• Journal of Mycology and Infection
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• 제24권2호
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• pp.37-44
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• 2019

To date, hundreds of fungal genomes have been sequenced, and many more are underway. Recently developed cutting-edge techniques generate very large amounts of data, and the field of fungal genomics in dermatology has consequently evolved substantially. Methodological improvements have broadened the scope of large-scale ecological studies in dermatology, including biodiversity assessments and genomic identification of fungi. Here, we aimed to provide a brief introduction to bioinformatic approaches to fungal genomics in the field of dermatology. We described the history and basic concepts of fungal genomics and presented sequencing-based techniques for fungal identification, including a list of the revised taxa of dermatophytes, as determined by current phylogenetic analysis. Finally, we discussed the emerging trends in fungal genomics in dermatology, such as next-generation sequencing.

• Genomics & Informatics
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• 제10권2호
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• pp.69-73
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• 2012

The explosive development of genomics technologies including microarrays and next generation sequencing (NGS) has provided comprehensive maps of cancer genomes, including the expression of mRNAs and microRNAs, DNA copy numbers, sequence variations, and epigenetic changes. These genome-wide profiles of the genetic aberrations could reveal the candidates for diagnostic and/or prognostic biomarkers as well as mechanistic insights into tumor development and progression. Recent efforts to establish the huge cancer genome compendium and integrative omics analyses, so-called "integromics", have extended our understanding on the cancer genome, showing its daunting complexity and heterogeneity. However, the challenges of the structured integration, sharing, and interpretation of the big omics data still remain to be resolved. Here, we review several issues raised in cancer omics data analysis, including NGS, focusing particularly on the study design and analysis strategies. This might be helpful to understand the current trends and strategies of the rapidly evolving cancer genomics research.

• Molecules and Cells
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• 제44권3호
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• pp.127-135
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• 2021

Since the introduction of RNA sequencing (RNA-seq) as a high-throughput mRNA expression analysis tool, this procedure has been increasingly implemented to identify cell-level transcriptome changes in a myriad of model systems. However, early methods processed cell samples in bulk, and therefore the unique transcriptomic patterns of individual cells would be lost due to data averaging. Nonetheless, the recent and continuous development of new single-cell RNA sequencing (scRNA-seq) toolkits has enabled researchers to compare transcriptomes at a single-cell resolution, thus facilitating the analysis of individual cellular features and a deeper understanding of cellular functions. Nonetheless, the rapid evolution of high throughput single-cell "omics" tools has created the need for effective hypothesis verification strategies. Particularly, this issue could be addressed by coupling cell engineering techniques with single-cell sequencing. This approach has been successfully employed to gain further insights into disease pathogenesis and the dynamics of differentiation trajectories. Therefore, this review will discuss the current status of cell engineering toolkits and their contributions to single-cell and genome-wide data collection and analyses.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2002년도 제2차워크샵
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• pp.171-189
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• 2002

• 한국육종학회지
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• 제43권2호
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• pp.103-114
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• 2011

In recent years, genomic resources and information have accumulated at an ever increasing pace, in many plant species, through whole genome sequencing, large scale analysis of transcriptomes, DNA markers and functional studies of individual genes. Well-characterized species within key plant taxa, co-called "model systems", have played a pivotal role in nucleating the accumulation of genomic information and databases, thereby providing the basis for comparative genomic studies. In addition, recent advances to "Next Generation" sequencing technologies have propelled a new wave of genomics, enabling rapid, low cost analysis of numerous genomes, and the accumulation of genetic diversity data for large numbers of accessions within individual species. The resulting wealth of genomic information provides an opportunity to discern evolutionary processes that have impacted genome structure and the function of genes, using the tools of comparative analysis. Comparative genomics provides a platform to translate information from model species to crops, and to relate knowledge of genome function among crop species. Ultimately, the resulting knowledge will accelerate the development of more efficient breeding strategies through the identification of trait-associated orthologous genes and next generation functional gene-based markers.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.31-36
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• 2021

RNA sequencing (RNA-Seq) is a technology that facilitates transcriptome analysis using next-generation sequencing (NSG) tools. Information on the quantity and sequences of RNA is vital to relate our genomes to functional protein expression. RNA-Seq data are characterized as being high-dimensional in that the number of variables (i.e., transcripts) far exceeds the number of observations (e.g., experiments). Given the wide range of dimensionality reduction techniques, it is not clear which is best for RNA-Seq data analysis. In this paper, we study the effect of three dimensionality reduction techniques to improve the classification of the RNA-Seq dataset. In particular, we use PCA, SVD, and SOM to obtain a reduced feature space. We built nine classification models for a cancer dataset and compared their performance. Our experimental results indicate that better classification performance is obtained with PCA and SOM. Overall, the combinations PCA+KNN, SOM+RF, and SOM+KNN produce preferred results.

• Journal of Veterinary Science
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• 제24권3호
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• pp.40.1-40.6
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• 2023

Analysis of the VP1 gene sequence of the foot and mouth disease virus (FMDV) is critical to understanding viral evolution and disease epidemiology. A standard set of primers have been used for the detection and sequence analysis of the VP1 gene of FMDV directly from suspected clinical samples with limited success. The study validated VP1-specific degenerate primer-based reverse transcription polymerase chain reaction (RT-PCR) for the qualitative detection and sequencing of serotype O FMDV lineages circulating in India. The novel degenerate primer-based RT-PCR amplifying the VP1 gene can circumvent the genetic heterogeneity observed in viruses after cell culture adaptation and facilitate precise viral gene sequence analysis from clinical samples.

• Asian-Australasian Journal of Animal Sciences
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• 제31권1호
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• pp.13-18
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• 2018

Objective: Meat quality including muscle color in chickens is an important trait and continuous selective pressures for fast growth and high yield have negatively impacted this trait. This study was conducted to investigate genetic variations responsible for regulating muscle color. Methods: Whole genome re-sequencing analysis using Illumina HiSeq paired end read method was performed with pooled DNA samples isolated from two broiler chicken lines divergently selected for muscle color (high muscle color [HMC] and low muscle color [LMC]) along with their random bred control line (RAN). Sequencing read data was aligned to the chicken reference genome sequence for Red Jungle Fowl (Galgal4) using reference based genome alignment with NGen program of the Lasergene software package. The potential causal single nucleotide polymorphisms (SNPs) showing non-synonymous changes in coding DNA sequence regions were chosen in each line. Bioinformatic analyses to interpret functions of genes retaining SNPs were performed using the ingenuity pathways analysis (IPA). Results: Millions of SNPs were identified and totally 2,884 SNPs (1,307 for HMC and 1,577 for LMC) showing >75% SNP rates could induce non-synonymous mutations in amino acid sequences. Of those, SNPs showing over 10 read depths yielded 15 more reliable SNPs including 1 for HMC and 14 for LMC. The IPA analyses suggested that meat color in chickens appeared to be associated with chromosomal DNA stability, the functions of ubiquitylation (UBC) and quality and quantity of various subtypes of collagens. Conclusion: In this study, various potential genetic markers showing amino acid changes were identified in differential meat color lines, that can be used for further animal selection strategy.

• 생명과학회지
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• 제25권3호
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• pp.357-367
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• 2015

매우 빠른 속도로 발전하고 있는 차세대 염기서열 분석 플랫폼과 최신 생물정보학적 분석도구들로 말미암아, 1,000달러 이하의 가격으로 인간 유전체 염기서열을 해독하고자 하는 궁극적인 목표가 조만간 곧 실현될 수 있을 것 같다. 차세대 염기서열 분석 분야의 급속한 기술적 진전은 NGS 데이터의 분석과 관리를 위한 통계적 방법과 생물정보학적 분석도구들에 대한 수요를 꾸준히 증대시키고 있다. NGS 플랫폼이 상용화되어 쓰이기 시작한 초창기부터, NGS 데이터를 분석하고 해석하거나, 가시화 해주는 다수의 응용프로그램이나 도구들이 개발되어 활용되어 왔다. 그러나, NGS 데이터의 엄청난 범람으로 데이터 저장, 데이터 분석 및 관리 등에 있어서 해결해야 할 많은 문제들이 부각되고 있다. NGS 데이터 분석은 단편서열과 참조서열간의 서열정렬, 염기식별, 다형성 발견, 쌍단편 서열이나 비쌍단편 서열 등을 이용한 어셈블리 작업, 구조변이 발견, 유전체 브라우징 등을 본질적으로 포함한다. 본 논문은 주요 차세대 염기서열 결정기술과 NGS 데이터 분석을 위한 생물정보학적 분석도구들에 대해 개관적으로 소개하고자 한다.

• 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.