• BMB Reports
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• v.51 no.1
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• pp.14-20
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• 2018

Biomedical research involving nanoparticles has produced useful products with medical applications. However, the potential toxicity of nanoparticles in biofluids, cells, tissues, and organisms is a major challenge. The '-omics' analyses provide molecular profiles of multifactorial biological systems instead of focusing on a single molecule. The 'omics' approaches are necessary to evaluate nanotoxicity because classical methods for the detection of nanotoxicity have limited ability in detecting miniscule variations within a cell and do not accurately reflect the actual levels of nanotoxicity. In addition, the 'omics' approaches allow analyses of in-depth changes and compensate for the differences associated with high-throughput technologies between actual nanotoxicity and results from traditional cytotoxic evaluations. However, compared with a single omics approach, integrated omics provides precise and sensitive information by integrating complex biological conditions. Thus, these technologies contribute to extended safety evaluations of nanotoxicity and allow the accurate diagnoses of diseases far earlier than was once possible in the nanotechnology era. Here, we review a novel approach for evaluating nanotoxicity by integrating metabolomics with metabolomic profiling and transcriptomics, which is termed "metabotranscriptomics."

• Genomics & Informatics
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• v.2 no.4
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• pp.153-162
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• 2004

• Proceedings of the Korean Society of Food Science and Nutrition Conference
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• 2004.11a
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• pp.17-23
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• 2004

Not all individuals respond identically, or at times in the same direction, to dietary interventions. These inconsistencies likely arise because of diet and genomic interactions (nutrigenomics effects). A host of factors may influence the response to bioactive food components including specific polymorphisms (nutrigenetic effect), DNA methylation patterns and other epigenomic factors (nutritional epigenomic effects), capacity to induce anuo. suppress specific mRNA expression and patterns (nutritional transcriptomics), the occurrence and activity of proteins (proteomic effects), and/or the dose and temporal changes in cellular small molecular weight compounds will not only provide clues about specificity in response to food components, but assist in the identification of surrogate tissues and biomarkers that can predict a response. While this 'discovery' phase is critical for defining mechanisms and targets, and thus those who will benefit most from intervention, its true usefulness depends on moving this understanding into 'development' (interventions for better prevention, detection, diagnosis, and treatment) and a 'delivery' phase where information is provided to those most in need. It is incumbent on those involved with food and nutrition to embrace the 'omics' that relate to nutrition when considering not only the nutritional value of foods and their food components, but also when addressing acceptability and safety. The future of 'Nutrigenomics and Health Promotion' depends on the ability of the scientific community to identity appropriate biomarkers and susceptibility variants, effective communications about the merits of such undertakings with the health care community and with consumers, and doing all of this within a responsible bioethical framework.

• 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.

• 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.

• Food Science of Animal Resources
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• v.43 no.6
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• pp.1067-1086
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• 2023

With rapid advances in meat science in recent decades, changes in meat quality during the pre-slaughter phase of muscle growth and the post-slaughter process from muscle to meat have been investigated. Commonly used techniques have evolved from early physicochemical indicators such as meat color, tenderness, water holding capacity, flavor, and pH to various omic tools such as genomics, transcriptomics, proteomics, and metabolomics to explore fundamental molecular mechanisms and screen biomarkers related to meat quality and taste characteristics. This review highlights the application of omics and integrated multi-omics in meat quality and taste characteristics studies. It also discusses challenges and future perspectives of multi-omics technology to improve meat quality and taste. Consequently, multi-omics techniques can elucidate the molecular mechanisms responsible for changes of meat quality at transcriptome, proteome, and metabolome levels. In addition, the application of multi-omics technology has great potential for exploring and identifying biomarkers for meat quality and quality control that can make it easier to optimize production processes in the meat industry.

• Molecules and Cells
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• v.47 no.2
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• pp.100031.1-100031.13
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• 2024

It is now well-accepted that obesity-induced inflammation plays an important role in the development of insulin resistance and type 2 diabetes. A key source of the inflammation is the murine epididymal and human visceral adipose tissue. The current paradigm is that obesity activates multiple proinflammatory immune cell types in adipose tissue, including adipose-tissue macrophages (ATMs), T Helper 1 (Th1) T cells, and natural killer (NK) cells, while concomitantly suppressing anti-inflammatory immune cells such as T Helper 2 (Th2) T cells and regulatory T cells (Tregs). A key feature of the current paradigm is that obesity induces the anti-inflammatory M2 ATMs in lean adipose tissue to polarize into proinflammatory M1 ATMs. However, recent single-cell transcriptomics studies suggest that the story is much more complex. Here we describe the single-cell genomics technologies that have been developed recently and the emerging results from studies using these technologies. While further studies are needed, it is clear that ATMs are highly heterogeneous. Moreover, while a variety of ATM clusters with quite distinct features have been found to be expanded by obesity, none truly resemble classical M1 ATMs. It is likely that single-cell transcriptomics technology will further revolutionize the field, thereby promoting our understanding of ATMs, adipose-tissue inflammation, and insulin resistance and accelerating the development of therapies for type 2 diabetes.

• 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.

• 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.

• 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.