• Title/Summary/Keyword: Gene organization

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Cell line-specific features of 3D chromatin organization in hepatocellular carcinoma

  • Yeonwoo Kim;Hyeokjun Yang;Daeyoup Lee
    • Genomics & Informatics
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    • v.21 no.2
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    • pp.19.1-19.13
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    • 2023
  • Liver cancer, particularly hepatocellular carcinoma (HCC), poses a significant global threat to human lives. To advance the development of innovative diagnostic and treatment approaches, it is essential to examine the hidden features of HCC, particularly its 3D genome architecture, which is not well understood. In this study, we investigated the 3D genome organization of four HCC cell lines-Hep3B, Huh1, Huh7, and SNU449-using in situ Hi-C and assay for transposase-accessible chromatin sequencing. Our findings revealed that HCC cell lines had more long-range interactions, both intra-and interchromosomal, compared to human mammary epithelial cells (HMECs). Unexpectedly, HCC cell lines displayed cell line-specific compartmental modifications at the megabase (Mb) scale, which could potentially be leveraged in determining HCC subtypes. At the sub-Mb scale, we observed decreases in intra-TAD (topologically associated domain) interactions and chromatin loops in HCC cell lines compared to HMECs. Lastly, we discovered a correlation between gene expression and the 3D chromatin architecture of SLC8A1, which encodes a sodium-calcium antiporter whose modulation is known to induce apoptosis by comparison between HCC cell lines and HMECs. Our findings suggest that HCC cell lines have a distinct 3D genome organization that is different from those of normal and other cancer cells based on the analysis of compartments, TADs, and chromatin loops. Overall, we take this as evidence that genome organization plays a crucial role in cancer phenotype determination. Further exploration of epigenetics in HCC will help us to better understand specific gene regulation mechanisms and uncover novel targets for cancer treatment.

Efficient Strategy to Identify Gene-Gene Interactions and Its Application to Type 2 Diabetes

  • Li, Donghe;Wo, Sungho
    • Genomics & Informatics
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    • v.14 no.4
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    • pp.160-165
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    • 2016
  • Over the past decade, the detection of gene-gene interactions has become more and more popular in the field of genome-wide association studies (GWASs). The goal of the GWAS is to identify genetic susceptibility to complex diseases by assaying and analyzing hundreds of thousands of single-nucleotide polymorphisms. However, such tests are computationally demanding and methodologically challenging. Recently, a simple but powerful method, named "BOolean Operation-based Screening and Testing" (BOOST), was proposed for genome-wide gene-gene interaction analyses. BOOST was designed with a Boolean representation of genotype data and is approximately equivalent to the log-linear model. It is extremely fast, and genome-wide gene-gene interaction analyses can be completed within a few hours. However, BOOST can not adjust for covariate effects, and its type-1 error control is not correct. Thus, we considered two-step approaches for gene-gene interaction analyses. First, we selected gene-gene interactions with BOOST and applied logistic regression with covariate adjustments to select gene-gene interactions. We applied the two-step approach to type 2 diabetes (T2D) in the Korea Association Resource (KARE) cohort and identified some promising pairs of single-nucleotide polymorphisms associated with T2D.

GSnet: An Integrated Tool for Gene Set Analysis and Visualization

  • Choi, Yoon-Jeong;Woo, Hyun-Goo;Yu, Ung-Sik
    • Genomics & Informatics
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    • v.5 no.3
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    • pp.133-136
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    • 2007
  • The Gene Set network viewer (GSnet) visualizes the functional enrichment of a given gene set with a protein interaction network and is implemented as a plug-in for the Cytoscape platform. The functional enrichment of a given gene set is calculated using a hypergeometric test based on the Gene Ontology annotation. The protein interaction network is estimated using public data. Set operations allow a complex protein interaction network to be decomposed into a functionally-enriched module of interest. GSnet provides a new framework for gene set analysis by integrating a priori knowledge of a biological network with functional enrichment analysis.

An information-theoretical analysis of gene nucleotide sequence structuredness for a selection of aging and cancer-related genes

  • Blokh, David;Gitarts, Joseph;Stambler, Ilia
    • Genomics & Informatics
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    • v.18 no.4
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    • pp.41.1-41.8
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    • 2020
  • We provide an algorithm for the construction and analysis of autocorrelation (information) functions of gene nucleotide sequences. As a measure of correlation between discrete random variables, we use normalized mutual information. The information functions are indicative of the degree of structuredness of gene sequences. We construct the information functions for selected gene sequences. We find a significant difference between information functions of genes of different types. We hypothesize that the features of information functions of gene nucleotide sequences are related to phenotypes of these genes.

Current trends of stem cell-mediated gene therapy (줄기 세포 분야의 유전자 치료 연구 동향)

  • Oh, Yu-Kyoung;Chung, Hyung-Min
    • Journal of Pharmaceutical Investigation
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    • v.32 no.2
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    • pp.65-72
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    • 2002
  • Recently, stem cell-mediated gene therapy is emerging as a novel therapeutic approach. For the successful gene modification of stem cells, the development of a suitable gene transfer technique needs to be preceded. This review focuses on the various gene transfer techniques based on nonviral and viral vectors, and physical methods. The advantages and disadvantages of each gene transfer method are compared, and the general properties of these vectors are discussed in relation to the gene transfer in stem cell research. This review also highlights the therapeutic application of stem cell-mediated gene therapy. The choice of gene transfer vectors may vary depending on the type of the stem cells and the target of stem cell therapy. Of various gene transfer methods, viral vector-based gene therapy has been emphasized due to the higher transfection efficiency. The current status and up-to-date findings of stem cell-mediated gene therapy are discussed in the viewpoint of the various targets of stem cell therapy such as the modification of stem cell potency, the acceleration of regeneration process and the formation of expressional organization.

HOTAIR Long Non-coding RNA: Characterizing the Locus Features by the In Silico Approaches

  • Hajjari, Mohammadreza;Rahnama, Saghar
    • Genomics & Informatics
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    • v.15 no.4
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    • pp.170-177
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    • 2017
  • HOTAIR is an lncRNA that has been known to have an oncogenic role in different cancers. There is limited knowledge of genetic and epigenetic elements and their interactions for the gene encoding HOTAIR. Therefore, understanding the molecular mechanism and its regulation remains to be challenging. We used different in silico analyses to find genetic and epigenetic elements of HOTAIR gene to gain insight into its regulation. We reported different regulatory elements including canonical promoters, transcription start sites, CpGIs as well as epigenetic marks that are potentially involved in the regulation of HOTAIR gene expression. We identified repeat sequences and single nucleotide polymorphisms that are located within or next to the CpGIs of HOTAIR. Our analyses may help to find potential interactions between genetic and epigenetic elements of HOTAIR gene in the human tissues and show opportunities and limitations for researches on HOTAIR gene in future studies.

Gene Expression Pattern Analysis via Latent Variable Models Coupled with Topographic Clustering

  • Chang, Jeong-Ho;Chi, Sung Wook;Zhang, Byoung Tak
    • Genomics & Informatics
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    • v.1 no.1
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    • pp.32-39
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    • 2003
  • We present a latent variable model-based approach to the analysis of gene expression patterns, coupled with topographic clustering. Aspect model, a latent variable model for dyadic data, is applied to extract latent patterns underlying complex variations of gene expression levels. Then a topographic clustering is performed to find coherent groups of genes, based on the extracted latent patterns as well as individual gene expression behaviors. Applied to cell cycle­regulated genes of the yeast Saccharomyces cerevisiae, the proposed method could discover biologically meaningful patterns related with characteristic expression behavior in particular cell cycle phases. In addition, the display of the variation in the composition of these latent patterns on the cluster map provided more facilitated interpretation of the resulting cluster structure. From this, we argue that latent variable models, coupled with topographic clustering, are a promising tool for explorative analysis of gene expression data.

Investigation of gene-gene interactions of clock genes for chronotype in a healthy Korean population

  • Park, Mira;Kim, Soon Ae;Shin, Jieun;Joo, Eun-Jeong
    • Genomics & Informatics
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    • v.18 no.4
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    • pp.38.1-38.9
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    • 2020
  • Chronotype is an important moderator of psychiatric illnesses, which seems to be controlled in some part by genetic factors. Clock genes are the most relevant genes for chronotype. In addition to the roles of individual genes, gene-gene interactions of clock genes substantially contribute to chronotype. We investigated genetic associations and gene-gene interactions of the clock genes BHLHB2, CLOCK, CSNK1E, NR1D1, PER1, PER2, PER3, and TIMELESS for chronotype in 1,293 healthy Korean individuals. Regression analysis was conducted to find associations between single nucleotide polymorphism (SNP) and chronotype. For gene-gene interaction analyses, the quantitative multifactor dimensionality reduction (QMDR) method, a nonparametric model-free method for quantitative phenotypes, were performed. No individual SNP or haplotype showed a significant association with chronotype by both regression analysis and single-locus model of QMDR. QMDR analysis identified NR1D1 rs2314339 and TIMELESS rs4630333 as the best SNP pairs among two-locus interaction models associated with chronotype (cross-validation consistency [CVC] = 8/10, p = 0.041). For the three-locus interaction model, the SNP combination of NR1D1 rs2314339, TIMELESS rs4630333, and PER3 rs228669 showed the best results (CVC = 4/10, p < 0.001). However, because the mean differences between genotype combinations were minor, the clinical roles of clock gene interactions are unlikely to be critical.

Cloning and Organization of the Ribosomal RNA Genes of the Mushroom Trichloma matsutake

  • Hwang, Seon-Kap;Kim, Jong-Guk
    • Journal of Microbiology and Biotechnology
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    • v.5 no.4
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    • pp.194-199
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    • 1995
  • A portion (7.4 kb) of ribosomal DNA tandem repeat unit from a genome of the mushroom T. matsutake has been cloned. A 1.75 kb EcoRI fragment was cloned first using S. cerevisiae 255 rRNA gene as a probe, and this was then used for further cloning. A chromosomal walking experiment was carried out and the upstream region of the 1.75 kb fragment was cloned using SmaI/BamHI enzyme, the size was estimated to be 5.2 kb in length. Part of the downstream region of the 1.75 kb fragment was also cloned using XbaI/BamHI enzymes. Restriction enzyme maps of three cloned DNA fragments were constructed. Northern hybridization, using total RNA of T. matsutake, and the restriction fragments of three cloned DNAs as probes, revealed that all four ribosomal RNA genes (large subunit[LSU], small subunit [SSU], 5.85 and 5S rRNA genes) are present in the cloned region. The gene organization of the rDNA are regarded as an intergenic spacer [IGS]2 (partial) - SSU rRNA - internal transcribed spacer [ITS]1 - 5.8S rRNA - ITS2 - LSU rRNA - IGS1 -5S rRNA - IG52 (partial).

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