• Title/Summary/Keyword: genetic structure

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Implementation of genomic selection in Hanwoo breeding program (유전체정보활용 한우개량효율 증진)

  • Lee, Seung Hwan;Cho, Yong Min;Lee, Jun Heon;Oh, Seong Jong
    • Korean Journal of Agricultural Science
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    • v.42 no.4
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    • pp.397-406
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    • 2015
  • Quantitative traits are mostly controlled by a large number of genes. Some of these genes tend to have a large effect on quantitative traits in cattle and are known as major genes primarily located at quantitative trait loci (QTL). The genetic merit of animals can be estimated by genomic selection, which uses genome-wide SNP panels and statistical methods that capture the effects of large numbers of SNPs simultaneously. In practice, the accuracy of genomic predictions will depend on the size and structure of reference and training population, the effective population size, the density of marker and the genetic architecture of the traits such as number of loci affecting the traits and distribution of their effects. In this review, we focus on the structure of Hanwoo reference and training population in terms of accuracy of genomic prediction and we then discuss of genetic architecture of intramuscular fat(IMF) and marbling score(MS) to estimate genomic breeding value in real small size of reference population.

Computational Analysis of Human Chemokine Receptor Type 6

  • Sridharan, Sindhiya;Saifullah, Ayesha Zainab;Nagarajan, Santhosh Kumar;Madhavan, Thirumurthy
    • Journal of Integrative Natural Science
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    • v.11 no.2
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    • pp.121-129
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    • 2018
  • CXCR6 is a major target in drug design as it is a determinant receptor in many diseases like AIDS, Type I Diabetes, some cancer types, atherosclerosis, tumor formation, liver disease and steatohepatitis. In this study, we propose the active site residues of CXCR6 molecule. We employed homology modelling and molecular docking approach to generate the 3D structure for CXCR6 and to explore its interaction between the antagonists and agonists. 3D models were generated using 14 different templates having high sequence identity with CXCR6. Surflex docking studies using pyridine and pyrimidine derivatives enabled the analysis of the binding site and finding of the important residues involved in binding. 3D structure of CXCL16, a natural ligand for CXCR6, was modelled using PHYRE and protein - protein docking was performed using ClusPro. The residues which were found to be crucial in interaction with the ligand are THR110, PHE113, TYR114, GLN160, GLN195, CYS251 and SER255. This study can be used as a guide for therapeutic studies of human CXCR6.

Development and Characterization of 14 Microsatellite Markers for the Antarctic Midge Parochlus steinenii (Diptera, Chironomidae) in Maritime Antarctic

  • Kim, Hanna;Kang, Seunghyun;Kim, Hanul;Kim, Sanghee;Jung, Jongwoo
    • Animal Systematics, Evolution and Diversity
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    • v.33 no.2
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    • pp.140-143
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    • 2017
  • A winged midge species, Parochlus steinenii is one of the most abundant species in Antarctica, which is distributed over a wide area from the South American continent to the South Shetland Islands in Antarctica. It was dispersed into islands in the South Shetland Islands from the South American continent, and it adapted to a variety of environments and settled. This species, therefore, is a good model organism to explain the evolutionary process of Antarctic terrestrial fauna. Nevertheless, there are few genetic studies on this species, which are necessary for understanding the genetic diversity, population structure, etc. Here, we developed and characterized 14 polymorphic microsatellite markers. The number of alleles per locus ranged from 2 to 5. The observed and expected heterozygosities were in the range of 0.024 to 0.561 and 0.024 to 0.535, respectively. Identifying genetic differences between populations, they are suitable markers for researches investigating genetic diversity and population structure of P. steinenii, which provide us with clues to dispersion, evolution and ecology of this species.

Genetic Structure of Macrophomina phaseolina Populations, the Causal Agent of Sesame Charcoal Rot Disease in Iran

  • Maryam Dolatkhah;Fariba ghaderi;Abdollah Ahmadpour
    • Research in Plant Disease
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    • v.30 no.1
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    • pp.50-59
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    • 2024
  • Charcoal rot disease, caused by the fungus Macrophomina phaseolina, is one of the most important diseases of Sesame (Sesamum indicum) all over the world. However, the population biology of M. phaseolina is poorly understood. In this study, M. phaseolina isolates from five different regions of Iran (Khuzestan, Fars, Bushehr, Hormozgan, and Kohgiluyeh & Boyer-Ahmad provinces) (n=200) were analyzed for genetic variation using inter simple sequence repeats marker. In total, 152 unique haplotypes were identified among the 200 M. phaseolina isolates, and gene diversity (H=0.46-0.84) and genotypic diversity were high in each of the regions. The structure analysis clustered five Iranian populations into two distinct groups, the individuals from group 1 were assigned to the Bushehr population and the individuals from Khuzestan, Fars, Hormozgan and Kohgiluyeh & Boyer-Ahmad were aggregated and formed group 2. The results matched with genetic differentiation and gene flow among regions. Analyses of the distribution of gene diversity within and among five Iranian populations were 61% and 39%, respectively. Our results showed that infected seeds are thought to be the dominant mechanism responsible for the spreading of the pathogen in southern parts of Iran. In summary, it is essential to have local quarantine and prevent seed exchanges between geographical populations to restrict the dispersal of pathogen over long distances and provide certified seeds in Iran.

Genetic Diversity and Population Genetic Structure of Cephalotaxus koreana in South Korea

  • Hong, Kyung Nak;Kim, Young Mi;Park, Yu Jin;Lee, Jei Wan
    • Korean Journal of Plant Resources
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    • v.27 no.6
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    • pp.660-670
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    • 2014
  • The Korean plum yew (Cephalotaxus koreana Nakai) is a shade-tolerant, coniferous shrub. The seeds have been used as a folk medicine in Korea, and an alkaloid extract (HTT) is known to have anticancer properties. We estimated the genetic diversity of 429 trees in 16 populations in South Korea using 194 polymorphic amplicons from seven combinations of AFLP primer-restriction enzymes. The average number of effective alleles and the percentage of polymorphic loci were 1.37 and 79.4%, respectively. Shannon's diversity index and the expected heterozygosity were 0.344 and 0.244, respectively. We divided 16 populations into four groups on the UPGMA dendrogram and the PCA biplot. The first two principal components explained 84% of the total genetic variation. Genetic differentiation between populations explained 14% of total genetic variation, and the remaining 86% came from difference between individuals within populations, as determined by an analysis of molecular variance (AMOVA). However, the genetic differentiation did not correlate with the geographic distance between populations from the Mantel test. The Bayesian statistics, which are comparable to Wright's $F_{ST}$ and Nei's $G_{ST}$, were ${\theta}^I=0.406$ and ${\theta}^{II}=0.172$, respectively. The population genetic diversity was slightly lower, and the strength of genetic differentiation was much weaker, than the average of those plants having similar life histories, as assessed using arbitrary marker systems. We discuss strategies for the genetic conservation of the plum yew in Korea.

Comparison of Breeding System Between Single Population and Two Sub-population Scheme by Computer Simulation I. Equal genetic level for Sub-populations

  • Oikawa, T.;Matsura, Y.;Sato, K.
    • Asian-Australasian Journal of Animal Sciences
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    • v.10 no.4
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    • pp.422-427
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    • 1997
  • Breeding efficiency was investigated to reveal crucial factors for constructing effective breeding system with subdivided populations under equal genetic level. Simulation study of selection experiment was performed for 20 generations with 20 replications each, comparing average breeding values and inbreeding coefficients between the two breeding systems; single population scheme and two population scheme, each of which had the same genetic parameters. Genetic correlations (-0.5 to 0.5) were assumed to be caused only by pleiotropic effect of a gene. Phenotypes of the two traits generated by polygenic effect with additive 36 loci and residuals distributed normally were selected by two traits selection index procedure. Comparing between the single population scheme and the two population scheme, the single population scheme showed higher genetic gain with lower inbreeding coefficient. This result was confirmed particularly for the situation of high selection intensity, high heritability and high degree of unevenness for economic weight. Genetic correlations in the single population scheme were significantly lower than the two population scheme when initial genetic correlation was negative. When terminal crossbreeding for the two population scheme is taken into account, superiority of the two population scheme was suggested. The terminal crossbreeding was effective under the situation of long term selection, existence of moderate inbreeding depression and use of less extreme economic weight.

The Fuzzy Modeling by Virus-messy Genetic Algorithm (바이러스-메시 유전 알고리즘에 의한 퍼지 모델링)

  • 최종일;이연우;주영훈;박진배
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.157-160
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    • 2000
  • This paper deals with the fuzzy modeling for the complex and uncertain system in which conventional and mathematical models may fail to give satisfactory results. mGA(messy Genetic Algorithm) has more effective and adaptive structure than sGA with respect to using changeable-length string and VEGA(Virus Evolution Genetic) Algorithm) can search the global and local optimal solution simultaneously with reverse transcription operator and transduction operator. Therefore in this paper, the optimal fuzzy model is obtained using Virus-messy Genetic Algorithm(Virus-mGA). In this method local information is exchanged in population so that population may sustain genetic divergence. To prove the surperioty of the proposed approach, we provide the numerical example.

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Hybrid Genetic Algorithm Reinforced by Fuzzy Logic Controller (퍼지로직제어에 의해 강화된 혼합유전 알고리듬)

  • Yun, Young-Su
    • Journal of Korean Institute of Industrial Engineers
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    • v.28 no.1
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    • pp.76-86
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    • 2002
  • In this paper, we suggest a hybrid genetic algorithm reinforced by a fuzzy logic controller (flc-HGA) to overcome weaknesses of conventional genetic algorithms: the problem of parameter fine-tuning, the lack of local search ability, and the convergence speed in searching process. In the proposed flc-HGA, a fuzzy logic controller is used to adaptively regulate the fine-tuning structure of genetic algorithm (GA) parameters and a local search technique is applied to find a better solution in GA loop. In numerical examples, we apply the proposed algorithm to a simple test problem and two complex combinatorial optimization problems. Experiment results show that the proposed algorithm outperforms conventional GAs and heuristics.

Design of a Rule Based Controller using Genetic Programming and Its Application to Fuzzy Logic Controller (유전 프로그래밍을 이용한 규칙 기반 제어기의 설계와 퍼지로직 제어기로의 응용)

  • 정일권;이주장
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.5
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    • pp.624-629
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    • 1998
  • Evolutionary computation techniques can solve search problems using simulated evolution based on the ‘survival of the fittest’. Recently, the genetic programming (GP) which evolves computer programs using the genetic algorithm was introduced. In this paper, the genetic programming technique is used in order to design a rule based controller consisting of condition-action rules for an unknown system. No a priori knowledge about the structure of the controller is needed. Representation of a solution, functions and terminals in GP are analyzed, and a method of constructing a fuzzy logic controller using the obtained rule based controller is described. A simulation example using a nonlinear system shows the validity and efficiency of the proposed method.

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Design of Genetic Algorithms-based Fuzzy Polynomial Neural Networks Using Symbolic Encoding (기호 코딩을 이용한 유전자 알고리즘 기반 퍼지 다항식 뉴럴네트워크의 설계)

  • Lee, In-Tae;Oh, Sung-Kwun;Choi, Jeoung-Nae
    • Proceedings of the KIEE Conference
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    • 2006.04a
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    • pp.270-272
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    • 2006
  • In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs) using symbolic coding for non-linear data. One of the major subject of genetic algorithms is representation of chromosomes. The proposed model optimized by the means genetic algorithms which used symbolic code to represent chromosomes. The proposed gFPNN used a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. The performance of the proposed model is quantified through experimentation that exploits standard data already used in fuzzy modeling. These results reveal superiority of the proposed networks over the existing fuzzy and neural models.

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