• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.214-214
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• 2022

Soluble starch synthases (SSs) elongate α-glucans from ADP-Glc to the glucan nonreducing ends and play a critical role in synthesizing resistant starch in the rice. A total of 10 SSs isoforms were reported in rice, including granules-bound starch synthase I (GBSSI), GBSSII, starch synthase I (SSI), SSIIa (SSII-3), SSIIb (SSII-2), SSIIc (SSII-1), SSIIIa (SSIII-2), SSIIIb (SSIII-1), SSIVa (SSIV-1), and SSIVb (SSIV-2). SSIII proteins are involved in forming the B chain and elongating cluster filling chains in amylopectin metabolism. The functions of SSIIIb (SSIII-1) are less clear as compared to SSs. Here, we sought to shed light on the genetic diversity profiling of the SSIII-1 gene in 374 rice accessions composed of 54 wild-type accessions and 320 bred cultivars (temperate japonica, indica, tropical japonica, aus, aromatic, and admixture). In total, 17 haplotypes were identified in the SSIII-1 coding region of 320 bred cultivars, while 44 haplotypes were detected from 54 wild-type accessions. The genetic diversity indices revealed the most negative Tajima's D value in the temperate-japonica, followed by the wild type, while Tajima's D values in other ecotypes were positive, indicating balancing selection. Nucleotide diversity in the SSIII-1 region was highest in the wild group (0.0047) while lowest in temperate-japonica. Lower nucleotide diversity in the temperate-japonica is evidenced by the negative Tajima's D and suggested purifying selection. The fixation index (F_ST) revealed a very high level of gene flow (low F_ST) between the tropical-japonica and admixture groups (F_ST=-0.21) followed by admixture and wild groups (-0.04), indica and admixture groups (0.02), while low gene flow with higher F_ST estimates between the temperate-japonica and aus groups (0.72), tropical-japonica and aromatic groups (0.71), and temperate-japonica and admixture groups (0.52). Taken together, our study offers insights into haplotype diversity and evolutionary fingerprints of SSIII-1. It provides genomic information to increase the resistant starch content of cooked rice.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.219-219
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• 2022

Granule-bound starch synthase I (GBSSI), encoded by the waxy gene, is responsible for the accumulation of amylose during the development of starch granules in rice endosperm. Despite many findings on waxy alleles, the genetic diversity and evolutionary studies are still not fully explored regarding their functional effects. Comprehensive evolutionary analyses were performed to investigate the genetic variations and relatedness of the GBSSI gene in 374 rice accessions composed of 54 wild accessions and 320 bred cultivars (temperate japonica, tropical japonica, indica, aus, aromatic, and admixture). GBSS1 coding regions were analyzed from a VCF file retrieved from whole-genome resequencing data, and eight haplotypes were identified in the GBSSI coding region of 320 bred cultivars. The genetic diversity indices revealed the most negative Tajima's D value in the tropical-japonica, followed by the aus and temperate-japonica, while Tajima's D values in indica were positive, indicating balancing selection. Diversity reduction was noticed in temperate japonica (0.0003) compared to the highest one (wild, 0.0044), illustrating their higher genetic differentiation by F_ST-value (0.604). The most positive Tajima's D value was observed in indica (0.5224), indicating the GBSSI gene domestication signature under balancing selection. In contrast, the lowest and negative Tajima's D value was found in tropical japonica (-0.5291), which might have experienced a positive selection and purified due to the excess of rare alleles. Overall, our study offers insights into haplotype diversity and evolutionary fingerprints of GBSSI. It ako provides genomic information to increase the starch content of cooked rice.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.157-176
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• 2024

Integrative analysis for better understanding of complex biological systems gains more attention. Observing subjects from various perspectives and conducting integrative analysis of those multiple datasets enables a deeper understanding of the subject. In this paper, we compared two methods that simultaneously consider two datasets gathered from the same objects, canonical correlation analysis (CCA) and co-inertia analysis (CIA). Since CCA cannot handle the case when the data exhibit high-dimensionality, two strategies were considered instead: Utilization of a ridge constant (CCA-ridge) and substitution of covariance matrices of each data to identity matrix and then applying penalized singular value decomposition (CCA-PMD). To illustrate CIA and CCA, both extensions of CCA and CIA were applied to NCI60 cell line data. It is shown that both methods yield biologically meaningful and significant results by identifying important genes that enhance our comprehension of the data. Their results shows some dissimilarities arisen from the different criteria used to measure the relationship between two sets of data in each method. Additionally, CIA exhibits variations dependent on the weight matrices employed.

• Animal Bioscience
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• v.37 no.2_spc
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• pp.370-384
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• 2024

Rumen microbiota play a central role in the digestive process of ruminants. Their remarkable ability to break down complex plant fibers and proteins, converting them into essential organic compounds that provide animals with energy and nutrition. Research on rumen microbiota not only contributes to improving animal production performance and enhancing feed utilization efficiency but also holds the potential to reduce methane emissions and environmental impact. Nevertheless, studies on rumen microbiota face numerous challenges, including complexity, difficulties in cultivation, and obstacles in functional analysis. This review provides an overview of microbial species involved in the degradation of macromolecules, the fermentation processes, and methane production in the rumen, all based on cultivation methods. Additionally, the review introduces the applications, advantages, and limitations of emerging omics technologies such as metagenomics, meta-transcriptomics, metaproteomics, and metabolomics, in investigating the functionality of rumen microbiota. Finally, the article offers a forward-looking perspective on the new horizons and technologies in the field of rumen microbiota functional research. These emerging technologies, with continuous refinement and mutual complementation, have deepened our understanding of rumen microbiota functionality, thereby enabling effective manipulation of the rumen microbial community.

• BMB Reports
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• v.49 no.12
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• pp.671-680
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• 2016

Accumulating evidence indicates many brain functions are mediated by epigenetic regulation of neural genes, and their dysregulations result in neuronal disorders. Experiences such as learning and recall, as well as physical exercise, induce neuronal activation through epigenetic modifications and by changing the noncoding RNA profiles. Animal models, brain samples from patients, and the development of diverse analytical methods have broadened our understanding of epigenetic regulation in the brain. Diverse and specific epigenetic changes are suggested to correlate with neuronal development, learning and memory, aging and age-related neuronal diseases. Although the results show some discrepancies, a careful comparison of the data (including methods, regions and conditions examined) would clarify the problems confronted in understanding epigenetic regulation in the brain.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.418-424
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• 2005

The complexity of the biological system/biological systems has been fascinating and challenging for a long time. With the advent of mathematical tools with various omics technology, systems biology was born and is already ubiquitous in every area of biology and biotechnology. Microalgal biotechnology is no exception in this new trend. As tens of microalgal genomes become publicly available on the Internet, vast amounts of data from genomics, transcriptomics, and proteomics are reported everyday. Though there has not yet been enough data gathered on microalgal metabolomics, the in silica models for relatively simple cyanobacteria or for organelles, such as chloroplasts, will appear presently. With the help of systems biology, a more in-depth understanding of microalgae will be possible. Consequently, most industrially-interested microalgae can be metabolically redesigned/reconfigured as cell factories. Microalgae will be served as the hosts in white biotechnology.

• Journal of Microbiology and Biotechnology
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• v.30 no.6
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• pp.793-803
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• 2020

Adaptive laboratory evolution (ALE) is an evolutionary engineering approach in artificial conditions that improves organisms through the imitation of natural evolution. Due to the development of multi-level omics technologies in recent decades, ALE can be performed for various purposes at the laboratory level. This review delineates the basics of the experimental design of ALE based on several ALE studies of industrial microbial strains and updates current strategies combined with progressed metabolic engineering, in silico modeling and automation to maximize the evolution efficiency. Moreover, the review sheds light on the applicability of ALE as a strain development approach that complies with non-recombinant preferences in various food industries. Overall, recent progress in the utilization of ALE for strain development leading to successful industrialization is discussed.

• Journal of the Korean Magnetic Resonance Society
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• v.21 no.3
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• pp.96-101
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• 2017

Metabolomics is one of latest '-omics', which is to analyze metabolome in cells, tissues and biofluids and to study metabolisms. It has become increasingly popular since 1990. The first goal of metabolomics is to analyze metabolites in a technical aspect. The major two analytical platforms in metabolomics are NMR spectroscopy and mass spectrometry (MS). MS is superior to NMR for detecting many more metabolites. That is one of the most important factors in metabolomics. However, NMR also has several advantages over MS. In this review, I firstly introduced metabolomics by comparing NMR-based metabolomics and MS-based metabolomics. Second, I explored technical issues on sample preparation and NMR experiments for metabolite identification and quantification.

• Genomics & Informatics
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• v.10 no.4
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• pp.263-265
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• 2012

We developed a user-friendly, interactive program to simultaneously cluster and visualize omics data, such as DNA and protein array profiles. This program provides diverse algorithms for the hierarchical clustering of two-dimensional data. The clustering results can be interactively visualized and optimized on a heatmap. The present tool does not require any prior knowledge of scripting languages to carry out the data clustering and visualization. Furthermore, the heatmaps allow the selective display of data points satisfying user-defined criteria. For example, a clustered heatmap of experimental values can be differentially visualized based on statistical values, such as p-values. Including diverse menu-based display options, QCanvas provides a convenient graphical user interface for pattern analysis and visualization with high-quality graphics.

• Biotechnology and Bioprocess Engineering:BBE
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• v.11 no.3
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• pp.187-198
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• 2006

The aromatic hydrocarbons (AHs), which include benzene, polycyclic aromatic hydrocarbons, and dioxin, are important chemical and environmental contaminants in industry that usually cause various diseases. Over the years, numerous studies have described and evaluated the adverse health effects induced by AHs. Currently, "Omics" technologies, transcriptomics and proteomics, have been applied in AH toxicity studies. Proteomics has been used to identify molecular mechanisms and biomarkers associated with global chemical toxicity. It could enhance our ability to characterize chemical-induced toxicities and to identify noninvasive biomarkers. The proteomic approach (e.g. 2-dimensional electrophoresis [2-DE]), can be used to observe changes in protein expression during chemical exposure with high sensitivity and specificity. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) and electrospray ionization-quadrupole (ESI-Q)-TOF MS/MS are recognized as the most important protein identification tools. This review describes proteomic technologies and their application in the proteomic analysis of AH toxicity.