• Title/Summary/Keyword: Multi-Omics

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Bioinformatics services for analyzing massive genomic datasets

  • Ko, Gunhwan;Kim, Pan-Gyu;Cho, Youngbum;Jeong, Seongmun;Kim, Jae-Yoon;Kim, Kyoung Hyoun;Lee, Ho-Yeon;Han, Jiyeon;Yu, Namhee;Ham, Seokjin;Jang, Insoon;Kang, Byunghee;Shin, Sunguk;Kim, Lian;Lee, Seung-Won;Nam, Dougu;Kim, Jihyun F.;Kim, Namshin;Kim, Seon-Young;Lee, Sanghyuk;Roh, Tae-Young;Lee, Byungwook
    • Genomics & Informatics
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    • v.18 no.1
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    • pp.8.1-8.10
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    • 2020
  • The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/.

Toluene Inhalation Causes Early Anxiety and Delayed Depression with Regulation of Dopamine Turnover, 5-HT1A Receptor, and Adult Neurogenesis in Mice

  • Kim, Jinhee;Lim, Juhee;Moon, Seong-Hee;Liu, Kwang-Hyeon;Choi, Hyun Jin
    • Biomolecules & Therapeutics
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    • v.28 no.3
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    • pp.282-291
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    • 2020
  • Inhaled solvents such as toluene are of particular concern due to their abuse potential that is easily exposed to the environment. The inhalation of toluene causes various behavioral problems, but, the effect of short-term exposure of toluene on changes in emotional behaviors over time after exposure and the accompanying pathological characteristics have not been fully identified. Here, we evaluated the behavioral and neurochemical changes observed over time in mice that inhaled toluene. The mice were exposed to toluene for 30 min at a concentration of either 500 or 2,000 ppm. Toluene did not cause social or motor dysfunction in mice. However, increased anxiety-like behavior was detected in the short-term after exposure, and depression-like behavior appeared as delayed effects. The amount of striatal dopamine metabolites was significantly decreased by toluene, which continued to be seen for up to almost two weeks after inhalation. Additionally, an upregulation of serotonin 1A (5-HT1A) receptor in the hippocampus and the substantia nigra, as well as reduced immunoreactivity of neurogenesis markers in the dentate gyrus, was observed in the mice after two weeks. These results suggest that toluene inhalation, even single exposure, mimics early anxiety-and delayed depression-like emotional disturbances, underpinned by pathological changes in the brain.

Augmenting Plant Immune Responses and Biological Control by Microbial Determinants (새로운 생물적 방제 전략: 미생물 인자 유래 식물면역 유도)

  • Lee, Sang Moo;Chung, Joon-hui;Ryu, Choong-Min
    • Research in Plant Disease
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    • v.21 no.3
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    • pp.161-179
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    • 2015
  • Plant have developed sophisticated defence mechanisms against microbial pathogens. The recent accumulated information allow us to understand the nature of plant immune responses followed by recognition of microbial factors/determinants through cutting-edge genomics and multi-omics techniques. However, the practical approaches to sustain plant health using enhancement of plant immunity is yet to be fully appreciated. Here, we overviewed the general concept and representative examples on the plant immunity. The fungal, bacterial, and viral determinants that was previously reported as the triggers of plant immune responses are introduced and described as the potential protocol of biological control. Specifically, the role of chitin, glucan, lipopolysaccharides/extracellular polysaccharides, microbe/pathogen-associated molecular pattern, antibiotics, mimic-phytohormones, N-acyl homoserine lactone, harpin, vitamins, and volatile organic compounds are considered. We hope that this review stimulates scientific community and farmers to broaden their knowledge on the microbial determinant-based biological control and to apply the technology on the integrated pest management program.

From genome sequencing to the discovery of potential biomarkers in liver disease

  • Oh, Sumin;Jo, Yeeun;Jung, Sungju;Yoon, Sumin;Yoo, Kyung Hyun
    • BMB Reports
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    • v.53 no.6
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    • pp.299-310
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    • 2020
  • Chronic liver disease progresses through several stages, fatty liver, steatohepatitis, cirrhosis, and eventually, it leads to hepatocellular carcinoma (HCC) over a long period of time. Since a large proportion of patients with HCC are accompanied by cirrhosis, it is considered to be an important factor in the diagnosis of liver cancer. This is because cirrhosis leads to an irreversible harmful effect, but the early stages of chronic liver disease could be reversed to a healthy state. Therefore, the discovery of biomarkers that could identify the early stages of chronic liver disease is important to prevent serious liver damage. Biomarker discovery at liver cancer and cirrhosis has enhanced the development of sequencing technology. Next generation sequencing (NGS) is one of the representative technical innovations in the biological field in the recent decades and it is the most important thing to design for research on what type of sequencing methods are suitable and how to handle the analysis steps for data integration. In this review, we comprehensively summarized NGS techniques for identifying genome, transcriptome, DNA methylome and 3D/4D chromatin structure, and introduced framework of processing data set and integrating multi-omics data for uncovering biomarkers.

Identification of Putative Regulatory Alterations Leading to Changes in Gene Expression in Chronic Obstructive Pulmonary Disease

  • Kim, Dong-Yeop;Kim, Woo Jin;Kim, Jung-Hyun;Hong, Seok-Ho;Choi, Sun Shim
    • Molecules and Cells
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    • v.42 no.4
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    • pp.333-344
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    • 2019
  • Various genetic and environmental factors are known to be associated with chronic obstructive pulmonary disease (COPD). We identified COPD-related differentially expressed genes (DEGs) using 189 samples accompanying either adenocarcinoma (AC) or squamous cell carcinoma (SC), comprising 91 normal and 98 COPD samples. DEGs were obtained from the intersection of two DEG sets separately identified for AC and SC to exclude the influence of different cancer backgrounds co-occurring with COPD. We also measured patient samples named group 'I', which were unable to be determined as normal or COPD based on alterations in gene expression. The Gene Ontology (GO) analysis revealed significant alterations in the expression of genes categorized with the 'cell adhesion', 'inflammatory response', and 'mitochondrial functions', i.e., well-known functions related to COPD, in samples from patients with COPD. Multi-omics data were subsequently integrated to decipher the upstream regulatory changes linked to the gene expression alterations in COPD. COPD-associated expression quantitative trait loci (eQTLs) were located at the upstream regulatory regions of 96 DEGs. Additionally, 45 previously identified COPD-related miRNAs were predicted to target 66 of the DEGs. The eQTLs and miRNAs might affect the expression of 'respiratory electron transport chain' genes and 'cell proliferation' genes, respectively, while both eQTLs and miRNAs might affect the expression of 'apoptosis' genes. We think that our present study will contribute to our understanding of the molecular etiology of COPD accompanying lung cancer.

Prognostic role of EGR1 in breast cancer: a systematic review

  • Saha, Subbroto Kumar;Islam, S.M. Riazul;Saha, Tripti;Nishat, Afsana;Biswas, Polash Kumar;Gil, Minchan;Nkenyereye, Lewis;El-Sappagh, Shaker;Islam, Md. Saiful;Cho, Ssang-Goo
    • BMB Reports
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    • v.54 no.10
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    • pp.497-504
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    • 2021
  • EGR1 (early growth response 1) is dysregulated in many cancers and exhibits both tumor suppressor and promoter activities, making it an appealing target for cancer therapy. Here, we used a systematic multi-omics analysis to review the expression of EGR1 and its role in regulating clinical outcomes in breast cancer (BC). EGR1 expression, its promoter methylation, and protein expression pattern were assessed using various publicly available tools. COSMIC-based somatic mutations and cBioPortal-based copy number alterations were analyzed, and the prognostic roles of EGR1 in BC were determined using Prognoscan and Kaplan-Meier Plotter. We also used bc-GenEx-Miner to investigate the EGR1 co-expression profile. EGR1 was more often downregulated in BC tissues than in normal breast tissue, and its knockdown was positively correlated with poor survival. Low EGR1 expression levels were also associated with increased risk of ER+, PR+, and HER2- BCs. High positive correlations were observed among EGR1, DUSP1, FOS, FOSB, CYR61, and JUN mRNA expression in BC tissue. This systematic review suggested that EGR1 expression may serve as a prognostic marker for BC patients and that clinicopathological parameters influence its prognostic utility. In addition to EGR1, DUSP1, FOS, FOSB, CYR61, and JUN can jointly be considered prognostic indicators for BC.

Combined transcriptome and proteome analyses reveal differences in the longissimus dorsi muscle between Kazakh cattle and Xinjiang brown cattle

  • Yan, XiangMin;Wang, Jia;Li, Hongbo;Gao, Liang;Geng, Juan;Ma, Zhen;Liu, Jianming;Zhang, Jinshan;Xie, Penggui;Chen, Lei
    • Animal Bioscience
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    • v.34 no.9
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    • pp.1439-1450
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    • 2021
  • Objective: With the rapid development of proteomics sequencing and RNA sequencing technology, multi-omics analysis has become a current research hotspot. Our previous study indicated that Xinjiang brown cattle have better meat quality than Kazakh cattle. In this study, Xinjiang brown cattle and Kazakh cattle were used as the research objects. Methods: Proteome sequencing and RNA sequencing technology were used to analyze the proteome and transcriptome of the longissimus dorsi muscle of the two breeds of adult steers (n = 3). Results: In this project, 22,677 transcripts and 1,874 proteins were identified through quantitative analysis of the transcriptome and proteome. By comparing the identified transcriptome and proteome, we found that 1,737 genes were identified at both the transcriptome and proteome levels. The results of the study revealed 12 differentially expressed genes and proteins: troponin I1, crystallin alpha B, cysteine, and glycine rich protein 3, phosphotriesterase-related, myosin-binding protein H, glutathione s-transferase mu 3, myosin light chain 3, nidogen 2, dihydropyrimidinase like 2, glutamate-oxaloacetic transaminase 1, receptor accessory protein 5, and aspartoacylase. We performed functional enrichment of these differentially expressed genes and proteins. The Kyoto encyclopedia of genes and genomes results showed that these differentially expressed genes and proteins are enriched in the fatty acid degradation and histidine metabolism signaling pathways. We performed parallel reaction monitoring (PRM) verification of the differentially expressed proteins, and the PRM results were consistent with the sequencing results. Conclusion: Our study provided and identified the differentially expressed genes and proteins. In addition, identifying functional genes and proteins with important breeding value will provide genetic resources and technical support for the breeding and industrialization of new genetically modified beef cattle breeds.

Cancer Patient Specific Driver Gene Identification by Personalized Gene Network and PageRank (개인별 유전자 네트워크 구축 및 페이지랭크를 이용한 환자 특이적 암 유발 유전자 탐색 방법)

  • Jung, Hee Won;Park, Ji Woo;Ahn, Jae Gyoon
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.12
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    • pp.547-554
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    • 2021
  • Cancer patients can have different kinds of cancer driver genes, and identification of these patient-specific cancer driver genes is an important step in the development of personalized cancer treatment and drug development. Several bioinformatic methods have been proposed for this purpose, but there is room for improvement in terms of accuracy. In this paper, we propose NPD (Network based Patient-specific Driver gene identification) for identifying patient-specific cancer driver genes. NPD consists of three steps, constructing a patient-specific gene network, applying the modified PageRank algorithm to assign scores to genes, and identifying cancer driver genes through a score comparison method. We applied NPD on six cancer types of TCGA data, and found that NPD showed generally higher F1 score compared to existing patient-specific cancer driver gene identification methods.