• 제목/요약/키워드: genetic structure

검색결과 1,603건 처리시간 0.034초

Development of novel microsatellite markers to analyze the genetic structure of dog populations in Taiwan

  • Lai, Fang-Yu;Lin, Yu-Chen;Ding, Shih-Torng;Chang, Chi-Sheng;Chao, Wi-Lin;Wang, Pei-Hwa
    • Animal Bioscience
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    • 제35권9호
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    • pp.1314-1326
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    • 2022
  • Objective: Alongside the rise of animal-protection awareness in Taiwan, the public has been paying more attention to dog genetic deficiencies due to inbreeding in the pet market. The goal of this study was to isolate novel microsatellite markers for monitoring the genetic structure of domestic dog populations in Taiwan. Methods: A total of 113 DNA samples from three dog breeds-beagles (BEs), bichons (BIs), and schnauzers (SCs)-were used in subsequent polymorphic tests applying the 14 novel microsatellite markers that were isolated in this study. Results: The results showed that the high level of genetic diversity observed in these novel microsatellite markers provided strong discriminatory power. The estimated probability of identity (P(ID)) and the probability of identity among sibs (P(ID)sib) for the 14 novel microsatellite markers were 1.7×10-12 and 1.6×10-5, respectively. Furthermore, the power of exclusion for the 14 novel microsatellite markers was 99.98%. The neighbor-joining trees constructed among the three breeds indicated that the 14 sets of novel microsatellite markers were sufficient to correctly cluster the BEs, BIs, and SCs. The principal coordinate analysis plot showed that the dogs could be accurately separated by these 14 loci based on different breeds; moreover, the Beagles from different sources were also distinguished. The first, the second, and the third principal coordinates could be used to explain 44.15%, 26.35%, and 19.97% of the genetic variation. Conclusion: The results of this study could enable powerful monitoring of the genetic structure of domestic dog populations in Taiwan.

Assessment of population structure and genetic diversity of German Angora rabbit through pedigree analysis

  • Abdul Rahim;K. S. Rajaravindra;Om Hari Chaturvedi;S. R. Sharma
    • Animal Bioscience
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    • 제36권5호
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    • pp.692-703
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    • 2023
  • Objective: The main goals of this investigation were to i) assess the population structure and genetic diversity and ii) determine the efficiency of the ongoing breeding program in a closed flock of Angora rabbits through pedigree analysis. Methods: The pedigree records of 6,145 animals, born between 1996 to 2020 at NTRS, ICAR-CSWRI, Garsa were analyzed using ENDOG version 4.8 software package. The genealogical information, genetic conservation index and parameters based on gene origin probabilities were estimated. Results: Analysis revealed that, 99.09% of the kits had both parents recorded in the whole dataset. The completeness levels for the whole pedigree were 99.12%, 97.12%, 90.66%, 82.49%, and 74.11% for the 1st, 2nd, 3rd, 4th, and 5th generations, respectively, reflecting well-maintained pedigree records. The maximum inbreeding, average inbreeding and relatedness were 36.96%, 8.07%, and 15.82%, respectively. The mean maximum, mean equivalent and mean completed generations were 10.28, 7.91, and 5.51 with 0.85%, 1.19%, and 1.85% increase in inbreeding, respectively. The effective population size estimated from maximum, equivalent and complete generations were 58.50, 27.05, and 42.08, respectively. Only 1.51% of total mating was highly inbred. The effective population size computed via the individual increase in inbreeding was 42.83. The effective numbers of founders (fe), ancestors (fa), founder genomes (fg) and non-founder genomes (fng) were 18, 16, 6.22, and 9.50, respectively. The fe/fa ratio was 1.12, indicating occasional bottlenecks had occurred in the population. The six most influential ancestors explained 50% of genes contributed to the gene pool. The average generation interval was 1.51 years and was longer for the sire-offspring pathway. The population lost 8% genetic diversity over time, however, considerable genetic variability still existed in the closed Angora population. Conclusion: This study provides important and practical insights to manage and maintain the genetic variability within the individual flock and the entire population.

Genetic diversity and population structure among accessions of Perilla frutescens (L.) Britton in East Asia using new developed microsatellite markers

  • Sa, Kyu Jin;Choi, Ik?Young;Park, Kyong?Cheul;Lee, Ju Kyong
    • Genes and Genomics
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    • 제40권12호
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    • pp.1319-1329
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    • 2018
  • SSRs were successfully isolated from the Perilla crop in our current study, and used to analyze Perilla accessions from East Asia. Analyses of the clear genetic diversity and relationship for Perilla crop still remain insufficient. In this study, 40 new simple sequence repeat (SSR) primer sets were developed from RNA sequences using transcriptome analysis. These new SSR markers were applied to analyze the diversity, relationships, and population structure among 35 accessions of the two cultivated types of Perilla crop and their weedy types. A total of 220 alleles were identified at all loci, with an average of 5.5 alleles per locus and a range between 2 and 10 alleles per locus. The MAF (major allele frequency) per locus varied from 0.229 to 0.943, with an average of 0.466. The average polymorphic information content (PIC) value was 0.603, ranging from 0.102 to 0.837. The genetic diversity (GD) ranged from 0.108 to 0.854, with an average of 0.654. Based on population structure analysis, all accessions were divided into three groups: Group I, Group II and the admixed group. This study demonstrated the utility of new SSR analysis for the study of genetic diversity and population structure among 35 Perilla accessions. The GD of each locus for accessions of cultivated var. frutescens, weedy var. frutescens, cultivated var. crispa, and weedy var. crispa were 0.415, 0.606, 0.308, and 0.480, respectively. Both weedy accessions exhibited higher GD and PIC values than their cultivated types in East Asia. The new SSR primers of Perilla species reported in this study may provide potential genetic markers for population genetics to enhance our understanding of the genetic diversity, genetic relationship and population structure of the cultivated and weedy types of P. frutescens in East Asia. In addition, new Perilla SSR primers developed from RNA-seq can be used in the future for cultivar identification, conservation of Perilla germplasm resources, genome mapping and tagging of important genes/QTLs for Perilla breeding programs.

Assessment of genetic diversity and phylogenetic relationship of Limousin herds in Hungary using microsatellite markers

  • Szucs, Marton;Szabo, Ferenc;Ban, Beata;Jozsa, Csilla;Rozsa, Laszlo;Zsolnai, Attila;Anton, Istvan
    • Asian-Australasian Journal of Animal Sciences
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    • 제32권2호
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    • pp.176-182
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    • 2019
  • Objective: This study was conducted to investigate basic information on genetic structure and characteristics of Limousin population in Hungary. Obtained results will be taken into consideration when adopting the new breeding strategy by the Association of Hungarian Limousin and Blonde d'Aquitaine Breeders (AHLBB). Methods: Genetic diversity and phylogenetic relationship of 3,443 Limousin cattle from 16 different herds were investigated by performing genotyping using 18 microsatellite markers. Amplified DNA was genotyped using an automated genetic analyzer. Results: Mean of effective alleles ($n_e$) of the populations was 3.77. Population C had the lowest number of effective alleles (3.01) and the lowest inbreeding coefficient ($F_{IS}$) value (-0.15). Principal component analysis of estimated genetic distance ($F_{ST}$) values (p<0.000) revealed two herds (C and E) distinct from the majority of other Limousin herds. The pairwise $F_{ST}$ values of population C compared to the others (0.066 to 0.120) fell into the range of moderate genetic distance: 0.050 to 0.150, while population E displayed also moderate genetic distance ($F_{ST}$ values in range 0.052 to 0.064) but only to six populations (G, H, J, L, N, and P). $F_{ST(C-E)}$ was 0.148, all other pairs -excluding C and E herds- displayed low genetic distance ($F_{ST}$<0.049). Population D, F, I, J, K, L, N, O, and P carried private alleles, which alleles belonged to 1.1% of the individuals. Most probable number of clusters (K) were 2 and 7 determined by Structure and BAPS software. Conclusion: This study showed useful genetic diversity and phylogenetic relationship data that can be utilized for the development of a new breeding strategy by AHLBB. The results presented could also contribute to the proper selection of animals for further whole genome scan studies of Limousins.

가축에서 세포유전학의 응용 (Utilization of Cytogenetics in Domestic Animals)

  • 여정수
    • 한국수정란이식학회지
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    • 제4권1호
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    • pp.14-20
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    • 1989
  • Abnormalities of structure and morphology of chromosomes concentrated with genetic materials, DNA, are directly related to phenotypical performances of animals. So, cytogenetical research in domestic animals is important to prevent congenital deformity and improve genetic performances. Especially utilities of egg transfer technique combined with cytogenetical study can be accelerated by the wide spread of the best genetic sources dependent on the micromanipulation and sexing of eggs.

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유전 알고리듬을 이용한 퍼지 신경망의 최적화 및 혼돈 시계열 데이터 예측에의 응용 (The optimization of fuzzy neural network using genetic algorithms and its application to the prediction of the chaotic time series data)

  • 장욱;권오국;주영훈;윤태성;박진배
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.708-711
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    • 1997
  • This paper proposes the hybrid algorithm for the optimization of the structure and parameters of the fuzzy neural networks by genetic algorithms (GA) to improve the behaviour and the design of fuzzy neural networks. Fuzzy neural networks have a distinguishing feature in that they can possess the advantage of both neural networks and fuzzy systems. In this way, we can bring the low-level learning and computational power of neural networks into fuzzy systems and also high-level, human like IF-THEN rule thinking and reasoning of fuzzy systems into neural networks. As a result, there are many research works concerning the optimization of the structure and parameters of fuzzy neural networks. In this paper, we propose the hybrid algorithm that can optimize both the structure and parameters of fuzzy neural networks. Numerical example is provided to show the advantages of the proposed method.

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Multi-Item Inventory Problems Revisited Using Genetic Algorithm

  • Das, Prasun
    • Management Science and Financial Engineering
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    • 제13권2호
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    • pp.29-46
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    • 2007
  • This paper makes an attempt to compare the two important methods for finding solutions of multi-item inventory problem with more than one conflicting objectives. Panda et al.[9] discusses a distance-based method to find the best possible compromise solution with variation of priority under the given weight structure. In this paper, the problem in [9] is revisited through the Pareto-optimal front of genetic algorithm with the help of a situation of retail stocking of FMCG business. The advantages of using the solutions from the perspective of the decision maker obtained through multi-objective optimization are highlighted in terms of population search, weighted goals and priority structure, cost, set of compromise solutions along with prevention of stock-out situation.

유전 알고리즘 기반의 심층 학습 신경망 구조와 초모수 최적화 (Genetic algorithm based deep learning neural network structure and hyperparameter optimization)

  • 이상협;강도영;박장식
    • 한국멀티미디어학회논문지
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    • 제24권4호
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    • pp.519-527
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    • 2021
  • Alzheimer's disease is one of the challenges to tackle in the coming aging era and is attempting to diagnose and predict through various biomarkers. While the application of various deep learning-based technologies as powerful imaging technologies has recently expanded across the medical industry, empirical design is not easy because there are various deep earning neural networks architecture and categorical hyperparameters that rely on problems and data to solve. In this paper, we show the possibility of optimizing a deep learning neural network structure and hyperparameters for Alzheimer's disease classification in amyloid brain images in a representative deep earning neural networks architecture using genetic algorithms. It was observed that the optimal deep learning neural network structure and hyperparameter were chosen as the values of the experiment were converging.

An integrated optimal design of energy dissipation structures under wind loads considering SSI effect

  • Zhao, Xuefei;Jiang, Han;Wang, Shuguang
    • Wind and Structures
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    • 제29권2호
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    • pp.99-110
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    • 2019
  • This paper provides a simple numerical method to determine the optimal parameters of tuned mass damper (TMD) and viscoelastic dampers (VEDs) in frame structure for wind vibration control considering the soil-structure interation (SSI) effect in frequency domain. Firstly, the numerical model of frame structure equipped with TMD and VEDs considering SSI effect is established in frequency domain. Then, the genetic algorithm (GA) is applied to obtain the optimal parameters of VEDs and TMD. The optimization process is demonstrated by a 20-storey frame structure supported by pile group for different soil conditions. Two wind resistant systems are considered in the analysis, the Structure-TMD system and the Structure-TMD-VEDs system. The example proves that this method can quickly determine the optimal parameters of energy dissipation devices compared with the traditional finite element method, thus is practically valuable.

Amplified fragment length polymorphism analysis and genetic variation of the pinewood nematode Bursaphelenchus xylophilus in South Korea

  • Jung, Jong-Woo;Han, Hye-Rim;Ryu, Sung-Hee;Kim, Won
    • Animal cells and systems
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    • 제14권1호
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    • pp.31-36
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    • 2010
  • The pinewood nematode Bursaphelenchus xylophilus causes pine wilt disease and is a serious economic concern for the forest industry of South Korea. To achieve effective control with limited resources, it is necessary to clarify the transmission routes and mechanisms of dispersal of this organism. Highly polymorphic and easy-to-use molecular markers can be used for investigating this aspect. In this study, we evaluated the usefulness of amplified fragment length polymorphisms (AFLPs) for investigating the genetic variations of B. xylophilus and related individuals from China, Japan, and South Korea. The AFLP patterns obtained in our study were similar to the microsatellite patterns reported in a previous study; our AFLP patterns indicated high genetic variability and cryptic genetic structure, but did not indicate any peculiar geographic structure. Moreover, the genetic distances between individuals suggested that the Korean population was affected to a greater extent by the Chinese population than the Japanese population. Further, the gene flow among the related species appeared to be limited; however, there may be also the possibility of genetic introgression among species. These results confirm the usefulness of AFLPs for understanding the epidemiology of pine wilt disease, thereby contributing to the effective control of this disease.