• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1512-1518
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• 2021

Since single cell RNA sequencing provides the expression profiles of individual cells, it provides higher cellular differential resolution than traditional bulk RNA sequencing. Using these single cell RNA sequencing data, clustering analysis is generally conducted to find cell types and understand high level biological processes. In order to effectively process the high-dimensional single cell RNA sequencing data fir the clustering analysis, this paper uses a variational autoencoder to transform a high dimensional data space into a lower dimensional latent space, expecting to produce a latent space that can give more accurate clustering results. By clustering the features in the transformed latent space, we compare the performance of various classical clustering methods for single cell RNA sequencing data. Experimental results demonstrate that the proposed framework outperforms many state-of-the-art methods under various clustering performance metrics.

• The Korean Journal of Pesticide Science
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• v.21 no.1
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• pp.1-8
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• 2017

Although a global ban on the use of endosulfan, an organochloline insecticide, has taken effect in mid-2012, it has been still used in several countries, including India and China, and detected in diverse environments in the world due to its relative persistence and semi-volatility. In this study, the effect of endosulfan on soil bacterial community was investigated using 16S rRNA gene pyrosequencing method. When endosulfan was applied to an upland soil at a rate of 100 mg/kg soil (ES soil), the number of operational taxonomic units (OTU) and diversity indices for bacteria initially decreased and gradually recovered to the level of the non-treated soil (NT soil) during an eight-week incubation period. At bacterial phylum level, relative abundances of Proteobacteria and Verrucomicrobia were higher while those of Chloroflexi and Spirochaetes were lower in the ES soil than in the NT soil, suggesting that an endosulfan application affects the bacterial community structure in soil. In the ES soil, the relative abundances of the OTUs affiliated to the genera Sphingomonas and Burkholderia increased in the initial period of incubation while those affiliated to the genera Pseudonocardia and Opitutus increased in the late period of incubation. Because the first three genera contain bacterial strains reported to degrade endosulfan, they are expected to be involved in the degradation of endosulfan, probably one after another.

• Journal of Plant Biotechnology
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• v.48 no.1
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• pp.34-43
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• 2021

Targeted genome editing using the CRISPR/Cas9 system is a ground-breaking technology that is being widely used to produce plants with useful traits. However, for woody plants, only a few successful attempts have been reported. These successes have used Agrobacterium-mediated transformation, which has been reported to be very efficient at producing genetically modified trees. Nonetheless, there are unresolved problems with plasmid sequences that remain in the plant genome. In this study, we demonstrated a DNA-free genome editing technique in which purified CRISPR/Cas9 ribonucleoproteins (RNPs) are delivered directly to the protoplasts of a hybrid poplar (Populus alba × Populus glandulosa). We designed three single-guide RNAs (sgRNAs) to target the stress-associated protein 1 gene (PagSAP1) in the hybrid poplar. Deep sequencing results showed that pre-assembled RNPs had a more efficient target mutagenesis insertion and deletion (indel) frequency than did non-assembled RNPs. Moreover, the RNP of sgRNA3 had a significantly higher editing efficacy than those of sgRNA1 and sgRNA2. Our results suggest that the CRISPR/Cas9 ribonucleoprotein-mediated transfection approach is useful for the production of transgene-free genome-edited tree plants.

• The Korean Journal of Applied Statistics
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• v.35 no.5
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• pp.667-684
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• 2022

Gene expression data present the level of mRNA abundance of each gene, and analyses of gene expressions have provided key ideas for understanding the mechanism of diseases and developing new drugs and therapies. Nowadays high-throughput technologies such as DNA microarray and RNA-sequencing enabled the simultaneous measurement of thousands of gene expressions, giving rise to a characteristic of gene expression data known as high dimensionality. Due to the high-dimensionality, learning models to analyze gene expression data are prone to overfitting problems, and to solve this issue, dimension reduction or feature selection techniques are commonly used as a preprocessing step. In particular, we can remove irrelevant and redundant genes and identify important genes using gene selection methods in the preprocessing step. Various gene selection methods have been developed in the context of machine learning so far. In this paper, we intensively review recent works on gene selection methods using machine learning approaches. In addition, the underlying difficulties with current gene selection methods as well as future research directions are discussed.

• 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.

• Journal of Life Science
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• v.32 no.12
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• pp.1005-1012
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• 2022

This study was conducted to investigate the taxonomic composition and diversity of fecal microbiota between birth and weaning stages of Halla horses using 16S rRNA gene amplicon sequencing analysis. Proteobacteria (35.7%) and Firmicutes (45.6%) were identified as the most common phylum in birth and weaning, respectively. Escherichia (19.7%) and Clostridium (14.0%) were observed as the most dominant genus in birth, and Fibrobacter (6.6%) was the highest in weaning. The results of α-diversity showed that the richness and evenness in microbial communities were statistically significant (p<0.001) in birth and weaning. The results of β-diversity indicated that the birth and weaning stages were clearly divided into two groups at the genus and species levels. Permutational multivariate analysis of variance (PERMANOVA) showed that the microbiota composition differences between birth and weaning were statistically significant (q<0.001). A linear discriminant analysis effect (LEfSe) was performed to select taxonomic makers between the birth and weaning stages. On the genus level, Escherichia, Bacteroides, Clostridium, and Methylobacterium were relatively abundant at birth, whereas Fibrobacter was more abundant at weaning. We expect that this research can be utilized as basic data in the identification of microbial communities involved in disease prevention and nutrient absorption in Halla horses.

• Journal of agriculture & life science
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• v.50 no.1
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• pp.117-124
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• 2016

Researches on soil microbial community are increasing to assess ecosystem responses to anthropogenic disturbances and to provide an indicator of ecosystem recovery. Microbial communities are able to respond more rapidly to environmental changes than plants and therefore they may provide an early indication of the ecosystem recovery trajectory. This study was conducted using 16S rRNA gene pyrosequencing of soil samples to compare soil bacterial community composition between artificially covered soils of the Baedudaegan ridgeline and their adjacent forest soils in two restoration project sites, Ihwaryeong and Yuksimnyeong, which were completed in 2012 and 2013, respectively. Richness of the Phylum level was 29.3 in Ihwaryeong and 32.3 in Yuksimnyeong. Significant difference in the richness between artificial restored soils and adjacent forest soils(p<0.01) was observed, however no significant difference was observed for site location and soil depth. Acidobacteria(37.3%) and Proteobacteria(31.1%) were more abundant than any other phylum in collected soil samples. Also, we found the significant difference in the relative abundance of the two abundant phyla between artificially restored soils and their adjacent forest soils (Proteobacteria, 38.1% in restored soils vs 24.2% in adjacent forest soils, p<0.01; Acidobacteria, 55.4% in restored soils vs 19.2% in adjacent forest soils, p<0.001). The results support the previous researches indicating that soil bacterial community composition is affected by nutritional status of soils and that Acidobacteria is also strongly influenced by pH, thus favoring soils with lower pH. This study could be utilized to monitor and evaluate restoration success of forest soil environment quantitatively.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.7
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• pp.503-508
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• 2013

The aim of this study was to investigate the microbial communities in animal carcass disposal soils to examine the possible threat of pathogens from leachate. DNA extraction was performed for the soils in three carcass disposal sites located in Gyeonggi-do, Korea, and then 16S rRNA pyrosequencing was conducted to identify the microbial communities. Results indicate that, according to phylum classification, Proteobacteria (100%) was identified in soil A, Actinobacteria (66.4%) > Proteobacteria (31.1%) > Bacteriodetes (2.1%) > Acidobacteria (0.3%) in soil B, and Actinobacteria (63.1%) > Proteobacteria (36.9%) in soil C. According to genus classification, Pseudomonas was dominant in soil A (98%), Arthrobacter in soil B (68%) and C (61%). There were no detections of pathogens such as Salmonella, Campylobacter and Clostridium perfringens. However, high concentration of Ralstonia pickettii causing bacteremia was observed. Although carcass disposal soils examined in this study were not highly contaminated with pathogens, further monitoring is still needed to examine the potential threat of pathogens in leachate derived from carcass disposal sites.

• Clinical and Experimental Reproductive Medicine
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• v.37 no.1
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• pp.25-31
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• 2010

Objective: X inactivation is the silencing one of the two X chromosomes in female mammals for gene dosage on the X-chromosome between female and male. X inactivation is controlled by X inactive-specific transcript (XIST) gene, untranslated RNA. XIST is expressed only from the inactive X (Xi), not expressed from the active X (Xa). The Xist promoter is methylated on the silent Xist allele on the Xa in somatic cells, and less methylated on the Xist-expressing Xi. We investigated the difference of XIST methylation pattern of the promoter and 5'-region of XIST from male (XY) and female (XX) subjects. Methods: The direct quantification of XIST methylation is required for clinical application of normal XX and XY blood. Methylation percentage of eight CpG sites (-1696, -1679, -1475, -1473, -1469, +947, +956, +971) of XIST gene were diagnosed by pyrosequencing. Results: We directly quantitated the methylation percentage of the promoter and 5'-end of XIST by pyrosequencing. The average methylation percentages at CpG6-8 sites (+947, +956, +971) were 45.2% at CpG6, 49.9% at CpG7, and 44.2% at CpG8 from normal female and normal male were 90.6%, 96.7%, 87.8%, respectively. Nether CpG 1-5sites (-1696, -1679, -1475, -1473, -1469) had any effect on XX and XY. Conclusion: This method is sensitive for quantifying the small percentage change in the methylation status of XIST, and may be used for diagnosis.

• Korean Journal of Veterinary Research
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• v.57 no.2
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• pp.117-126
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• 2017

Bovine mastitis is an important microbial disease in the dairy industry. We investigated the frequencies of bacterial pathogens in 62 farms and pathogen antibiotic resistance from mastitis samples (n = 748). We tested the antimicrobial activity of chicken and duck egg white and lysozyme purified from chicken egg white. Moreover, we compared the microbiomes of normal and mastitic raw milk obtained by 16S rRNA gene pyrosequencing and culture methods. The results showed that the frequencies of Gram-positive pathogens (Enterococcus faecalis 37% and Staphylococcus aureus 36%) were higher than that of a Gram-negative pathogen (Escherichia coli 15%). Resistance frequencies to ampicillin and norfloxacin were lowest in Staphylococcus aureus (21%), Enterococcus faecalis (23%), and Escherichia coli (33%), and the antimicrobial activity of chicken egg white was higher than those of lysozyme and duck egg white. Pyrosequencing results revealed clear differences between the microbiomes of mastitic and normal raw milk samples and revealed a slightly similar, but clearly different, composition of pathogens compared to that from the culture method. Thus, pyrosequencing may be useful for elucidating changes in microbiomes during mastitis progression and treatment. A chicken egg white and antibiotic combination may help with mastitis treatment; however, further studies are needed.