• 제목/요약/키워드: Multi-omics analysis

검색결과 28건 처리시간 0.021초

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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    • 제18권1호
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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/.

Advanced Bioremediation Strategies for Organophosphorus Compounds

  • Anish Kumar Sharma;Jyotsana Pandit
    • 한국미생물·생명공학회지
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    • 제51권4호
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    • pp.374-389
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    • 2023
  • Organophosphorus (OP) pesticides, particularly malathion, parathion, diazinon, and chlorpyrifos, are widely used in both agricultural and residential contexts. This refractory quality is shared by certain organ phosphorus insecticides, and it may have unintended consequences for certain non-target soil species. Bioremediation cleans organic and inorganic contaminants using microbes and plants. Organophosphate-hydrolyzing enzymes can transform pesticide residues into non-hazardous byproducts and are increasingly being considered viable solutions to the problem of decontamination. When coupled with system analysis, the multi-omics technique produces important data for functional validation and genetic manipulation, both of which may be used to boost the efficiency of bioremediation systems. RNA-guided nucleases and RNA-guided base editors include zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeats (CRISPR), which are used to alter genes and edit genomes. The review sheds light on key knowledge gaps and suggests approaches to pesticide cleanup using a variety of microbe-assisted methods. Researches, ecologists, and decision-makers can all benefit from having a better understanding of the usefulness and application of systems biology and gene editing in bioremediation evaluations.

Human CD8+ T-Cell Populations That Express Natural Killer Receptors

  • June-Young Koh;Dong-Uk Kim;Bae-Hyeon Moon;Eui-Cheol Shin
    • IMMUNE NETWORK
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    • 제23권1호
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    • pp.8.1-8.13
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    • 2023
  • CD8+ T cells are activated by TCRs that recognize specific cognate Ags, while NK-cell activation is regulated by a balance between signals from germline-encoded activating and inhibitory NK receptors. Through these different processes of Ag recognition, CD8+ T cells and NK cells play distinct roles as adaptive and innate immune cells, respectively. However, some human CD8+ T cells have been found to express activating or inhibitory NK receptors. CD8+ T-cell populations expressing NK receptors straddle the innate-adaptive boundary with their innate-like features. Recent breakthrough technical advances in multi-omics analysis have enabled elucidation of the unique immunologic characteristics of these populations. However, studies have not yet fully clarified the heterogeneity and immunological characteristics of each CD8+ T-cell population expressing NK receptors. Here we aimed to review the current knowledge of various CD8+ T-cell populations expressing NK receptors, and to pave the way for delineating the landscape and identifying the various roles of these T-cell populations.

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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    • 제53권6호
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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.

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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    • 제34권9호
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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.

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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    • 제42권4호
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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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    • 제54권10호
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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.

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

  • 정희원;박지우;안재균
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제10권12호
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    • pp.547-554
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    • 2021
  • 암을 유발하는 유전자는 모든 암 환자에게 공통적인 것은 아니며, 이러한 환자 특이적 암 유발 유전자의 탐색은 개인 맟춤형 암 치료 및 항암제 개발에 있어서 매우 중요하다. 환자 특이적 암 유발 유전자를 찾기 위한 생물 정보학 연구들이 있어왔지만, 아직 정확도 면에서는 발전의 여지가 있다. 본 논문에서는 환자 특이적 암 유발 유전자를 탐색하기 위하여 NPD (Network based Patient-specific Driver gene identification)라는 방법을 제안한다. NPD는 환자 특이적 유전자 네트워크를 구축하고, 여기에 수정된 PageRank 알고리즘을 적용하여 유전자에 점수를 부여한 후, 유전적 변이 데이터를 사용한 승률 계산 방법을 통하여 암 유발 유전자를 찾는 세 단계로 이루어진다. TCGA 데이터 베이스의 여섯 개의 암 데이터에 NPD를 적용한 결과, NPD가 기존의 환자 특이적 암 유발 유전자 탐색 방법들보다 전체적으로 높은 F1 점수를 보여줌을 확인할 수 있었다.