethical law in the country's parliament. This article will highlight the constitutional normative of Venezuela's 1999 Constitution regarding this subject, as it establishes the framework from which this matter will be legally regulated. The approach this article makes towards the genetic biotechnology applied to the human genome is made taking into account the Venezuelan penal law and by highlighting the violent genetic manipulations that have criminal relevance. The genetic biotechnology applied to the human genome has another important relevance as a consequence of the reformulation of the Venezuelan Penal Code discussed by the country's National Assembly. Therefore, a concise study of the country's penal code will be made in this article to better understand what judicial-penal properties have been protected by the Venezuelan penal legislation. This last step will enable us to identify the penal tools Venezuela counts on to face direct genetic manipulations. We will equally indicate the existing punitive loophole and that should be covered by the penal legislator. In conclusion, this essay concerns criminal policy, referred to the direct genetic manipulations on the human genome that haven't been typified in Venezuelan law, thus discovering a genetic biotechnology paradise.

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.

Distinguishing genetics and eugenics on the basis of fairness.

PubMed Central

Ledley, F D

1994-01-01

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

Genetic testing and genetic counseling in patients with sudden death risk due to heritable arrhythmias.

PubMed

Spoonamore, Katherine G; Ware, Stephanie M

2016-03-01

Sudden cardiac death due to heritable ventricular arrhythmias is an important cause of mortality, especially in young healthy individuals. The identification of the genetic basis of Mendelian diseases associated with arrhythmia has allowed the integration of this information into the diagnosis and clinical management of patients and at-risk family members. The rapid expansion of genetic testing options and the increasing complexity involved in the interpretation of results creates unique opportunities and challenges. There is a need for competency to incorporate genetics into clinical management and to provide appropriate family-based risk assessment and information. In addition, disease-specific genetic knowledge is required to order and correctly interpret and apply genetic testing results. Importantly, genetic diagnosis has a critical role in the risk stratification and clinical management of family members. This review summarizes the approach to genetic counseling and genetic testing for inherited arrhythmias and highlights specific genetic principles that apply to long QT syndrome, short QT syndrome, Brugada syndrome, and catecholaminergic polymorphic ventricular tachycardia. Copyright © 2016 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Hereditary arrhythmias and cardiomyopathies: decision-making about genetic testing.

PubMed

Louis, Clauden; Calamaro, Emily; Vinocur, Jeffrey M

2018-01-01

The modern field of clinical genetics has advanced beyond the traditional teachings familiar to most practicing cardiologists. Increased understanding of the roles of genetic testing may improve uptake and appropriateness of use. Clinical genetics has become integral to the management of patients with hereditary arrhythmia and cardiomyopathy diagnoses. Depending on the condition, genetic testing may be useful for diagnosis, prognosis, treatment, family screening, and reproductive planning. However, genetic testing is a powerful tool with potential for underuse, overuse, and misuse. In the absence of a substantial body of literature on how these guidelines are applied in clinical practice, we use a case-based approach to highlight key lessons and pitfalls. Importantly, in many scenarios genetic testing has become the standard of care supported by numerous class I recommendations; genetic counselors can improve accessibility to and appropriate use and application of testing. Optimal management of hereditary arrhythmias and cardiomyopathies incorporates genetic testing, applied as per consensus guidelines, with involvement of a multidisciplinary team.

An 8-Year Breeding Program for Asian Seabass Lates calcarifer: Genetic Evaluation, Experiences, and Challenges.

PubMed

Khang, Pham Van; Phuong, Truong Ha; Dat, Nguyen Khac; Knibb, Wayne; Nguyen, Nguyen Hong

2018-01-01

Selective breeding for marine finfish is challenging due to difficulties in reproduction, larval rearing, and on-growth in captive environments. The farming of Asian seabass ( Lates calcarifer ) has all these problems and our knowledge of the quantitative genetic information (heritability and correlations) of traits necessary for commercial exploitation is poor. The present study was conducted to address this knowledge gap and to provide information that can be applied to sea bass and other aquaculture species. We carried out a comprehensive genetic evaluation for three traits (body weight, total length, and survival) collected from a breeding population for Asian seabass over an eight-year period from 2010 to 2017. Statistical analysis was carried out on 4,567 adult fish at 105, 180, 270, 360, 450, and 570 days post-hatch (dph). The heritabilities (h 2 ) estimated for body weight and length using linear mixed model were moderate to high (0.12 to 0.78 and 0.41 to 0.85, respectively) and they differed between the measurement periods. Survival during grow-out phase was analyzed using threshold logistic and probit models. The heritability estimates for survival rate on the underlying liability scale ( h L 2 ) varied from 0.05 to 0.21. When the observed heritability obtained from the linear mixed model was back-transformed to the liability scale, they were similar but not significant. In addition, we examined effects of genotype by environment (G × E) interaction on body traits. The genetic correlation for body weight between tank and sea cage cultures were high (0.91-0.94) in the first and second rearing periods (180 and 270 dph) but the correlation was decreased to 0.59 ± 0.33 at 360 dph. This suggests that the genotype by environment interaction is important for body traits in this population. Furthermore, the genetic correlations of body weights between different measurement periods were moderate but different from one. This suggests that body weights measured at different time points may be different traits and selection for improved early weight may not capture all genetic expressions in subsequent rearing periods in Asian seabass. Selection of the nucleus in sea cages may produce genotypes that do not perform equally well in tanks, although this deserves further studies to determine a suitable selection environment and optimize the breeding program. This paper discusses challenges encountered during implementation of the selection program for L. calcarifer .

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.

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.

Genetic and environmental influences on dimensional representations of DSM-IV cluster C personality disorders: a population-based multivariate twin study.

PubMed

Reichborn-Kjennerud, Ted; Czajkowski, Nikolai; Neale, Michael C; Ørstavik, Ragnhild E; Torgersen, Svenn; Tambs, Kristian; Røysamb, Espen; Harris, Jennifer R; Kendler, Kenneth S

2007-05-01

The DSM-IV cluster C Axis II disorders include avoidant (AVPD), dependent (DEPD) and obsessive-compulsive (OCPD) personality disorders. We aimed to estimate the genetic and environmental influences on dimensional representations of these disorders and examine the validity of the cluster C construct by determining to what extent common familial factors influence the individual PDs. PDs were assessed using the Structured Interview for DSM-IV Personality (SIDP-IV) in a sample of 1386 young adult twin pairs from the Norwegian Institute of Public Health Twin Panel (NIPHTP). A single-factor independent pathway multivariate model was applied to the number of endorsed criteria for the three cluster C disorders, using the statistical modeling program Mx. The best-fitting model included genetic and unique environmental factors only, and equated parameters for males and females. Heritability ranged from 27% to 35%. The proportion of genetic variance explained by a common factor was 83, 48 and 15% respectively for AVPD, DEPD and OCPD. Common genetic and environmental factors accounted for 54% and 64% respectively of the variance in AVPD and DEPD but only 11% of the variance in OCPD. Cluster C PDs are moderately heritable. No evidence was found for shared environmental or sex effects. Common genetic and individual environmental factors account for a substantial proportion of the variance in AVPD and DEPD. However, OCPD appears to be largely etiologically distinct from the other two PDs. The results do not support the validity of the DSM-IV cluster C construct in its present form.

Applying a Genetic Algorithm to Reconfigurable Hardware

NASA Technical Reports Server (NTRS)

Wells, B. Earl; Weir, John; Trevino, Luis; Patrick, Clint; Steincamp, Jim

2004-01-01

This paper investigates the feasibility of applying genetic algorithms to solve optimization problems that are implemented entirely in reconfgurable hardware. The paper highlights the pe$ormance/design space trade-offs that must be understood to effectively implement a standard genetic algorithm within a modem Field Programmable Gate Array, FPGA, reconfgurable hardware environment and presents a case-study where this stochastic search technique is applied to standard test-case problems taken from the technical literature. In this research, the targeted FPGA-based platform and high-level design environment was the Starbridge Hypercomputing platform, which incorporates multiple Xilinx Virtex II FPGAs, and the Viva TM graphical hardware description language.

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.

Integrating population genetics and conservation biology in the era of genomics.

PubMed

Ouborg, N Joop

2010-02-23

As one of the final activities of the ESF-CONGEN Networking programme, a conference entitled 'Integrating Population Genetics and Conservation Biology' was held at Trondheim, Norway, from 23 to 26 May 2009. Conference speakers and poster presenters gave a display of the state-of-the-art developments in the field of conservation genetics. Over the five-year running period of the successful ESF-CONGEN Networking programme, much progress has been made in theoretical approaches, basic research on inbreeding depression and other genetic processes associated with habitat fragmentation and conservation issues, and with applying principles of conservation genetics in the conservation of many species. Future perspectives were also discussed in the conference, and it was concluded that conservation genetics is evolving into conservation genomics, while at the same time basic and applied research on threatened species and populations from a population genetic point of view continues to be emphasized.

Microsatellite data analysis for population genetics

USDA-ARS?s Scientific Manuscript database

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

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.

Genetic Engineering and the Amelioration of Genetic Defect

ERIC Educational Resources Information Center

Lederberg, Joshua

1970-01-01

Discusses the claims for a brave new world of genetic manipulation" and concludes that if we could agree upon applying genetic (or any other effective) remedies to global problems we probably would need no rescourse to them. Suggests that effective methods of preventing genetic disease are prevention of mutations and detection and…

Heritability of body weight and resistance to ammonia in the Pacific white shrimp Litopenaeus vannamei juveniles

NASA Astrophysics Data System (ADS)

Li, Wenjia; Lu, Xia; Luan, Sheng; Luo, Kun; Sui, Juan; Kong, Jie

2016-09-01

Ammonia, toxic to aquaculture organisms, represents a potential problem in aquaculture systems, and the situation is exacerbated in closed and intensive shrimp farming operations, expecially for Litopenaeus vannamei. Assessing the potential for the genetic improvement of resistance to ammonia in L. vannamei requires knowledge of the genetic parameters of this trait. The heritability of resistance to ammonia was estimated using two descriptors in the present study: the survival time (ST) and the survival status at half lethal time (SS50) for each individual under high ammonia challenge. The heritability of ST and SS50 were low (0.154 4±0.044 6 and 0.147 5±0.040 0, respectively), but they were both significantly different from zero ( P<0.01). Moreover, these two estimates were basically the same and showed no significant differences from each other ( P>0.05), suggesting that ST and SS50 could be used as suitable indicators for resistance to ammonia. There were also positive phenotypic and genetic correlation between resistance to ammonia and body weight, which means that resistance to ammonia can be enhanced by the improvement of husbandry practices that increase the body weight. The results from the present study suggest that the selection for higher body weight does not have any negative consequences for resistance to ammonia. In addition to quantitative genetics, tools from molecular genetics can be applied to selective breeding programs to improve the efficiency of selection for traits with low heritability.

Statistics for Learning Genetics

ERIC Educational Resources Information Center

Charles, Abigail Sheena

2012-01-01

This study investigated the knowledge and skills that biology students may need to help them understand statistics/mathematics as it applies to genetics. The data are based on analyses of current representative genetics texts, practicing genetics professors' perspectives, and more directly, students' perceptions of, and performance in, doing…

MULTI-OBJECTIVE OPTIMAL DESIGN OF GROUNDWATER REMEDIATION SYSTEMS: APPLICATION OF THE NICHED PARETO GENETIC ALGORITHM (NPGA). (R826614)

EPA Science Inventory

A multiobjective optimization algorithm is applied to a groundwater quality management problem involving remediation by pump-and-treat (PAT). The multiobjective optimization framework uses the niched Pareto genetic algorithm (NPGA) and is applied to simultaneously minimize the...

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.

Training Software in Artificial-Intelligence Computing Techniques

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

2005-01-01

The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

Automatic Generation of English-Japanese Translation Pattern Utilizing Genetic Programming Technique

NASA Astrophysics Data System (ADS)

Matsumura, Koki; Tamekuni, Yuji; Kimura, Shuhei

There are a lot of constructional differences in an English-Japanese phrase template, and that often makes the act of translation difficult. Moreover, there exist various and tremendous phrase templates and sentence to be refered to. It is not easy to prepare the corpus that covers the all. Therefore, it is very significant to generate the translation pattern of the sentence pattern automatically from a viewpoint of the translation success rate and the capacity of the pattern dictionary. Then, for the purpose of realizing the automatic generation of the translation pattern, this paper proposed the new method for the generation of the translation pattern by using the genetic programming technique (GP). The technique tries to generate the translation pattern of various sentences which are not registered in the phrase template dictionary automatically by giving the genetic operation to the parsing tree of a basic pattern. The tree consists of the pair of the English-Japanese sentence generated as the first stage population. The analysis tree data base with 50,100,150,200 pairs was prepared as the first stage population. And this system was applied and executed for an English input of 1,555 sentences. As a result, the analysis tree increases from 200 to 517, and the accuracy rate of the translation pattern has improved from 42.57% to 70.10%. And, 86.71% of the generated translations was successfully done, whose meanings are enough acceptable and understandable. It seemed that this proposal technique became a clue to raise the translation success rate, and to find the possibility of the reduction of the analysis tree data base.

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

Fungal genome sequencing: basic biology to biotechnology.

PubMed

Sharma, Krishna Kant

2016-08-01

The genome sequences provide a first glimpse into the genomic basis of the biological diversity of filamentous fungi and yeast. The genome sequence of the budding yeast, Saccharomyces cerevisiae, with a small genome size, unicellular growth, and rich history of genetic and molecular analyses was a milestone of early genomics in the 1990s. The subsequent completion of fission yeast, Schizosaccharomyces pombe and genetic model, Neurospora crassa initiated a revolution in the genomics of the fungal kingdom. In due course of time, a substantial number of fungal genomes have been sequenced and publicly released, representing the widest sampling of genomes from any eukaryotic kingdom. An ambitious genome-sequencing program provides a wealth of data on metabolic diversity within the fungal kingdom, thereby enhancing research into medical science, agriculture science, ecology, bioremediation, bioenergy, and the biotechnology industry. Fungal genomics have higher potential to positively affect human health, environmental health, and the planet's stored energy. With a significant increase in sequenced fungal genomes, the known diversity of genes encoding organic acids, antibiotics, enzymes, and their pathways has increased exponentially. Currently, over a hundred fungal genome sequences are publicly available; however, no inclusive review has been published. This review is an initiative to address the significance of the fungal genome-sequencing program and provides the road map for basic and applied research.

Contribution of genetics to ecological restoration.

PubMed

Mijangos, Jose Luis; Pacioni, Carlo; Spencer, Peter B S; Craig, Michael D

2015-01-01

Ecological restoration of degraded ecosystems has emerged as a critical tool in the fight to reverse and ameliorate the current loss of biodiversity and ecosystem services. Approaches derived from different genetic disciplines are extending the theoretical and applied frameworks on which ecological restoration is based. We performed a search of scientific articles and identified 160 articles that employed a genetic approach within a restoration context to shed light on the links between genetics and restoration. These articles were then classified on whether they examined association between genetics and fitness or the application of genetics in demographic studies, and on the way the studies informed restoration practice. Although genetic research in restoration is rapidly growing, we found that studies could make better use of the extensive toolbox developed by applied fields in genetics. Overall, 41% of reviewed studies used genetic information to evaluate or monitor restoration, and 59% provided genetic information to guide prerestoration decision-making processes. Reviewed studies suggest that restoration practitioners often overlook the importance of including genetic aspects within their restoration goals. Even though there is a genetic basis influencing the provision of ecosystem services, few studies explored this relationship. We provide a view of research gaps, future directions and challenges in the genetics of restoration. © 2014 John Wiley & Sons Ltd.

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.

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.

Medical genetics

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

Jorde, L.B.; Carey, J.C.; White, R.L.

This book on the subject of medical genetics is a textbook aimed at a very broad audience: principally, medical students, nursing students, graduate, and undergraduate students. The book is actually a primer of general genetics as applied to humans and provides a well-balanced introduction to the scientific and clinical basis of human genetics. The twelve chapters include: Introduction, Basic Cell Biology, Genetic Variation, Autosomal Dominant and Recessive Inheritance, Sex-linked and Mitochondrial Inheritance, Clinical Cytogenetics, Gene Mapping, Immunogenetics, Cancer Genetics, Multifactorial Inheritance and Common Disease, Genetic Screening, Genetic Diagnosis and Gene Therapy, and Clinical Genetics and Genetic Counseling.

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.

Applying remote sensing expertise to crop improvement: progress and challenges to scale up high throughput field phenotyping from research to industry

NASA Astrophysics Data System (ADS)

Gouache, David; Beauchêne, Katia; Mini, Agathe; Fournier, Antoine; de Solan, Benoit; Baret, Fred; Comar, Alexis

2016-05-01

Digital and image analysis technologies in greenhouses have become commonplace in plant science research and started to move into the plant breeding industry. However, the core of plant breeding work takes place in fields. We will present successive technological developments that have allowed the migration and application of remote sensing approaches at large into the field of crop genetics and physiology research, with a number of projects that have taken place in France. These projects have allowed us to develop combined sensor plus vector systems, from tractor mounted and UAV (unmanned aerial vehicle) mounted spectroradiometry to autonomous vehicle mounted spectroradiometry, RGB (red-green-blue) imagery and Lidar. We have tested these systems for deciphering the genetics of complex plant improvement targets such as the robustness to nitrogen and water deficiency of wheat and maize. Our results from wheat experiments indicate that these systems can be used both to screen genetic diversity for nitrogen stress tolerance and to decipher the genetics behind this diversity. We will present our view on the next critical steps in terms of technology and data analysis that will be required to reach cost effective implementation in industrial plant breeding programs. If this can be achieved, these technologies will largely contribute to resolving the equation of increasing food supply in the resource limited world that lies ahead.

Systematic analysis of Ca2+ homeostasis in Saccharomyces cerevisiae based on chemical-genetic interaction profiles

PubMed Central

Ghanegolmohammadi, Farzan; Yoshida, Mitsunori; Ohnuki, Shinsuke; Sukegawa, Yuko; Okada, Hiroki; Obara, Keisuke; Kihara, Akio; Suzuki, Kuninori; Kojima, Tetsuya; Yachie, Nozomu; Hirata, Dai; Ohya, Yoshikazu

2017-01-01

We investigated the global landscape of Ca2+ homeostasis in budding yeast based on high-dimensional chemical-genetic interaction profiles. The morphological responses of 62 Ca2+-sensitive (cls) mutants were quantitatively analyzed with the image processing program CalMorph after exposure to a high concentration of Ca2+. After a generalized linear model was applied, an analysis of covariance model was used to detect significant Ca2+–cls interactions. We found that high-dimensional, morphological Ca2+–cls interactions were mixed with positive (86%) and negative (14%) chemical-genetic interactions, whereas one-dimensional fitness Ca2+–cls interactions were all negative in principle. Clustering analysis with the interaction profiles revealed nine distinct gene groups, six of which were functionally associated. In addition, characterization of Ca2+–cls interactions revealed that morphology-based negative interactions are unique signatures of sensitized cellular processes and pathways. Principal component analysis was used to discriminate between suppression and enhancement of the Ca2+-sensitive phenotypes triggered by inactivation of calcineurin, a Ca2+-dependent phosphatase. Finally, similarity of the interaction profiles was used to reveal a connected network among the Ca2+ homeostasis units acting in different cellular compartments. Our analyses of high-dimensional chemical-genetic interaction profiles provide novel insights into the intracellular network of yeast Ca2+ homeostasis. PMID:28566553

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.

The Application of Structural Equation Modeling to Maternal Ratings of Twins' Behavior and Emotional Problems.

ERIC Educational Resources Information Center

Silberg, Judy L.; And Others

1994-01-01

Applied structural equation modeling to twin data to assess impact of genetic and environmental factors on children's behavioral and emotional functioning. Applied models to maternal ratings of behavior of 515 monozygotic and 749 dizygotic twin pairs. Importance of genetic, shared, and specific environmental factors for explaining variation was…

Perspectives for artificial insemination and genomics to improve global swine populations.

PubMed

Gerrits, Roger J; Lunney, Joan K; Johnson, Lawrence A; Pursel, Vernon G; Kraeling, Robert R; Rohrer, Gary A; Dobrinsky, John R

2005-01-15

Civilizations throughout the world continue to depend on pig meat as an important food source. Approximately 40% of the red meat consumed annually worldwide (94 million metric tons) is pig meat. Pig numbers (940 million) and consumption have increased consistent with the increasing world population (FAO 2002). In the past 50 years, research guided genetic selection and nutrition programs have had a major impact on improving carcass composition and efficiency of production in swine. The use of artificial insemination (AI) in Europe has also had a major impact on pig improvement in the past 35 years and more recently in the USA. Several scientific advances in gamete physiology and/or manipulation have been successfully utilized while others are just beginning to be applied at the production level. Semen extenders that permit the use of fresh semen for more than 5 days post-collection are largely responsible for the success of AI in pigs worldwide. Transfer of the best genetics has been enabled by use of AI with fresh semen, and to some extent, by use of AI with frozen semen over the past 25 years. Sexed semen, now a reality, has the potential for increasing the rate of genetic progress in AI programs when used in conjunction with newly developed low sperm number insemination technology. Embryo cryopreservation provides opportunities for international transport of maternal germplasm worldwide; non-surgical transfer of viable embryos in practice is nearing reality. While production of transgenic animals has been successful, the low level of efficiency in producing these animals and lack of information on multigene interactions limit the use of the technology in applied production systems. Technologies based on research in functional genomics, proteomics and cloning have significant potential, but considerable research effort will be required before they can be utilized for AI in pig production. In the past 15 years, there has been a coordinated worldwide scientific effort to develop the genetic linkage map of the pig with the goal of identifying pigs with genetic alleles that result in improved growth rate, carcass quality, and reproductive performance. Molecular genetic tests have been developed to select pigs with improved traits such as removal of the porcine stress (RYR1) syndrome, and selection for specific estrogen receptor (ESR) alleles. Less progress has been made in developing routine tests related to diseases. Major research in genomics is being pursued to improve the efficiency of selection for healthier pigs with disease resistance properties. The sequencing of the genome of the pig to identify new genes and unique regulatory elements holds great promise to provide new information that can be used in pig production. AI, in vitro embryo production and embryo transfer will be the preferred means of implementing these new technologies to enhance efficiency of pig production in the future.

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.

Genomic selection signatures in sheep from the Western Pyrenees.

PubMed

Ruiz-Larrañaga, Otsanda; Langa, Jorge; Rendo, Fernando; Manzano, Carmen; Iriondo, Mikel; Estonba, Andone

2018-03-22

The current large spectrum of sheep phenotypic diversity results from the combined product of sheep selection for different production traits such as wool, milk and meat, and its natural adaptation to new environments. In this study, we scanned the genome of 25 Sasi Ardi and 75 Latxa sheep from the Western Pyrenees for three types of regions under selection: (1) regions underlying local adaptation of Sasi Ardi semi-feral sheep, (2) regions related to a long traditional dairy selection pressure in Latxa sheep, and (3) regions experiencing the specific effect of the modern genetic improvement program established for the Latxa breed during the last three decades. Thirty-two selected candidate regions including 147 annotated genes were detected by using three statistical parameters: pooled heterozygosity H, Tajima's D, and Wright's fixation index F st . For Sasi Ardi sheep, chromosomes Ovis aries (OAR)4, 6, and 22 showed the strongest signals and harbored several candidate genes related to energy metabolism and morphology (BBS9, ELOVL3 and LDB1), immunity (NFKB2), and reproduction (H2AFZ). The major genomic difference between Sasi Ardi and Latxa sheep was on OAR6, which is known to affect milk production, with highly selected regions around the ABCG2, SPP1, LAP3, NCAPG, LCORL, and MEPE genes in Latxa sheep. The effect of the modern genetic improvement program on Latxa sheep was also evident on OAR15, on which several olfactory genes are located. We also detected several genes involved in reproduction such as ESR1 and ZNF366 that were affected by this selection program. Natural and artificial selection have shaped the genome of both Sasi Ardi and Latxa sheep. Our results suggest that Sasi Ardi traits related to energy metabolism, morphological, reproductive, and immunological features have been under positive selection to adapt this semi-feral sheep to its particular environment. The highly selected Latxa sheep for dairy production showed clear signatures of selection in genomic regions related to milk production. Furthermore, our data indicate that the selection criteria applied in the modern genetic improvement program affect immunity and reproduction traits.

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.

Study of parameter identification using hybrid neural-genetic algorithm in electro-hydraulic servo system

NASA Astrophysics Data System (ADS)

Moon, Byung-Young

2005-12-01

The hybrid neural-genetic multi-model parameter estimation algorithm was demonstrated. This method can be applied to structured system identification of electro-hydraulic servo system. This algorithms consist of a recurrent incremental credit assignment(ICRA) neural network and a genetic algorithm. The ICRA neural network evaluates each member of a generation of model and genetic algorithm produces new generation of model. To evaluate the proposed method, electro-hydraulic servo system was designed and manufactured. The experiment was carried out to figure out the hybrid neural-genetic multi-model parameter estimation algorithm. As a result, the dynamic characteristics were obtained such as the parameters(mass, damping coefficient, bulk modulus, spring coefficient), which minimize total square error. The result of this study can be applied to hydraulic systems in industrial fields.

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.

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.

Epistasis analysis using artificial intelligence.

PubMed

Moore, Jason H; Hill, Doug P

2015-01-01

Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of expert knowledge as a guide. The methodology presented here is based on computational evolution, which is a type of genetic programming. The ability to generate interesting solutions while at the same time learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data.

Thermal-economic optimisation of a CHP gas turbine system by applying a fit-problem genetic algorithm

NASA Astrophysics Data System (ADS)

Ferreira, Ana C. M.; Teixeira, Senhorinha F. C. F.; Silva, Rui G.; Silva, Ângela M.

2018-04-01

Cogeneration allows the optimal use of the primary energy sources and significant reductions in carbon emissions. Its use has great potential for applications in the residential sector. This study aims to develop a methodology for thermal-economic optimisation of small-scale micro-gas turbine for cogeneration purposes, able to fulfil domestic energy needs with a thermal power out of 125 kW. A constrained non-linear optimisation model was built. The objective function is the maximisation of the annual worth from the combined heat and power, representing the balance between the annual incomes and the expenditures subject to physical and economic constraints. A genetic algorithm coded in the java programming language was developed. An optimal micro-gas turbine able to produce 103.5 kW of electrical power with a positive annual profit (i.e. 11,925 €/year) was disclosed. The investment can be recovered in 4 years and 9 months, which is less than half of system lifetime expectancy.

Canonical Genetic Signatures of the Adult Human Brain

PubMed Central

Hawrylycz, Michael; Miller, Jeremy A.; Menon, Vilas; Feng, David; Dolbeare, Tim; Guillozet-Bongaarts, Angela L.; Jegga, Anil G.; Aronow, Bruce J.; Lee, Chang-Kyu; Bernard, Amy; Glasser, Matthew F.; Dierker, Donna L.; Menche, Jörge; Szafer, Aaron; Collman, Forrest; Grange, Pascal; Berman, Kenneth A.; Mihalas, Stefan; Yao, Zizhen; Stewart, Lance; Barabási, Albert-László; Schulkin, Jay; Phillips, John; Ng, Lydia; Dang, Chinh; Haynor, David R.; Jones, Allan; Van Essen, David C.; Koch, Christof; Lein, Ed

2015-01-01

The structure and function of the human brain are highly stereotyped, implying a conserved molecular program responsible for its development, cellular structure, and function. We applied a correlation-based metric of “differential stability” (DS) to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing meso-scale genetic organization. The highest DS genes are highly biologically relevant, with enrichment for brain-related biological annotations, disease associations, drug targets, and literature citations. Using high DS genes we identified 32 anatomically diverse and reproducible gene expression signatures, which represent distinct cell types, intracellular components, and/or associations with neurodevelopmental and neurodegenerative disorders. Genes in neuron-associated compared to non-neuronal networks showed higher preservation between human and mouse; however, many diversely-patterned genes displayed dramatic shifts in regulation between species. Finally, highly consistent transcriptional architecture in neocortex is correlated with resting state functional connectivity, suggesting a link between conserved gene expression and functionally relevant circuitry. PMID:26571460

Experimental Design for Estimating Unknown Hydraulic Conductivity in a Confined Aquifer using a Genetic Algorithm and a Reduced Order Model

NASA Astrophysics Data System (ADS)

Ushijima, T.; Yeh, W.

2013-12-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provides the maximum information about unknown hydraulic conductivity in a confined, anisotropic aquifer. The design employs a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. Because that the formulated problem is non-convex and contains integer variables (necessitating a combinatorial search), for a realistically-scaled model, the problem may be difficult, if not impossible, to solve through traditional mathematical programming techniques. Genetic Algorithms (GAs) are designed to search out the global optimum; however because a GA requires a large number of calls to a groundwater model, the formulated optimization problem may still be infeasible to solve. To overcome this, Proper Orthogonal Decomposition (POD) is applied to the groundwater model to reduce its dimension. The information matrix in the full model space can then be searched without solving the full model.

SSRPrimer and SSR Taxonomy Tree: Biome SSR discovery

PubMed Central

Jewell, Erica; Robinson, Andrew; Savage, David; Erwin, Tim; Love, Christopher G.; Lim, Geraldine A. C.; Li, Xi; Batley, Jacqueline; Spangenberg, German C.; Edwards, David

2006-01-01

Simple sequence repeat (SSR) molecular genetic markers have become important tools for a broad range of applications such as genome mapping and genetic diversity studies. SSRs are readily identified within DNA sequence data and PCR primers can be designed for their amplification. These PCR primers frequently cross amplify within related species. We report a web-based tool, SSR Primer, that integrates SPUTNIK, an SSR repeat finder, with Primer3, a primer design program, within one pipeline. On submission of multiple FASTA formatted sequences, the script screens each sequence for SSRs using SPUTNIK. Results are then parsed to Primer3 for locus specific primer design. We have applied this tool for the discovery of SSRs within the complete GenBank database, and have designed PCR amplification primers for over 13 million SSRs. The SSR Taxonomy Tree server provides web-based searching and browsing of species and taxa for the visualisation and download of these SSR amplification primers. These tools are available at . PMID:16845092

SSRPrimer and SSR Taxonomy Tree: Biome SSR discovery.

PubMed

Jewell, Erica; Robinson, Andrew; Savage, David; Erwin, Tim; Love, Christopher G; Lim, Geraldine A C; Li, Xi; Batley, Jacqueline; Spangenberg, German C; Edwards, David

2006-07-01

Simple sequence repeat (SSR) molecular genetic markers have become important tools for a broad range of applications such as genome mapping and genetic diversity studies. SSRs are readily identified within DNA sequence data and PCR primers can be designed for their amplification. These PCR primers frequently cross amplify within related species. We report a web-based tool, SSR Primer, that integrates SPUTNIK, an SSR repeat finder, with Primer3, a primer design program, within one pipeline. On submission of multiple FASTA formatted sequences, the script screens each sequence for SSRs using SPUTNIK. Results are then parsed to Primer3 for locus specific primer design. We have applied this tool for the discovery of SSRs within the complete GenBank database, and have designed PCR amplification primers for over 13 million SSRs. The SSR Taxonomy Tree server provides web-based searching and browsing of species and taxa for the visualisation and download of these SSR amplification primers. These tools are available at http://bioinformatics.pbcbasc.latrobe.edu.au/ssrdiscovery.html.

Simplified process model discovery based on role-oriented genetic mining.

PubMed

Zhao, Weidong; Liu, Xi; Dai, Weihui

2014-01-01

Process mining is automated acquisition of process models from event logs. Although many process mining techniques have been developed, most of them are based on control flow. Meanwhile, the existing role-oriented process mining methods focus on correctness and integrity of roles while ignoring role complexity of the process model, which directly impacts understandability and quality of the model. To address these problems, we propose a genetic programming approach to mine the simplified process model. Using a new metric of process complexity in terms of roles as the fitness function, we can find simpler process models. The new role complexity metric of process models is designed from role cohesion and coupling, and applied to discover roles in process models. Moreover, the higher fitness derived from role complexity metric also provides a guideline for redesigning process models. Finally, we conduct case study and experiments to show that the proposed method is more effective for streamlining the process by comparing with related studies.

Genetically modified organisms in the United States: implementation, concerns, and public perception.

PubMed

Oeschger, Max P; Silva, Catherine E

2007-01-01

We examine the state of biotechnology with respect to genetically modified (GM) organisms in agriculture. Our focus is on the USA, where there has been significant progress and implementation but where, to date, the matter has drawn little attention. GM organisms are the result of lateral gene transfers, the transfer of genes from one species to another, or sometimes, from one kingdom to another. The introduction of foreign genes makes some people very uncomfortable, and a small group of activists have grave concerns about the technology. Attempts by activists to build concern in the general public have garnered little attention; however, the producers of GM organisms have responded to their concerns and established extensive testing programs to be applied to each candidate organism that is produced. In the meantime, GM varieties of corn, cotton, soybean and rapeseed have been put into agricultural production and are now extensively planted. These crops, and the other, newer GM crops, have produced no problems and have pioneered a silent agricultural revolution in the USA.

Multiobjective Genetic Algorithm applied to dengue control.

PubMed

Florentino, Helenice O; Cantane, Daniela R; Santos, Fernando L P; Bannwart, Bettina F

2014-12-01

Dengue fever is an infectious disease caused by a virus of the Flaviridae family and transmitted to the person by a mosquito of the genus Aedes aegypti. This disease has been a global public health problem because a single mosquito can infect up to 300 people and between 50 and 100 million people are infected annually on all continents. Thus, dengue fever is currently a subject of research, whether in the search for vaccines and treatments for the disease or efficient and economical forms of mosquito control. The current study aims to study techniques of multiobjective optimization to assist in solving problems involving the control of the mosquito that transmits dengue fever. The population dynamics of the mosquito is studied in order to understand the epidemic phenomenon and suggest strategies of multiobjective programming for mosquito control. A Multiobjective Genetic Algorithm (MGA_DENGUE) is proposed to solve the optimization model treated here and we discuss the computational results obtained from the application of this technique. Copyright © 2014 Elsevier Inc. All rights reserved.

MEGA-CC: computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis.

PubMed

Kumar, Sudhir; Stecher, Glen; Peterson, Daniel; Tamura, Koichiro

2012-10-15

There is a growing need in the research community to apply the molecular evolutionary genetics analysis (MEGA) software tool for batch processing a large number of datasets and to integrate it into analysis workflows. Therefore, we now make available the computing core of the MEGA software as a stand-alone executable (MEGA-CC), along with an analysis prototyper (MEGA-Proto). MEGA-CC provides users with access to all the computational analyses available through MEGA's graphical user interface version. This includes methods for multiple sequence alignment, substitution model selection, evolutionary distance estimation, phylogeny inference, substitution rate and pattern estimation, tests of natural selection and ancestral sequence inference. Additionally, we have upgraded the source code for phylogenetic analysis using the maximum likelihood methods for parallel execution on multiple processors and cores. Here, we describe MEGA-CC and outline the steps for using MEGA-CC in tandem with MEGA-Proto for iterative and automated data analysis. http://www.megasoftware.net/.

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

Polyphasic characterization of Gluconacetobacter diazotrophicus isolates obtained from different sugarcane varieties

PubMed Central

Guedes, Helma V.; dos Santos, Samuel T.; Perin, Liamara; Teixeira, Kátia R. dos S.; Reis, Veronica M.; Baldani, José I.

2008-01-01

A polyphasic approach was applied to characterize 35 G. diazotrophicus isolates obtained from sugarcane varieties cultivated in Brazil. The isolates were analyzed by phenotypic (use of different carbon sources) and genotypic tests (ARDRA and RISA–RFLP techniques). Variability among the isolates was observed in relation to the carbon source use preference. Glucose and sucrose were used by all isolates in contrast to myo-inositol, galactose and ribose that were not metabolized. The results of the analysis showed the presence of two groups clustered at 68% of similarity. The genetic distance was higher when RISA-RFLP analysis was used. Analysis of 16S rDNA sequences from isolates showed that all of them belonged to the G. diazotrophicus species. Neither effect of the plant part nor sugarcane variety was observed during the cluster analysis. The observed metabolic and genetic variability will be helpful during the strain selection studies for sugarcane inoculation in association with sugarcane breeding programs. PMID:24031296

Mapping genetic variations to three-dimensional protein structures to enhance variant interpretation: a proposed framework.

PubMed

Glusman, Gustavo; Rose, Peter W; Prlić, Andreas; Dougherty, Jennifer; Duarte, José M; Hoffman, Andrew S; Barton, Geoffrey J; Bendixen, Emøke; Bergquist, Timothy; Bock, Christian; Brunk, Elizabeth; Buljan, Marija; Burley, Stephen K; Cai, Binghuang; Carter, Hannah; Gao, JianJiong; Godzik, Adam; Heuer, Michael; Hicks, Michael; Hrabe, Thomas; Karchin, Rachel; Leman, Julia Koehler; Lane, Lydie; Masica, David L; Mooney, Sean D; Moult, John; Omenn, Gilbert S; Pearl, Frances; Pejaver, Vikas; Reynolds, Sheila M; Rokem, Ariel; Schwede, Torsten; Song, Sicheng; Tilgner, Hagen; Valasatava, Yana; Zhang, Yang; Deutsch, Eric W

2017-12-18

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods.

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.

Genetic and economic benefits of selection based on performance recording and genotyping in lower tiers of multi-tiered sheep breeding schemes.

PubMed

Santos, Bruno F S; van der Werf, Julius H J; Gibson, John P; Byrne, Timothy J; Amer, Peter R

2017-01-17

Performance recording and genotyping in the multiplier tier of multi-tiered sheep breeding schemes could potentially reduce the difference in the average genetic merit between nucleus and commercial flocks, and create additional economic benefits for the breeding structure. The genetic change in a multiple-trait breeding objective was predicted for various selection strategies that included performance recording, parentage testing and genomic selection. A deterministic simulation model was used to predict selection differentials and the flow of genetic superiority through the different tiers. Cumulative discounted economic benefits were calculated based on trait gains achieved in each of the tiers and considering the extra revenue and associated costs of applying recording, genotyping and selection practices in the multiplier tier of the breeding scheme. Performance recording combined with genomic or parentage information in the multiplier tier reduced the genetic lag between the nucleus and commercial flock by 2 to 3 years. The overall economic benefits of improved performance in the commercial tier offset the costs of recording the multiplier. However, it took more than 18 years before the cumulative net present value of benefits offset the costs at current test prices. Strategies in which recorded multiplier ewes were selected as replacements for the nucleus flock did modestly increase profitability when compared to a closed nucleus structure. Applying genomic selection is the most beneficial strategy if testing costs can be reduced or by genotyping only a proportion of the selection candidates. When the cost of genotyping was reduced, scenarios that combine performance recording with genomic selection were more profitable and reached breakeven point about 10 years earlier. Economic benefits can be generated in multiplier flocks by implementing performance recording in conjunction with either DNA pedigree recording or genomic technology. These recording practices reduce the long genetic lag between the nucleus and commercial flocks in multi-tiered breeding programs. Under current genotyping costs, the time to breakeven was found to be generally very long, although this varied between strategies. Strategies using either genomic selection or DNA pedigree verification were found to be economically viable provided the price paid for the tests is lower than current prices, in the long-term.

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle.

PubMed

Boligon, A A; Baldi, F; Mercadante, M E Z; Lobo, R B; Pereira, R J; Albuquerque, L G

2011-06-28

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression analyses, all female weight records from birth to eight years of age (data set I) were considered. From this general data set, a subset was created (data set II), which included only nine weight records: at birth, weaning, 365 and 550 days of age, and 2, 3, 4, 5, and 6 years of age. Data set II was analyzed using random regression and multi-trait models. The model of analysis included the contemporary group as fixed effects and age of dam as a linear and quadratic covariable. In the random regression analyses, average growth trends were modeled using a cubic regression on orthogonal polynomials of age. Residual variances were modeled by a step function with five classes. Legendre polynomials of fourth and sixth order were utilized to model the direct genetic and animal permanent environmental effects, respectively, while third-order Legendre polynomials were considered for maternal genetic and maternal permanent environmental effects. Quadratic polynomials were applied to model all random effects in random regression models on B-spline functions. Direct genetic and animal permanent environmental effects were modeled using three segments or five coefficients, and genetic maternal and maternal permanent environmental effects were modeled with one segment or three coefficients in the random regression models on B-spline functions. For both data sets (I and II), animals ranked differently according to expected breeding value obtained by random regression or multi-trait models. With random regression models, the highest gains in accuracy were obtained at ages with a low number of weight records. The results indicate that random regression models provide more accurate expected breeding values than the traditionally finite multi-trait models. Thus, higher genetic responses are expected for beef cattle growth traits by replacing a multi-trait model with random regression models for genetic evaluation. B-spline functions could be applied as an alternative to Legendre polynomials to model covariance functions for weights from birth to mature age.

Genetic variation in IL-16 miRNA target site and time to prostate cancer diagnosis in African American men

PubMed Central

Hughes, Lucinda; Ruth, Karen; Rebbeck, Timothy R.; Giri, Veda N.

2013-01-01

Background Men with a family history of prostate cancer and African American men are at high risk for prostate cancer and in need of personalized risk estimates to inform screening decisions. This study evaluated genetic variants in genes encoding microRNA (miRNA) binding sites for informing of time to prostate cancer diagnosis among ethnically-diverse, high-risk men undergoing prostate cancer screening. Methods The Prostate Cancer Risk Assessment Program (PRAP) is a longitudinal screening program for high-risk men. Eligibility includes men ages 35-69 with a family history of prostate cancer or African descent. Participants with ≥ 1 follow-up visit were included in the analyses (n=477). Genetic variants in regions encoding miRNA binding sites in four target genes (ALOX15, IL-16, IL-18, and RAF1) previously implicated in prostate cancer development were evaluated. Genotyping methods included Taqman® SNP Genotyping Assay (Applied Biosystems) or pyrosequencing. Cox models were used to assess time to prostate cancer diagnosis by risk genotype. Results Among 256 African Americans with ≥ one follow-up visit, the TT genotype at rs1131445 in IL-16 was significantly associated with earlier time to prostate cancer diagnosis vs. the CC/CT genotypes (p=0.013), with a suggestive association after correction for false-discovery (p=0.065). Hazard ratio after controlling for age and PSA for TT vs. CC/CT among African Americans was 3.0 (95% CI 1.26-7.12). No association to time to diagnosis was detected among Caucasians by IL-16 genotype. No association to time to prostate cancer diagnosis was found for the other miRNA target genotypes. Conclusions Genetic variation in IL-16 encoding miRNA target site may be informative of time to prostate cancer diagnosis among African American men enrolled in prostate cancer risk assessment, which may inform individualized prostate cancer screening strategies in the future. PMID:24061634

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)

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.

Solving bi-level optimization problems in engineering design using kriging models

NASA Astrophysics Data System (ADS)

Xia, Yi; Liu, Xiaojie; Du, Gang

2018-05-01

Stackelberg game-theoretic approaches are applied extensively in engineering design to handle distributed collaboration decisions. Bi-level genetic algorithms (BLGAs) and response surfaces have been used to solve the corresponding bi-level programming models. However, the computational costs for BLGAs often increase rapidly with the complexity of lower-level programs, and optimal solution functions sometimes cannot be approximated by response surfaces. This article proposes a new method, namely the optimal solution function approximation by kriging model (OSFAKM), in which kriging models are used to approximate the optimal solution functions. A detailed example demonstrates that OSFAKM can obtain better solutions than BLGAs and response surface-based methods, and at the same time reduce the workload of computation remarkably. Five benchmark problems and a case study of the optimal design of a thin-walled pressure vessel are also presented to illustrate the feasibility and potential of the proposed method for bi-level optimization in engineering design.

Investigations into the metabolic diversity of microorganisms as part of microbial diversity

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

Leadbetter, Jared

DOE funds supported a key portion of the MBL Microbial Diversity (Woods Hole) program across 6 complete summers. The initial 4 years of the funded period were overseen by two co-Directors, Daniel Buckley (Cornell) and Steve Zinder (Cornell), who then completed their term. The final 2 summers were overseen by 2 new co-Directors, Jared R. Leadbetter (Caltech) and Dianne Newman (Caltech). The 6 funded summer iterations of the course included the incorporation of new themes such as single cell approaches applied to natural microbial communities (cell separation and sorting, genome amplification from single cells, and the use of Nano-SIMS tomore » examine assimilation of carbon and nitrogen from isotopically labeled substrates into single cells), genetics and genomics on bacteria freshly isolated during the course of the programs, quantitative systems biology, and modern quantitative light microscopy.« less

Comparison of two non-convex mixed-integer nonlinear programming algorithms applied to autoregressive moving average model structure and parameter estimation

NASA Astrophysics Data System (ADS)

Uilhoorn, F. E.

2016-10-01

In this article, the stochastic modelling approach proposed by Box and Jenkins is treated as a mixed-integer nonlinear programming (MINLP) problem solved with a mesh adaptive direct search and a real-coded genetic class of algorithms. The aim is to estimate the real-valued parameters and non-negative integer, correlated structure of stationary autoregressive moving average (ARMA) processes. The maximum likelihood function of the stationary ARMA process is embedded in Akaike's information criterion and the Bayesian information criterion, whereas the estimation procedure is based on Kalman filter recursions. The constraints imposed on the objective function enforce stability and invertibility. The best ARMA model is regarded as the global minimum of the non-convex MINLP problem. The robustness and computational performance of the MINLP solvers are compared with brute-force enumeration. Numerical experiments are done for existing time series and one new data set.

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

Genetic polymorphisms in lung disease: bandwagon or breakthrough?

PubMed Central

Iannuzzi, Michael C; Maliarik, Mary; Rybicki, Benjamin

2002-01-01

The study of genetic polymorphisms has touched every aspect of pulmonary and critical care medicine. We review recent progress made using genetic polymorphisms to define pathophysiology, to identify persons at risk for pulmonary disease and to predict treatment response. Several pitfalls are commonly encountered in studying genetic polymorphisms, and this article points out criteria that should be applied to design high-quality genetic polymorphism studies. PMID:11980584

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 factors in Threatened Species Recovery Plans on three continents

EPA Science Inventory

Threatened species' recovery planning is applied globally to stem the current species extinction crisis. Evidence supports a key role of genetic processes, such as inbreeding depression, in determining species viability. We examined whether genetic factors are considered in threa...

TRANSGENE ESCAPE MONITORING, POPULATION GENETICS, AND THE LAW

EPA Science Inventory

There has been little discussion about how to apply population genetics methods to monitor the spread of transgenes that are detected outside the agricultural populations where they are deployed. Population geneticists have developed tools for analyzing the genetic makeup of indi...

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...

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.…

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

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

PubMed

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

2002-01-01

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

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.

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.

Toward an Understanding of "Genetic Sociology" and Its Relationships to Medical Sociology and Medical Genetics in the Educational Enterprise

ERIC Educational Resources Information Center

Fredericks, Marcel; Odiet, Jeff A.; Miller, Steven I.; Fredericks, Janet

2004-01-01

In this research, we have demonstrated that a new subdiscipline in the field of Medical Sociology is urgently needed to integrate, interpret, and synthesize the interrelationships and implications of genetic discoveries, treatments, and prognoses upon societal behavior. That subdiscipline in our view is "Genetic Sociology."We applied the…

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…

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.

[Teaching design and practice of human blood type traits in genetics comprehensive laboratory course].

PubMed

Zhao, Jian; Hu, Dong-mei; Yu, Da-de; Dong, Ming-liang; Li, Yun; Fan, Ying-ming; Wang, Yan-wei; Zhang, Jin-feng

2016-05-01

Comprehensive laboratory courses, which enable students to aptly apply theoretic knowledge and master experiment skills, play an important role in the present educational reform of laboratory courses. We utilized human ABO blood type as the experimental subject, and designed the experiment--"Molecular Genotyping of Human ABO Blood Type and Analysis of Population Genetic Equilibrium". In the experiment, DNA in mucosal cells is extracted from students' saliva, and each student's genotype is identified using a series of molecular genetics technologies, including PCR amplification of target fragments, enzymatic digestion, and electrophoretic separation. Then, taking the whole class as an analogous Mendel population, a survey of genotype frequency of ABO blood type is conducted, followed with analyses of various population genetic parameters using Popgene. Through the open laboratory course, students can not only master molecular genetic experimental skills, but also improve their understanding of theoretic knowledge through independent design and optimization of molecular techniques. After five years of research and practice, a stable experimental system of molecular genetics has been established to identify six genotypes of ABO blood types, namely I(A)I(A), I(A)i, I(B)I(B), I(B)i, I(A)I(B) and ii. Laboratory courses of molecular and population genetics have been integrated by calculating the frequencies of the six genotypes and three multiple alleles and testing population genetic equilibrium. The goal of the open laboratory course with independent design and implementation by the students has been achieved. This laboratory course has proved effective and received good reviews from the students. It could be applied as a genetics laboratory course for the biology majors directly, and its ideas and methods could be promoted and applied to other biological laboratory courses.

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.

Genome resources for climate-resilient cowpea, an essential crop for food security.

PubMed

Muñoz-Amatriaín, María; Mirebrahim, Hamid; Xu, Pei; Wanamaker, Steve I; Luo, MingCheng; Alhakami, Hind; Alpert, Matthew; Atokple, Ibrahim; Batieno, Benoit J; Boukar, Ousmane; Bozdag, Serdar; Cisse, Ndiaga; Drabo, Issa; Ehlers, Jeffrey D; Farmer, Andrew; Fatokun, Christian; Gu, Yong Q; Guo, Yi-Ning; Huynh, Bao-Lam; Jackson, Scott A; Kusi, Francis; Lawley, Cynthia T; Lucas, Mitchell R; Ma, Yaqin; Timko, Michael P; Wu, Jiajie; You, Frank; Barkley, Noelle A; Roberts, Philip A; Lonardi, Stefano; Close, Timothy J

2017-03-01

Cowpea (Vigna unguiculata L. Walp.) is a legume crop that is resilient to hot and drought-prone climates, and a primary source of protein in sub-Saharan Africa and other parts of the developing world. However, genome resources for cowpea have lagged behind most other major crops. Here we describe foundational genome resources and their application to the analysis of germplasm currently in use in West African breeding programs. Resources developed from the African cultivar IT97K-499-35 include a whole-genome shotgun (WGS) assembly, a bacterial artificial chromosome (BAC) physical map, and assembled sequences from 4355 BACs. These resources and WGS sequences of an additional 36 diverse cowpea accessions supported the development of a genotyping assay for 51 128 SNPs, which was then applied to five bi-parental RIL populations to produce a consensus genetic map containing 37 372 SNPs. This genetic map enabled the anchoring of 100 Mb of WGS and 420 Mb of BAC sequences, an exploration of genetic diversity along each linkage group, and clarification of macrosynteny between cowpea and common bean. The SNP assay enabled a diversity analysis of materials from West African breeding programs. Two major subpopulations exist within those materials, one of which has significant parentage from South and East Africa and more diversity. There are genomic regions of high differentiation between subpopulations, one of which coincides with a cluster of nodulin genes. The new resources and knowledge help to define goals and accelerate the breeding of improved varieties to address food security issues related to limited-input small-holder farming and climate stress. © 2016 The Authors. The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

Genetic analyses of Per.C6 cell clones producing a therapeutic monoclonal antibody regarding productivity and long-term stability.

PubMed

Tsuruta, Lilian Rumi; Lopes Dos Santos, Mariana; Yeda, Fernanda Perez; Okamoto, Oswaldo Keith; Moro, Ana Maria

2016-12-01

Genetic characterization of protein-producing clones represents additional value to cell line development. In the present study, ten Per.C6 clones producing a Rebmab100 monoclonal antibody were selected using two cloning methods: six clones originated from limiting dilution cloning and four by the automated colony picker ClonePix FL. A stability program was performed for 50 generations, including 4 batches distributed along the timeframe to determine specific productivity (Qp) maintenance. Four stable clones (two from limiting dilution and two from ClonePix FL) were further evaluated. The relative mRNA expression levels of both heavy chain (HC) and light chain (LC) genes were verified at generations 0, 30-35, and 50-55 of the stability program. At generations 0 and 30-35, LC gene expression level was higher than HC gene, whereas at generation 50-55, the opposite prevailed. A high correlation was observed between Qp and HC or LC mRNA expression level for all clones at each generation analyzed along the continuous culture. The mRNA stability study was performed at steady-state culture. The LC gene displayed a higher half-life and lower decay constant than HC gene, accounting for the higher observed expression level of LC mRNA in comparison to HC mRNA. Clone R6 was highlighted due its high Qp, mRNA expression levels, and mRNA stability. Besides the benefits of applying genetic characterization for the selection of stable and high-producing clones, the present study shows for the first time the correlation between Qp and HC or LC expression levels and also mRNA stability in clones derived from human cell line Per.C6(®).

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.

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.

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

Plant hairy root cultures as plasmodium modulators of the slime mold emergent computing substrate Physarum polycephalum.

PubMed

Ricigliano, Vincent; Chitaman, Javed; Tong, Jingjing; Adamatzky, Andrew; Howarth, Dianella G

2015-01-01

Roots of the medicinal plant Valeriana officinalis are well-studied for their various biological activities. We applied genetically transformed V. officinalis root biomass to exert control of Physarum polycephalum, an amoeba-based emergent computing substrate. The plasmodial stage of the P. polycephalum life cycle constitutes a single, multinucleate cell visible by unaided eye. The plasmodium modifies its network of oscillating protoplasm in response to spatial configurations of attractants and repellents, a behavior that is interpreted as biological computation. To program the computing behavior of P. polycephalum, a diverse and sustainable library of plasmodium modulators is required. Hairy roots produced by genetic transformation with Agrobacterium rhizogenes are a metabolically stable source of bioactive compounds. Adventitious roots were induced on in vitro V. officinalis plants following infection with A. rhizogenes. A single hairy root clone was selected for massive propagation and the biomass was characterized in P. polycephalum chemotaxis, maze-solving, and electrical activity assays. The Agrobacterium-derived roots of V. officinalis elicited a positive chemotactic response and augmented maze-solving behavior. In a simple plasmodium circuit, introduction of hairy root biomass stimulated the oscillation patterns of slime mold's surface electrical activity. We propose that manipulation of P. polycephalum with the plant root culture platform can be applied to the development of slime mold microfluidic devices as well as future models for engineering the plant rhizosphere.

Plant hairy root cultures as plasmodium modulators of the slime mold emergent computing substrate Physarum polycephalum

PubMed Central

Ricigliano, Vincent; Chitaman, Javed; Tong, Jingjing; Adamatzky, Andrew; Howarth, Dianella G.

2015-01-01

Roots of the medicinal plant Valeriana officinalis are well-studied for their various biological activities. We applied genetically transformed V. officinalis root biomass to exert control of Physarum polycephalum, an amoeba-based emergent computing substrate. The plasmodial stage of the P. polycephalum life cycle constitutes a single, multinucleate cell visible by unaided eye. The plasmodium modifies its network of oscillating protoplasm in response to spatial configurations of attractants and repellents, a behavior that is interpreted as biological computation. To program the computing behavior of P. polycephalum, a diverse and sustainable library of plasmodium modulators is required. Hairy roots produced by genetic transformation with Agrobacterium rhizogenes are a metabolically stable source of bioactive compounds. Adventitious roots were induced on in vitro V. officinalis plants following infection with A. rhizogenes. A single hairy root clone was selected for massive propagation and the biomass was characterized in P. polycephalum chemotaxis, maze-solving, and electrical activity assays. The Agrobacterium-derived roots of V. officinalis elicited a positive chemotactic response and augmented maze-solving behavior. In a simple plasmodium circuit, introduction of hairy root biomass stimulated the oscillation patterns of slime mold's surface electrical activity. We propose that manipulation of P. polycephalum with the plant root culture platform can be applied to the development of slime mold microfluidic devices as well as future models for engineering the plant rhizosphere. PMID:26236301

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

Peptidic tools applied to redirect alternative splicing events.

PubMed

Nancy, Martínez-Montiel; Nora, Rosas-Murrieta; Rebeca, Martínez-Contreras

2015-05-01

Peptides are versatile and attractive biomolecules that can be applied to modulate genetic mechanisms like alternative splicing. In this process, a single transcript yields different mature RNAs leading to the production of protein isoforms with diverse or even antagonistic functions. During splicing events, errors can be caused either by mutations present in the genome or by defects or imbalances in regulatory protein factors. In any case, defects in alternative splicing have been related to several genetic diseases including muscular dystrophy, Alzheimer's disease and cancer from almost every origin. One of the most effective approaches to redirect alternative splicing events has been to attach cell-penetrating peptides to oligonucleotides that can modulate a single splicing event and restore correct gene expression. Here, we summarize how natural existing and bioengineered peptides have been applied over the last few years to regulate alternative splicing and genetic expression. Under different genetic and cellular backgrounds, peptides have been shown to function as potent vehicles for splice correction, and their therapeutic benefits have reached clinical trials and patenting stages, emphasizing the use of regulatory peptides as an exciting therapeutic tool for the treatment of different genetic diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2003-01-01

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

Actor-network theory: a tool to support ethical analysis of commercial genetic testing.

PubMed

Williams-Jones, Bryn; Graham, Janice E

2003-12-01

Social, ethical and policy analysis of the issues arising from gene patenting and commercial genetic testing is enhanced by the application of science and technology studies, and Actor-Network Theory (ANT) in particular. We suggest the potential for transferring ANT's flexible nature to an applied heuristic methodology for gathering empirical information and for analysing the complex networks involved in the development of genetic technologies. Three concepts are explored in this paper--actor-networks, translation, and drift--and applied to the case of Myriad Genetics and their commercial BRACAnalysis genetic susceptibility test for hereditary breast cancer. Treating this test as an active participant in socio-technical networks clarifies the extent to which it interacts with, shapes and is shaped by people, other technologies, and institutions. Such an understanding enables more sophisticated and nuanced technology assessment, academic analysis, as well as public debate about the social, ethical and policy implications of the commercialization of new genetic technologies.

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.

Improved Evolutionary Programming with Various Crossover Techniques for Optimal Power Flow Problem

NASA Astrophysics Data System (ADS)

Tangpatiphan, Kritsana; Yokoyama, Akihiko

This paper presents an Improved Evolutionary Programming (IEP) for solving the Optimal Power Flow (OPF) problem, which is considered as a non-linear, non-smooth, and multimodal optimization problem in power system operation. The total generator fuel cost is regarded as an objective function to be minimized. The proposed method is an Evolutionary Programming (EP)-based algorithm with making use of various crossover techniques, normally applied in Real Coded Genetic Algorithm (RCGA). The effectiveness of the proposed approach is investigated on the IEEE 30-bus system with three different types of fuel cost functions; namely the quadratic cost curve, the piecewise quadratic cost curve, and the quadratic cost curve superimposed by sine component. These three cost curves represent the generator fuel cost functions with a simplified model and more accurate models of a combined-cycle generating unit and a thermal unit with value-point loading effect respectively. The OPF solutions by the proposed method and Pure Evolutionary Programming (PEP) are observed and compared. The simulation results indicate that IEP requires less computing time than PEP with better solutions in some cases. Moreover, the influences of important IEP parameters on the OPF solution are described in details.

Estimates of population genetic diversity in brown bullhead catfish by DNA fingerprinting

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

Roth, A.C.; Wessendarp, T.K.; Gordon, D.A.

Estimates of population genetic diversity may be a sensitive indicator of environmental impact, since limiting the effective breeding population by any means will result in loss of some variant genotypes, as has been demonstrated by allozyme analysis. DNA fingerprinting techniques are also coming into use for population analyses, and the authors chose to apply fingerprinting analysis three populations of brown bullhead catfish collected in Northern Ohio. DNA was isolated from the red blood cells of individual fish. Purified DNAs were digested with EcoR1 restriction enzyme; the digests were then sized on a 1% agarose gel, transferred to nylon membranes andmore » probed with a radiolabeled M13 probe using the Westneat hybridization protocol (Southern blotting). This method effects fragments containing VNTR (variable number of tandem repeat) sequences complementary to the M13, which are highly variable among individual catfish. Hybridized bands were visualized by a Molecular Dynamics phosphorimager and recorded and analyzed with its proprietary Imagequant image analysis program, Excel and SAS. A total of 10 variable bands were identified and their presence or absence scored in each individual. These data were analyzed to determine between and within-population similarity indices as well as population heterozygosity and genetic diversity measures.« less

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.

Genetic Parameters of Milk β-Hydroxybutyric Acid and Acetone and Their Genetic Association with Milk Production Traits of Holstein Cattle

PubMed Central

Lee, SeokHyun; Cho, KwangHyun; Park, MiNa; Choi, TaeJung; Kim, SiDong; Do, ChangHee

2016-01-01

This study was conducted to estimate the genetic parameters of β-hydroxybutyrate (BHBA) and acetone concentration in milk by Fourier transform infrared spectroscopy along with test-day milk production traits including fat %, protein % and milk yield based on monthly samples of milk obtained as part of a routine milk recording program in Korea. Additionally, the feasibility of using such data in the official dairy cattle breeding system for selection of cows with low susceptibility of ketosis was evaluated. A total of 57,190 monthly test-day records for parities 1, 2, and 3 of 7,895 cows with pedigree information were collected from April 2012 to August 2014 from herds enrolled in the Korea Animal Improvement Association. Multi-trait random regression models were separately applied to estimate genetic parameters of test-day records for each parity. The model included fixed herd test-day effects, calving age and season effects, and random regressions for additive genetic and permanent environmental effects. Abundance of variation of acetone may provide a more sensitive indication of ketosis than many zero observations in concentration of milk BHBA. Heritabilities of milk BHBA levels ranged from 0.04 to 0.17 with a mean of 0.09 for the interval between 4 and 305 days in milk during three lactations. The average heritabilities for milk acetone concentration were 0.29, 0.29, and 0.22 for parities 1, 2, and 3, respectively. There was no clear genetic association of the concentration of two ketone bodies with three test-day milk production traits, even if some correlations among breeding values of the test-day records in this study were observed. These results suggest that genetic selection for low susceptibility of ketosis in early lactation is possible. Further, it is desirable for the breeding scheme of dairy cattle to include the records of milk acetone rather than the records of milk BHBA. PMID:27608643

Genetic Parameters of Milk β-Hydroxybutyric Acid and Acetone and Their Genetic Association with Milk Production Traits of Holstein Cattle.

PubMed

Lee, SeokHyun; Cho, KwangHyun; Park, MiNa; Choi, TaeJung; Kim, SiDong; Do, ChangHee

2016-11-01

This study was conducted to estimate the genetic parameters of β-hydroxybutyrate (BHBA) and acetone concentration in milk by Fourier transform infrared spectroscopy along with test-day milk production traits including fat %, protein % and milk yield based on monthly samples of milk obtained as part of a routine milk recording program in Korea. Additionally, the feasibility of using such data in the official dairy cattle breeding system for selection of cows with low susceptibility of ketosis was evaluated. A total of 57,190 monthly test-day records for parities 1, 2, and 3 of 7,895 cows with pedigree information were collected from April 2012 to August 2014 from herds enrolled in the Korea Animal Improvement Association. Multi-trait random regression models were separately applied to estimate genetic parameters of test-day records for each parity. The model included fixed herd test-day effects, calving age and season effects, and random regressions for additive genetic and permanent environmental effects. Abundance of variation of acetone may provide a more sensitive indication of ketosis than many zero observations in concentration of milk BHBA. Heritabilities of milk BHBA levels ranged from 0.04 to 0.17 with a mean of 0.09 for the interval between 4 and 305 days in milk during three lactations. The average heritabilities for milk acetone concentration were 0.29, 0.29, and 0.22 for parities 1, 2, and 3, respectively. There was no clear genetic association of the concentration of two ketone bodies with three test-day milk production traits, even if some correlations among breeding values of the test-day records in this study were observed. These results suggest that genetic selection for low susceptibility of ketosis in early lactation is possible. Further, it is desirable for the breeding scheme of dairy cattle to include the records of milk acetone rather than the records of milk BHBA.

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

Importance of genetic diversity assessment in crop plants and its recent advances: an overview of its analytical perspectives.

PubMed

Govindaraj, M; Vetriventhan, M; Srinivasan, M

2015-01-01

The importance of plant genetic diversity (PGD) is now being recognized as a specific area since exploding population with urbanization and decreasing cultivable lands are the critical factors contributing to food insecurity in developing world. Agricultural scientists realized that PGD can be captured and stored in the form of plant genetic resources (PGR) such as gene bank, DNA library, and so forth, in the biorepository which preserve genetic material for long period. However, conserved PGR must be utilized for crop improvement in order to meet future global challenges in relation to food and nutritional security. This paper comprehensively reviews four important areas; (i) the significance of plant genetic diversity (PGD) and PGR especially on agriculturally important crops (mostly field crops); (ii) risk associated with narrowing the genetic base of current commercial cultivars and climate change; (iii) analysis of existing PGD analytical methods in pregenomic and genomic era; and (iv) modern tools available for PGD analysis in postgenomic era. This discussion benefits the plant scientist community in order to use the new methods and technology for better and rapid assessment, for utilization of germplasm from gene banks to their applied breeding programs. With the advent of new biotechnological techniques, this process of genetic manipulation is now being accelerated and carried out with more precision (neglecting environmental effects) and fast-track manner than the classical breeding techniques. It is also to note that gene banks look into several issues in order to improve levels of germplasm distribution and its utilization, duplication of plant identity, and access to database, for prebreeding activities. Since plant breeding research and cultivar development are integral components of improving food production, therefore, availability of and access to diverse genetic sources will ensure that the global food production network becomes more sustainable. The pros and cons of the basic and advanced statistical tools available for measuring genetic diversity are briefly discussed and their source links (mostly) were provided to get easy access; thus, it improves the understanding of tools and its practical applicability to the researchers.

Importance of Genetic Diversity Assessment in Crop Plants and Its Recent Advances: An Overview of Its Analytical Perspectives

PubMed Central

Govindaraj, M.; Vetriventhan, M.; Srinivasan, M.

2015-01-01

The importance of plant genetic diversity (PGD) is now being recognized as a specific area since exploding population with urbanization and decreasing cultivable lands are the critical factors contributing to food insecurity in developing world. Agricultural scientists realized that PGD can be captured and stored in the form of plant genetic resources (PGR) such as gene bank, DNA library, and so forth, in the biorepository which preserve genetic material for long period. However, conserved PGR must be utilized for crop improvement in order to meet future global challenges in relation to food and nutritional security. This paper comprehensively reviews four important areas; (i) the significance of plant genetic diversity (PGD) and PGR especially on agriculturally important crops (mostly field crops); (ii) risk associated with narrowing the genetic base of current commercial cultivars and climate change; (iii) analysis of existing PGD analytical methods in pregenomic and genomic era; and (iv) modern tools available for PGD analysis in postgenomic era. This discussion benefits the plant scientist community in order to use the new methods and technology for better and rapid assessment, for utilization of germplasm from gene banks to their applied breeding programs. With the advent of new biotechnological techniques, this process of genetic manipulation is now being accelerated and carried out with more precision (neglecting environmental effects) and fast-track manner than the classical breeding techniques. It is also to note that gene banks look into several issues in order to improve levels of germplasm distribution and its utilization, duplication of plant identity, and access to database, for prebreeding activities. Since plant breeding research and cultivar development are integral components of improving food production, therefore, availability of and access to diverse genetic sources will ensure that the global food production network becomes more sustainable. The pros and cons of the basic and advanced statistical tools available for measuring genetic diversity are briefly discussed and their source links (mostly) were provided to get easy access; thus, it improves the understanding of tools and its practical applicability to the researchers. PMID:25874132

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.

Using genetic algorithm to solve a new multi-period stochastic optimization model

NASA Astrophysics Data System (ADS)

Zhang, Xin-Li; Zhang, Ke-Cun

2009-09-01

This paper presents a new asset allocation model based on the CVaR risk measure and transaction costs. Institutional investors manage their strategic asset mix over time to achieve favorable returns subject to various uncertainties, policy and legal constraints, and other requirements. One may use a multi-period portfolio optimization model in order to determine an optimal asset mix. Recently, an alternative stochastic programming model with simulated paths was proposed by Hibiki [N. Hibiki, A hybrid simulation/tree multi-period stochastic programming model for optimal asset allocation, in: H. Takahashi, (Ed.) The Japanese Association of Financial Econometrics and Engineering, JAFFE Journal (2001) 89-119 (in Japanese); N. Hibiki A hybrid simulation/tree stochastic optimization model for dynamic asset allocation, in: B. Scherer (Ed.), Asset and Liability Management Tools: A Handbook for Best Practice, Risk Books, 2003, pp. 269-294], which was called a hybrid model. However, the transaction costs weren't considered in that paper. In this paper, we improve Hibiki's model in the following aspects: (1) The risk measure CVaR is introduced to control the wealth loss risk while maximizing the expected utility; (2) Typical market imperfections such as short sale constraints, proportional transaction costs are considered simultaneously. (3) Applying a genetic algorithm to solve the resulting model is discussed in detail. Numerical results show the suitability and feasibility of our methodology.

Establishment of the mathematical model for diagnosing the engine valve faults by genetic programming

NASA Astrophysics Data System (ADS)

Yang, Wen-Xian

2006-05-01

Available machine fault diagnostic methods show unsatisfactory performances on both on-line and intelligent analyses because their operations involve intensive calculations and are labour intensive. Aiming at improving this situation, this paper describes the development of an intelligent approach by using the Genetic Programming (abbreviated as GP) method. Attributed to the simple calculation of the mathematical model being constructed, different kinds of machine faults may be diagnosed correctly and quickly. Moreover, human input is significantly reduced in the process of fault diagnosis. The effectiveness of the proposed strategy is validated by an illustrative example, in which three kinds of valve states inherent in a six-cylinders/four-stroke cycle diesel engine, i.e. normal condition, valve-tappet clearance and gas leakage faults, are identified. In the example, 22 mathematical functions have been specially designed and 8 easily obtained signal features are used to construct the diagnostic model. Different from existing GPs, the diagnostic tree used in the algorithm is constructed in an intelligent way by applying a power-weight coefficient to each feature. The power-weight coefficients vary adaptively between 0 and 1 during the evolutionary process. Moreover, different evolutionary strategies are employed, respectively for selecting the diagnostic features and functions, so that the mathematical functions are sufficiently utilized and in the meantime, the repeated use of signal features may be fully avoided. The experimental results are illustrated diagrammatically in the following sections.

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

PubMed

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

2016-01-01

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

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.

Imaging C. elegans embryos using an epifluorescent microscope and open source software.

PubMed

Verbrugghe, Koen J C; Chan, Raymond C

2011-03-24

Cellular processes, such as chromosome assembly, segregation and cytokinesis,are inherently dynamic. Time-lapse imaging of living cells, using fluorescent-labeled reporter proteins or differential interference contrast (DIC) microscopy, allows for the examination of the temporal progression of these dynamic events which is otherwise inferred from analysis of fixed samples(1,2). Moreover, the study of the developmental regulations of cellular processes necessitates conducting time-lapse experiments on an intact organism during development. The Caenorhabiditis elegans embryo is light-transparent and has a rapid, invariant developmental program with a known cell lineage(3), thus providing an ideal experiment model for studying questions in cell biology(4,5)and development(6-9). C. elegans is amendable to genetic manipulation by forward genetics (based on random mutagenesis(10,11)) and reverse genetics to target specific genes (based on RNAi-mediated interference and targeted mutagenesis(12-15)). In addition, transgenic animals can be readily created to express fluorescently tagged proteins or reporters(16,17). These traits combine to make it easy to identify the genetic pathways regulating fundamental cellular and developmental processes in vivo(18-21). In this protocol we present methods for live imaging of C. elegans embryos using DIC optics or GFP fluorescence on a compound epifluorescent microscope. We demonstrate the ease with which readily available microscopes, typically used for fixed sample imaging, can also be applied for time-lapse analysis using open-source software to automate the imaging process.

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

PubMed

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

2017-09-29

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

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

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.

Not all GMOs are crop plants: non-plant GMO applications in agriculture

USDA-ARS?s Scientific Manuscript database

In the time since the tools of modern biotechnology have become available, the most commonly applied and often discussed genetically modified organisms are genetically modified crop plants, although genetic engineering is also being used successfully in organisms other than plants, including bacteri...

An Adaptive Niching Genetic Algorithm using a niche size equalization mechanism

NASA Astrophysics Data System (ADS)

Nagata, Yuichi

Niching GAs have been widely investigated to apply genetic algorithms (GAs) to multimodal function optimization problems. In this paper, we suggest a new niching GA that attempts to form niches, each consisting of an equal number of individuals. The proposed GA can be applied also to combinatorial optimization problems by defining a distance metric in the search space. We apply the proposed GA to the job-shop scheduling problem (JSP) and demonstrate that the proposed niching method enhances the ability to maintain niches and improve the performance of GAs.

AAAI (American Association on Artificial Intelligence) Workshop on AI (Artificial Intelligence) Simulation Held in Philadelphia, Pennsylvania on August 11, 1986,

DTIC Science & Technology

1986-08-01

is then applied in i ABSTRCT : ,.:,.vu knowledge acquisition from those multiple sources for a specific design, for example, an expert system for...67. N 181.1 47.U3 a75 269;9.6 % A. %3 3 Genetic Explanations: For the concept of a genetic explanation (see .d -. above) to apply to the Gaither...Simulation Research Unit (Acock,1985; Baker,1983; Baker,1985). -. MD’,EX srves as an inner shell for apPlying Artificial Intelligence and E:pert System

A recoding scheme for X-linked and pseudoautosomal loci to be used with computer programs for autosomal LOD-score analysis.

PubMed

Strauch, Konstantin; Baur, Max P; Wienker, Thomas F

2004-01-01

We present a recoding scheme that allows for a parametric multipoint X-chromosomal linkage analysis of dichotomous traits in the context of a computer program for autosomes that can use trait models with imprinting. Furthermore, with this scheme, it is possible to perform a joint multipoint analysis of X-linked and pseudoautosomal loci. It is required that (1) the marker genotypes of all female nonfounders are available and that (2) there are no male nonfounders who have daughters in the pedigree. The second requirement does not apply if the trait locus is pseudoautosomal. The X-linked marker loci are recorded by adding a dummy allele to the males' hemizygous genotypes. For modelling an X-linked trait locus, five different liability classes are defined, in conjunction with a paternal imprinting model for male nonfounders. The formulation aims at the mapping of a diallelic trait locus relative to an arbitrary number of codominant markers with known genetic distances, in cases where a program for a genuine X-chromosomal analysis is not available. 2004 S. Karger AG, Basel.

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.

Genetic harm: bitten by the body that keeps you?

PubMed

Kahn, Jeffrey P

1991-10-01

... We must attempt to explain, how, if ever, our existence may harm us. To address this and the other questions raised, I propose to examine what constitutes harm and whether it makes sense to say that our genetic makeup may harm us. To do this I will describe three approaches to the problem of describing the status of negative effects our genes have upon us, which I have named the "technical harm" view, the "constitutive" view, and the "harmful conditions" view. On the technical harm view, the standard definitions of harm are applied to genetic disposition in an attempt to couch genetic defects or flaws in terms of harming. The constitutive view rejects applying the concept of harm to genetic disposition on the grounds that it is impossible to separate genetic disposition from individual identity. Lastly, the harmful conditions view, which I conclude is the most successful of the three, focuses on the tendency of certain genetic dispositions to cause harm in the future and thus avoids what I will argue are the "context" shortcomings of the other two approaches. To conclude the discussion I will very briefly analyze the ramifications of a harmful conditions view for the concept of genetic disease and the prospects for genetic counseling, gene therapy, and reproductive decision making.

Beyond the Triplet Code: Context Cues Transform Translation.

PubMed

Brar, Gloria A

2016-12-15

The elucidation of the genetic code remains among the most influential discoveries in biology. While innumerable studies have validated the general universality of the code and its value in predicting and analyzing protein coding sequences, established and emerging work has also suggested that full genome decryption may benefit from a greater consideration of a codon's neighborhood within an mRNA than has been broadly applied. This Review examines the evidence for context cues in translation, with a focus on several recent studies that reveal broad roles for mRNA context in programming translation start sites, the rate of translation elongation, and stop codon identity. Copyright © 2016 Elsevier Inc. All rights reserved.

Prediction of laser cutting heat affected zone by extreme learning machine

NASA Astrophysics Data System (ADS)

Anicic, Obrad; Jović, Srđan; Skrijelj, Hivzo; Nedić, Bogdan

2017-01-01

Heat affected zone (HAZ) of the laser cutting process may be developed based on combination of different factors. In this investigation the HAZ forecasting, based on the different laser cutting parameters, was analyzed. The main goal was to predict the HAZ according to three inputs. The purpose of this research was to develop and apply the Extreme Learning Machine (ELM) to predict the HAZ. The ELM results were compared with genetic programming (GP) and artificial neural network (ANN). The reliability of the computational models were accessed based on simulation results and by using several statistical indicators. Based upon simulation results, it was demonstrated that ELM can be utilized effectively in applications of HAZ forecasting.

Nemo: an evolutionary and population genetics programming framework.

PubMed

Guillaume, Frédéric; Rougemont, Jacques

2006-10-15

Nemo is an individual-based, genetically explicit and stochastic population computer program for the simulation of population genetics and life-history trait evolution in a metapopulation context. It comes as both a C++ programming framework and an executable program file. Its object-oriented programming design gives it the flexibility and extensibility needed to implement a large variety of forward-time evolutionary models. It provides developers with abstract models allowing them to implement their own life-history traits and life-cycle events. Nemo offers a large panel of population models, from the Island model to lattice models with demographic or environmental stochasticity and a variety of already implemented traits (deleterious mutations, neutral markers and more), life-cycle events (mating, dispersal, aging, selection, etc.) and output operators for saving data and statistics. It runs on all major computer platforms including parallel computing environments. The source code, binaries and documentation are available under the GNU General Public License at http://nemo2.sourceforge.net.

Potential benefits of genomic selection on genetic gain of small ruminant breeding programs.

PubMed

Shumbusho, F; Raoul, J; Astruc, J M; Palhiere, I; Elsen, J M

2013-08-01

In conventional small ruminant breeding programs, only pedigree and phenotype records are used to make selection decisions but prospects of including genomic information are now under consideration. The objective of this study was to assess the potential benefits of genomic selection on the genetic gain in French sheep and goat breeding designs of today. Traditional and genomic scenarios were modeled with deterministic methods for 3 breeding programs. The models included decisional variables related to male selection candidates, progeny testing capacity, and economic weights that were optimized to maximize annual genetic gain (AGG) of i) a meat sheep breeding program that improved a meat trait of heritability (h(2)) = 0.30 and a maternal trait of h(2) = 0.09 and ii) dairy sheep and goat breeding programs that improved a milk trait of h(2) = 0.30. Values of ±0.20 of genetic correlation between meat and maternal traits were considered to study their effects on AGG. The Bulmer effect was accounted for and the results presented here are the averages of AGG after 10 generations of selection. Results showed that current traditional breeding programs provide an AGG of 0.095 genetic standard deviation (σa) for meat and 0.061 σa for maternal trait in meat breed and 0.147 σa and 0.120 σa in sheep and goat dairy breeds, respectively. By optimizing decisional variables, the AGG with traditional selection methods increased to 0.139 σa for meat and 0.096 σa for maternal traits in meat breeding programs and to 0.174 σa and 0.183 σa in dairy sheep and goat breeding programs, respectively. With a medium-sized reference population (nref) of 2,000 individuals, the best genomic scenarios gave an AGG that was 17.9% greater than with traditional selection methods with optimized values of decisional variables for combined meat and maternal traits in meat sheep, 51.7% in dairy sheep, and 26.2% in dairy goats. The superiority of genomic schemes increased with the size of the reference population and genomic selection gave the best results when nref > 1,000 individuals for dairy breeds and nref > 2,000 individuals for meat breed. Genetic correlation between meat and maternal traits had a large impact on the genetic gain of both traits. Changes in AGG due to correlation were greatest for low heritable maternal traits. As a general rule, AGG was increased both by optimizing selection designs and including genomic information.

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

Assessment of an Interactive Computer-Based Patient Prenatal Genetic Screening and Testing Education Tool

ERIC Educational Resources Information Center

Griffith, Jennifer M.; Sorenson, James R.; Bowling, J. Michael; Jennings-Grant, Tracey

2005-01-01

The Enhancing Patient Prenatal Education study tested the feasibility and educational impact of an interactive program for patient prenatal genetic screening and testing education. Patients at two private practices and one public health clinic participated (N = 207). The program collected knowledge and measures of anxiety before and after use of…

Breeding strategies for north central tree improvement programs

Treesearch

Ronald P. Overton; Hyun Kang

1985-01-01

The rationales and concepts of long-term tree breeding are discussed and compared with those for short-term breeding. A model breeding program is reviewed which maximizes short-term genetic gain for currently important traits and provides genetic resources that can be used effectively in future short-term breeding. The resources of the north-central region are examined...

Tissue culture of conifer seedlings-20 years on: Viewed through the lens of seedling quality

Treesearch

Steven C. Grossnickle

2011-01-01

Operational vegetative propagation systems provide a means of bringing new genetic material into forestry programs through the capture of a greater proportion of the genetic gain inherent within a selected tree species. Vegetative propagation systems also provide a method for multiplying superior varieties and/or families identified in tree improvement programs. Twenty...

Loss of genetic diversity in Culex quinquefasciatus targeted by a lymphatic filariasis vector control program in Recife, Brazil.

PubMed

Cartaxo, Marina F S; Ayres, Constância F J; Weetman, David

2011-09-01

Recife is one of the largest cities in north-eastern Brazil and is endemic for lymphatic filariasis transmitted by Culex quinquefasciatus. Since 2003 a control program has targeted mosquito larvae by elimination of breeding sites and bimonthly application of Bacillus sphaericus. To assess the impact of this program on the local vector population we monitored the genetic diversity and differentiation of Cx. quinquefasciatus using microsatellites and a B. sphaericus-resistance associated mutation (cqm1(REC)) over a 3-year period. We detected a significant but gradual decline in allelic diversity, which, coupled with subtle temporal genetic structure, suggests a major impact of the control program on the vector population. Selection on cqm1(REC) does not appear to be involved with loss of neutral diversity from the population, with no temporal trend in resistant allele frequency and no correlation with microsatellite differentiation. The evidence for short-term genetic drift we detected suggests a low ratio of effective population size: census population size for Cx. quinquefasciatus, perhaps coupled with strong geographically-restricted population structure. Spatial definition of populations will be an important step for success of an expanded vector control program. Copyright © 2011 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved.

Reasoning across Ontologically Distinct Levels: Students' Understandings of Molecular Genetics

ERIC Educational Resources Information Center

Duncan, Ravit Golan; Reiser, Brian J.

2007-01-01

In this article we apply a novel analytical framework to explore students' difficulties in understanding molecular genetics--a domain that is particularly challenging to learn. Our analytical framework posits that reasoning in molecular genetics entails mapping across ontologically distinct levels--an information level containing the genetic…

Application of molecular genetic tools for forest pathology

Treesearch

Mee-Sook Kim; John Hanna; Amy Ross-Davis; Ned Klopfenstein

2012-01-01

In recent years, advances in molecular genetics have provided powerful tools to address critical issues in forest pathology to help promote resilient forests. Although molecular genetic tools are initially applied to understand individual components of forest pathosystems, forest pathosystems involve dynamic interactions among biotic and abiotic components of the...

Genetic structure of populations and differentiation in forest trees

Treesearch

Raymond P. Guries; F. Thomas Ledig

1981-01-01

Electrophoretic techniques permit population biologists to analyze genetic structure of natural populations by using large numbers of allozyme loci. Several methods of analysis have been applied to allozyme data, including chi-square contingency tests, F-statistics, and genetic distance. This paper compares such statistics for pitch pine (Pinus rigida...

Genetic counseling for schizophrenia: a review of referrals to a provincial medical genetics program from 1968–2007

PubMed Central

Hunter, MJ; Hippman, Catriona; Honer, William G; Austin, Jehannine C.

2014-01-01

Purpose Recent studies have shown that individuals with schizophrenia and their family members are interested in genetic counseling, but few have received this service. We conducted an exploratory, retrospective study to describe (a) the population of individuals who were referred to the provincial program for genetic counseling for a primary indication of schizophrenia, and (b) trends in number of referrals between 1968 and 2007. Methods Referrals for a primary indication of schizophrenia were identified through the provincial program database. Charts were reviewed and the following information was recorded: discipline of referring physician, demographics, psychiatric diagnosis, referred individual’s and partner’s (if applicable) family history, and any current pregnancy history. Data were characterized using descriptive statistics. Results Between 1968 and 2007, 288 referrals were made for a primary indication of schizophrenia. Most referrals were made: (a) for individuals who had a first-degree family member with schizophrenia, rather than for affected individuals, (b) for preconception counseling, and (c) by family physicians (69%), with only 2% by psychiatrists. Conclusions In British Columbia, individuals affected with schizophrenia and their family members are rarely referred for psychiatric genetic counseling. There is a need to identify barriers to psychiatric genetic counseling and develop strategies to improve access. PMID:20034078

A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2001-01-01

In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.

A hybrid genetic algorithm for resolving closely spaced objects

NASA Technical Reports Server (NTRS)

Abbott, R. J.; Lillo, W. E.; Schulenburg, N.

1995-01-01

A hybrid genetic algorithm is described for performing the difficult optimization task of resolving closely spaced objects appearing in space based and ground based surveillance data. This application of genetic algorithms is unusual in that it uses a powerful domain-specific operation as a genetic operator. Results of applying the algorithm to real data from telescopic observations of a star field are presented.

Molecular and genetic basis for partial resistance of western white pine against Cronartium ribicola.

Treesearch

Jun-Jun Liu; Arezoo Zamany; Richard Sniezko

2012-01-01

Western white pine (Pinus monticola Douglas ex D. Don) is an important forest species in North America. Forest genetics programs have been breeding for durable genetic resistance against white pine blister rust (WPBR) caused by Cronartium ribicola in the past few decades. As various genetic resistance resources are screened and...

Strategies for conserving forest genetic resources in the face of climate change

Treesearch

John Bradley St. Clair; Glenn Thomas Howe

2011-01-01

Conservation of genetic diversity is important for continued evolution of populations to new environments, as well as continued availability of traits of interest in genetic improvement programs. Rapidly changing climates present new threats to the conservation of forest genetic resources. We can no longer assume that in situ reserves will continue to preserve existing...

Evolving binary classifiers through parallel computation of multiple fitness cases.

PubMed

Cagnoni, Stefano; Bergenti, Federico; Mordonini, Monica; Adorni, Giovanni

2005-06-01

This paper describes two versions of a novel approach to developing binary classifiers, based on two evolutionary computation paradigms: cellular programming and genetic programming. Such an approach achieves high computation efficiency both during evolution and at runtime. Evolution speed is optimized by allowing multiple solutions to be computed in parallel. Runtime performance is optimized explicitly using parallel computation in the case of cellular programming or implicitly taking advantage of the intrinsic parallelism of bitwise operators on standard sequential architectures in the case of genetic programming. The approach was tested on a digit recognition problem and compared with a reference classifier.

Genetic evaluation for cow livability

USDA-ARS?s Scientific Manuscript database

When genetic evaluations for Productive Life were introduced by USDA in 1994, U.S. dairy producers had an opportunity to produce healthier cows, and it happened. The genetic evaluations were incorporated into selection programs and the deterioration occurring in pregnancy rate and somatic cell score...

Methods of analysis and resources available for genetic trait mapping.

PubMed

Ott, J

1999-01-01

Methods of genetic linkage analysis are reviewed and put in context with other mapping techniques. Sources of information are outlined (books, web sites, computer programs). Special consideration is given to statistical problems in canine genetic mapping (heterozygosity, inbreeding, marker maps).

EHR based Genetic Testing Knowledge Base (iGTKB) Development

PubMed Central

2015-01-01

Background The gap between a large growing number of genetic tests and a suboptimal clinical workflow of incorporating these tests into regular clinical practice poses barriers to effective reliance on advanced genetic technologies to improve quality of healthcare. A promising solution to fill this gap is to develop an intelligent genetic test recommendation system that not only can provide a comprehensive view of genetic tests as education resources, but also can recommend the most appropriate genetic tests to patients based on clinical evidence. In this study, we developed an EHR based Genetic Testing Knowledge Base for Individualized Medicine (iGTKB). Methods We extracted genetic testing information and patient medical records from EHR systems at Mayo Clinic. Clinical features have been semi-automatically annotated from the clinical notes by applying a Natural Language Processing (NLP) tool, MedTagger suite. To prioritize clinical features for each genetic test, we compared odds ratio across four population groups. Genetic tests, genetic disorders and clinical features with their odds ratios have been applied to establish iGTKB, which is to be integrated into the Genetic Testing Ontology (GTO). Results Overall, there are five genetic tests operated with sample size greater than 100 in 2013 at Mayo Clinic. A total of 1,450 patients who was tested by one of the five genetic tests have been selected. We assembled 243 clinical features from the Human Phenotype Ontology (HPO) for these five genetic tests. There are 60 clinical features with at least one mention in clinical notes of patients taking the test. Twenty-eight clinical features with high odds ratio (greater than 1) have been selected as dominant features and deposited into iGTKB with their associated information about genetic tests and genetic disorders. Conclusions In this study, we developed an EHR based genetic testing knowledge base, iGTKB. iGTKB will be integrated into the GTO by providing relevant clinical evidence, and ultimately to support development of genetic testing recommendation system, iGenetics. PMID:26606281

EHR based Genetic Testing Knowledge Base (iGTKB) Development.

PubMed

Zhu, Qian; Liu, Hongfang; Chute, Christopher G; Ferber, Matthew

2015-01-01

The gap between a large growing number of genetic tests and a suboptimal clinical workflow of incorporating these tests into regular clinical practice poses barriers to effective reliance on advanced genetic technologies to improve quality of healthcare. A promising solution to fill this gap is to develop an intelligent genetic test recommendation system that not only can provide a comprehensive view of genetic tests as education resources, but also can recommend the most appropriate genetic tests to patients based on clinical evidence. In this study, we developed an EHR based Genetic Testing Knowledge Base for Individualized Medicine (iGTKB). We extracted genetic testing information and patient medical records from EHR systems at Mayo Clinic. Clinical features have been semi-automatically annotated from the clinical notes by applying a Natural Language Processing (NLP) tool, MedTagger suite. To prioritize clinical features for each genetic test, we compared odds ratio across four population groups. Genetic tests, genetic disorders and clinical features with their odds ratios have been applied to establish iGTKB, which is to be integrated into the Genetic Testing Ontology (GTO). Overall, there are five genetic tests operated with sample size greater than 100 in 2013 at Mayo Clinic. A total of 1,450 patients who was tested by one of the five genetic tests have been selected. We assembled 243 clinical features from the Human Phenotype Ontology (HPO) for these five genetic tests. There are 60 clinical features with at least one mention in clinical notes of patients taking the test. Twenty-eight clinical features with high odds ratio (greater than 1) have been selected as dominant features and deposited into iGTKB with their associated information about genetic tests and genetic disorders. In this study, we developed an EHR based genetic testing knowledge base, iGTKB. iGTKB will be integrated into the GTO by providing relevant clinical evidence, and ultimately to support development of genetic testing recommendation system, iGenetics.

Tracking the Genetic Stability of a Honey Bee (Hymenoptera: Apidae) Breeding Program With Genetic Markers.

PubMed

Bourgeois, Lelania; Beaman, Lorraine

2017-08-01

A genetic stock identification (GSI) assay was developed in 2008 to distinguish Russian honey bees from other honey bee stocks that are commercially produced in the United States. Probability of assignment (POA) values have been collected and maintained since the stock release in 2008 to the Russian Honey Bee Breeders Association. These data were used to assess stability of the breeding program and the diversity levels of the contemporary breeding stock through comparison of POA values and genetic diversity parameters from the initial release to current values. POA values fluctuated throughout 2010-2016, but have recovered to statistically similar levels in 2016 (POA(2010) = 0.82, POA(2016) = 0.74; P = 0.33). Genetic diversity parameters (i.e., allelic richness and gene diversity) in 2016 also remained at similar levels when compared to those in 2010. Estimates of genetic structure revealed stability (FST(2009/2016) = 0.0058) with a small increase in the estimate of the inbreeding coefficient (FIS(2010) = 0.078, FIS(2016) = 0.149). The relationship among breeding lines, based on genetic distance measurement, was similar in 2008 and 2016 populations, but with increased homogeneity among lines (i.e., decreased genetic distance). This was expected based on the closed breeding system used for Russian honey bees. The successful application of the GSI assay in a commercial breeding program demonstrates the utility and stability of such technology to contribute to and monitor the genetic integrity of a breeding stock of an insect species. Published by Oxford University Press on behalf of Entomological Society of America 2017. This work is written by US Government employees and is in the public domain in the US.

Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools.

PubMed

Fuller, Zachary L; Niño, Elina L; Patch, Harland M; Bedoya-Reina, Oscar C; Baumgarten, Tracey; Muli, Elliud; Mumoki, Fiona; Ratan, Aakrosh; McGraw, John; Frazier, Maryann; Masiga, Daniel; Schuster, Stephen; Grozinger, Christina M; Miller, Webb

2015-07-10

With the development of inexpensive, high-throughput sequencing technologies, it has become feasible to examine questions related to population genetics and molecular evolution of non-model species in their ecological contexts on a genome-wide scale. Here, we employed a newly developed suite of integrated, web-based programs to examine population dynamics and signatures of selection across the genome using several well-established tests, including F ST, pN/pS, and McDonald-Kreitman. We applied these techniques to study populations of honey bees (Apis mellifera) in East Africa. In Kenya, there are several described A. mellifera subspecies, which are thought to be localized to distinct ecological regions. We performed whole genome sequencing of 11 worker honey bees from apiaries distributed throughout Kenya and identified 3.6 million putative single-nucleotide polymorphisms. The dense coverage allowed us to apply several computational procedures to study population structure and the evolutionary relationships among the populations, and to detect signs of adaptive evolution across the genome. While there is considerable gene flow among the sampled populations, there are clear distinctions between populations from the northern desert region and those from the temperate, savannah region. We identified several genes showing population genetic patterns consistent with positive selection within African bee populations, and between these populations and European A. mellifera or Asian Apis florea. These results lay the groundwork for future studies of adaptive ecological evolution in honey bees, and demonstrate the use of new, freely available web-based tools and workflows ( http://usegalaxy.org/r/kenyanbee ) that can be applied to any model system with genomic information.

Genetic diversity analysis in Malaysian giant prawns using expressed sequence tag microsatellite markers for stock improvement program.

PubMed

Atin, K H; Christianus, A; Fatin, N; Lutas, A C; Shabanimofrad, M; Subha, B

2017-08-17

The Malaysian giant prawn is among the most commonly cultured species of the genus Macrobrachium. Stocks of giant prawns from four rivers in Peninsular Malaysia have been used for aquaculture over the past 25 years, which has led to repeated harvesting, restocking, and transplantation between rivers. Consequently, a stock improvement program is now important to avoid the depletion of wild stocks and the loss of genetic diversity. However, the success of such an improvement program depends on our knowledge of the genetic variation of these base populations. The aim of the current study was to estimate genetic variation and differentiation of these riverine sources using novel expressed sequence tag-microsatellite (EST-SSR) markers, which not only are informative on genetic diversity but also provide information on immune and metabolic traits. Our findings indicated that the tested stocks have inbreeding depression due to a significant deficiency in heterozygotes, and F IS was estimated as 0.15538 to 0.31938. An F-statistics analysis suggested that the stocks are composed of one large panmictic population. Among the four locations, stocks from Johor, in the southern region of the peninsular, showed higher allelic and genetic diversity than the other stocks. To overcome inbreeding problems, the Johor population could be used as a base population in a stock improvement program by crossing to the other populations. The study demonstrated that EST-SSR markers can be incorporated in future marker assisted breeding to aid the proper management of the stocks by breeders and stakeholders in Malaysia.

Strain gage selection in loads equations using a genetic algorithm

NASA Technical Reports Server (NTRS)

1994-01-01

Traditionally, structural loads are measured using strain gages. A loads calibration test must be done before loads can be accurately measured. In one measurement method, a series of point loads is applied to the structure, and loads equations are derived via the least squares curve fitting algorithm using the strain gage responses to the applied point loads. However, many research structures are highly instrumented with strain gages, and the number and selection of gages used in a loads equation can be problematic. This paper presents an improved technique using a genetic algorithm to choose the strain gages used in the loads equations. Also presented are a comparison of the genetic algorithm performance with the current T-value technique and a variant known as the Best Step-down technique. Examples are shown using aerospace vehicle wings of high and low aspect ratio. In addition, a significant limitation in the current methods is revealed. The genetic algorithm arrived at a comparable or superior set of gages with significantly less human effort, and could be applied in instances when the current methods could not.

Breeding of Acrocomia aculeata using genetic diversity parameters and correlations to select accessions based on vegetative, phenological, and reproductive characteristics.

PubMed

Coser, S M; Motoike, S Y; Corrêa, T R; Pires, T P; Resende, M D V

2016-10-17

Macaw palm (Acrocomia aculeata) is a promising species for use in biofuel production, and establishing breeding programs is important for the development of commercial plantations. The aim of the present study was to analyze genetic diversity, verify correlations between traits, estimate genetic parameters, and select different accessions of A. aculeata in the Macaw Palm Germplasm Bank located in Universidade Federal de Viçosa, to develop a breeding program for this species. Accessions were selected based on precocity (PREC), total spathe (TS), diameter at breast height (DBH), height of the first spathe (HFS), and canopy area (CA). The traits were evaluated in 52 accessions during the 2012/2013 season and analyzed by restricted estimation maximum likelihood/best linear unbiased predictor procedures. Genetic diversity resulted in the formation of four groups by Tocher's clustering method. The correlation analysis showed it was possible to have indirect and early selection for the traits PREC and DBH. Estimated genetic parameters strengthened the genetic variability verified by cluster analysis. Narrow-sense heritability was classified as moderate (PREC, TS, and CA) to high (HFS and DBH), resulting in strong genetic control of the traits and success in obtaining genetic gains by selection. Accuracy values were classified as moderate (PREC and CA) to high (TS, HFS, and DBH), reinforcing the success of the selection process. Selection of accessions for PREC, TS, and HFS by the rank-average method permits selection gains of over 100%, emphasizing the successful use of the accessions in breeding programs and obtaining superior genotypes for commercial plantations.

Role of genetic improvement in the Short Rotation Woody Crops Program

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

Layton, P.A.; Wright, L.L.

1986-01-01

A major effort in the Short Rotation Woody Crops Program (SRWCP) is species screening and genetic improvement of selected species. Of the 125 species initially evaluated for SRIC, 20 are being seriously considered with most of emphasis on 16 hardwood species. Range-wide seed collections of 12 species were provenance tested; these include Platanus occidentalis (sycamore), Alnus glutinosa (European black alder), and Robinia pseudoacacia (black locust). Based on the results of these tests, highly productive, site-specific seed sources are being chosen for several geographic regions. Three of these species re currently being bred for increased productivity in SRIC systems. Genetic improvementmore » is viewed as a tool for increasing productivity, having anticipated gains of 40 to 50%. The techniques of somaclonal screening and genetic engineering are being evaluated for their usefulness in the SRIC improvement program. Currently, salt-tolerant Atriplex canescens (four-wing saltbush) and herbicide-resistant Populus spp. are being sought via somaclonal screening. 35 refs., 4 figs., 3 tabs.« less

Genetic Associations with Intimate Partner Violence in a Sample of Hazardous Drinking Men in Batterer Intervention Programs

PubMed Central

Stuart, Gregory L.; McGeary, John; Shorey, Ryan C.; Knopik, Valerie; Beaucage, Kayla; Temple, Jeff R.

2014-01-01

The etiology of intimate partner violence (IPV) is multifactorial. However, etiological theories of IPV have rarely included potential genetic factors. The purpose of the present study was to examine whether a cumulative genetic score (CGS) containing the MAOA and 5-HTTLPR polymorphisms was associated with IPV perpetration after accounting for the effects of alcohol problems, drug problems, age, and length of relationship. We obtained DNA from 97 men in batterer intervention programs in the state of Rhode Island. In the full sample, the CGS was significantly associated with physical and psychological aggression and injuries caused to one's partner, even after controlling for the effects of alcohol problems, drug problems, age, and length of relationship. Two of the men in the sample likely had Klinefelter's syndrome and analyses were repeated excluding these two individuals, leading to similar results. The implications of the genetics findings for the etiology and treatment of IPV among men in batter intervention programs are briefly discussed. PMID:24759925

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

PubMed

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

2016-03-01

The aim of this article is to present an updated unifying theory of the mechanisms underlying eye growth and myopia development. A series of model simulation programs were developed to illustrate the mechanism of eye growth regulation and myopia development. Two fundamental processes are presumed to govern the relationship between physiological optics and eye growth: genetically pre-programmed signaling and blur feedback. Cornea/lens is considered to have only a genetically pre-programmed component, whereas eye growth is considered to have both a genetically pre-programmed and a blur feedback component. Moreover, based on the Incremental Retinal-Defocus Theory (IRDT), the rate of change of blur size provides the direction for blur-driven regulation. The various factors affecting eye growth are shown in 5 simulations: (1 - unregulated eye growth): blur feedback is rendered ineffective, as in the case of form deprivation, so there is only genetically pre-programmed eye growth, generally resulting in myopia; (2 - regulated eye growth): blur feedback regulation demonstrates the emmetropization process, with abnormally excessive or reduced eye growth leading to myopia and hyperopia, respectively; (3 - repeated near-far viewing): simulation of large-to-small change in blur size as seen in the accommodative stimulus/response function, and via IRDT as well as nearwork-induced transient myopia (NITM), leading to the development of myopia; (4 - neurochemical bulk flow and diffusion): release of dopamine from the inner plexiform layer of the retina, and the subsequent diffusion and relay of neurochemical cascade show that a decrease in dopamine results in a reduction of proteoglycan synthesis rate, which leads to myopia; (5 - Simulink model): model of genetically pre-programmed signaling and blur feedback components that allows for different input functions to simulate experimental manipulations that result in hyperopia, emmetropia, and myopia. These model simulation programs (available upon request) can provide a useful tutorial for the general scientist and serve as a quantitative tool for researchers in eye growth and myopia. Copyright © 2016 Elsevier Ltd. All rights reserved.

From observational to dynamic genetics

PubMed Central

Haworth, Claire M. A.; Davis, Oliver S. P.

2014-01-01

Twin and family studies have shown that most traits are at least moderately heritable. But what are the implications of finding genetic influence for the design of intervention and prevention programs? For complex traits, heritability does not mean immutability, and research has shown that genetic influences can change with age, context, and in response to behavioral and drug interventions. The most significant implications for intervention will come when we move from observational genetics to investigating dynamic genetics, including genetically sensitive interventions. Future interventions should be designed to overcome genetic risk and draw upon genetic strengths by changing the environment. PMID:24478793

Animal breeding strategies can improve meat quality attributes within entire populations.

PubMed

Berry, D P; Conroy, S; Pabiou, T; Cromie, A R

2017-10-01

The contribution of animal breeding to changes in animal performance is well documented across a range of species. Once genetic variation in a trait exists, then breeding to improve the characteristics of that trait is possible, if so desired. Considerable genetic variation exists in a range of meat quality attributes across a range of species. The genetic variation that exists for meat quality is as large as observed for most performance traits; thus, within a well-structured breeding program, rapid genetic gain for meat quality could be possible. The rate of genetic gain can be augmented through the integration of DNA-based technologies into the breeding program; such DNA-based technologies should, however, be based on thousands of DNA markers dispersed across the entire genome. Genetic and genomic technologies can also have beneficial impact outside the farm gate as a tool to segregate carcasses or meat cuts based on expected meat quality features. Copyright © 2017 Elsevier Ltd. All rights reserved.

The study of relatedness and genetic diversity in cranes

USGS Publications Warehouse

Gee, G.F.; Dessauer, H.C.; Longmire, J.; Briles, W.E.; Simon, R.C.; Wood, Don A.

1992-01-01

The U.S. Fish and Wildlife Service (Service) is responsible for recovery of endangered species in the wild and, when necessary, maintenance in captivity. These programs provide an immediate measure of insurance against extinction. A prerequisite inherent in all of these programs is the preservation of enough genetic diversity to maintain a viable population and to maintain the capacity of the population to respond to change. Measures of genetic diversity examine polymorphic genes that are not influenced by selection pressures. Examples of these techniques and those used to determine relatedness are discussed. Studies of genetic diversity, electrophoresis of blood proteins, relatedness, blood typing, and restriction fragment length polymorphisms which are being used by the Patuxent Wildlife Research Center are discussed in detail.

Genetic algorithms for adaptive real-time control in space systems

NASA Technical Reports Server (NTRS)

Vanderzijp, J.; Choudry, A.

1988-01-01

Genetic Algorithms that are used for learning as one way to control the combinational explosion associated with the generation of new rules are discussed. The Genetic Algorithm approach tends to work best when it can be applied to a domain independent knowledge representation. Applications to real time control in space systems are discussed.

Genetics/Silviculture Workshop Proceedings; Wenatchee, WA; August 27-31, 1990

Treesearch

Richard G. Miller; Dennis D. Murphy

1990-01-01

The primary objective of the 1990 Genetics/Silviculture Workshop was to review and discuss the virtues, concerns, and opportunities for applying the five regeneration harvest methods and their variations in forest management. The first two papers discuss population dynamics and the importance of understanding genetic variation. These are followed by the moderator'...

Standards of Practice: Applying Genetics and Genomics Resources to Oncology
.

PubMed

Kerber, Alice S; Ledbetter, Nancy J

2017-04-01

Knowledge about genetics and genomics and its application to oncology care is rapidly expanding and evolving. As a result, oncology nurses at all levels must develop and maintain their knowledge of genetics and genomics, as well as be aware of resources to guide practice. This article focuses on implementation of the standards described in the updated Genetics/Genomics Nursing: Scope and Standards of Practice by the basic practitioner.
.

[Application of case-based method in genetics and eugenics teaching].

PubMed

Li, Ya-Xuan; Zhao, Xin; Zhang, Fei-Xiong; Hu, Ying-Kao; Yan, Yue-Ming; Cai, Min-Hua; Li, Xiao-Hui

2012-05-01

Genetics and Eugenics is a cross-discipline between genetics and eugenics. It is a common curriculum in many Chinese universities. In order to increase the learning interest, we introduced case teaching method and got a better teaching effect. Based on our teaching practices, we summarized some experiences about this subject. In this article, the main problem of case-based method applied in Genetics and Eugenics teaching was discussed.

Comparison of the effectiveness of ISJ and SSR markers and detection of outlier loci in conservation genetics of Pulsatilla patens populations

PubMed Central

Szczecińska, Monika

2016-01-01

Background Research into the protection of rare and endangered plant species involves genetic analyses to determine their genetic variation and genetic structure. Various categories of genetic markers are used for this purpose. Microsatellites, also known as simple sequence repeats (SSR), are the most popular category of markers in population genetics research. In most cases, microsatellites account for a large part of the noncoding DNA and exert a neutral effect on the genome. Neutrality is a desirable feature in evaluations of genetic differences between populations, but it does not support analyses of a population’s ability to adapt to a given environment or its evolutionary potential. Despite the numerous advantages of microsatellites, non-neutral markers may supply important information in conservation genetics research. They are used to evaluate adaptation to specific environmental conditions and a population’s adaptive potential. The aim of this study was to compare the level of genetic variation in Pulsatilla patens populations revealed by neutral SSR markers and putatively adaptive ISJ markers (intron-exon splice junction). Methods The experiment was conducted on 14 Polish populations of P. patens and three P. patens populations from the nearby region of Vitebsk in Belarus. A total of 345 individuals were examined. Analyses were performed with the use of eight SSR primers specific to P. patens and three ISJ primers. Results SSR markers revealed a higher level of genetic variation than ISJ markers (He = 0.609, He = 0.145, respectively). An analysis of molecular variance (AMOVA) revealed that, the overall genetic diversity between the analyzed populations defined by parameters FST and ΦPT for SSR (20%) and ΦPT for ISJ (21%) markers was similar. Analysis conducted in the Structure program divided analyzed populations into two groups (SSR loci) and three groups (ISJ markers). Mantel test revealed correlations between the geographic distance and genetic diversity of Polish populations of P. patens for ISJ markers, but not for SSR markers. Conclusions The results of the present study suggest that ISJ markers can complement the analyses based on SSRs. However, neutral and adaptive markers should not be alternatively applied. Neutral microsatellite markers cannot depict the full range of genetic variation in a population because they do not enable to analyze functional variation. Although ISJ markers are less polymorphic, they can contribute to the reliability of analyses based on SSRs. PMID:27833793

45 CFR 148.102 - Scope, applicability, and effective dates.

Code of Federal Regulations, 2013 CFR

2013-10-01

... against discrimination based on genetic information apply to all issuers of individual health insurance... newborns), and § 148.180 (prohibition of health discrimination based on genetic information) of this part...

45 CFR 148.102 - Scope, applicability, and effective dates.

Code of Federal Regulations, 2012 CFR

2012-10-01

... against discrimination based on genetic information apply to all issuers of individual health insurance... newborns), and § 148.180 (prohibition of health discrimination based on genetic information) of this part...

An optimized high quality male DNA extraction from spermatophores in open thelycum shrimp species.

PubMed

Planella, Laia; Heras, Sandra; Vera, Manuel; García-Marín, José-Luis; Roldán, María Inés

2017-09-01

The crucial step of most of the current genetic studies is the extraction of DNA of sufficient quantity and quality. Several genomic DNA isolation methods have been described to successfully obtain male DNA from shrimp species. However, all current protocols require invasive handling methods with males for DNA isolation. Using Aristeus antennatus as a model we tested a reliable non-invasive differential DNA extraction method to male DNA isolation from spermatophores attached to female thelycum. The present protocol provides high quality and quantity DNA for polymerase chain reaction amplification and male genotyping. This new approach could be useful to experimental shrimp culture to select sires with relevant genetic patterns for selective breeding programs. More importantly, it can be applied to identify the mating pairs and male structure in wild populations of species as A. antennatus, where males are often difficult to capture. Our method could be also valuable for biological studies on other spermatophore-using species, such as myriapods, arachnids and insects. © 2016 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Optimization of groundwater artificial recharge systems using a genetic algorithm: a case study in Beijing, China

NASA Astrophysics Data System (ADS)

Hao, Qichen; Shao, Jingli; Cui, Yali; Zhang, Qiulan; Huang, Linxian

2018-05-01

An optimization approach is used for the operation of groundwater artificial recharge systems in an alluvial fan in Beijing, China. The optimization model incorporates a transient groundwater flow model, which allows for simulation of the groundwater response to artificial recharge. The facilities' operation with regard to recharge rates is formulated as a nonlinear programming problem to maximize the volume of surface water recharged into the aquifers under specific constraints. This optimization problem is solved by the parallel genetic algorithm (PGA) based on OpenMP, which could substantially reduce the computation time. To solve the PGA with constraints, the multiplicative penalty method is applied. In addition, the facilities' locations are implicitly determined on the basis of the results of the recharge-rate optimizations. Two scenarios are optimized and the optimal results indicate that the amount of water recharged into the aquifers will increase without exceeding the upper limits of the groundwater levels. Optimal operation of this artificial recharge system can also contribute to the more effective recovery of the groundwater storage capacity.

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.

Model-Based Linkage Analysis of a Quantitative Trait.

PubMed

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

2017-01-01

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

Conserving and managing the trees of the future: genetic resources for Pacific Northwest forests.

Treesearch

Sally Duncan

2003-01-01

Genetic resource management has historically called for altering the genetic structure of plant populations through selection for traits of interest such as rapid growth. Although this is still a principal component of tree breeding programs in the Pacific Northwest, managing genetic resources now also brings a clear focus on retaining a broad diversity within and...

Nutritional and Genetic Determinants of Early Puberty

DTIC Science & Technology

2007-06-01

AD_________________ Award Number: W81XWH-04-1-0575 TITLE: Nutritional and Genetic Determinants...CONTRACT NUMBER Nutritional and Genetic Determinants of Early Puberty 5b. GRANT NUMBER W81XWH-04-1-0575 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR...later in life. Nutritional factors during childhood and puberty, and inherited genetic factors are suspected to interact in modulating these early

Analysis of genetic diversity of rapeseed genetic resources in Japan and core collection construction

PubMed Central

Chen, Ruikun; Hara, Takashi; Ohsawa, Ryo; Yoshioka, Yosuke

2017-01-01

Diversity analysis of rapeseed accessions preserved in the Japanese Genebank can provide valuable information for breeding programs. In this study, 582 accessions were genotyped with 30 SSR markers covering all 19 rapeseed chromosomes. These markers amplified 311 alleles (10.37 alleles per marker; range, 3–39). The genetic diversity of Japanese accessions was lower than that of overseas accessions. Analysis of molecular variance indicated significant genetic differentiation between Japanese and overseas accessions. Small but significant differences were found among geographical groups in Japan, and genetic differentiation tended to increase with geographical distance. STRUCTURE analysis indicated the presence of two main genetic clusters in the NARO rapeseed collection. With the membership probabilities threshold, 227 accessions mostly originating from overseas were assigned to one subgroup, and 276 accessions mostly originating from Japan were assigned to the other subgroup. The remaining 79 accessions are assigned to admixed group. The core collection constructed comprises 96 accessions of diverse origin. It represents the whole collection well and thus it may be useful for rapeseed genetic research and breeding programs. The core collection improves the efficiency of management, evaluation, and utilization of genetic resources. PMID:28744177

Using Multi-Objective Genetic Programming to Synthesize Stochastic Processes

NASA Astrophysics Data System (ADS)

Ross, Brian; Imada, Janine

Genetic programming is used to automatically construct stochastic processes written in the stochastic π-calculus. Grammar-guided genetic programming constrains search to useful process algebra structures. The time-series behaviour of a target process is denoted with a suitable selection of statistical feature tests. Feature tests can permit complex process behaviours to be effectively evaluated. However, they must be selected with care, in order to accurately characterize the desired process behaviour. Multi-objective evaluation is shown to be appropriate for this application, since it permits heterogeneous statistical feature tests to reside as independent objectives. Multiple undominated solutions can be saved and evaluated after a run, for determination of those that are most appropriate. Since there can be a vast number of candidate solutions, however, strategies for filtering and analyzing this set are required.

34 CFR 400.2 - What programs are governed by these regulations?

Code of Federal Regulations, 2010 CFR

2010-07-01

... VOCATIONAL AND ADULT EDUCATION, DEPARTMENT OF EDUCATION VOCATIONAL AND APPLIED TECHNOLOGY EDUCATION PROGRAMS... apply to the Vocational and Applied Technology Education Programs as follows: (a) State-administered programs. (1) State Vocational and Applied Technology Education Program (34 CFR part 403). (2) State...

Acceleration of genetic gain in cattle by reduction of generation interval.

PubMed

Kasinathan, Poothappillai; Wei, Hong; Xiang, Tianhao; Molina, Jose A; Metzger, John; Broek, Diane; Kasinathan, Sivakanthan; Faber, David C; Allan, Mark F

2015-03-02

Genomic selection (GS) approaches, in combination with reproductive technologies, are revolutionizing the design and implementation of breeding programs in livestock species, particularly in cattle. GS leverages genomic readouts to provide estimates of breeding value early in the life of animals. However, the capacity of these approaches for improving genetic gain in breeding programs is limited by generation interval, the average age of an animal when replacement progeny are born. Here, we present a cost-effective approach that combines GS with reproductive technologies to reduce generation interval by rapidly producing high genetic merit calves.

Accelerating global optimization of aerodynamic shapes using a new surrogate-assisted parallel genetic algorithm

NASA Astrophysics Data System (ADS)

Ebrahimi, Mehdi; Jahangirian, Alireza

2017-12-01

An efficient strategy is presented for global shape optimization of wing sections with a parallel genetic algorithm. Several computational techniques are applied to increase the convergence rate and the efficiency of the method. A variable fidelity computational evaluation method is applied in which the expensive Navier-Stokes flow solver is complemented by an inexpensive multi-layer perceptron neural network for the objective function evaluations. A population dispersion method that consists of two phases, of exploration and refinement, is developed to improve the convergence rate and the robustness of the genetic algorithm. Owing to the nature of the optimization problem, a parallel framework based on the master/slave approach is used. The outcomes indicate that the method is able to find the global optimum with significantly lower computational time in comparison to the conventional genetic algorithm.

Exotic germplasm introgression effect on agronomic and fiber properties of upland cotton

USDA-ARS?s Scientific Manuscript database

Genetic diversity is an important breeder’s tool for selection and improvement in crop cultivar development. Any successful breeding program depends on selecting superior quality parents. Lack of genetic diversity limits the potential of the breeder in selecting elite parents. Genetic uniformity pre...

World Collection of Sugarcane and Related Grasses: Utilizing a Vast Genetic Resource

USDA-ARS?s Scientific Manuscript database

Sugarcane (Saccharum spp.) cultivar improvement programs have not yet systematically utilized most of the genetic sources of yield potential and resistance to biotic and abiotic stresses that may exist in the Saccharum germplasm. Two collections of genetic material potentially useful to sugarcane br...

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...

Developing a Model of Advanced Training to Promote Career Advancement for Certified Genetic Counselors: An Investigation of Expanded Skills, Advanced Training Paths, and Professional Opportunities.

PubMed

Baty, Bonnie J; Trepanier, Angela; Bennett, Robin L; Davis, Claire; Erby, Lori; Hippman, Catriona; Lerner, Barbara; Matthews, Anne; Myers, Melanie F; Robbins, Carol B; Singletary, Claire N

2016-08-01

There are currently multiple paths through which genetic counselors can acquire advanced knowledge and skills. However, outside of continuing education opportunities, there are few formal training programs designed specifically for the advanced training of genetic counselors. In the genetic counseling profession, there is currently considerable debate about the paths that should be available to attain advanced skills, as well as the skills that might be needed for practice in the future. The Association of Genetic Counseling Program Directors (AGCPD) convened a national committee, the Committee on Advanced Training for Certified Genetic Counselors (CATCGC), to investigate varied paths to post-master's training and career development. The committee began its work by developing three related grids that view career advancement from the viewpoints of the skills needed to advance (skills), ways to obtain these skills (paths), and existing genetic counselor positions that offer career change or advancement (positions). Here we describe previous work related to genetic counselor career advancement, the charge of the CATCGC, our preliminary work in developing a model through which to view genetic counselor advanced training and career advancement opportunities, and our next steps in further developing and disseminating the model.

Evaluating a hybrid web-based basic genetics course for health professionals.

PubMed

Wallen, Gwenyth R; Cusack, Georgie; Parada, Suzan; Miller-Davis, Claiborne; Cartledge, Tannia; Yates, Jan

2011-08-01

Health professionals, particularly nurses, continue to struggle with the expanding role of genetics information in the care of their patients. This paper describes an evaluation study of the effectiveness of a hybrid basic genetics course for healthcare professionals combining web-based learning with traditional face-to-face instructional techniques. A multidisciplinary group from the National Institutes of Health (NIH) created "Basic Genetics Education for Healthcare Providers" (BGEHCP). This program combined 7 web-based self-education modules with monthly traditional face-to-face lectures by genetics experts. The course was pilot tested by 186 healthcare providers from various disciplines with 69% (n=129) of the class registrants enrolling in a pre-post evaluation trial. Outcome measures included critical thinking knowledge items and a Web-based Learning Environment Inventory (WEBLEI). Results indicated a significant (p<0.001) change in knowledge scores. WEBLEI scores indicated program effectiveness particularly in the area of convenience, access and the course structure and design. Although significant increases in overall knowledge scores were achieved, scores in content areas surrounding genetic risk identification and ethical issues regarding genetic testing reflected continued gaps in knowledge. Web-based genetics education may help overcome genetics knowledge deficits by providing access for health professionals with diverse schedules in a variety of national and international settings. Published by Elsevier Ltd.

Exploiting genotypic variation in plant nutrient accumulation to alleviate micronutrient deficiency in populations.

PubMed

Genc, Yusuf; Humphries, Julia M; Lyons, Graham H; Graham, Robin D

2005-01-01

More than 2 billion people consume diets that are less diverse than 30 years ago, leading to deficiencies in micronutrients, especially iron (Fe), zinc (Zn), selenium (Se), iodine (I), and also vitamin A. A strategy that exploits genetic variability to breed staple crops with enhanced ability to fortify themselves with micronutrients (genetic biofortification) offers a sustainable, cost-effective alternative to conventional supplementation and fortification programs. This is more likely to reach those most in need, has the added advantages of requiring no change in current consumer behaviour to be effective, and is transportable to a range of countries. Research by our group, along with studies elsewhere, has demonstrated conclusively that substantial genotypic variation exists in nutrient (e.g. Fe, Zn) and nutrient promotor (e.g. inulin) concentrations in wheat and other staple foods. A rapid screening technique has been developed for lutein content of wheat and triticale, and also for pro-vitamin A carotenoids in bread wheat. This will allow cost-effective screening of a wider range of genotypes that may reveal greater genotypic variation in these traits. Moreover, deeper understanding of genetic control mechanisms and development of molecular markers will facilitate breeding programs. We suggest that a combined strategy utilising plant breeding for higher micronutrient density; maximising the effects of nutritional promoters (e.g. inulin, vitamin C) by promoting favourable dietary combinations, as well as by plant breeding; and agronomic biofortification (e.g. adding iodide or iodate as fertiliser; applying selenate to cereal crops by spraying or adding to fertiliser) is likely to be the most effective way to improve the nutrition of populations. Furthermore, the importance of detecting and exploiting beneficial interactions is illustrated by our discovery that in Fe-deficient chickens, circulating Fe concentrations can be restored to normal levels by lutein supplementation. Further bioavailability/bioefficacy trials with animals and humans are needed, using varying dietary concentrations of Fe, Zn, carotenoids, inulin, Se and I to elucidate other important interactions in order to optimise delivery in biofortification programs.

Including nonadditive genetic effects in mating programs to maximize dairy farm profitability.

PubMed

Aliloo, H; Pryce, J E; González-Recio, O; Cocks, B G; Goddard, M E; Hayes, B J

2017-02-01

We compared the outcome of mating programs based on different evaluation models that included nonadditive genetic effects (dominance and heterozygosity) in addition to additive effects. The additive and dominance marker effects and the values of regression on average heterozygosity were estimated using 632,003 single nucleotide polymorphisms from 7,902 and 7,510 Holstein cows with calving interval and production (milk, fat, and protein yields) records, respectively. Expected progeny values were computed based on the estimated genetic effects and genotype probabilities of hypothetical progeny from matings between the available genotyped cows and the top 50 young genomic bulls. An index combining the traits based on their economic values was developed and used to evaluate the performance of different mating scenarios in terms of dollar profit. We observed that mating programs with nonadditive genetic effects performed better than a model with only additive effects. Mating programs with dominance and heterozygosity effects increased milk, fat, and protein yields by up to 38, 1.57, and 1.21 kg, respectively. The inclusion of dominance and heterozygosity effects decreased calving interval by up to 0.70 d compared with random mating. The average reduction in progeny inbreeding by the inclusion of nonadditive genetic effects in matings compared with random mating was between 0.25 to 1.57 and 0.64 to 1.57 percentage points for calving interval and production traits, respectively. The reduction in inbreeding was accompanied by an average of A$8.42 (Australian dollars) more profit per mating for a model with additive, dominance, and heterozygosity effects compared with random mating. Mate allocations that benefit from nonadditive genetic effects can improve progeny performance only in the generation where it is being implemented, and the gain from specific combining abilities cannot be accumulated over generations. Continuous updating of genomic predictions and mate allocation programs are required to benefit from nonadditive genetic effects in the long term. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Form Follows Function: A Model for Clinical Supervision of Genetic Counseling Students.

PubMed

Wherley, Colleen; Veach, Patricia McCarthy; Martyr, Meredith A; LeRoy, Bonnie S

2015-10-01

Supervision plays a vital role in genetic counselor training, yet models describing genetic counseling supervision processes and outcomes are lacking. This paper describes a proposed supervision model intended to provide a framework to promote comprehensive and consistent clinical supervision training for genetic counseling students. Based on the principle "form follows function," the model reflects and reinforces McCarthy Veach et al.'s empirically derived model of genetic counseling practice - the "Reciprocal Engagement Model" (REM). The REM consists of mutually interactive educational, relational, and psychosocial components. The Reciprocal Engagement Model of Supervision (REM-S) has similar components and corresponding tenets, goals, and outcomes. The 5 REM-S tenets are: Learning and applying genetic information are key; Relationship is integral to genetic counseling supervision; Student autonomy must be supported; Students are capable; and Student emotions matter. The REM-S outcomes are: Student understands and applies information to independently provide effective services, develop professionally, and engage in self-reflective practice. The 16 REM-S goals are informed by the REM of genetic counseling practice and supported by prior literature. A review of models in medicine and psychology confirms the REM-S contains supervision elements common in healthcare fields, while remaining unique to genetic counseling. The REM-S shows promise for enhancing genetic counselor supervision training and practice and for promoting research on clinical supervision. The REM-S is presented in detail along with specific examples and training and research suggestions.

Genetic evaluation of a Great Lakes lake trout hatchery program

USGS Publications Warehouse

Page, K.S.; Scribner, K.T.; Bast, D.; Holey, M.E.; Burnham-Curtis, M. K.

2005-01-01

Efforts over several decades to restore lake trout Salvelinus namaycush in U.S. waters of the upper Great Lakes have emphasized the stocking of juveniles from each of six hatchery broodstocks. Retention of genetic diversity across all offspring life history stages throughout the hatchery system has been an important component of the restoration hatchery and stocking program. Different stages of the lake trout hatchery program were examined to determine how effective hatchery practices have been in minimizing the loss of genetic diversity in broodstock adults and in progeny stocked. Microsatellite loci were used to estimate allele frequencies, measures of genetic diversity, and relatedness for wild source populations, hatchery broodstocks, and juveniles. We also estimated the effective number of breeders for each broodstock. Hatchery records were used to track destinations of fertilized eggs from all spawning dates to determine whether adult contributions to stocking programs were proportional to reproductive effort. Overall, management goals of maintaining genetic diversity were met across all stages of the hatchery program; however, we identified key areas where changes in mating regimes and in the distribution of fertilized gametes and juveniles could be improved. Estimates of effective breeding population size (Nb) were 9-41% of the total number of adults spawned. Low estimates of Nb were primarily attributed to spawning practices, including the pooling of gametes from multiple males and females and the reuse of males. Nonrandom selection and distribution of fertilized eggs before stocking accentuated declines in effective breeding population size and increased levels of relatedness of juveniles distributed to different rearing facilities and stocking locales. Adoption of guidelines that decrease adult reproductive variance and promote more equitable reproductive contributions of broodstock adults to juveniles would further enhance management goals of maintaining genetic diversity and minimize probabilities of consanguineous matings among stocked individuals when sexually mature. ?? Copyright by the American Fisheries Society 2005.

FORMATOMATIC: a program for converting diploid allelic data between common formats for population genetic analysis.

PubMed

Manoukis, Nicholas C

2007-07-01

There has been a great increase in both the number of population genetic analysis programs and the size of data sets being studied with them. Since the file formats required by the most popular and useful programs are variable, automated reformatting or conversion between them is desirable. formatomatic is an easy to use program that can read allelic data files in genepop, raw (csv) or convert formats and create data files in nine formats: raw (csv), arlequin, genepop, immanc/bayesass +, migrate, newhybrids, msvar, baps and structure. Use of formatomatic should greatly reduce time spent reformatting data sets and avoid unnecessary errors.

Learning genetic inquiry through the use, revision, and justification of explanatory models

NASA Astrophysics Data System (ADS)

Cartier, Jennifer Lorraine

Central to the process of inquiry in science is the construction and assessment of models that can be used to explain (and in some cases, predict) natural phenomena. This dissertation is a qualitative study of student learning in a high school biology course that was designed to give students opportunities to learn about genetic inquiry in part by providing them with authentic experiences doing inquiry in the discipline. With the aid of a computer program that generates populations of "fruit flies", the students in this class worked in groups structured like scientific communities to build, revise, and defend explanatory models for various inheritance phenomena. Analysis of the ways in which the first cohort of students assessed their inheritance models revealed that all students assessed models based upon empirical fit (data/model match). However, in contrast to the practice of scientists and despite explicit instruction, students did not consistently apply conceptual assessment criteria to their models. That is, they didn't seek consistency between underlying concepts or processes in their models and those of other important genetic models, such as meiosis. This is perhaps in part because they lacked an understanding of models as conceptual rather than physical entities. Subsequently, the genetics curriculum was altered in order to create more opportunities for students to address epistemological issues associated with model assessment throughout the course. The second cohort of students' understanding of models changed over the nine-week period: initially the majority of students equated scientific models with "proof" (generally physical) of "theories"; at the end of the course, most students demonstrated understanding of the conceptual nature of scientific models and the need to justify such knowledge according to both its empirical utility and conceptual consistency. Through model construction and assessment (i.e. scientific inquiry), students were able to come to a rich understanding of both the central concepts of transmission genetics and important epistemological aspects of genetic practice.

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.

An analysis of indirect genetic effects on adult body weight of the Pacific white shrimp Litopenaeus vannamei at low rearing density.

PubMed

Luan, Sheng; Luo, Kun; Chai, Zhan; Cao, Baoxiang; Meng, Xianhong; Lu, Xia; Liu, Ning; Xu, Shengyu; Kong, Jie

2015-12-14

Our aim was to estimate the genetic parameters for the direct genetic effect (DGE) and indirect genetic effects (IGE) on adult body weight in the Pacific white shrimp. IGE is the heritable effect of an individual on the trait values of its group mates. To examine IGE on body weight, 4725 shrimp from 105 tagged families were tested in multiple small test groups (MSTG). Each family was separated into three groups (15 shrimp per group) that were randomly assigned to 105 concrete tanks with shrimp from two other families. To estimate breeding values, one large test group (OLTG) in a 300 m(2) circular concrete tank was used for the communal rearing of 8398 individuals from 105 families. Body weight was measured after a growth-test period of more than 200 days. Variance components for body weight in the MSTG programs were estimated using an animal model excluding or including IGE whereas variance components in the OLTG programs were estimated using a conventional animal model that included only DGE. The correlation of DGE between MSTG and OLTG programs was estimated by a two-trait animal model that included or excluded IGE. Heritability estimates for body weight from the conventional animal model in MSTG and OLTG programs were 0.26 ± 0.13 and 0.40 ± 0.06, respectively. The log likelihood ratio test revealed significant IGE on body weight. Total heritable variance was the sum of direct genetic variance (43.5%), direct-indirect genetic covariance (2.1%), and indirect genetic variance (54.4%). It represented 73% of the phenotypic variance and was more than two-fold greater than that (32%) obtained by using a classical heritability model for body weight. Correlations of DGE on body weight between MSTG and OLTG programs were intermediate regardless of whether IGE were included or not in the model. Our results suggest that social interactions contributed to a large part of the heritable variation in body weight. Small and non-significant direct-indirect genetic correlations implied that neutral or slightly cooperative heritable interactions, rather than competition, were dominant in this population but this may be due to the low rearing density.

Myrciaria dubia, an Amazonian fruit: population structure and its implications for germplasm conservation and genetic improvement.

PubMed

Nunes, C F; Setotaw, T A; Pasqual, M; Chagas, E A; Santos, E G; Santos, D N; Lima, C G B; Cançado, G M A

2017-03-22

Myrciaria dubia (camu-camu) is an Amazon tree that produces a tart fruit with high vitamin C content. It is probably the fruit with the highest vitamin C content among all Brazilian fruit crops and it can be used to supplement daily vitamin C dose. This property has attracted the attention of consumers and, consequently, encouraged fruit farmers to produce it. In order to identify and select potential accessions for commercial exploitation and breeding programs, M. dubia has received considerable research attention. The identification and characterization of genetic diversity, as well as identification of the population structure of accessions preserved in germplasm banks are fundamental for the success of any breeding program. The objective of this study was to evaluate the genetic variability of 10 M. dubia populations obtained from the shores of Reis Lake, located in the municipality of Caracaraí, Roraima, Brazil. Fourteen polymorphic inter simple sequence repeat (ISSR) markers were used to study the population genetic diversity, which resulted in 108 identified alleles. Among the 14 primers, GCV, UBC810, and UBC827 produced the highest number of alleles. The study illustrated the suitability and efficiency of ISSR markers to study the genetic diversity of M. dubia accessions. We also revealed the existence of high genetic variability among both accessions and populations that can be exploited in future breeding programs and conservation activities of this species.

Knowledge Discovery in Variant Databases Using Inductive Logic Programming

PubMed Central

Nguyen, Hoan; Luu, Tien-Dao; Poch, Olivier; Thompson, Julie D.

2013-01-01

Understanding the effects of genetic variation on the phenotype of an individual is a major goal of biomedical research, especially for the development of diagnostics and effective therapeutic solutions. In this work, we describe the use of a recent knowledge discovery from database (KDD) approach using inductive logic programming (ILP) to automatically extract knowledge about human monogenic diseases. We extracted background knowledge from MSV3d, a database of all human missense variants mapped to 3D protein structure. In this study, we identified 8,117 mutations in 805 proteins with known three-dimensional structures that were known to be involved in human monogenic disease. Our results help to improve our understanding of the relationships between structural, functional or evolutionary features and deleterious mutations. Our inferred rules can also be applied to predict the impact of any single amino acid replacement on the function of a protein. The interpretable rules are available at http://decrypthon.igbmc.fr/kd4v/. PMID:23589683

Knowledge discovery in variant databases using inductive logic programming.

PubMed

Nguyen, Hoan; Luu, Tien-Dao; Poch, Olivier; Thompson, Julie D

2013-01-01

Understanding the effects of genetic variation on the phenotype of an individual is a major goal of biomedical research, especially for the development of diagnostics and effective therapeutic solutions. In this work, we describe the use of a recent knowledge discovery from database (KDD) approach using inductive logic programming (ILP) to automatically extract knowledge about human monogenic diseases. We extracted background knowledge from MSV3d, a database of all human missense variants mapped to 3D protein structure. In this study, we identified 8,117 mutations in 805 proteins with known three-dimensional structures that were known to be involved in human monogenic disease. Our results help to improve our understanding of the relationships between structural, functional or evolutionary features and deleterious mutations. Our inferred rules can also be applied to predict the impact of any single amino acid replacement on the function of a protein. The interpretable rules are available at http://decrypthon.igbmc.fr/kd4v/.

Species management benchmarking: outcomes over outputs in a changing operating environment.

PubMed

Hogg, Carolyn J; Hibbard, Chris; Ford, Claire; Embury, Amanda

2013-03-01

Species management has been utilized by the zoo and aquarium industry, since the mid-1990s, to ensure the ongoing genetic and demographic viability of populations, which can be difficult to maintain in the ever-changing operating environments of zoos. In 2009, the Zoo and Aquarium Association Australasia reviewed their species management services, focusing on addressing issues that had arisen as a result of the managed programs maturing and operating environments evolving. In summary, the project examined resourcing, policies, processes, and species to be managed. As a result, a benchmarking tool was developed (Health Check Report, HCR), which evaluated the programs against a set of broad criteria. A comparison of managed programs (n = 98), between 2008 and 2011, was undertaken to ascertain the tool's effectiveness. There was a marked decrease in programs that were designated as weak (37 down to 13); and an increase in excellent programs (24 up to 49) between the 2 years. Further, there were significant improvements in the administration benchmarking area (submission of reports, captive management plan development) across a number of taxon advisory groups. This HCR comparison showed that a benchmarking tool enables a program's performance to be quickly assessed and any remedial measures applied. The increases observed in program health were mainly due to increased management goals being attained. The HCR will be an ongoing program, as the management of the programs increases and goals are achieved, criteria will be refined to better highlight ongoing issues and ways in which these can be resolved. © 2012 Wiley Periodicals, Inc.

A Road Map for 21st Century Genetic Restoration: Gene Pool Enrichment of the Black-Footed Ferret.

PubMed

Wisely, Samantha M; Ryder, Oliver A; Santymire, Rachel M; Engelhardt, John F; Novak, Ben J

2015-01-01

Interspecies somatic cell nuclear transfer (iSCNT) could benefit recovery programs of critically endangered species but must be weighed with the risks of failure. To weigh the risks and benefits, a decision-making process that evaluates progress is needed. Experiments that evaluate the efficiency and efficacy of blastocyst, fetal, and post-parturition development are necessary to determine the success or failure or species-specific iSCNT programs. Here, we use the black-footed ferret (Mustela nigripes) as a case study for evaluating this emerging biomedical technology as a tool for genetic restoration. The black-footed ferret has depleted genetic variation yet genome resource banks contain genetic material of individuals not currently represented in the extant lineage. Thus, genetic restoration of the species is in theory possible and could help reduce the persistent erosion of genetic diversity from drift. Extensive genetic, genomic, and reproductive science tools have previously been developed in black-footed ferrets and would aid in the process of developing an iSCNT protocol for this species. Nonetheless, developing reproductive cloning will require years of experiments and a coordinated effort among recovery partners. The information gained from a well-planned research effort with the goal of genetic restoration via reproductive cloning could establish a 21st century model for evaluating and implementing conservation breeding that would be applicable to other genetically impoverished species. © The American Genetic Association. 2015.

Genetics Reasoning with Multiple External Representations.

ERIC Educational Resources Information Center

Tsui, Chi-Yan; Treagust, David F.

2003-01-01

Explores a case study of a class of 10th grade students whose learning of genetics involved activities using BioLogica, a computer program that features multiple external representations (MERs). Findings indicate that the MERs in BioLogica contributed to students' development of genetics reasoning by engendering their motivation and interest but…

77 FR 7172 - Sequoyah National Wildlife Refuge, Sequoyah, Muskogee, and Haskell Counties, OK; Comprehensive...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-10

.... Scoping for the environmental assessment (EA) on use of specified genetically modified crops in... of genetically modified crops in association with the cooperative farming program was released on... assessment of using specified genetically modified crops into the CCP and determined that an environmental...

Germplasm Release: Tissue Culture-Derived Curly Top-Resistant Genetic Stock

USDA-ARS?s Scientific Manuscript database

The USDA-ARS sugarbeet research program at Kimberly is focused on discovering novel genes for resistance to beet curly top and other economically important diseases. It is vital in genetics research to develop uniform breeding lines and genetic stocks to study inheritance, gene transfer (through co...

Exposing college students to exercise: the training interventions and genetics of exercise response (TIGER) study

USDA-ARS?s Scientific Manuscript database

The Training Interventions and Genetics of Exercise Response (TIGER) study is an exercise program designed to introduce sedentary college students to regular physical activity and to identify genetic factors that influence response to exercise. A multiracial/ethnic cohort (N = 1,567; 39% male), age ...

Tracking the genetic stability of a honeybee breeding program with genetic markers

USDA-ARS?s Scientific Manuscript database

A genetic stock identification (GSI) assay was developed in 2008 to distinguish Russian honey bees from other honey bee stocks that are commercially produced in the United States. Probability of assignment (POA) values have been collected and maintained since the stock release in 2008 to the Russian...

Research at the Institute of Forest Genetics, Rhinelander, Wisconsin.

Treesearch

Richard M. Jeffers

1971-01-01

Reports research at the Forest Genetics Institute in Rhinelander, Wisconsin, since its beginning in 1957. Describes the physical plant, study objectives, and work program. The latter includes studies of seed source, inheritance in white spruce, disease and insect resistance, interspecific hybridization, radiation genetics and radiobiology, vegetative propagation,...

ECUT (Energy Conversion and Utilization Technologies) program: Biocatalysis project

NASA Technical Reports Server (NTRS)

Baresi, Larry

1989-01-01

The Annual Report presents the fiscal year (FY) 1988 research activities and accomplishments, for the Biocatalysis Project of the U.S. Department of Energy, Energy Conversion and Utilization Technologies (ECUT) Division. The ECUT Biocatalysis Project is managed by the Jet Propulsion Laboratory, California Institute of Technology. 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: (1) The Molecular Modeling and Applied Genetics work element includes research on modeling of biological systems, developing rigorous methods for the prediction of three-dimensional (tertiary) protein structure from the amino acid sequence (primary structure) for designing new biocatalysis, defining kinetic models of biocatalyst reactivity, and developing genetically engineered solutions to the generic technical barriers that preclude widespread application of biocatalysis. (2) The Bioprocess Engineering work element supports efforts in novel bioreactor concepts that are likely to lead to substantially higher levels of reactor productivity, product yields and lower separation energetics. Results of work within this work element will be used to establish the technical feasibility of critical bioprocess monitoring and control subsystems. (3) The Bioprocess Design and Assessment work element attempts to develop procedures (via user-friendly computer software) for assessing the energy-economics of biocatalyzed chemical production processes, and initiation of technology transfer for advanced bioprocesses.

ECUT (Energy Conversion and Utilization Technologies) program: Biocatalysis project

NASA Astrophysics Data System (ADS)

Baresi, Larry

1989-03-01

The Annual Report presents the fiscal year (FY) 1988 research activities and accomplishments, for the Biocatalysis Project of the U.S. Department of Energy, Energy Conversion and Utilization Technologies (ECUT) Division. The ECUT Biocatalysis Project is managed by the Jet Propulsion Laboratory, California Institute of Technology. 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: (1) The Molecular Modeling and Applied Genetics work element includes research on modeling of biological systems, developing rigorous methods for the prediction of three-dimensional (tertiary) protein structure from the amino acid sequence (primary structure) for designing new biocatalysis, defining kinetic models of biocatalyst reactivity, and developing genetically engineered solutions to the generic technical barriers that preclude widespread application of biocatalysis. (2) The Bioprocess Engineering work element supports efforts in novel bioreactor concepts that are likely to lead to substantially higher levels of reactor productivity, product yields and lower separation energetics. Results of work within this work element will be used to establish the technical feasibility of critical bioprocess monitoring and control subsystems. (3) The Bioprocess Design and Assessment work element attempts to develop procedures (via user-friendly computer software) for assessing the energy-economics of biocatalyzed chemical production processes, and initiation of technology transfer for advanced bioprocesses.

Genetic engineering possibilities for CELSS: A bibliography and summary of techniques

NASA Technical Reports Server (NTRS)

Johnson, E. J.

1982-01-01

A bibliography of the most useful techniques employed in genetic engineering of higher plants, bacteria associated with plants, and plant cell cultures is provided. A resume of state-of-the-art genetic engineering of plants and bacteria is presented. The potential application of plant bacterial genetic engineering to CELSS (Controlled Ecological Life Support System) program and future research needs are discussed.

The Significance of Content Knowledge for Informal Reasoning regarding Socioscientific Issues: Applying Genetics Knowledge to Genetic Engineering Issues

ERIC Educational Resources Information Center

Sadler, Troy D.; Zeidler, Dana L.

2005-01-01

This study focused on informal reasoning regarding socioscientific issues. It sought to explore how content knowledge influenced the negotiation and resolution of contentious and complex scenarios based on genetic engineering. Two hundred and sixty-nine students drawn from undergraduate natural science and nonnatural science courses completed a…

New Results in Astrodynamics Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Coverstone-Carroll, V.; Hartmann, J. W.; Williams, S. N.; Mason, W. J.

1998-01-01

Generic algorithms have gained popularity as an effective procedure for obtaining solutions to traditionally difficult space mission optimization problems. In this paper, a brief survey of the use of genetic algorithms to solve astrodynamics problems is presented and is followed by new results obtained from applying a Pareto genetic algorithm to the optimization of low-thrust interplanetary spacecraft missions.

Genetic Variance in Processing Speed Drives Variation in Aging of Spatial and Memory Abilities

ERIC Educational Resources Information Center

Finkel, Deborah; Reynolds, Chandra A.; McArdle, John J.; Hamagami, Fumiaki; Pedersen, Nancy L.

2009-01-01

Previous analyses have identified a genetic contribution to the correlation between declines with age in processing speed and higher cognitive abilities. The goal of the current analysis was to apply the biometric dual change score model to consider the possibility of temporal dynamics underlying the genetic covariance between aging trajectories…

Global Optimization of a Periodic System using a Genetic Algorithm

NASA Astrophysics Data System (ADS)

Stucke, David; Crespi, Vincent

2001-03-01

We use a novel application of a genetic algorithm global optimizatin technique to find the lowest energy structures for periodic systems. We apply this technique to colloidal crystals for several different stoichiometries of binary and trinary colloidal crystals. This application of a genetic algorithm is decribed and results of likely candidate structures are presented.

The Impact of a Web-Based Research Simulation in Bioinformatics on Students' Understanding of Genetics

ERIC Educational Resources Information Center

Gelbart, Hadas; Brill, Gilat; Yarden, Anat

2009-01-01

Providing learners with opportunities to engage in activities similar to those carried out by scientists was addressed in a web-based research simulation in genetics developed for high school biology students. The research simulation enables learners to apply their genetics knowledge while giving them an opportunity to participate in an authentic…

Invasion success in Cogongrass (Imperata cylindrica): A population genetic approach exploring genetic diversity and historical introductions

Treesearch

Rima D. Lucardi; Lisa E. Wallace; Gary N. Ervin

2014-01-01

Propagule pressure significantly contributes to and limits the potential success of a biological invasion, especially during transport, introduction, and establishment. Events such as multiple introductions of foreign parent material and gene flow among them can increase genetic diversity in founding populations, often leading to greater invasion success. We applied...

Genetics, the Big Five, and the Tendency to Be Self-Employed

ERIC Educational Resources Information Center

Shane, Scott; Nicolaou, Nicos; Cherkas, Lynn; Spector, Tim D.

2010-01-01

We applied multivariate genetics techniques to a sample of 3,412 monozygotic and dizygotic twins from the United Kingdom and 1,300 monozygotic and dizygotic twins from the United States to examine whether genetic factors account for part of the covariance between the Big Five personality characteristics and the tendency to be an entrepreneur. We…

Genetics

USDA-ARS?s Scientific Manuscript database

The genus Capsicum represents one of several well characterized Solanaceous genera. A wealth of classical and molecular genetics research is available for the genus. Information gleaned from its cultivated relatives, tomato and potato, provide further insight for basic and applied studies. Early ...

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

PubMed

Lin, Yu; Sakamoto, Norihiro

2009-05-12

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

Genetic variation and correlated changes in reproductive performance of a red tilapia line selected for improved growth over three generations.

PubMed

Thoa, Ngo Phu; Hamzah, Azhar; Nguyen, Nguyen Hong

2017-09-01

The present study examines genetic variation and correlated changes in reproductive performance traits in a red tilapia (Oreochromis spp.) population selected over three generations for improved growth. A total of 328 breeding females (offspring of 111 sires and 118 dams) had measurements of body weight prior to spawning (WBS), number of fry at hatching (NFH), total fry weight (TFW) and number of dead fry (NDF) or mortality of fry including unhatched eggs at hatching (MFH). Restricted maximum likelihood (REML) analysis in a multi-trait model showed that there are heritable genetic components for all traits studied. The heritability for WBS was very high (0.80). The estimates for traits related to fecundity (NFH, TFW) and survival (NDF) were low and they were associated with high standard errors. Genetic correlations of WBS with other reproductive performance traits (NFH, TFW and NDF) were generally positive. However, NFH was negatively correlated genetically with TFW. As expected, body measurements during growth stage exhibited strong positive genetic correlations with WBS. The genetic correlations between body traits and reproductive performance (NFH, TFW, NDF) were not significant. Correlated responses in reproductive traits were measured as changes in least squares means between generations or spawning years. Except for WBS that increased with the selection programs, the phenotypic changes in other reproductive traits observed were not statistically significant (P>0.05). It is concluded that the selection program for red tilapia has resulted in very little changes in reproductive performance of the animals after three generations. However, periodic monitoring of genetic changes in fecundity and fitness related traits such as NDF or MFH should be made in selective breeding programs for red tilapia. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Some Results of Weak Anticipative Concept Applied in Simulation Based Decision Support in Enterprise

NASA Astrophysics Data System (ADS)

Kljajić, Miroljub; Kofjač, Davorin; Kljajić Borštnar, Mirjana; Škraba, Andrej

2010-11-01

The simulation models are used as for decision support and learning in enterprises and in schools. Tree cases of successful applications demonstrate usefulness of weak anticipative information. Job shop scheduling production with makespan criterion presents a real case customized flexible furniture production optimization. The genetic algorithm for job shop scheduling optimization is presented. Simulation based inventory control for products with stochastic lead time and demand describes inventory optimization for products with stochastic lead time and demand. Dynamic programming and fuzzy control algorithms reduce the total cost without producing stock-outs in most cases. Values of decision making information based on simulation were discussed too. All two cases will be discussed from optimization, modeling and learning point of view.

Multi Agent Systems with Symbiotic Learning and Evolution using GNP

NASA Astrophysics Data System (ADS)

Eguchi, Toru; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

Recently, various attempts relevant to Multi Agent Systems (MAS) which is one of the most promising systems based on Distributed Artificial Intelligence have been studied to control large and complicated systems efficiently. In these trends of MAS, Multi Agent Systems with Symbiotic Learning and Evolution named Masbiole has been proposed. In Masbiole, symbiotic phenomena among creatures are considered in the process of learning and evolution of MAS. So we can expect more flexible and sophisticated solutions than conventional MAS. In this paper, we apply Masbiole to Iterative Prisoner’s Dilemma Games (IPD Games) using Genetic Network Programming (GNP) which is a newly developed evolutionary computation method for constituting agents. Some characteristics of Masbiole using GNP in IPD Games are clarified.

Optimization of the design of Gas Cherenkov Detectors for ICF diagnosis

NASA Astrophysics Data System (ADS)

Liu, Bin; Hu, Huasi; Han, Hetong; Lv, Huanwen; Li, Lan

2018-07-01

A design method, which combines a genetic algorithm (GA) with Monte-Carlo simulation, is established and applied to two different types of Cherenkov detectors, namely, Gas Cherenkov Detector (GCD) and Gamma Reaction History (GRH). For accelerating the optimization program, open Message Passing Interface (MPI) is used in the Geant4 simulation. Compared with the traditional optical ray-tracing method, the performances of these detectors have been improved with the optimization method. The efficiency for GCD system, with a threshold of 6.3 MeV, is enhanced by ∼20% and time response improved by ∼7.2%. For the GRH system, with threshold of 10 MeV, the efficiency is enhanced by ∼76% in comparison with previously published results.

Soft computing prediction of economic growth based in science and technology factors

NASA Astrophysics Data System (ADS)

Marković, Dušan; Petković, Dalibor; Nikolić, Vlastimir; Milovančević, Miloš; Petković, Biljana

2017-01-01

The purpose of this research is to develop and apply the Extreme Learning Machine (ELM) to forecast the gross domestic product (GDP) growth rate. In this study the GDP growth was analyzed based on ten science and technology factors. These factors were: research and development (R&D) expenditure in GDP, scientific and technical journal articles, patent applications for nonresidents, patent applications for residents, trademark applications for nonresidents, trademark applications for residents, total trademark applications, researchers in R&D, technicians in R&D and high-technology exports. The ELM results were compared with genetic programming (GP), artificial neural network (ANN) and fuzzy logic results. Based upon simulation results, it is demonstrated that ELM has better forecasting capability for the GDP growth rate.

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.

Multi-objective design optimization and control of magnetorheological fluid brakes for automotive applications

NASA Astrophysics Data System (ADS)

Shamieh, Hadi; Sedaghati, Ramin

2017-12-01

The magnetorheological brake (MRB) is an electromechanical device that generates a retarding torque through employing magnetorheological (MR) fluids. The objective of this paper is to design, optimize and control an MRB for automotive applications considering. The dynamic range of a disk-type MRB expressing the ratio of generated toque at on and off states has been formulated as a function of the rotational speed, geometrical and material properties, and applied electrical current. Analytical magnetic circuit analysis has been conducted to derive the relation between magnetic field intensity and the applied electrical current as a function of the MRB geometrical and material properties. A multidisciplinary design optimization problem has then been formulated to identify the optimal brake geometrical parameters to maximize the dynamic range and minimize the response time and weight of the MRB under weight, size and magnetic flux density constraints. The optimization problem has been solved using combined genetic and sequential quadratic programming algorithms. Finally, the performance of the optimally designed MRB has been investigated in a quarter vehicle model. A PID controller has been designed to regulate the applied current required by the MRB in order to improve vehicle’s slipping on different road conditions.

Genetic analysis of resistance to ticks, gastrointestinal nematodes and Eimeria spp. in Nellore cattle.

PubMed

Passafaro, Tiago Luciano; Carrera, Juan Pablo Botero; dos Santos, Livia Loiola; Raidan, Fernanda Santos Silva; dos Santos, Dalinne Chrystian Carvalho; Cardoso, Eduardo Penteado; Leite, Romário Cerqueira; Toral, Fabio Luiz Buranelo

2015-06-15

The aim of the present study was to obtain genetic parameters for resistance to ticks, gastrointestinal nematodes (worms) and Eimeria spp. in Nellore cattle, analyze the inclusion of resistance traits in Nellore breeding programs and evaluate genetic selection as a complementary tool in parasite control programs. Counting of ticks, gastrointestinal nematode eggs and Eimeria spp. oocysts per gram of feces totaling 4270; 3872 and 3872 records from 1188; 1142 and 1142 animals, respectively, aged 146 to 597 days were used. The animals were classified as resistant (counts equal to zero) or susceptible (counts above zero) to each parasite. The statistical models included systematics effects of contemporary groups and the mean trajectory. The random effects included additive genetic effects, direct permanent environmental effects and residual. The mean trajectory and random effects were modeled with linear Legendre polynomials for all traits except for the mean trajectory of resistance to Eimeria spp., which employed the cubic polynomial. Heritability estimates were of low to moderate magnitude and ranged from 0.06 to 0.30, 0.06 to 0.33 and 0.04 to 0.33 for resistance to ticks, gastrointestinal nematodes and Eimeria spp., respectively. The posterior mean of genetic and environmental correlations for the same trait at different ages (205, 365, 450 and 550 days) were favorable at adjacent ages and unfavorable at distant ages. In general, the posterior mean of the genetic and environmental correlations between traits of resistance were low and high-density intervals were large and included zero in many cases. The heritability estimates support the inclusion of resistance to ticks, gastrointestinal nematodes and Eimeria spp. in Nellore breeding programs. Genetic selection can increase the frequency of resistant animals and be used as a complementary tool in parasite control programs. Copyright © 2015 Elsevier B.V. All rights reserved.

Mitochondrial sequencing reveals five separate origins of 'black' Apis mellifera (Hymenoptera: Apidae) in eastern Australian commercial colonies.

PubMed

Oxley, P R; Oldroyd, B P

2009-04-01

Establishment of a closed population honey bee, Apis mellifera L. (Hymenoptera: Apidae), breeding program based on 'black' strains has been proposed for eastern Australia. Long-term success of such a program requires a high level of genetic variance. To determine the likely extent of genetic variation available, 50 colonies from 11 different commercial apiaries were sequenced in the mitochondrial cytochrome oxidase I and II intergenic region. Five distinct and novel mitotypes were identified. No colonies were found with the A. mellifera mellifera mitotype, which is often associated with undesirable feral strains. One group of mitotypes was consistent with a caucasica origin, two with carnica, and two with ligustica. The results suggest that there is sufficient genetic diversity to support a breeding program provided all these five sources were pooled.

Family-Based Interventions for the Prevention of Substance Abuse and Other Impulse Control Disorders in Girls

PubMed Central

Kumpfer, K. L.

2014-01-01

Standardized family-based interventions are the most effective way of preventing or treating adolescent substance abuse and delinquency. This paper first reviews the incidence of adolescent substance abuse worldwide emphasizing gender and causes by etiological risk and protective factors. New epigenetic research is included suggesting that nurturing parenting significantly prevents the phenotypic expression of inherited genetic diseases including substance abuse. Evidence-based family interventions are reviewed including family change theories behind their success, principles and types of family-based interventions, research results, cultural adaptation steps for ethnic and international translation, and dissemination issues. The author's Strengthening Family Program is used as an example of how these principles of effective prevention and cultural adaptation can result in highly effective prevention programs not only for substance abuse, but for other impulse control disorders as well. The conclusions include recommendations for more use of computer technologies to cut the high cost of family interventions relative to youth-only prevention programs and increase the public health impact of evidence-based prevention programs. The paper recommends that to reduce health care costs these family-based approaches should be applied to the prevention and treatment of other impulse control disorders such as obesity and type 2 diabetes, sexually transmitted diseases, and delinquency. PMID:25938121

Measuring Financial Gains from Genetically Superior Trees

Treesearch

George Dutrow; Clark Row

1976-01-01

Planting genetically superior loblolly pines will probably yield high profits.Forest economists have made computer simulations that predict financial gains expected from a tree improvement program under actual field conditions.

Linear genetic programming application for successive-station monthly streamflow prediction

NASA Astrophysics Data System (ADS)

Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit

2014-09-01

In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.

Predicting discovery rates of genomic features.

PubMed

Gravel, Simon

2014-06-01

Successful sequencing experiments require judicious sample selection. However, this selection must often be performed on the basis of limited preliminary data. Predicting the statistical properties of the final sample based on preliminary data can be challenging, because numerous uncertain model assumptions may be involved. Here, we ask whether we can predict "omics" variation across many samples by sequencing only a fraction of them. In the infinite-genome limit, we find that a pilot study sequencing 5% of a population is sufficient to predict the number of genetic variants in the entire population within 6% of the correct value, using an estimator agnostic to demography, selection, or population structure. To reach similar accuracy in a finite genome with millions of polymorphisms, the pilot study would require ∼15% of the population. We present computationally efficient jackknife and linear programming methods that exhibit substantially less bias than the state of the art when applied to simulated data and subsampled 1000 Genomes Project data. Extrapolating based on the National Heart, Lung, and Blood Institute Exome Sequencing Project data, we predict that 7.2% of sites in the capture region would be variable in a sample of 50,000 African Americans and 8.8% in a European sample of equal size. Finally, we show how the linear programming method can also predict discovery rates of various genomic features, such as the number of transcription factor binding sites across different cell types. Copyright © 2014 by the Genetics Society of America.

IRX3 Promotes the Browning of White Adipocytes and Its Rare Variants are Associated with Human Obesity Risk.

PubMed

Zou, Yaoyu; Lu, Peng; Shi, Juan; Liu, Wen; Yang, Minglan; Zhao, Shaoqian; Chen, Na; Chen, Maopei; Sun, Yingkai; Gao, Aibo; Chen, Qingbo; Zhang, Zhiguo; Ma, Qinyun; Ning, Tinglu; Ying, Xiayang; Jin, Jiabin; Deng, Xiaxing; Shen, Baiyong; Zhang, Yifei; Yuan, Bo; Kauderer, Sophie; Liu, Simin; Hong, Jie; Liu, Ruixin; Ning, Guang; Wang, Weiqing; Gu, Weiqiong; Wang, Jiqiu

2017-10-01

IRX3 was recently reported as the effector of the FTO variants. We aimed to test IRX3's roles in the browning program and to evaluate the association between the genetic variants in IRX3 and human obesity. IRX3 expression was examined in beige adipocytes in human and mouse models, and further validated in induced beige adipocytes. The browning capacity of primary preadipocytes was assessed with IRX3 knockdown. Luciferase reporter analysis and ChIP assay were applied to investigate IRX3's effects on UCP1 transcriptional activity. Moreover, genetic analysis of IRX3 was performed in 861 young obese subjects and 916 controls. IRX3 expression was induced in the browning process and was positively correlated with the browning markers. IRX3 knockdown remarkably inhibited UCP1 expression in induced mouse and human beige adipocytes, and also repressed the uncoupled oxygen consumption rate. Further, IRX3 directly bound to UCP1 promoter and increased its transcriptional activity. Moreover, 17 rare heterozygous missense/frameshift IRX3 variants were identified, with a significant enrichment in obese subjects (P=0.038, OR=2.27; 95% CI, 1.02-5.05). IRX3 deficiency repressed the browning program of white adipocytes partially by regulating UCP1 transcriptional activity. Rare variants of IRX3 were associated with human obesity. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

From prenatal genomic diagnosis to fetal personalized medicine: progress and challenges

PubMed Central

Bianchi, Diana W

2015-01-01

Thus far, the focus of personalized medicine has been the prevention and treatment of conditions that affect adults. Although advances in genetic technology have been applied more frequently to prenatal diagnosis than to fetal treatment, genetic and genomic information is beginning to influence pregnancy management. Recent developments in sequencing the fetal genome combined with progress in understanding fetal physiology using gene expression arrays indicate that we could have the technical capabilities to apply an individualized medicine approach to the fetus. Here I review recent advances in prenatal genetic diagnostics, the challenges associated with these new technologies and how the information derived from them can be used to advance fetal care. Historically, the goal of prenatal diagnosis has been to provide an informed choice to prospective parents. We are now at a point where that goal can and should be expanded to incorporate genetic, genomic and transcriptomic data to develop new approaches to fetal treatment. PMID:22772565

Implementing genetic education in primary care: the Gen-Equip programme.

PubMed

Paneque, Milena; Cornel, Martina C; Curtisova, Vaclava; Houwink, Elisa; Jackson, Leigh; Kent, Alastair; Lunt, Peter; Macek, Milan; Stefansdottir, Vigdis; Turchetti, Daniela; Skirton, Heather

2017-04-01

Genetics and genomics are increasingly relevant to primary healthcare but training is unavailable to many practitioners. Education that can be accessed by practitioners without cost or travel is essential. The Gen-Equip project was formed to provide effective education in genetics for primary healthcare in Europe and so improve patient care. Partners include patient representatives and specialists in genetics and primary care from six countries. Here, we report the progress and challenges involved in creating a European online educational program in genetics.

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.
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Primer Part 1-The building blocks of epilepsy genetics.

PubMed

Helbig, Ingo; Heinzen, Erin L; Mefford, Heather C

2016-06-01

This is the first of a two-part primer on the genetics of the epilepsies within the Genetic Literacy Series of the Genetics Commission of the International League Against Epilepsy. In Part 1, we cover the foundations of epilepsy genetics including genetic epidemiology and the range of genetic variants that can affect the risk for developing epilepsy. We discuss various epidemiologic study designs that have been applied to the genetics of the epilepsies including population studies, which provide compelling evidence for a strong genetic contribution in many epilepsies. We discuss genetic risk factors varying in size, frequency, inheritance pattern, effect size, and phenotypic specificity, and provide examples of how genetic risk factors within the various categories increase the risk for epilepsy. We end by highlighting trends in epilepsy genetics including the increasing use of massive parallel sequencing technologies. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

Public health implications from COGS and potential for risk stratification and screening.

PubMed

Burton, Hilary; Chowdhury, Susmita; Dent, Tom; Hall, Alison; Pashayan, Nora; Pharoah, Paul

2013-04-01

The PHG Foundation led a multidisciplinary program, which used results from COGS research identifying genetic variants associated with breast, ovarian and prostate cancers to model risk-stratified prevention for breast and prostate cancers. Implementing such strategies would require attention to the use and storage of genetic information, the development of risk assessment tools, new protocols for consent and programs of professional education and public engagement.

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

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

McInerney, Joseph D.

2003-03-31

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

Genetic diversity and population structure analysis of spinach by single-nucleotide polymorphisms identified through genotyping-by-sequencing.

PubMed

Shi, Ainong; Qin, Jun; Mou, Beiquan; Correll, James; Weng, Yuejin; Brenner, David; Feng, Chunda; Motes, Dennis; Yang, Wei; Dong, Lingdi; Bhattarai, Gehendra; Ravelombola, Waltram

2017-01-01

Spinach (Spinacia oleracea L., 2n = 2x = 12) is an economically important vegetable crop worldwide and one of the healthiest vegetables due to its high concentrations of nutrients and minerals. The objective of this research was to conduct genetic diversity and population structure analysis of a collection of world-wide spinach genotypes using single nucleotide polymorphisms (SNPs) markers. Genotyping by sequencing (GBS) was used to discover SNPs in spinach genotypes. Three sets of spinach genotypes were used: 1) 268 USDA GRIN spinach germplasm accessions originally collected from 30 countries; 2) 45 commercial spinach F1 hybrids from three countries; and 3) 30 US Arkansas spinach cultivars/breeding lines. The results from this study indicated that there was genetic diversity among the 343 spinach genotypes tested. Furthermore, the genetic background in improved commercial F1 hybrids and in Arkansas cultivars/lines had a different structured populations from the USDA germplasm. In addition, the genetic diversity and population structures were associated with geographic origin and germplasm from the US Arkansas breeding program had a unique genetic background. These data could provide genetic diversity information and the molecular markers for selecting parents in spinach breeding programs.