• Genomics & Informatics
• /
• v.1 no.1
• /
• pp.32-39
• /
• 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.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2005.09a
• /
• pp.161-164
• /
• 2005

Data mining techniques can be applied to identify patterns of interest in the gene expression data. One goal in mining gene expression data is to determine how the expression of any particular gene might affect the expression of other genes. To find relationships between different genes, association rules have been applied to gene expression data set [1]. A notable limitation of association rule mining method is that only the association in a single profile experiment can be detected. It cannot be used to find rules across different condition profiles or different time point profile experiments. However, with the appearance of time-series microarray data, it became possible to analyze the temporal relationship between genes. In this paper, we analyze the time-series microarray gene expression data to extract the sequential patterns which are similar to the association rules between genes among different time points in the yeast cell cycle. The sequential patterns found in our work can catch the associations between different genes which express or repress at diverse time points. We have applied sequential pattern mining method to time-series microarray gene expression data and discovered a number of sequential patterns from two groups of genes (test, control) and more sequential patterns have been discovered from test group (same CO term group) than from the control group (different GO term group). This result can be a support for the potential of sequential patterns which is capable of catching the biologically meaningful association between genes.

• Asian-Australasian Journal of Animal Sciences
• /
• v.17 no.9
• /
• pp.1192-1196
• /
• 2004

In order to detect the molecular mechanism of heterosis in pigs, the mRNA differential display technique was performed to investigate the differences in gene expression of pig's Longissimus dorsi between the high-parent heterosis cross combination Landrace${\times}$Large White and the mid-parent heterosis cross combination Large White${\times}$Meishan. Three pig purebreds, Large White, Meishan, and Landrace and four types of reciprocal $F_1$ hybrids were analyzed using nine 3'-end anchored primers in combination with ten 5'-end arbitrary primers and nearly 7,000 reproducible bands were examined. The patterns of gene expression of each cross combination were analyzed and eight common patterns (fifteen kinds) were found. When the results from the two cross combinations were put together and compared, eight different typical expression patterns were observed, these indicated that the patterns of gene expression of these two cross combinations had obvious differences. Gene expression correlation and cluster analyses of the two cross combinations indicated that the gene expression of the mid-parent heterosis cross combination was correlated with maternal effect, but in the high-parent heterosis cross combination, paternal effect acted in the gene expression of the hybrids or the gene expression of the hybrids was biased towards one parent.

• Journal of Periodontal and Implant Science
• /
• v.34 no.1
• /
• pp.205-221
• /
• 2004

Periodontal ligament(PDL) cells have been known as playing an important roles in periodontal regeneration and gingival fibroblasts are also important to periodontal regeneration by forming connective tissue attachment. There were rare studies about the gene expression patterns of PDL cells and gingival fibroblasts, therefore in this study, we tried cDNA microarray-based gene expression monitoring to explain the functional differences of PDL cells and gingival fibroblasts in vivo and to confirm the characteristics of PDL cells. Total RNA were extracted from PDL cells and gingival fibroblasts of same person and same passages, and mRNA were isolated from the total RNA using Oligotex mRNA midi kit(Qiagen) and then fluorescent cDNA probe were prepared. And microarray hybridization were performed. The gene expression patterns of PDL cells and gingival fibroblasts were quite different. About 400 genes were expressed more highly in the PDL cells than gingival fibroblasts and about 300 genes were more highly expressed in the gingival fibroblasts than PDL cells. Compared growth factor- and growth factor receptor-related gene expression patterns of PDL cells with gingival fibroblasts, IGF-2, IGF-2 associated protein, nerve growth factor, placental bone morphogenic protein, neuron-specific growth- associated protein, FGF receptor, EGF receptor-related gene and PDGF receptor were more highly expressed in the PDL cells than gingival fibroblasts. The results of collagen gene expression patterns showed that collagen type I, type III, type VI and type VII were more highly expressed in the PDL cells than gingival fibroblasts, and in the gingival fibroblasts collagen type V, XII were more highly expressed than PDL cells. The results of osteoblast-related gene expression patterns showed that osteoblast specific cysteine-rich protein were more highly expressed in the PDL cells than gingival fibroblasts. The results of cytoskeletal proteins gene expression patterns showed that a-smooth muscle actin, actin binding protein, smooth muscle myosin heavy chain homolog and myosin light chain were more highly expressed in the PDL cells than gingival fibrobalsts, and ${\beta}-actin$, actin-capping protein(${\beta}$ subunit), actin- related protein Arp3(ARP) and myosin class I(myh-1c) were more highly expressed in the gingival fibroblasts than PDL cells. Osteoprotegerin/osteoclastogenesis inhibitory factor(OPG/OCIF) was more highly expressed in the PDL cells than gingival fibroblasts. According to the results of this study, PDL cells and gingival fibroblasts were quite different gene expression patterns though they are the fibroblast which have similar shape. Therefore PDL cells & gingival fibroblasts are heterogeneous populations which represent distinct characteristics. If more studies about genes that were differently expressed in each PDL cells & gingival fibroblasts would be performed in the future, it would be expected that the characteristics of PDL cells would be more clear.

• BMB Reports
• /
• v.29 no.5
• /
• pp.474-480
• /
• 1996

We present a study of evolutionary changes in expression of actin genes among closely related sea urchin species that exhibit different modes of early development. For this purpose, polyclonal antisera raised against peptides from the carboxyl terminus of the HeCyI cytoskeletal actin of Heliocidaris erythrogramma were used. H. erythrogramma is a direct developing sea urchin that proceeds from embryonic to adult stages without an intervening feeding larval stage. Expression patterns of the CyI actin isoform were compared with those of Heliocidaris tuberculata and to a related sea urchin Strongylocentrotus purpuratus, which both produce a feeding pluteus larval stage. The CyI actin of all three species is expressed in the same cell types. However, its expression patterns have been changed with reorganization of early cell lineage differentiation, which is apparent among the three species. Thus. evolutionary changes in CyI actin gene expression patterns are correlated with not only phylogenetic relationship, but developmental mode. The implication of this observation is that evolutionary changes in expression patterns of histospecific genes may underlie the emergence of novel developmental processes.

• Journal of Periodontal and Implant Science
• /
• v.41 no.4
• /
• pp.167-175
• /
• 2011

Purpose: Periodontal ligament (PDL) cell differentiation into osteoblasts is important in bone formation. Bone formation is a complex biological process and involves several tightly regulated gene expression patterns of bone-related proteins. The expression patterns of bone related proteins are regulated in a temporal manner both in vivo and in vitro. The aim of this study was to observe the gene expression profile in PDL cell proliferation, differentiation, and mineralization in vitro. Methods: PDL cells were grown until confluence, which were then designated as day 0, and nodule formation was induced by the addition of 50 ${\mu}g$/mL ascorbic acid, 10 mM ${\beta}$-glycerophosphate, and 100 nM dexamethasone to the medium. The dishes were stained with Alizarin Red S on days 1, 7, 14, and 21. Real-time polymerase chain reaction was performed for the detection of various genes on days 0, 1, 7, 14, and 21. Results: On day 0 with a confluent monolayer, in the active proliferative stage, c-myc gene expression was observed at its maximal level. On day 7 with a multilayer, alkaline phosphatase, bone morphogenetic protein (BMP)-2, and BMP-4 gene expression had increased and this was followed by maximal expression of osteocalcin on day 14 with the initiation of nodule mineralization. In relationship to apoptosis, c-fos gene expression peaked on day 21 and was characterized by the post-mineralization stage. Here, various genes were regulated in a temporal manner during PDL fibroblast proliferation, extracellular matrix maturation, and mineralization. The gene expression pattern was similar. Conclusions: We can speculate that the gene expression pattern occurs during PDL cell proliferation, differentiation, and mineralization. On the basis of these results, it might be possible to understand the various factors that influence PDL cell proliferation, extracellular matrix maturation, and mineralization with regard to gene expression patterns.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2002.06a
• /
• pp.139-152
• /
• 2002

Gene-shaving(Hastie et al, 2000) is a very useful method to identify a meaningful group of genes when the variation of expression is large. By shaving off the low-correlated genes with the leading principal component, the primary genes with the coherent expression pattern can be identified. Gene-shaving method works well If expression levels are varied enough, but it may not catch the meaningful cluster in low expression level or different expression time even with coherent patterns. The sliding window gene-shaving method which is to apply gene-shaving in each sliding window after hierarchical clustering is to compensate losing a meaningful set of genes whose variation is not large but distinct. The performance to identify expression patterns is compared for the simulated profile data by the different variance and expression level.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2005.09a
• /
• pp.63-68
• /
• 2005

Transcription factors regulate gene expression by binding to gene upstream region. Each transcription factor has the specific binding site in promoter region. So the analysis of gene upstream sequence is necessary for understanding regulatory mechanism of genes, under a plausible idea that assumption that DNA sequence motif profiles are closely related to gene expression behaviors of the corresponding genes. Here, we present an effective approach to the analysis of the relation between gene expression profiles and gene upstream sequences on the basis of kernel canonical correlation analysis (kernel CCA). Kernel CCA is a useful method for finding relationships underlying between two different data sets. In the application to a yeast cell cycle data set, it is shown that gene upstream sequence profile is closely related to gene expression patterns in terms of canonical correlation scores. By the further analysis of the contributing values or weights of sequence motifs in the construction of a pair of sequence motif profiles and expression profiles, we show that the proposed method can identify significant DNA sequence motifs involved with some specific gene expression patterns, including some well known motifs and those putative, in the process of the yeast cell cycle.

• Asian-Australasian Journal of Animal Sciences
• /
• v.20 no.2
• /
• pp.153-159
• /
• 2007

In our previous study, overexpression of extracellular proteinase inhibitor (Expi) gene accelerated apoptosis of mammary epithelial cells, and induced expression of B cell activating factor (BAFF) gene. In this study, we found induction of BAFF-receptor (BAFF-R) gene expression in the Expi-transfected cells. A proliferation-inducing ligand (APRIL) gene is another TNF family member and the closest known relative of BAFF. We found induction of APRIL gene expression in the Expi-overexpressed apoptotic cells. NF-${\kappa}$B gene was also induced in the Expi-overexpressed cells. Expression patterns of BAFF and APRIL pathway-related genes were examined in in vivo mouse mammary gland at various reproductive stages. Expression levels of BAFF gene were very low at early pregnancy, increased from mid-pregnancy, and peaked at lactation, and thereafter decreased at involution stages of mammary gland. Expression of BAFF-R gene was highly induced in involution stages compared to lactation stages. Thus, expression patterns of BAFF-R gene were correlated to apoptotic status of mammary gland: active apoptosis of mammary epithelial cells occurs at involution stage of mammary gland. Expression levels of NF-${\kappa}$B gene were higher in involution stages compared to lactation stages. We analyzed mRNA levels of bcl-2 family genes from different stages of mammary development. Bcl-2 gene expression was relatively constant during lactation and involution stages. There was a slight increase in bcl-xL gene expression in involution stages compared to lactation state. Bax gene expression was highly induced in involution stage. Our results suggest that signaling pathways activated by both BAFF and ARRIL in mammary gland point towards NF-${\kappa}$B activation which causes upregulation of bax.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2001.08a
• /
• pp.77-102
• /
• 2001

Different high-throughput chip technologies are available for genome-wide gene expression studies. Quality control and prescreening analysis are important for rigorous analysis on each type of gene expression data. Statistical significance evaluation of differential expression patterns is needed. Major genome institutes develop database and analysis systems for information sharing of precious expression data.