• Title/Summary/Keyword: transcriptomics analysis

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Analysis of the mechanism of fibrauretine alleviating Alzheimer's disease based on transcriptomics and proteomics

  • Lu Han;Weijia Chen;Ying Zong;Yan Zhao;Jianming Li;Zhongmei He;Rui Du
    • The Korean Journal of Physiology and Pharmacology
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    • v.28 no.4
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    • pp.361-377
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    • 2024
  • The dried rattan stem of the Fibraurea Recisa Pierre plant contains the active ingredient known as fibrauretine (FN). Although it greatly affects Alzheimer's disease (AD), the mechanism of their effects still remains unclear. Proteomics and transcriptomics analysis methods were used in this study to determine the mechanism of FN in the treatment of AD. AD model is used through bilateral hippocampal injection of Aβ1-40. After successful modeling, FN was given for 30 days. The results showed that FN could improve the cognitive dysfunction of AD model rats, reduce the expression of AE and P-Tau, increase the content of acetylcholine and reduce the activity of acetylcholinesterase. The Kyoto Encyclopedia of Genes and Genomes enriched differentially expressed genes and proteins are involved in signaling pathways including metabolic pathway, AD, pathway in cancer, PI3K-AKT signaling pathway, and cAMP signaling pathway. Transcriptomics and proteomics sequencing resulted in 19 differentially expressed genes and proteins. Finally, in contrast to the model group, after FN treatment, the protein expressions and genes associated with the PI3K-AKT pathway were significantly improved in RT-qPCR and Western blot and assays. This is consistent with the findings of transcriptomic and proteomic analyses. Our study found that, FN may improve some symptoms of AD model rats through PI3K-AKT signaling pathway.

Deciphering Key Genes of Proliferative and Secretory Phase Using Integrated Transcriptomics and Network Analysis

  • Payal Gupta;Shriya Dube;Payal Priyadarshini;Shanvi Singh;Anasuya Pravallika R;Vijay Lakshmi Srivastava;Abhishek Sengupta;Priyanka Narad
    • Microbiology and Biotechnology Letters
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    • v.51 no.3
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    • pp.317-324
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    • 2023
  • Endometrium receptivity is a complex mechanism of intricate pathways that lead to the shift from the proliferative to the secretory phase. Our goal was to identify high-ranking differentially expressed genes and study the pathways associated with the phenomenon. Raw data were retrieved from six GEO datasets and 705 DEGs were identified through robust ranking aggregation after the integration of five datasets. 20 key genes were identified that were further re-validated in an additional dataset. Supporting evidence through the experimental references confirms them as major biomarkers of the shift from the proliferative to the secretory phase.

Single-cell and spatial transcriptomics approaches of cardiovascular development and disease

  • Roth, Robert;Kim, Soochi;Kim, Jeesu;Rhee, Siyeon
    • BMB Reports
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    • v.53 no.8
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    • pp.393-399
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    • 2020
  • Recent advancements in the resolution and throughput of single-cell analyses, including single-cell RNA sequencing (scRNA-seq), have achieved significant progress in biomedical research in the last decade. These techniques have been used to understand cellular heterogeneity by identifying many rare and novel cell types and characterizing subpopulations of cells that make up organs and tissues. Analysis across various datasets can elucidate temporal patterning in gene expression and developmental cues and is also employed to examine the response of cells to acute injury, damage, or disruption. Specifically, scRNA-seq and spatially resolved transcriptomics have been used to describe the identity of novel or rare cell subpopulations and transcriptional variations that are related to normal and pathological conditions in mammalian models and human tissues. These applications have critically contributed to advance basic cardiovascular research in the past decade by identifying novel cell types implicated in development and disease. In this review, we describe current scRNA-seq technologies and how current scRNA-seq and spatial transcriptomic (ST) techniques have advanced our understanding of cardiovascular development and disease.

Recent next-generation sequencing and bioinformatic analysis methods for food microbiome research (식품 미생물 균총 연구를 위한 최신 마이크로바이옴 분석 기술)

  • Kwon, Joon-Gi;Kim, Seon-Kyun;Lee, Ju-Hoon
    • Food Science and Industry
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    • v.52 no.3
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    • pp.220-228
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    • 2019
  • Rapid development of next-generation sequencing (NGS) technology is available to study microbes in genomic level. This NGS has been widely used in DNA/RNA sequencing for genome sequencing, metagenomics, and transcriptomics. The food microbiology area could be categorized into three groups. Food microbes including probiotics and food-borne pathogens are studied in genomic level using NGS for microbial genomics. While food fermentation or food spoilage are more complicated, their genomic study needs to be done with metagenomics using NGS for compositional analysis. Furthermore, because microbial response in food environments are also important to understand their roles in food fermentation or spoilage, pattern analysis of RNA expression in the specific food microbe is conducted using RNA-Seq. These microbial genomics, metagenomics, and transcriptomics for food fermentation and spoilage would extend our knowledge on effective utilization of fermenting bacteria for health promotion as well as efficient control of food-borne pathogens for food safety.

Recent advances in spatially resolved transcriptomics: challenges and opportunities

  • Lee, Jongwon;Yoo, Minsu;Choi, Jungmin
    • BMB Reports
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    • v.55 no.3
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    • pp.113-124
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    • 2022
  • Single-cell RNA sequencing (scRNA-seq) has greatly advanced our understanding of cellular heterogeneity by profiling individual cell transcriptomes. However, cell dissociation from the tissue structure causes a loss of spatial information, which hinders the identification of intercellular communication networks and global transcriptional patterns present in the tissue architecture. To overcome this limitation, novel transcriptomic platforms that preserve spatial information have been actively developed. Significant achievements in imaging technologies have enabled in situ targeted transcriptomic profiling in single cells at single-molecule resolution. In addition, technologies based on mRNA capture followed by sequencing have made possible profiling of the genome-wide transcriptome at the 55-100 ㎛ resolution. Unfortunately, neither imaging-based technology nor capture-based method elucidates a complete picture of the spatial transcriptome in a tissue. Therefore, addressing specific biological questions requires balancing experimental throughput and spatial resolution, mandating the efforts to develop computational algorithms that are pivotal to circumvent technology-specific limitations. In this review, we focus on the current state-of-the-art spatially resolved transcriptomic technologies, describe their applications in a variety of biological domains, and explore recent discoveries demonstrating their enormous potential in biomedical research. We further highlight novel integrative computational methodologies with other data modalities that provide a framework to derive biological insight into heterogeneous and complex tissue organization.

Analysis of toxicity using bio-digital contents (바이오 디지털 콘텐츠를 이용한 독성의 분석)

  • Kang, Jin-Seok
    • Journal of Digital Contents Society
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    • v.11 no.1
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    • pp.99-104
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    • 2010
  • Numerous bio-digital contents have been produced by new technology using biochip and others for analyzing early chemical-induced genes. These contents have little meaning by themselves, and so they should be modified and extracted after consideration of biological meaning. These include genomics, transcriptomics, protenomics, metabolomics, which combined into omics. Omics tools could be applied into toxicology, forming a new field of toxicogenomics. It is possible that approach of toxicogenomics can estimate toxicity more quickly and accurately by analyzing gene/protein/metabolite profiles. These approaches should help not only to discover highly sensitive and predictive biomarkers but also to understand molecular mechanism(s) of toxicity, based on the development of analysing technology. Furthermore, it is important that bio-digital contents should be obtained from specific cells having biological events more than from whole cells. Taken together, many bio-digital contents should be analyzed by careful calculating algorism under well-designed experimental protocols, network analysis using computational algorism and related profound databases.

Integrative Omics Reveals Metabolic and Transcriptomic Alteration of Nonalcoholic Fatty Liver Disease in Catalase Knockout Mice

  • Na, Jinhyuk;Choi, Soo An;Khan, Adnan;Huh, Joo Young;Piao, Lingjuan;Hwang, Inah;Ha, Hunjoo;Park, Youngja H
    • Biomolecules & Therapeutics
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    • v.27 no.2
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    • pp.134-144
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    • 2019
  • The prevalence of nonalcoholic fatty liver disease (NAFLD) has increased with the incidence of obesity; however, the underlying mechanisms are unknown. In this study, high-resolution metabolomics (HRM) along with transcriptomics were applied on animal models to draw a mechanistic insight of NAFLD. Wild type (WT) and catalase knockout (CKO) mice were fed with normal fat diet (NFD) or high fat diet (HFD) to identify the changes in metabolic and transcriptomic profiles caused by catalase gene deletion in correspondence with HFD. Integrated omics analysis revealed that cholic acid and $3{\beta}$, $7{\alpha}$-dihydroxy-5-cholestenoate along with cyp7b1 gene involved in primary bile acid biosynthesis were strongly affected by HFD. The analysis also showed that CKO significantly changed all-trans-5,6-epoxy-retinoic acid or all-trans-4-hydroxy-retinoic acid and all-trans-4-oxo-retinoic acid along with cyp3a41b gene in retinol metabolism, and ${\alpha}/{\gamma}$-linolenic acid, eicosapentaenoic acid and thromboxane A2 along with ptgs1 and tbxas1 genes in linolenic acid metabolism. Our results suggest that dysregulated primary bile acid biosynthesis may contribute to liver steatohepatitis, while up-regulated retinol metabolism and linolenic acid metabolism may have contributed to oxidative stress and inflammatory phenomena in our NAFLD model created using CKO mice fed with HFD.

Current status of peach genomics and transcriptomics research (복숭아 유전체 및 전사체 최근 연구 동향)

  • Cho, Kang Hee;Kwon, Jung Hyun;Kim, Se Hee;Jun, Ji Hae
    • Journal of Plant Biotechnology
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    • v.42 no.4
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    • pp.312-325
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    • 2015
  • In this review, we summarized the trends of genomics and transcriptomics research on peach, a model species of Rosaceae. Peach genome maps have been developed from various progeny groups with many next-generation sequencing (NGS) based single nucleotide polymorphism markers. Molecular markers of qualitative traits and quantitative trait loci (QTL) such as fruit characteristics, blooming date, and disease resistance have been analyzed. Among many characteristics, markers related to flesh softening and flesh adhesion are useful for marker assisted selection. Through comparative genomics, peach genome has been compared to the genome of Arabidopsis, Populus, Malus, and Fragaria species. Through transcriptomics and proteomics, fruit growth and development, and flavonoid synthesis, postharvest related transcriptomes and disease resistance related proteins have been reported. Recently, development of NGS based markers, construction of core collection of germplasm, and genotyping of various progenies have been preceded. In the near future, accurate QTL analysis and identification of useful genes are expected to establish a foundation for effective molecular breeding.

Advances in Systems Biology Approaches for Autoimmune Diseases

  • Kim, Ho-Youn;Kim, Hae-Rim;Lee, Sang-Heon
    • IMMUNE NETWORK
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    • v.14 no.2
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    • pp.73-80
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    • 2014
  • Because autoimmune diseases (AIDs) result from a complex combination of genetic and epigenetic factors, as well as an altered immune response to endogenous or exogenous antigens, systems biology approaches have been widely applied. The use of multi-omics approaches, including blood transcriptomics, genomics, epigenetics, proteomics, and metabolomics, not only allow for the discovery of a number of biomarkers but also will provide new directions for further translational AIDs applications. Systems biology approaches rely on high-throughput techniques with data analysis platforms that leverage the assessment of genes, proteins, metabolites, and network analysis of complex biologic or pathways implicated in specific AID conditions. To facilitate the discovery of validated and qualified biomarkers, better-coordinated multi-omics approaches and standardized translational research, in combination with the skills of biologists, clinicians, engineers, and bioinformaticians, are required.

Plant Biotechnology and Bioinformatics (식물 생명공학과 생물정보학)

  • Kim, Jung-Eun;Paik, Hyo-Jung;Kim, Young-Cheol;Hur, Cheol-Goo
    • Journal of Plant Biotechnology
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    • v.33 no.3
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    • pp.209-222
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    • 2006
  • The whole genome sequence was completed in arabidopsis and rice. Large amounts of EST data have been available from many other plants. Also, vast quantities of diverse biological data have been generated by various '-omics' technologies such as transcriptomics, proteomics, and metabolomics. Bioinformatics plays an essential role in extracting useful information from these tremendous amounts of biological data. In this review we introduced experimental methods to generate massive data, applications to plant science such as plant disease resistance and molecular breeding and bioinformatics tools and web sites available in plant biotechnology R&D. We concluded that new experimental methods and bioinfomation analysis techniques have made major contributions to the development of plant biotechnology and that bioinformatics has become a critical factor in plant biotechnology R&D.