• Title/Summary/Keyword: number-of-expressed-genes

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Functional Classification of Gene Expression Profiles During Differentiation of Mouse Embryonic Cells on Monolayer Culture

  • Leem, Sun-Hee;Ahn, Eun-Kyung;Heo, Jeong-Hoon
    • Animal cells and systems
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    • v.13 no.2
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    • pp.235-245
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    • 2009
  • Embryonic stem (ES) cells have a capability to generate all types of cells. However, the mechanism by which ES cells differentiate into specific cell is still unclear. Using microarray technology, the differentiation process in mouse embryonic stem cells was characterized by temporal gene expression changes of mouse ES cells during differentiation in a monolayer culture. A large number of genes were differentially regulated from 1 day to 14 days, and less number of genes were differentially expressed from 14 days to 28 days. The number of up-regulated genes was linearly increased throughout the 28 days of in vitro differentiation, while the number of down-regulated genes reached the plateau from 14 days to 28 days. Most differentially expressed genes were functionally classified into transcriptional regulation, development, extra cellular matrix (ECM),cytoskeleton organization, cytokines, receptors, RNA processing, DNA replication, chromatin assembly, proliferation and apoptosis related genes. While genes encoding ECM proteins were up-regulated, most of the genes related to proliferation, chromatin assembly, DNA replication, RNA processing, and cytoskeleton organization were down-regulated at 14 days. Genes known to be associated with embryo development or transcriptional regulation were differentially expressed mostly after 14 days of differentiation. These results indicate that the altered expression of ECM genes constitute an early event during the spontaneous differentiation, followed by the inhibition of proliferation and lineage specification. Our study might identify useful time-points for applying selective treatments for directed differentiation of mouse ES cells.

Expression of Coat Color Associated Genes in Korean Brindle Cattle by Microarray Analysis

  • Lee, Hae-Lee;Park, Jae-Hee;Kim, Jong Gug
    • Journal of Embryo Transfer
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    • v.30 no.2
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    • pp.99-107
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    • 2015
  • The aim of the present study was to identify coat color associated genes that are differentially expressed in mature Korean brindle cattle (KBC) with different coat colors and in Hanwoo cows. KBC calves, before and after coat color appearance, were included. Total cellular RNA was isolated from the tail hair cells and used for microarray. The number of expressed coat color associated genes/probes was 5813 in mature KBC and Hanwoo cows. Among the expressed coat color associated genes/probes, 167 genes were the coat color associated genes listed in the Gene card database and 125 genes were the pigment and melanocyte genes listed in the Gene ontology_bovine database. There were 23 genes/probes commonly listed in both databases and their expressions were further studied. Out of the 23 genes/probes, MLPH, PMEL, TYR and TYRP1 genes were expressed at least two fold higher (p<0.01) levels in KBC with brindle color than either Hanwoo or KBC with brown color. TYRP1 expression was 22.96 or 19.89 fold higher (p<0.01) in KBC with brindle color than either Hanwoo or KBC with brown color, respectively, which was the biggest fold difference. The hierarchical clustering analysis indicated that MLPH, PMEL, TYR and TYRP1 were the highly expressed genes in mature cattle. There were only a few genes differentially expressed after coat color appearance in KBC calves. Studies on the regulation and mechanism of gene expression of highly expressed genes would be next steps to better understand coat color determination and to improve brindle coat color appearance in KBC.

Design, Optimization and Validation of Genomic DNA Microarrays for Examining the Clostridium acetobutylicum Transcriptome

  • Alsaker, Keith V.;Paredes, Carlos J.;Papoutsakis, Eleftherios T.
    • Biotechnology and Bioprocess Engineering:BBE
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    • v.10 no.5
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    • pp.432-443
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    • 2005
  • Microarray technology has contributed Significantly to the understanding of bacterial genetics and transcriptional regulation. One neglected aspect of this technology has been optimization of microarray-generated signals and quality of generated information. Full genome microarrays were developed for Clostridium acetobutylicum through spotting of PCR products that were designed with minimal homology with all other genes within the genome. Using statistical analyses it is demonstrated that Signal quality is significantly improved by increasing the hybridization volume. possibly increasing the effective number of transcripts available to bind to a given spot, while changes in labeled probe amounts were found to be less sensitive to improving signal quality. In addition to Q-RT-PCR, array validation was tested by examining the transcriptional program of a mutant (M5) strain lacking the pSOL1 178-gene megaplasmid relative to the wildtype (WT) strain. Under optimal conditions, it is demonstrated that the fraction of false positive genes is 1% when considering differentially expressed genes and 7% when considering all genes with signal above background. To enhance genomic-scale understanding of organismal physiology, using data from these microarrays we estimated that $40{\sim}55%$ of the C. acetobutylicum genome is expressed at any time during batch culture, similar to estimates made for Bacillus subtilis.

Permutation-Based Test with Small Samples for Detecting Differentially Expressed Genes (극소수 샘플에서 유의발현 유전자 탐색에 사용되는 순열에 근거한 검정법)

  • Lee, Ju-Hyoung;Song, Hae-Hiang
    • The Korean Journal of Applied Statistics
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    • v.22 no.5
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    • pp.1059-1072
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    • 2009
  • In the analysis of microarray data with a small number of arrays, the most important task is the detection of differentially expressed genes by a significance test. For this purpose, one needs to construct a null distribution based on a large number of genes and one of the best way for constructing the null distribution for a small number of arrays is by means of permutation methods. In this paper we propose simple test statistics and permutation methods that are appropriate in constructing the null distribution. In a simulation study, we compare the null distributions generated by the proposed test statistics and permutation methods with the previous ones. With an example microarray data, differentially expressed genes are determined by applying these methods.

Transcriptome profiling of the coffee (C. arabica L.) seedlings under salt stress condition

  • Haile, Mesfin;Kang, Won Hee
    • Journal of Plant Biotechnology
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    • v.45 no.1
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    • pp.45-54
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    • 2018
  • This research was conducted to study the gene expression of coffee (Coffea arabica L.) seedlings under salt stress condition. A solution of five percent ($2.3dS\;m^{-1}$) deep sea water was used for the salt treatment, and it was thereby compared to normal irrigation water ($0.2dS\;m^{-1}$) used for the control treatment. The mRNA was extracted from the leaves of the coffee seedlings for a comprehensive analysis. In this study, a total of 19,581 genes were identified and aligned to the reference sequences available in the coffee genome database. The gene ontology analysis was performed to estimate the number of genes associated with the identified biological processes, cellular components and molecular functions. Among the 19,581 genes, 7369 (37.64%) were associated with biological processes, 5909 (30.18%) with cellular components, and 5325 (27.19%) with molecular functions. The remaining 978 (4.99%) genes were therefore grouped as unclassified. A differential gene expression analysis was performed using the DESeq2 package to identify the genes that were differentially expressed between the treatments based on fold changes and p-values. Namely, a total of 611 differentially expressed genes were identified (treatment/control) in that case. Among these, 336 genes were up-regulated while 275 of the genes were down-regulated. Of the differentially expressed genes, 60 genes showed statistically significant (p < 0.05) expression, 44 of which were up-regulated and 16 which were down-regulated. We also identified 11 differentially expressed transcription factor genes, 6 of which were up-regulated and rest 5 genes were down-regulated. The data generated from this study will help in the continued interest and understanding of the responses of coffee seedlings genes associated with salinity stress, in particular. This study will also provide important resources for further functional genomics studies.

Identification of Genes Expressed during Conidial Germination of the Pepper Anthracnose Pathogen, Colletotrichum acutatum (고추 탄저병균의 포자 발아 단계 발현 유전자 동정)

  • Kim, Jeong-Hwan;Lee, Jong-Hwan;Choi, Woobong
    • Journal of Life Science
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    • v.23 no.1
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    • pp.8-14
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    • 2013
  • Genes expressed during conidial germination of the pepper anthracnose fungus Colletotrichum acutatum were identified by sequencing the 5' end of unidirectional cDNA clones prepared from the conidial germination stage. A total of 983 expressed sequence tags (ESTs) corresponding to 464 genes, 197 contigs and 267 singletons, were generated. The deduced protein sequences from half of the 464 genes showed significant matches (e value less than 10-5) to proteins in public databases. The genes with known homologs were assigned to known functional categories. The most abundantly expressed genes belonged to those encoding the elongation factor, histone protein, ATP synthease, 14-3-3 protein, and clock controlled protein. A number of genes encoding proteins such as the GTP-binding protein, MAP kinase, transaldolase, and ABC transporter were detected. These genes are thought to be involved in the development of fungal cells. A putative pathogenicity function could be assigned for the genes of ATP citrate lyase, CAP20 and manganese-superoxide dismutase.

Clustering Approaches to Identifying Gene Expression Patterns from DNA Microarray Data

  • Do, Jin Hwan;Choi, Dong-Kug
    • Molecules and Cells
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    • v.25 no.2
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    • pp.279-288
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    • 2008
  • The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

Comparison of covariance thresholding methods in gene set analysis

  • Park, Sora;Kim, Kipoong;Sun, Hokeun
    • Communications for Statistical Applications and Methods
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    • v.29 no.5
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    • pp.591-601
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    • 2022
  • In gene set analysis with microarray expression data, a group of genes such as a gene regulatory pathway and a signaling pathway is often tested if there exists either differentially expressed (DE) or differentially co-expressed (DC) genes between two biological conditions. Recently, a statistical test based on covariance estimation have been proposed in order to identify DC genes. In particular, covariance regularization by hard thresholding indeed improved the power of the test when the proportion of DC genes within a biological pathway is relatively small. In this article, we compare covariance thresholding methods using four different regularization penalties such as lasso, hard, smoothly clipped absolute deviation (SCAD), and minimax concave plus (MCP) penalties. In our extensive simulation studies, we found that both SCAD and MCP thresholding methods can outperform the hard thresholding method when the proportion of DC genes is extremely small and the number of genes in a biological pathway is much greater than a sample size. We also applied four thresholding methods to 3 different microarray gene expression data sets related with mutant p53 transcriptional activity, and epithelium and stroma breast cancer to compare genetic pathways identified by each method.

cDNA Microarray Analysis of the Gene Expression Profile of Swine Muscle

  • Kim, Chul Wook;Chang, Kyu Tae;Hong, Yeon Hee;Jung, Won Yong;Kwon, Eun Jung;Cho, Kwang Keun;Chung, Ki Hwa;Kim, Byeong Woo;Lee, Jung Gyu;Yeo, Jung Sou;Kang, Yang Su;Joo, Young Kuk
    • Asian-Australasian Journal of Animal Sciences
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    • v.18 no.8
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    • pp.1080-1087
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    • 2005
  • By screening specific genes related to the muscle growth of swine using cDNA microarray technology, a total of 5 novel genes (GF (growth factor) I, II, III, IV and V) were identified. Results of southern blotting to investigate the number of copies of these genes in the genome of swine indicated that GF I, GF III, and GF V existed as one copy and GF II, and GF IV existed as more than two copies. It was suggested that there are many isoforms of these genes in the genome of swine. Also, results of northern blotting to investigate whether these genes were expressed in grown muscle, using GF I, III, and V indicated that all the genes were much more expressed in the muscle of swine with body weight of 90 kg. Expression patterns of these genes in other organs, namely muscle and propagation and fat tissues, were investigated by extracting RNA from the tissues. These genes were not expressed in the propagation and fat tissues, but were expressed in the muscle tissue. To determine the mechanism of muscle growth, further studies should be preceded using the 3 specific genes related to muscle growth, that is GF I, III, and V.

Identification of Differentially Expressed Radiation-induced Genes in Cervix Carcinoma Cells Using Suppression Subtractive Hybridization (자궁경부암세포에서 방사선조사시 차등 발현되는 유전자 동정)

  • Kim Jun-Sang;Lee Young-Sook;Lee Jeung Hoon;Lee Woong-Hee;Seo Eun Young;Cho Moon-June
    • Radiation Oncology Journal
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    • v.23 no.1
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    • pp.43-50
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    • 2005
  • Purpose : A number of genes and their products are Induced early or late following exposure of cells to ionizing radiation. These radiation-Induced genes have various effects on irradiated cells and tissues. Suppression subtractive hybridization (SSH) based on PCR was used to Identify the differentially expressed genes by radiation in cervix carcinoma cells. Materials and Methods : Total RNA and poly $(A)^+$ mRNA were Isolated from Irradiated and non-irradiated HeLa cells. Forward- and reverse-subtracted cDNA libraries were constructed using SSH. Eighty-eight clones of each were used to randomly select differentially expressed genes using reverse Northern blotting (dot blot analysis). Northern blotting was used to verify the screened genes. Results : Of the 17t clones, 10 genes in the forward-subtracted library and 9 genes In the reverse-subtracted library were identified as differentially expressed radiation-induced genes by PCR-select differential screening. Three clones from the forward-subtracted library were confirmed by Northern blotting, and showed increased expression in a dose-dependent manner, including a telomerase catalytic subunit and sodium channel-like protein gene, and an ESTs (expressed sequence tags) gene. Conclusion : We Identified differentially expressed radiation-induced genes with low-abundance genes with SSH, but further characterization of theses genes are necessary to clarify the biological functions of them.