• Title/Summary/Keyword: Genomic research

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Estimation of Genetic Characteristic and Cumulative Power of Breed Discrimination Using Microsatellite Markers in Hanwoo (Microsatellite Marker를 사용한 한우 품종 식별력 및 유전적 특성 분석)

  • Oh, Jae-Don;Lee, Jin-Ah;Kong, Hong-Sik;Park, Keong-Do;Yoon, Du-Hak;Jeon, Gwang-Ju;Lee, Hak-Kyo
    • Journal of Embryo Transfer
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    • v.23 no.3
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    • pp.203-209
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    • 2008
  • To estimate the genetic characteristics and cumulative power of discrimination (CPD) existing among Hanwoo (Korean cattle) and exotic foreign population (Angus, Herford, Charolais, Holstein) we used a total of 414 genomic DNAs from five breeds population (Hanwoo, Angus, Hereford, Charolais, Holstein). Genetic characteristics indices including mean allele number among loci, unbiased heterozygosity ($h_i$) within locus and polymorphic information content (PIC) and unbiased average heterozygosity (H) among loci in four breeds were calculated using the generated allele frequencies by each marker. The mean allele numbers for all loci ranged between 5 and 7 while heterozygosity (H) ranged from 0.75 (HW) to 0.64 (HF) among loci and across breeds heterozygosity (H) was 0.69. The generated unbiased average heterozygosity among loci in each breed was integrated to the global formula of CPD resulting in 99.71 % within the populations. The genetic variation of HW (Hanwoo) showed highest estimates among the analyzed breeds.

Comparison of the MGISEQ-2000 and Illumina HiSeq 4000 sequencing platforms for RNA sequencing

  • Jeon, Sol A;Park, Jong Lyul;Kim, Jong-Hwan;Kim, Jeong Hwan;Kim, Yong Sung;Kim, Jin Cheon;Kim, Seon-Young
    • Genomics & Informatics
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    • v.17 no.3
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    • pp.32.1-32.6
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    • 2019
  • Currently, Illumina sequencers are the globally leading sequencing platform in the next-generation sequencing market. Recently, MGI Tech launched a series of new sequencers, including the MGISEQ-2000, which promise to deliver high-quality sequencing data faster and at lower prices than Illumina's sequencers. In this study, we compared the performance of two major sequencers (MGISEQ-2000 and HiSeq 4000) to test whether the MGISEQ-2000 sequencer delivers high-quality sequence data as suggested. We performed RNA sequencing of four human colon cancer samples with the two platforms, and compared the sequencing quality and expression values. The data produced from the MGISEQ-2000 and HiSeq 4000 showed high concordance, with Pearson correlation coefficients ranging from 0.98 to 0.99. Various quality control (QC) analyses showed that the MGISEQ-2000 data fulfilled the required QC measures. Our study suggests that the performance of the MGISEQ-2000 is comparable to that of the HiSeq 4000 and that the MGISEQ-2000 can be a useful platform for sequencing.

A ChIP-Seq Data Analysis Pipeline Based on Bioconductor Packages

  • Park, Seung-Jin;Kim, Jong-Hwan;Yoon, Byung-Ha;Kim, Seon-Young
    • Genomics & Informatics
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    • v.15 no.1
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    • pp.11-18
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    • 2017
  • Nowadays, huge volumes of chromatin immunoprecipitation-sequencing (ChIP-Seq) data are generated to increase the knowledge on DNA-protein interactions in the cell, and accordingly, many tools have been developed for ChIP-Seq analysis. Here, we provide an example of a streamlined workflow for ChIP-Seq data analysis composed of only four packages in Bioconductor: dada2, QuasR, mosaics, and ChIPseeker. 'dada2' performs trimming of the high-throughput sequencing data. 'QuasR' and 'mosaics' perform quality control and mapping of the input reads to the reference genome and peak calling, respectively. Finally, 'ChIPseeker' performs annotation and visualization of the called peaks. This workflow runs well independently of operating systems (e.g., Windows, Mac, or Linux) and processes the input fastq files into various results in one run. R code is available at github: https://github.com/ddhb/Workflow_of_Chipseq.git.

Genetic Variation and Relationships of Korean Native Chickens and Foreign Breeds Using 15 Microsatellite Markers

  • Kong, H.S.;Oh, J.D.;Lee, J.H.;Jo, K.J.;Sang, B.D.;Choi, C.H.;Kim, S.D.;Lee, S.J.;Yeon, S.H.;Jeon, G.J.;Lee, H.K.
    • Asian-Australasian Journal of Animal Sciences
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    • v.19 no.11
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    • pp.1546-1550
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    • 2006
  • The purpose of this study was to assess the genetic variation and establish the relationship amongst breeds and strains using 15 chicken specific microsatellite markers. A total of 285 unrelated DNA samples from four Korean native chicken strains (Black strain of Korean native chicken; KL, Red Brown strain of Korean native chicken; KR, Ogol strain of Korean native chicken; KS and Yellow Brown strain of Korean native chicken; KY) and three introduced chicken breeds (F strain of White Leghorn; LF, K strain of White Leghorn; LK, Rhode Island Red; RC and Cornish; CN) were genotyped to estimate within and between breed genetic diversity indices. All the loci analyzed in 15 microsatellite markers showed a polymorphic pattern and the number of alleles ranged from 5 to 14. The polymorphism information content (PIC) of UMA1019 was the highest (0.872) and that of ADL0234 was the lowest (0.562). The expected total heterozygosity (He) within breed and mean number of observed alleles ranged from 0.540 (LF) to 0.689 (KY), and from 3.47 (LK) to 6.07 (KR), respectively. The genetic variation of KR and KY were the highest and the lowest within Korean native strains, respectively. The genetic distance results showed that Korean native chicken strains were separated with the three introduced chicken breeds clustered into another group. The lowest distance (0.149) was observed between the KR and KL breeds and the highest distance (0.855) between the KR and LK breeds. The microsatellite polymorphism data were shown to be useful for assessing the genetic relationship between Korean native strains and other foreign breeds.

Comparative Genome-Scale Expression Analysis of Growth Phase-dependent Genes in Wild Type and rpoS Mutant of Escherichia coli

  • Oh, Tae-Jeong;Jung, Il-Lae;Woo, Sook-Kyung;Kim, Myung-Soon;Lee, Sun-Woo;Kim, Keun-Ha;Kim, In-Gyu;An, Sung-Whan
    • Proceedings of the Korean Society for Applied Microbiology Conference
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    • 2004.06a
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    • pp.258-265
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    • 2004
  • Numerous genes of Escherichia coli have been shown to growth phase-dependent expression throughout growth. The global patterns of growth phase-dependent gene expression of E. coli throughout growth using oligonucleotide microarrays containing a nearly complete set of 4,289 annotated open reading frames. To determine the change of gene expression throughout growth, we compared RNAs taken from timecourses with common reference RNA, which is combined with equal amount of RNA pooled from each time point. The hierarchical clustering of the conditions in accordance with timecourse expression revealed that growth phases were clustered into four classes, consistent with known physiological growth status. We analyzed the differences of expression levels at genome level in both exponential and stationary growth phase cultures. Statistical analysis showed that 213 genes are shown to, growth phase-dependent expression. We also analyzed the expression of 256 known operons and 208 regulatory genes. To assess the global impact of RpoS, we identified 193 genes coregulated with rpoS and their expression levels were examined in the isogenic rpoS mutant. The results revealed that 99 of 193 were novel RpoS-dependent stationary phase-induced genes and the majority of those are functionally unknown. Our data provide that global changes and adjustments of gene expression are coordinately regulated by growth transition in E. coli.

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Identification of druggable genes for multiple myeloma based on genomic information

  • Rahmat Dani Satria;Lalu Muhammad Irham;Wirawan Adikusuma;Anisa Nova Puspitaningrum;Arief Rahman Afief;Riat El Khair;Abdi Wira Septama
    • Genomics & Informatics
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    • v.21 no.3
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    • pp.31.1-31.8
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    • 2023
  • Multiple myeloma (MM) is a hematological malignancy. It is widely believed that genetic factors play a significant role in the development of MM, as investigated in numerous studies. However, the application of genomic information for clinical purposes, including diagnostic and prognostic biomarkers, remains largely confined to research. In this study, we utilized genetic information from the Genomic-Driven Clinical Implementation for Multiple Myeloma database, which is dedicated to clinical trial studies on MM. This genetic information was sourced from the genome-wide association studies catalog database. We prioritized genes with the potential to cause MM based on established annotations, as well as biological risk genes for MM, as potential drug target candidates. The DrugBank database was employed to identify drug candidates targeting these genes. Our research led to the discovery of 14 MM biological risk genes and the identification of 10 drugs that target three of these genes. Notably, only one of these 10 drugs, panobinostat, has been approved for use in MM. The two most promising genes, calcium signal-modulating cyclophilin ligand (CAMLG) and histone deacetylase 2 (HDAC2), were targeted by four drugs (cyclosporine, belinostat, vorinostat, and romidepsin), all of which have clinical evidence supporting their use in the treatment of MM. Interestingly, five of the 10 drugs have been approved for other indications than MM, but they may also be effective in treating MM. Therefore, this study aimed to clarify the genomic variants involved in the pathogenesis of MM and highlight the potential benefits of these genomic variants in drug discovery.

Design of Distributed Cloud System for Managing large-scale Genomic Data

  • Seine Jang;Seok-Jae Moon
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.2
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    • pp.119-126
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    • 2024
  • The volume of genomic data is constantly increasing in various modern industries and research fields. This growth presents new challenges and opportunities in terms of the quantity and diversity of genetic data. In this paper, we propose a distributed cloud system for integrating and managing large-scale gene databases. By introducing a distributed data storage and processing system based on the Hadoop Distributed File System (HDFS), various formats and sizes of genomic data can be efficiently integrated. Furthermore, by leveraging Spark on YARN, efficient management of distributed cloud computing tasks and optimal resource allocation are achieved. This establishes a foundation for the rapid processing and analysis of large-scale genomic data. Additionally, by utilizing BigQuery ML, machine learning models are developed to support genetic search and prediction, enabling researchers to more effectively utilize data. It is expected that this will contribute to driving innovative advancements in genetic research and applications.

BaSDAS: a web-based pooled CRISPR-Cas9 knockout screening data analysis system

  • Park, Young-Kyu;Yoon, Byoung-Ha;Park, Seung-Jin;Kim, Byung Kwon;Kim, Seon-Young
    • Genomics & Informatics
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    • v.18 no.4
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    • pp.46.1-46.4
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    • 2020
  • We developed the BaSDAS (Barcode-Seq Data Analysis System), a GUI-based pooled knockout screening data analysis system, to facilitate the analysis of pooled knockout screen data easily and effectively by researchers with limited bioinformatics skills. The BaSDAS supports the analysis of various pooled screening libraries, including yeast, human, and mouse libraries, and provides many useful statistical and visualization functions with a user-friendly web interface for convenience. We expect that BaSDAS will be a useful tool for the analysis of genome-wide screening data and will support the development of novel drugs based on functional genomics information.