• Asian-Australasian Journal of Animal Sciences
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• 제32권4호
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• pp.508-518
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• 2019

Objective: This research aimed to determine biological pathways and protein-protein interaction (PPI) networks for 305-d milk yield (MY), 305-d fat yield (FY), and age at first calving (AFC) in the Thai multibreed dairy population. Methods: Genotypic information contained 75,776 imputed and actual single nucleotide polymorphisms (SNP) from 2,661 animals. Single-step genomic best linear unbiased predictions were utilized to estimate SNP genetic variances for MY, FY, and AFC. Fixed effects included herd-year-season, breed regression and heterosis regression effects. Random effects were animal additive genetic and residual. Individual SNP explaining at least 0.001% of the genetic variance for each trait were used to identify nearby genes in the National Center for Biotechnology Information database. Pathway enrichment analysis was performed. The PPI of genes were identified and visualized of the PPI network. Results: Identified genes were involved in 16 enriched pathways related to MY, FY, and AFC. Most genes had two or more connections with other genes in the PPI network. Genes associated with MY, FY, and AFC based on the biological pathways and PPI were primarily involved in cellular processes. The percent of the genetic variance explained by genes in enriched pathways (303) was 2.63% for MY, 2.59% for FY, and 2.49% for AFC. Genes in the PPI network (265) explained 2.28% of the genetic variance for MY, 2.26% for FY, and 2.12% for AFC. Conclusion: These sets of SNP associated with genes in the set enriched pathways and the PPI network could be used as genomic selection targets in the Thai multibreed dairy population. This study should be continued both in this and other populations subject to a variety of environmental conditions because predicted SNP values will likely differ across populations subject to different environmental conditions and changes over time.

• 한국컴퓨터정보학회논문지
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• 제15권12호
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• pp.197-207
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• 2010

대용량(High-throughput) 형태로 얻어진 cDNA 마이크로어레이 데이터에 다양한 데이터 마이닝 기법을 적용하면 서로 다른 조직에서 추출한 유전자의 발현정도를 비교할 수 있고 정상세포와 암세포에서 발현량의 차이를 보이는 DEG(Differently Expression Gene) 유전자를 추출할 수 있다. 이들을 이용하여 병을 진단할 수 있을 뿐만 아니라, 암의 진행 단계(Cancer Stage)에 따른 치료 방법을 결정할 수 있다. 마이크로어레이를 기반으로 한 대부분의 암 분류자는 기계학습 기법을 이용하여 암 관련 유전자를 추출하여, 이들 유전자를 총체적으로 이용하여 독립 샘플의 클래스(암, 정상)를 판정한다. 하지만 유전자의 발현량의 차이뿐만 아니라 유전자와 유전자의 상관관계의 변화가 질병 진단에 활용될 수 있다. 대부분의 질병은 단독 유전자의 변이에 의한 것이 아니라 유전자의 모듈로 이루어진 유전자조절네트워크의 변이에 의한 것이기 때문이다. 본 논문에서는 조건에 따라 특이적 관계를 나타내는 유전자 쌍을 식별하여, 이들 유전자 쌍을 이용한 유전자 분류 모듈을 생성한다. 분류 모듈을 이용한 암 분류 방법이 기존의 암 분류 방법보다 높은 정확도로 암과정상 샘플을 분류함을 보여주고 있다. 분류 모듈을 구성하는 유전자의 수가 상대적으로 적으므로 임상키트로의 개발도 고려할 수 있다. 향후 분류 모듈에 속하는 유전자의 기능적 검증을, GO(Gene Ontology)를 활용함으로서, 밝혀지지 않은 새로운 암 관련 유전자를 식별하고, 분류 모듈을 확대하여 암 특이적 유전자조절네트워크 구성에 활용할 계획이다.

• 대한한의학회지
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• 제45권1호
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• pp.114-125
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• 2024

Objectives: Network pharmacology is an analysis method that explores drug-centered efficacy and mechanism by constructing a compound-target-disease network based on system biology, and is attracting attention as a methodology for studying herbal medicine that has the characteristics for multi-compound therapeutics. Thus, we investigated the potential functions and pathways of Myrrha on Allergic Rhinitis (AR) via network pharmacology analysis and molecular docking. Methods: Using public databases and PubChem database, compounds of Myrrha and their target genes were collected. The putative target genes of Myrrha and known target genes of AR were compared and found the correlation. Then, the network was constructed using STRING database, and functional enrichment analysis was conducted based on the Gene Ontology (GO) Biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways. Binding-Docking stimulation was performed using CB-Dock. Results: The result showed that total 3 compounds and 55 related genes were gathered from Myrrha. 33 genes were interacted with AR gene set, suggesting that the effects of Myrrha are closely related to AR. Target genes of Myrrha are considerably associated with various pathways including 'Fc epsilon RI signaling pathway' and 'JAK-STAT signaling pathway'. As a result of blinding docking, AKT1, which is involved in both mechanisms, had high binding energies for abietic acid and dehydroabietic acid, which are components of Myrrha. Conclusion: Through a network pharmacological method, Myrrha was predicted to have high relevance with AR by regulating AKT1. This study could be used as a basis for studying therapeutic effects of Myrrha on AR.

• 대한한의학방제학회지
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• 제30권3호
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• pp.175-182
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• 2022

Objective : This study aims to investigate the active ingredients and potential mechanisms of the beneficial herb on human cancers such as the liver by employing network pharmacology. Methods : Ingredients and their target information was obtained from various databases such as TM-MC, TTD, and Drugbank. Related protein for liver cancer was retrieved from the Comparative Toxicogenomics Database and literature. A hypergeometric test and gene set enrichment analysis were conducted to evaluate associations between protein targets of red ginseng (Panax ginseng C. A. Meyer) and liver cancer-related proteins and identify related signaling pathways, respectively. Network proximity was employed to identify active ingredients of red ginseng on liver cancer. Results : A compound-target network of red ginseng was constructed, which consisted of 363 edges between 53 ingredients and 121 protein targets. MAPK signaling pathway, PI3K-Akt signaling pathway, p53 signaling pathway, TGF-beta signaling pathway, and cell cycle pathway was significantly associated with protein targets of red ginseng. Network proximity results indicated that Ginsenoside Rg1, Acetic Acid, Ginsenoside Rh2, 20(R)-Ginsenoside Rg3, Notoginsenoside R1, Ginsenoside Rk1, 2-Methylfuran, Hexanal, Ginsenoside Rd, Ginsenoside Rh1 could be active ingredients of red ginseng against liver cancer. Conclusion : This study suggests that network-based approaches could be useful to explore potential mechanisms and active ingredients of red ginseng for liver cancer.

• Asian-Australasian Journal of Animal Sciences
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• 제29권3호
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• pp.343-351
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• 2016

Although the chemical, physical, and nutritional properties of bovine milk have been extensively studied, only a few studies have attempted to characterize milk-synthesizing genes using RNA-seq data. RNA-seq data was collected from 21 Holstein samples, along with group information about milk production ability; milk yield; and protein, fat, and solid contents. Meta-analysis was employed in order to generally characterize genes related to milk production. In addition, we attempted to investigate the relationship between milk related traits, parity, and lactation period. We observed that milk fat is highly correlated with lactation period; this result indicates that this effect should be considered in the model in order to accurately detect milk production related genes. By employing our developed model, 271 genes were significantly (false discovery rate [FDR] adjusted p-value<0.1) detected as milk production related differentially expressed genes. Of these genes, five (albumin, nitric oxide synthase 3, RNA-binding region (RNP1, RRM) containing 3, secreted and transmembrane 1, and serine palmitoyltransferase, small subunit B) were technically validated using quantitative real-time polymerase chain reaction (qRT-PCR) in order to check the accuracy of RNA-seq analysis. Finally, 83 gene ontology biological processes including several blood vessel and mammary gland development related terms, were significantly detected using DAVID gene-set enrichment analysis. From these results, we observed that detected milk production related genes are highly enriched in the circulation system process and mammary gland related biological functions. In addition, we observed that detected genes including caveolin 1, mammary serum amyloid A3.2, lingual antimicrobial peptide, cathelicidin 4 (CATHL4), cathelicidin 6 (CATHL6) have been reported in other species as milk production related gene. For this reason, we concluded that our detected 271 genes would be strong candidates for determining milk production.

• Genomics & Informatics
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• 제12권4호
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• pp.195-202
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• 2014

Metabolic syndrome (MetS) is a complex disorder related to insulin resistance, obesity, and inflammation. Genetic and environmental factors also contribute to the development of MetS, and through genome-wide association studies (GWASs), important susceptibility loci have been identified. However, GWASs focus more on individual single-nucleotide polymorphisms (SNPs), explaining only a small portion of genetic heritability. To overcome this limitation, pathway analyses are being applied to GWAS datasets. The aim of this study is to elucidate the biological pathways involved in the pathogenesis of MetS through pathway analysis. Cohort data from the Korea Associated Resource (KARE) was used for analysis, which include 8,842 individuals (age, $52.2{\pm}8.9years$ ; body mass index, $24.6{\pm}3.2kg/m^2$). A total of 312,121 autosomal SNPs were obtained after quality control. Pathway analysis was conducted using Meta-analysis Gene-Set Enrichment of Variant Associations (MAGENTA) to discover the biological pathways associated with MetS. In the discovery phase, SNPs from chromosome 12, including rs11066280, rs2074356, and rs12229654, were associated with MetS (p < $5{\times}10^{-6}$), and rs11066280 satisfied the Bonferroni-corrected cutoff (unadjusted p < $1.38{\times}10^{-7}$, Bonferroni-adjusted p < 0.05). Through pathway analysis, biological pathways, including electron carrier activity, signaling by platelet-derived growth factor (PDGF), the mitogen-activated protein kinase kinase kinase cascade, PDGF binding, peroxisome proliferator-activated receptor (PPAR) signaling, and DNA repair, were associated with MetS. Through pathway analysis of MetS, pathways related with PDGF, mitogen-activated protein kinase, and PPAR signaling, as well as nucleic acid binding, protein secretion, and DNA repair, were identified. Further studies will be needed to clarify the genetic pathogenesis leading to MetS.

• Journal of Ginseng Research
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• 제47권3호
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• pp.469-478
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• 2023

Background: Nitrogen (N) is an essential macronutrient for plant growth and development. To support agricultural production and enhance crop yield, two major N sources, nitrate and ammonium, are applied as fertilizers to the soil. Although many studies have been conducted on N uptake and signal transduction, the molecular genetic mechanisms of N-mediated physiological roles, such as the secondary growth of storage roots, remain largely unknown. Methods: One-year-old P. ginseng seedlings treated with KNO₃ were analyzed for the secondary growth of storage roots. The histological paraffin sections were subjected to bright and polarized light microscopic analysis. Genome-wide RNA-seq and network analysis were carried out to dissect the molecular mechanism of nitrate-mediated promotion of ginseng storage root thickening. Results: Here, we report the positive effects of nitrate on storage root secondary growth in Panax ginseng. Exogenous nitrate supply to ginseng seedlings significantly increased the root secondary growth. Histological analysis indicated that the enhancement of root secondary growth could be attributed to the increase in cambium stem cell activity and the subsequent differentiation of cambium-derived storage parenchymal cells. RNA-seq and gene set enrichment analysis (GSEA) revealed that the formation of a transcriptional network comprising auxin, brassinosteroid (BR)-, ethylene-, and jasmonic acid (JA)-related genes mainly contributed to the secondary growth of ginseng storage roots. In addition, increased proliferation of cambium stem cells by a N-rich source inhibited the accumulation of starch granules in storage parenchymal cells. Conclusion: Thus, through the integration of bioinformatic and histological tissue analyses, we demonstrate that nitrate assimilation and signaling pathways are integrated into key biological processes that promote the secondary growth of P. ginseng storage roots.

• BMB Reports
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• 제56권11호
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• pp.600-605
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• 2023

Intrahepatic cholangiocarcinoma (ICC) is a bile duct cancer and a rare malignant tumor with a poor prognosis owing to the lack of an early diagnosis and resistance to conventional chemotherapy. A combination of gemcitabine and cisplatin is the typically attempted first-line treatment approach. However, the underlying mechanism of resistance to chemotherapy is poorly understood. We addressed this by studying dynamics in the human ICC SCK cell line. Here, we report that the regulation of glucose and glutamine metabolism was a key factor in overcoming cisplatin resistance in SCK cells. RNA sequencing analysis revealed a high enrichment cell cycle-related gene set score in cisplatin-resistant SCK (SCK-R) cells compared to parental SCK (SCK WT) cells. Cell cycle progression correlates with increased nutrient requirement and cancer proliferation or metastasis. Commonly, cancer cells are dependent upon glucose and glutamine availability for survival and proliferation. Indeed, we observed the increased expression of GLUT (glucose transporter), ASCT2 (glutamine transporter), and cancer progression markers in SCK-R cells. Thus, we inhibited enhanced metabolic reprogramming in SCK-R cells through nutrient starvation. SCK-R cells were sensitized to cisplatin, especially under glucose starvation. Glutaminase-1 (GLS1), which is a mitochondrial enzyme involved in tumorigenesis and progression in cancer cells, was upregulated in SCK-R cells. Targeting GLS1 with the GLS1 inhibitor CB-839 (telaglenastat) effectively reduced the expression of cancer progression markers. Taken together, our study results suggest that a combination of GLUT inhibition, which mimics glucose starvation, and GLS1 inhibition could be a therapeutic strategy to increase the chemosensitivity of ICC.

• Journal of Ginseng Research
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• 제48권5호
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• pp.511-519
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• 2024

Background: The cycle of seasonal dormancy of perennating buds is an essential adaptation of perennial plants to unfavorable winter conditions. Plant hormones are key regulators of this critical biological process, which is intricately connected with diverse internal and external factors. Recently, global warming has increased the frequency of aberrant temperature events that negatively affect the dormancy cycle of perennials. Although many studies have been conducted on the perennating organs of Panax ginseng, the molecular aspects of bud dormancy in this species remain largely unknown. Methods: In this study, the molecular physiological responses of three P. ginseng cultivars with different dormancy break phenotypes in the spring were dissected using comparative genome-wide RNA-seq and network analyses. These analyses identified a key role for abscisic acid (ABA) activity in the regulation of bud dormancy. Gene set enrichment analysis revealed that a transcriptional network comprising stress-related hormone responses made a major contribution to the maintenance of dormancy. Results: Increased expression levels of cold response and photosynthesis-related genes were associated with the transition from dormancy to active growth in perennating buds. Finally, the expression patterns of genes encoding ABA transporters, receptors (PYRs/PYLs), PROTEIN PHOSPHATASE 2Cs (PP2Cs), and DELLAs were highly correlated with different dormancy states in three P. ginseng cultivars. Conclusion: This study provides evidence that ABA and stress signaling outputs are intricately connected with a key signaling network to regulate bud dormancy under seasonal conditions in the perennial plant P. ginseng.

• 대한한의학회지
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• 제44권2호
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• pp.106-118
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• 2023

Objectives: Network pharmacology is a method of constructing and analyzing a drug-compound-target network to predict potential efficacy and mechanisms related to drug targets. In that large-scale analysis can be performed in a short time, it is considered a suitable tool to explore the function and role of herbal medicine. Thus, we investigated the potential functions and pathways of Chongmyunggongjin-dan (CMGJD) on Alzheimer's disease (AD) via network pharmacology analysis. Methods: Using public databases and PubChem database, compounds of CMGJD and their target genes were collected. The putative target genes of CMGJD and known target genes of AD were compared and found the correlation. Then, the network was constructed using Cytoscape 3.9.1. and functional enrichment analysis was conducted based on the Gene Ontology (GO) Biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways to predict the mechanisms. Results: The result showed that total 104 compounds and 1157 related genes were gathered from CMGJD. The network consisted of 1157nodes and 10034 edges. 859 genes were interacted with AD gene set, suggesting that the effects of CMGJD are closely related to AD. Target genes of CMGJD are considerably associated with various pathways including 'Positive regulation of chemokine production', 'Cellular response to toxic substance', 'Arachidonic acid metabolic process', 'PI3K-Akt signaling pathway', 'Metabolic pathways', 'IL-17 signaling pathway' and 'Neuroactive ligand-receptor interaction'. Conclusion: Through a network pharmacological method, CMGJD was predicted to have high relevance with AD by regulating inflammation. This study could be used as a basis for effects of CMGJD on AD.