• Title/Summary/Keyword: Gene Expression

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Effect of Transposable Element Insertion on Gene Expression (Transposable Element 삽입의 유전자 발현에 미치는 영향)

  • 김화영
    • Proceedings of the Botanical Society of Korea Conference
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    • pp.349-356
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    • 1987
  • Insertions of transposable elements in or near a structural gene give rise to null phenotypes, reduced levels of gene expression, or alteration on the tissue-specific pattern of gene expression. Null phenotypes often result from insertions in exons. Reduced levels of gene expression results from insertions in various regions such as promoter region, 5' non-translated region, exon and intron. The maize allele of Adh1-3F1124 is an example of alteration in the tissue-specific patetern of gene expression. Adh1-3F1124 contains a Mu element inserted 31 bp 5' to the transcriptional start site of the wild-type Adh1 activity in seeds and anaerobically-treated seedlings but normal levels in the pollen. Upon the insertion of a transposable element a certain number of host DNA sequences at the insertion site is duplcated. When transposable elements excise, all element sequences are deleted. However, the duplicated host sequences may be left intact or deleted to various extents. This results in null phenotypes, restoration of original levels of gene expression, or altered levels of gene expression. On the basis of effects of transposable-element insertions or excisions on gene expression, the usefulness of transposable ellements for studies on gene expression is discussed.

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Analysis and Subclass Classification of Microarray Gene Expression Data Using Computational Biology (전산생물학을 이용한 마이크로어레이의 유전자 발현 데이터 분석 및 유형 분류 기법)

  • Yoo, Chang-Kyoo;Lee, Min-Young;Kim, Young-Hwang;Lee, In-Beum
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.10
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    • pp.830-836
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    • 2005
  • Application of microarray technologies which monitor simultaneously the expression pattern of thousands of individual genes in different biological systems results in a tremendous increase of the amount of available gene expression data and have provided new insights into gene expression during drug development, within disease processes, and across species. There is a great need of data mining methods allowing straightforward interpretation, visualization and analysis of the relevant information contained in gene expression profiles. Specially, classifying biological samples into known classes or phenotypes is an important practical application for microarray gene expression profiles. Gene expression profiles obtained from tissue samples of patients thus allowcancer classification. In this research, molecular classification of microarray gene expression data is applied for multi-class cancer using computational biology such gene selection, principal component analysis and fuzzy clustering. The proposed method was applied to microarray data from leukemia patients; specifically, it was used to interpret the gene expression pattern and analyze the leukemia subtype whose expression profiles correlated with four cases of acute leukemia gene expression. A basic understanding of the microarray data analysis is also introduced.

Nutritional and Tissue Specificity of IGF-I and IGFBP-2 Gene Expression in Growing Chickens - A Review -

  • Kita, K.;Nagao, K.;Okumura, J.
    • Asian-Australasian Journal of Animal Sciences
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    • v.18 no.5
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    • pp.747-754
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    • 2005
  • Nutritional regulation of gene expression associated with growth and feeding behavior in avian species can become an important technique to improve poultry production according to the supply of nutrients in the diet. Insulin-like growth factor-I (IGF-I) found in chickens has been characterized to be a 70 amino acid polypeptide and plays an important role in growth and metabolism. Although it is been well known that IGF-I is highly associated with embryonic development and post-hatching growth, changes in the distribution of IGF-I gene expression throughout early- to late-embryogenesis have not been studied so far. We revealed that the developmental pattern of IGF-I gene expression during embryogenesis differed among various tissues. No bands of IGF-I mRNA were detected in embryonic liver at 7 days of incubation, and thereafter the amount of hepatic IGF-I mRNA was increased from 14 to 20 days of incubation. In eyes, a peak in IGF-I mRNA levels occurred at mid-embryogenesis, but by contrast, IGF-I mRNA was barely detectable in the heart throughout all incubation periods. In the muscle, no significant difference in IGF-I gene expression was observed during different stages of embryogenesis. After hatching, hepatic IGF-I gene expression as well as plasma IGF-I concentration increases rapidly with age, reaches a peak before sexual maturity, and then declines. The IGF-I gene expression is very sensitive to changes in nutritional conditions. Food-restriction and fasting decreased hepatic IGF-I gene expression and refeeding restored IGF-I gene expression to the level of fed chickens. Dietary protein is also a very strong factor in changing hepatic IGF-I gene expression. Refeeding with dietary protein alone successfully restored hepatic IGF-I gene expression of fasted chickens to the level of fed controls. In most circumstances, IGF-I makes a complex with specific high-affinity IGF-binding proteins (IGFBPs). So far, four different IGFBPs have been identified in avian species and the major IGFBP in chicken plasma has been reported to be IGFBP-2. We studied the relationship between nutritional status and IGFBP-2 gene expression in various tissues of young chickens. In the liver of fed chickens, almost no IGFBP-2 mRNA was detected. However, fasting markedly increased hepatic IGFBP-2 gene expression, and the level was reduced after refeeding. In the gizzard of well-fed young chickens, IGFBP-2 gene expression was detected and fasting significantly elevated gizzard IGFBP-2 mRNA levels to about double that of fed controls. After refeeding, gizzard IGFBP-2 gene expression decreased similar to hepatic IGFBP-2 gene expression. In the brain, IGFBP-2 mRNA was observed in fed chickens and had significantly decreased by fasting. In the kidney, IGFBP-2 gene expression was observed but not influenced by fasting and refeeding. Recently, we have demonstrated in vivo that gizzard and hepatic IGFBP-2 gene expression in fasted chickens was rapidly reduced by intravenous administration of insulin, as indicated that in young chickens the reduction in gizzard and hepatic IGFBP-2 gene expression in vivo stimulated by malnutrition may be, in part, regulated by means of the increase in plasma insulin concentration via an insulin-response element. The influence of dietary protein source (isolated soybean protein vs. casein) and the supplementation of essential amino acids on gizzard IGFBP-2 gene expression was examined. In both soybean protein and casein diet groups, the deficiency of essential amino acids stimulated chickens to increase gizzard IGFBP-2 gene expression. Although amino acid supplementation of a soybean protein diet significantly decreased gizzard IGFBP-2 mRNA levels, a similar reduction was not observed in chickens fed a casein diet supplemented with amino acids. This overview of nutritional regulation of IGF-I and IGFBP-2 gene expression in young chickens would serve for the establishment of the supply of nutrients to diets to improve poultry production.

A Unique Gene Expression Signature of 5-fluorouracil

  • Kim, Ja-Eun;Yoo, Chang-Hyuk;Park, Dong-Yoon;Lee, Han-Yong;Yoon, Jeong-Ho;Kim, Se-Nyun
    • Molecular & Cellular Toxicology
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    • v.1 no.4
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    • pp.248-255
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    • 2005
  • To understand the response of cancer cells to anticancer drugs at the gene expression level, we examined the gene expression changes in response to five anticancer drugs, 5-fluorouracil, cytarabine, cisplatin, paclitaxel, and cytochalasin D in NCI-H460 human lung cancer cells. Of the five drugs, 5-fluorouracil had the most distinctive gene expression signature. By clustering genes whose expression changed significantly, we identified three clusters with unique gene expression patterns. The first cluster reflected the up-regulation of gene expression by cisplatin, and included genes involved in cell death and DNA repair. The second cluster pointed to a general reduction of gene expression by most of the anticancer drugs tested. A number of genes in this cluster are involved in signal transduction that is important for communication between cells and reception of extracellular signals. The last cluster represented reduced gene expression in response to 5-fluorouracil, the genes involved being implicated in DNA metabolism, the cell cycle, and RNA processing. Since the gene expression signature of 5-fluorouracil was unique, we investigated it in more detail. Significance analysis of microarray data (SAM) identified 808 genes whose expression was significantly altered by 5-fluorouracil. Among the up-regulated genes, those affecting apoptosis were the most noteworthy. The down-regulated genes were mainly associated with transcription-and translation-related processes which are known targets of 5-fluorouracil. These results suggest that the gene expression signature of an anticancer drug is closely related to its physiological action and the response of caner cells.

Reverting Gene Expression Pattern of Cancer into Normal-Like Using Cycle-Consistent Adversarial Network

  • Lee, Chan-hee;Ahn, TaeJin
    • International Journal of Advanced Culture Technology
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    • v.6 no.4
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    • pp.275-283
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    • 2018
  • Cancer show distinct pattern of gene expression when it is compared to normal. This difference results malignant characteristic of cancer. Many cancer drugs are targeting this difference so that it can selectively kill cancer cells. One of the recent demand for personalized treating cancer is retrieving normal tissue from a patient so that the gene expression difference between cancer and normal be assessed. However, in most clinical situation it is hard to retrieve normal tissue from a patient. This is because biopsy of normal tissues may cause damage to the organ function or a risk of infection or side effect what a patient to take. Thus, there is a challenge to estimate normal cell's gene expression where cancers are originated from without taking additional biopsy. In this paper, we propose in-silico based prediction of normal cell's gene expression from gene expression data of a tumor sample. We call this challenge as reverting the cancer into normal. We divided this challenge into two parts. The first part is making a generator that is able to fool a pretrained discriminator. Pretrained discriminator is from the training of public data (9,601 cancers, 7,240 normals) which shows 0.997 of accuracy to discriminate if a given gene expression pattern is cancer or normal. Deceiving this pretrained discriminator means our method is capable of generating very normal-like gene expression data. The second part of the challenge is to address whether generated normal is similar to true reverse form of the input cancer data. We used, cycle-consistent adversarial networks to approach our challenges, since this network is capable of translating one domain to the other while maintaining original domain's feature and at the same time adding the new domain's feature. We evaluated that, if we put cancer data into a cycle-consistent adversarial network, it could retain most of the information from the input (cancer) and at the same time change the data into normal. We also evaluated if this generated gene expression of normal tissue would be the biological reverse form of the gene expression of cancer used as an input.

Enhancing Gene Expression Classification of Support Vector Machines with Generative Adversarial Networks

  • Huynh, Phuoc-Hai;Nguyen, Van Hoa;Do, Thanh-Nghi
    • Journal of information and communication convergence engineering
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    • v.17 no.1
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    • pp.14-20
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    • 2019
  • Currently, microarray gene expression data take advantage of the sufficient classification of cancers, which addresses the problems relating to cancer causes and treatment regimens. However, the sample size of gene expression data is often restricted, because the price of microarray technology on studies in humans is high. We propose enhancing the gene expression classification of support vector machines with generative adversarial networks (GAN-SVMs). A GAN that generates new data from original training datasets was implemented. The GAN was used in conjunction with nonlinear SVMs that efficiently classify gene expression data. Numerical test results on 20 low-sample-size and very high-dimensional microarray gene expression datasets from the Kent Ridge Biomedical and Array Expression repositories indicate that the model is more accurate than state-of-the-art classifying models.

Effects of Ginseng Saponin on the Cytokine Gene Expression in Human Immune System (인삼 사포닌이 인간면역계 사이토카인 유전자의 발현에 미치는 영향)

  • 박종욱;한인숙
    • Journal of Ginseng Research
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    • v.20 no.1
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    • pp.15-22
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    • 1996
  • In order to investigate the Immunomodulatory effects of ginseng, we have studied the effects of ginseng saponin on the proliferation and cytosine gene expression of human pheripheral blood mononuclear cell (PBMC). In the PBMC proliferation assay, total saponin exhibited proliferation inhibition on the PBMC or phytohemagglutinin(PHA)-stimulated PBMC in a dose-dependent fashion. Immunomodulatory effects of ginseng were further investigated using the cytokine gene expression as the indicators. In the reverse transcription-polymerase chain reaction (RT-PCR) test, interleukin (IL)-1, IL-2, IL-3, IL-4, IL-6, IL-13, granulocyte macrophage-colony stimulating factor, tumor necrosis factor (TNF), migration inhibitory factor and transforming growth factor genes were expressed in the PHA-stimulated PBMC 48 hrs after cell culture. Among expressed cytokines, total saponin could increase the expression of IL-1 and TNF of PBMC without stimulation of PHA. All of ginsenosides, $Rb_1$, $Rb_2$, $Rg_1$, Rc, Re, incresed TNF gene expression. Especially, Rb2 (20 g/ml) showed most prominent effect on TNF gene expression and it also slightly increased IL-1 gene expression of PBMC.

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