• The Korea Genome Conference
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• 2005.09a
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• pp.93-93
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• 2005

• Proceedings of the Korean Vacuum Society Conference
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• 2006.08a
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• pp.42-42
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• 2006

• Proceedings of the PSK Conference
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• 2005.11a
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• pp.167-167
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• 2005

• Genomics & Informatics
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• v.10 no.1
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• pp.1-8
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• 2012

Recently, the technologies of DNA sequence variation and gene expression profiling have been used widely as approaches in the expertise of genome biology and genetics. The application to genome study has been particularly developed with the introduction of the nextgeneration DNA sequencer (NGS) Roche/454 and Illumina/ Solexa systems, along with bioinformation analysis technologies of whole-genome $de$ $novo$ assembly, expression profiling, DNA variation discovery, and genotyping. Both massive whole-genome shotgun paired-end sequencing and mate paired-end sequencing data are important steps for constructing $de$ $novo$ assembly of novel genome sequencing data. It is necessary to have DNA sequence information from a multiplatform NGS with at least $2{\times}$ and $30{\times}$ depth sequence of genome coverage using Roche/454 and Illumina/Solexa, respectively, for effective an way of de novo assembly. Massive shortlength reading data from the Illumina/Solexa system is enough to discover DNA variation, resulting in reducing the cost of DNA sequencing. Whole-genome expression profile data are useful to approach genome system biology with quantification of expressed RNAs from a wholegenome transcriptome, depending on the tissue samples. The hybrid mRNA sequences from Rohce/454 and Illumina/Solexa are more powerful to find novel genes through $de$ $novo$ assembly in any whole-genome sequenced species. The $20{\times}$ and $50{\times}$ coverage of the estimated transcriptome sequences using Roche/454 and Illumina/Solexa, respectively, is effective to create novel expressed reference sequences. However, only an average $30{\times}$ coverage of a transcriptome with short read sequences of Illumina/Solexa is enough to check expression quantification, compared to the reference expressed sequence tag sequence.

• Journal of Animal Science and Technology
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• v.63 no.4
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• pp.854-863
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• 2021

Weaning induces physiological changes in intestinal development that affect pigs' growth performance and susceptibility to disease. As a posttranscriptional regulator, microRNAs (miRNAs) regulate cellular homeostasis during intestinal development. We performed small RNA expression profiling in the small intestine of piglets before weaning (BW), 1 week after weaning (1W), and 2 weeks after weaning (2W) to identify weaning-associated differentially expressed miRNAs. We identified 38 differentially expressed miRNAs with varying expression levels among BW, 1W, and 2W. Then, we classified expression patterns of the identified miRNAs into four types. ssc-miR-196a and ssc-miR-451 represent pattern 1, which had an increased expression at 1W and a decreased expression at 2W. ssc-miR-499-5p represents pattern 2, which had an increased expression at 1W and a stable expression at 2W. ssc-miR-7135-3p and ssc-miR-144 represent pattern 3, which had a stable expression at 1W and a decreased expression at 2W. Eleven miRNAs (ssc-miR-542-3p, ssc-miR-214, ssc-miR-758, ssc-miR-4331, ssc-miR-105-1, ssc-miR-1285, ssc-miR-10a-5p, ssc-miR-4332, ssc-miR-503, ssc-miR-6782-3p, and ssc-miR-424-5p) represent pattern 4, which had a decreased expression at 1W and a stable expression at 2W. Moreover, we identified 133 candidate targets for miR-196a using a target prediction database. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that the target genes were associated with 19 biological processes, 4 cellular components, 8 molecular functions, and 7 KEGG pathways, including anterior/posterior pattern specification as well as the cancer, PI3K-Akt, MAPK, GnRH, and neurotrophin signaling pathways. These findings suggest that miRNAs regulate the development of the small intestine during the weaning process in piglets by anterior/posterior pattern specification as well as the cancer, PI3K-Akt, MAPK, GnRH, and neurotrophin signaling pathways.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.155-160
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• 2016

Breast cancer (BC) is the second most common cancer in the world and by far the most frequent cancer among women, with an estimated 1.67 million new cancer cases diagnosed in 2012 (25% of all cancers). Polygene expression analysis is used to predict the prognosis and determine the most appropriate treatment regimen. The objective of this study was to examine the gene expression profiles of SIRT3, HRAS, LSP1, SCUBE2 and AP2A2 in Iranian women with BC.A total of 136 patients including healthy controls were categorized into three groups based on the relapse of the disease. Expression of desired genes in formalin-fixed, paraffin embedded tissues collected from all groups of participants was analyzed via the RT PCR method. RNA extraction and cDNA synthesis were performed then real-time quantitative PCR was carried out. Gene expression analysis revealed that the expression of SIRT3 was equal among patient and control groups. LSP1 was down regulated in all patient groups relative to controls but reduced expression in the metastatic group relative to the non-metastatic one was not significant. HRAS was significantly overexpressed in total and metastatic tumor samples versus normal but not in non-metastatic cases. SCUBE2 expression showed significant over-expression in both overall tumor samples and the non-metastatic group as compared to normal tissues. Gene expression level of AP2A2 in all groups was not detectable. Our data are compatible with a tumor suppressor role of LSP1 related to potential prognostic factor for tumor recurrence and outcome. This study for the first time assayed the prognostic value and changes in the expression of SIRT3, LSP1, HRAS, SCUBE2 and AP2A2 genes in women with breast cancer in the Iranian population and findings confirmed potential biomarker and prognostic capability of these genes. Such expression profiling data can critically improve prognosis and treatment decisions in cancer patients.

• The Plant Pathology Journal
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• v.24 no.4
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• pp.384-391
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• 2008

Rice blast disease, caused by the pathogenic fungus Magnaporthe grisea, is a serious issue in rice (Oryza sativa L.) growing regions of the world. Transcript profiling in rice inoculated with the fungus has been investigated using the transcriptomics technology, serial analysis of gene expression (SAGE). Short sequence tags containing sufficient information which are ten base-pairs representing the unique transcripts were identified by SAGE technology. We identified a total of 910 tag sequences via the GenBank database, and the resulting genes were shown to be up-regulated in all functional categories under the fungal biotic stress. Compared to the compatible interaction, the stress and defense genes in the incompatible interaction appear to be more up-regulated. Particularly, thaumatin-like gene (TLP) was investigated in determining the gene and protein expression level utilizing Northern and Western blotting analyses, resulting in an increase in both the gene and the protein expression level which arose earlier in the incompatible interaction than in the compatible interaction.

• BMB Reports
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• v.46 no.11
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• pp.539-543
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• 2013

There is a correlation between obesity and the amount of brown adipose tissue; however, the molecular mechanism of brown adipogenic differentiation has not been as extensively studied. In this study, we performed a protein tyrosine phosphatase (PTP) profiling analysis during the brown adipogenic differentiation of mouse primary brown preadipocytes. Several PTPs, including PTPRF, PTPRZ, and DUSP12 showing differential expression patterns were identified. In the case of DUSP12, the expression level is dramatically downregulated during brown adipogenesis. The ectopic expression of DUSP12 using a retroviral expression system induces the suppression of adipogenic differentiation, whereas a catalytic inactive DUSP12 mutant showed no effect on differentiation. These results suggest that DUSP12 is involved in brown adipogenic differentiation and may be used as a target protein for the treatment or prevention of obesity by the regulation of brown adipogenic differentiation.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.3027-3033
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• 2022

Background: In this study, various types of deep-learning models for predicting in vitro radiosensitivity from gene-expression profiling were compared. Methods: The clonogenic surviving fractions at 2 Gy from previous publications and microarray gene-expression data from the National Cancer Institute-60 cell lines were used to measure the radiosensitivity. Seven different prediction models including three distinct multi-layered perceptrons (MLP), four different convolutional neural networks (CNN) were compared. Folded cross-validation was applied to train and evaluate model performance. The criteria for correct prediction were absolute error < 0.02 or relative error < 10%. The models were compared in terms of prediction accuracy, training time per epoch, training fluctuations, and required calculation resources. Results: The strength of MLP-based models was their fast initial convergence and short training time per epoch. They represented significantly different prediction accuracy depending on the model configuration. The CNN-based models showed relatively high prediction accuracy, low training fluctuations, and a relatively small increase in the memory requirement as the model deepens. Conclusion: Our findings suggest that a CNN-based model with moderate depth would be appropriate when the prediction accuracy is important, and a shallow MLP-based model can be recommended when either the training resources or time are limited.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.2
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• pp.105-112
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• 2023

Leucine-rich repeat kinase 2 (LRRK2) is known to play a crucial role in the pathophysiology of neurodegenerative disorders such as Parkinson's disease. LRRK2 is predominantly expressed in the lung as well as the brain. However, it is unclear whether LRRK2 expression correlates with the pathogenesis of lung squamous cell carcinoma (LUSC). This study analyzes the prognostic significance of LRRK2 in LUSC using the Kaplan-Meier plotter tool. High expression of LRRK2 is known to be associated with a bad prognosis in patients with LUSC. Patients with high LRRK2 expression, tumor mutational burden, high neoantigen load, and even gender correlation reportedly have the worse survival rates. In the gene expression profiling interactive analysis (GEPIA) database, the severity of pathogenesis in LUSC with high LRRK2 expression positively corresponds to a high expression of anti-inflammatory cytokines but not inflammatory cytokines. Similarly, the increased expression of interleukin (IL)10-related genes was shown to be significantly linked in LRRK2-high LUSC patients having a poor prognosis. Moreover, the tumor immune estimation resource (TIMER) database suggests that macrophages are one of the cellular sources of IL10 in LRRK2-high LUSC patients. Collectively, our results demonstrate that the postulated LRRK2-IL10 axis is a potential therapeutic target and prognostic biomarker for LUSC.