• Title/Summary/Keyword: Genomic analysis

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Image Analysis Algorithms for Comparative Genomic Hybridization (분자 세포 유전학 기법에 응용되는 영상 처리 기술)

  • Kim, De-Sok;Yoo, Jin-Sung;Lee, Jin-Woo;Kim, Jong-Won;Moon, Shin-Yong;Choi, Young-Min
    • Proceedings of the KOSOMBE Conference
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    • v.1998 no.11
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    • pp.66-69
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    • 1998
  • Comparative genomic hybridization (CGH) is an important molecular cytogenetics technique that maps abnormal copy number of specific DNA sequence of the chromosome. CGH is based on quantitative digital image analysis of ratio images from fluorescently labeled chromosomes. In this paper, we would like to introduce how recently developed image analysis algorithms are used for CGH techniques. To average the ratio profile of each chromosome, binarization, skeletonization, and stretching of chromosome images have been studied. Developed algorithms have been implemented in the karyotyping system ChIPS commercially developed at Biomedlab Co. Ltd.

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Recent next-generation sequencing and bioinformatic analysis methods for food microbiome research (식품 미생물 균총 연구를 위한 최신 마이크로바이옴 분석 기술)

  • Kwon, Joon-Gi;Kim, Seon-Kyun;Lee, Ju-Hoon
    • Food Science and Industry
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    • v.52 no.3
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    • pp.220-228
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    • 2019
  • Rapid development of next-generation sequencing (NGS) technology is available to study microbes in genomic level. This NGS has been widely used in DNA/RNA sequencing for genome sequencing, metagenomics, and transcriptomics. The food microbiology area could be categorized into three groups. Food microbes including probiotics and food-borne pathogens are studied in genomic level using NGS for microbial genomics. While food fermentation or food spoilage are more complicated, their genomic study needs to be done with metagenomics using NGS for compositional analysis. Furthermore, because microbial response in food environments are also important to understand their roles in food fermentation or spoilage, pattern analysis of RNA expression in the specific food microbe is conducted using RNA-Seq. These microbial genomics, metagenomics, and transcriptomics for food fermentation and spoilage would extend our knowledge on effective utilization of fermenting bacteria for health promotion as well as efficient control of food-borne pathogens for food safety.

Construction of an Analysis System Using Digital Breeding Technology for the Selection of Capsicum annuum

  • Donghyun Jeon;Sehyun Choi;Yuna Kang;Changsoo Kim
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2022.10a
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    • pp.233-233
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    • 2022
  • As the world's population grows and food needs diversify, the demand for horticultural crops for beneficial traits is increasing. In order to meet this demand, it is necessary to develop suitable cultivars and breeding methods accordingly. Breeding methods have changed over time. With the recent development of sequencing technology, the concept of genomic selection (GS) has emerged as large-scale genome information can be used. GS shows good predictive ability even for quantitative traits by using various markers, breaking away from the limitations of Marker Assisted Selection (MAS). Moreover, GS using machine learning (ML) and deep learning (DL) has been studied recently. In this study, we aim to build a system that selects phenotype-related markers using the genomic information of the pepper population and trains a genomic selection model to select individuals from the validation population. We plan to establish an optimal genome wide association analysis model by comparing and analyzing five models. Validation of molecular markers by applying linkage markers discovered through genome wide association analysis to breeding populations. Finally, we plan to establish an optimal genome selection model by comparing and analyzing 12 genome selection models. Then We will use the genome selection model of the learning group in the breeding group to verify the prediction accuracy and discover a prediction model.

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Identification and Analysis of PIT1 Polymorphisms and Its Association with Growth and Carcass Traits in Korean Cattles (Hanwoo) (한우에서 Pituitary-specific Transcription Factor (PIT1) 유전자와 경제 형질과의 연관성 분석)

  • Choi, J.R.;Oh, J.D.;Cho, K.J.;Lee, J.H.;Kong, H.S.;Lee, H.K.
    • Journal of Embryo Transfer
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    • v.22 no.3
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    • pp.167-172
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    • 2007
  • Pituitary-specific transcription factor (PIT1) 유전자는 동물의 성장을 조절하고 근육 형성에 관여하는 유전자로서 최근에는 단일염기다형성 변이가 한우를 비롯한 동물에서 관찰되었으며, 한우의 경제 형질과 연관성이 보고되었다. 본 연구는 PIT1 유전자의 단일염기다형성 변이가 한우에서 성장 인자에 미치는 영향과 경제 형질에 대한 유전자형간 육종가와의 상관성에 대해 알아보고자 하였다. 도체 성적을 보유하고 있는 한우 후보종모우 집단 268두를 대상으로 PIT1 유전자 A1256G 다형성을 조사하여 유전자형의 빈도를 분석하였고 각각의 유전형에 따른 기본적인 검정 성적을 바탕으로 경제 형질과의 연관성을 비교 분석하였다. 268두의 한우에서 PIT1 유전자의 A1256G 유전자형 빈도는 MseI 제한 효소를 사용했을 때 A 유전자 빈도(0.37)보다 G 유전자 빈도(0.62)가 높게 나타났다. 통계적 분석을 통하여 각 유전자형에 대한 경제 형질과의 관련성을 분석한 결과, 각 유전자형 간에 12개월령 체중 (body weight 12, BW12)에서 유의한 차이를 보였고, 등지방 두께 육종가 (Backfat thickness-estimated breeding value, BF-EBV)와도 유의한 차이가 있었지만 (p<0.05), marbling score (MS), carcass weight (CW), M. longissimus dorsi area (LDA) 등 다른 경제 형질과는 통계학적으로 유의한 차이가 없었다. PIT1 유전자의 A1256G 다형성은 한우의 성장과 도체체중에 관여하는 인자로 작용하는 것으로 보여진다.

Sequence and Phylogenetic Analyses of the M and S Genomic Segments of Hantaan and Seoul Viruses (한타바이러스와 서울바이러스의 M 및 S 분절의 염기서열 및 계통분석)

  • Song, Ki-Joon;Yang, Jeong-In;Kim, Sang-Hyun;Kim, Jong-Hun;Lee, Young-Eun;Baek, Luck-Ju;Lee, Yong-Ju;Song, Jin-Won
    • The Journal of Korean Society of Virology
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    • v.28 no.4
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    • pp.327-335
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    • 1998
  • Hantaan (HTN) and Seoul (SEO) viruses, murid rodent-borne hantaviruses, are known to causes hemorrhagic fever with renal syndrome (HFRS) in Korea. To determine the genomic diversity and molecular phylogeny of HTN and SEO viruses found in Korea, we amplified for part of M and S genomic segments of hantaviruses from sera of HFRS patients and lung tissues of hantavirus seropositive striped-field mice. Both M and S segment of 16 HTN and 2 SEO viruses were amplified by nested reverse transcription-polymerase chain reaction. Based on 324 nucleotides in the M genomic segment, the HTN and SEO strains showed $93.8{\sim}100%$ and $99.1{\sim}99.4%$ homologies, respectively. Similarly, based on 230 nucleotides in the S genomic segment, HTN and SEO strains showed $90.9{\sim}100%$ and 100% homologies, respectively. Phylogenetic analysis of M and S segments indicated that HTN strains could be divided into at least two main groups in M and S trees and the sequence differences detected among the Sand M genomic segments of HTN viruses are consistent with reassortment having taken place between HTN virus strains.

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Identification of Novel SNPs with Effect on Economic Traits in Uncoupling Protein Gene of Korean Native Chicken

  • Oh, J.D.;Kong, H.S.;Lee, J.H.;Choi, I.S.;Lee, S.J.;Lee, S.G.;Sang, B.D.;Choi, C.H.;Cho, B.W.;Jeon, G.J.;Lee, H.K.
    • Asian-Australasian Journal of Animal Sciences
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    • v.19 no.8
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    • pp.1065-1070
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    • 2006
  • The avian uncoupling protein (avUCP) is a member of the mitochondrial transporter superfamily that uncouples proton entry in the mitochondrial matrix from ATP synthesis. The sequencing analysis method was used to identify nucleotide polymorphisms within the avUCP gene in Korean native chicken (KNC). This study identified ten single nucleotide polymorphisms (SNPs) in the avUCP gene. We analyzed the SNPs of the avUCP gene to investigate whether polymorphism in the gene might be responsible for quantitative variations in economic traits in KNC. Three significant polymorphic sites for economic traits were avUCP C+282T (mean body weight, p<0.05), avUCP C+433T (daily percent lay, p<0.05), and avUCP T+1316C (daily percent lay, p<0.05). The frequency of each SNP was 0.125 (C+282T in avUCP gene exon 1 region), 0.150 (C+433T in avUCP gene intron 1 region), and 0.15 (T+1316C in avUCP gene exon 3 region), respectively. Among the identified SNPs, one pair of SNPs (genotype CC, C+282T and TT, avUCP C+433T) showed the highest daily percent lay (p<0.05) and mean body weight (p<0.05) and the frequency was 0.067. This study of the avUCP gene could be useful for genetic studies of this gene and selection on economic traits for KNC.

Network-based regularization for analysis of high-dimensional genomic data with group structure (그룹 구조를 갖는 고차원 유전체 자료 분석을 위한 네트워크 기반의 규제화 방법)

  • Kim, Kipoong;Choi, Jiyun;Sun, Hokeun
    • The Korean Journal of Applied Statistics
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    • v.29 no.6
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    • pp.1117-1128
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    • 2016
  • In genetic association studies with high-dimensional genomic data, regularization procedures based on penalized likelihood are often applied to identify genes or genetic regions associated with diseases or traits. A network-based regularization procedure can utilize biological network information (such as genetic pathways and signaling pathways in genetic association studies) with an outstanding selection performance over other regularization procedures such as lasso and elastic-net. However, network-based regularization has a limitation because cannot be applied to high-dimension genomic data with a group structure. In this article, we propose to combine data dimension reduction techniques such as principal component analysis and a partial least square into network-based regularization for the analysis of high-dimensional genomic data with a group structure. The selection performance of the proposed method was evaluated by extensive simulation studies. The proposed method was also applied to real DNA methylation data generated from Illumina Innium HumanMethylation27K BeadChip, where methylation beta values of around 20,000 CpG sites over 12,770 genes were compared between 123 ovarian cancer patients and 152 healthy controls. This analysis was also able to indicate a few cancer-related genes.

Comparison of genome-wide association and genomic prediction methods for milk production traits in Korean Holstein cattle

  • Lee, SeokHyun;Dang, ChangGwon;Choy, YunHo;Do, ChangHee;Cho, Kwanghyun;Kim, Jongjoo;Kim, Yousam;Lee, Jungjae
    • Asian-Australasian Journal of Animal Sciences
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    • v.32 no.7
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    • pp.913-921
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    • 2019
  • Objective: The objectives of this study were to compare identified informative regions through two genome-wide association study (GWAS) approaches and determine the accuracy and bias of the direct genomic value (DGV) for milk production traits in Korean Holstein cattle, using two genomic prediction approaches: single-step genomic best linear unbiased prediction (ss-GBLUP) and Bayesian Bayes-B. Methods: Records on production traits such as adjusted 305-day milk (MY305), fat (FY305), and protein (PY305) yields were collected from 265,271 first parity cows. After quality control, 50,765 single-nucleotide polymorphic genotypes were available for analysis. In GWAS for ss-GBLUP (ssGWAS) and Bayes-B (BayesGWAS), the proportion of genetic variance for each 1-Mb genomic window was calculated and used to identify informative genomic regions. Accuracy of the DGV was estimated by a five-fold cross-validation with random clustering. As a measure of accuracy for DGV, we also assessed the correlation between DGV and deregressed-estimated breeding value (DEBV). The bias of DGV for each method was obtained by determining regression coefficients. Results: A total of nine and five significant windows (1 Mb) were identified for MY305 using ssGWAS and BayesGWAS, respectively. Using ssGWAS and BayesGWAS, we also detected multiple significant regions for FY305 (12 and 7) and PY305 (14 and 2), respectively. Both single-step DGV and Bayes DGV also showed somewhat moderate accuracy ranges for MY305 (0.32 to 0.34), FY305 (0.37 to 0.39), and PY305 (0.35 to 0.36) traits, respectively. The mean biases of DGVs determined using the single-step and Bayesian methods were $1.50{\pm}0.21$ and $1.18{\pm}0.26$ for MY305, $1.75{\pm}0.33$ and $1.14{\pm}0.20$ for FY305, and $1.59{\pm}0.20$ and $1.14{\pm}0.15$ for PY305, respectively. Conclusion: From the bias perspective, we believe that genomic selection based on the application of Bayesian approaches would be more suitable than application of ss-GBLUP in Korean Holstein populations.

Genomic DNA Chip: Genome-wide profiling in Cancer

  • 이종호
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2001.10a
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    • pp.61-86
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    • 2001
  • All cancers are caused by abnormalities in DNA sequence. Throughout life, the DNA in human cells is exposed to mutagens and suffers mistakes in replication, resulting in progressive, subtle changes in the DNA sequence in each cell. Since the development of conventional and molecular cytogenetic methods to the analysis of chromosomal aberrations in cancers, more than 1,800 recurring chromosomal breakpoints have been identified. These breakpoints and regions of nonrandom copy number changes typically point to the location of genes involved in cancer initiation and progression. With the introduction of molecular cytogenetic methodologies based on fluorescence in situ hybridization (FISH), namely, comparative genomic hybridization (CGH) and multicolor FISH (m-FISH) in carcinomas become susceptible to analysis. Conventional CGH has been widely applied for the detection of genomic imbalances in tumor cells, and used normal metaphase chromosomes as targets for the mapping of copy number changes. However, this limits the mapping of such imbalances to the resolution limit of metaphase chromosomes (usually 10 to 20 Mb). Efforts to increase this resolution have led to the "new"concept of genomic DNA chip (1 to 2 Mb), whereby the chromosomal target is replaced with cloned DNA immobilized on such as glass slides. The resulting resolution then depends on the size of the immobilized DNA fragments. We have completed the first draft of its Korean Genome Project. The project proceeded by end sequencing inserts from a library of 96,768 bacterial artificial chromosomes (BACs) containing genomic DNA fragments from Korean ethnicity. The sequenced BAC ends were then compared to the Human Genome Project′s publicly available sequence database and aligned according to known cancer gene sequences. These BAC clones were biotinylated by nick translation, hybridized to cytogenetic preparations of metaphase cells, and detected with fluorescein-conjugated avidin. Only locations of unique or low-copy Portions of the clone are identified, because high-copy interspersed repetitive sequences in the probe were suppressed by the addition of unlabelled Cotl DNA. Banding patterns were produced using DAPI. By this means, every BAC fragment has been matched to its appropriate chromosomal location. We have placed 86 (156 BAC clones) cytogenetically defined landmarks to help with the characterization of known cancer genes. Microarray techniques would be applied in CGH by replacement of metaphase chromosome to arrayed BAC confirming in oncogene and tumor suppressor gene: and an array BAC clones from the collection is used to perform a genome-wide scan for segmental aneuploidy by array-CGH. Therefore, the genomic DNA chip (arrayed BAC) will be undoubtedly provide accurate diagnosis of deletions, duplication, insertions and rearrangements of genomic material related to various human phenotypes, including neoplasias. And our tumor markers based on genetic abnormalities of cancer would be identified and contribute to the screening of the stage of cancers and/or hereditary diseases

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Comparative Genome Analysis Reveals Natural Variations in the Genomes of Erwinia pyrifoliae, a Black Shoot Blight Pathogen in Apple and Pear

  • Lee, Gyu Min;Ko, Seyoung;Oh, Eom-Ji;Song, Yu-Rim;Kim, Donghyuk;Oh, Chang-Sik
    • The Plant Pathology Journal
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    • v.36 no.5
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    • pp.428-439
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    • 2020
  • Erwinia pyrifoliae is a Gram-negative bacterial plant pathogen that causes black shoot blight in apple and pear. Although earlier studies reported the genome comparison of Erwinia species, E. pyrifoliae strains for such analysis were isolated in 1996. In 2014, the strain E. pyrifoliae EpK1/15 was newly isolated in the apple tree showing black shoot blight in South Korea. This study aimed to better understand the similarities and differences caused by natural variations at the genomic level between newly isolated E. pyrifoliae EpK1/15 and the strain Ep1/96, which were isolated almost 20 years apart. Several comparative genomic analyses were conducted, and Clusters of Orthologous Groups of proteins (COG) database was used to classify functional annotation for each strain. E. pyrifoliae EpK1/15 had similarities with the Ep1/96 strain in stress-related genes, Tn3 transposase of insertion sequences, type III secretion systems, and small RNAs. The most remarkable difference to emerge from this comparison was that although the draft genome of E. pyrifoliae EpK1/15 was almost conserved, Epk1/15 strain had at least three sorts of structural variations in functional annotation according to COG database; chromosome inversion, translocation, and duplication. These results indicate that E. pyrifoliae species has gone natural variations within almost 20 years at the genomic level, and we can trace their similarities and differences with comparative genomic analysis.