• 제목/요약/키워드: RNA sequencing

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Analysis of Whole Transcriptome Sequencing Data: Workflow and Software

  • Yang, In Seok;Kim, Sangwoo
    • Genomics & Informatics
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    • 제13권4호
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    • pp.119-125
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    • 2015
  • RNA is a polymeric molecule implicated in various biological processes, such as the coding, decoding, regulation, and expression of genes. Numerous studies have examined RNA features using whole transcriptome sequencing (RNA-seq) approaches. RNA-seq is a powerful technique for characterizing and quantifying the transcriptome and accelerates the development of bioinformatics software. In this review, we introduce routine RNA-seq workflow together with related software, focusing particularly on transcriptome reconstruction and expression quantification.

단일세포 RNA-SEQ의 유전자 발현 군집화를 위한 변이 자동인코더 기반의 차원감소와 군집화 (Variational Autoencoder Based Dimension Reduction and Clustering for Single-Cell RNA-seq Gene Expression)

  • 지상문
    • 한국정보통신학회논문지
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    • 제25권11호
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    • pp.1512-1518
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    • 2021
  • 단일세포 RNA-Seq 은 개별 세포의 유전자 발현을 제공하므로 세포마다 차등적인 고해상도 정보를 준다. 단일세포 RNA-Seq 자료에 대하여 군집화는 세포의 유형과 고수준의 생물 과정을 이해하기 위하여 수행된다. 매우 고차원이고 대용량인 단일세포 RNA-Seq을 효과적으로 처리하기 위하여, 본 논문은 변이 자동인코더를 사용하여 고차원의 자료공간을 저차원의 잠재공간으로 변환하여, 보다 정확한 군집화를 수행할 수 있는 특징공간을 만든다. 차원이 축소된 잠재공간에 다양한 군집화 방법을 적용하는 접근을 다양한 전통적인 단일세포 RNA-Seq 군집화 방법과 성능을 비교하였다. 군집화 실험을 통하여, 제안한 방법은 기존 방법들보다 다양한 군집화 성능기준에서 성능이 개선되었다.

COEX-Seq: Convert a Variety of Measurements of Gene Expression in RNA-Seq

  • Kim, Sang Cheol;Yu, Donghyeon;Cho, Seong Beom
    • Genomics & Informatics
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    • 제16권4호
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    • pp.36.1-36.3
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    • 2018
  • Next generation sequencing (NGS), a high-throughput DNA sequencing technology, is widely used for molecular biological studies. In NGS, RNA-sequencing (RNA-Seq), which is a short-read massively parallel sequencing, is a major quantitative transcriptome tool for different transcriptome studies. To utilize the RNA-Seq data, various quantification and analysis methods have been developed to solve specific research goals, including identification of differentially expressed genes and detection of novel transcripts. Because of the accumulation of RNA-Seq data in the public databases, there is a demand for integrative analysis. However, the available RNA-Seq data are stored in different formats such as read count, transcripts per million, and fragments per kilobase million. This hinders the integrative analysis of the RNA-Seq data. To solve this problem, we have developed a web-based application using Shiny, COEX-seq (Convert a Variety of Measurements of Gene Expression in RNA-Seq) that easily converts data in a variety of measurement formats of gene expression used in most bioinformatic tools for RNA-Seq. It provides a workflow that includes loading data set, selecting measurement formats of gene expression, and identifying gene names. COEX-seq is freely available for academic purposes and can be run on Windows, Mac OS, and Linux operating systems. Source code, sample data sets, and supplementary documentation are available as well.

Development of an RNA sequencing panel to detect gene fusions in thyroid cancer

  • Kim, Dongmoung;Jung, Seung-Hyun;Chung, Yeun-Jun
    • Genomics & Informatics
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    • 제19권4호
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    • pp.41.1-41.10
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    • 2021
  • In addition to mutations and copy number alterations, gene fusions are commonly identified in cancers. In thyroid cancer, fusions of important cancer-related genes have been commonly reported; however, extant panels do not cover all clinically important gene fusions. In this study, we aimed to develop a custom RNA-based sequencing panel to identify the key fusions in thyroid cancer. Our ThyChase panel was designed to detect 87 types of gene fusion. As quality control of RNA sequencing, five housekeeping genes were included in this panel. When we applied this panel for the analysis of fusions containing reference RNA (HD796), three expected fusions (EML4-ALK, CCDC6-RET, and TPM3-NTRK1) were successfully identified. We confirmed the fusion breakpoint sequences of the three fusions from HD796 by Sanger sequencing. Regarding the limit of detection, this panel could detect the target fusions from a tumor sample containing a 1% fusion-positive tumor cellular fraction. Taken together, our ThyChase panel would be useful to identify gene fusions in the clinical field.

Transcriptomic Analysis of Cellular Senescence: One Step Closer to Senescence Atlas

  • Kim, Sohee;Kim, Chuna
    • Molecules and Cells
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    • 제44권3호
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    • pp.136-145
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    • 2021
  • Senescent cells that gradually accumulate during aging are one of the leading causes of aging. While senolytics can improve aging in humans as well as mice by specifically eliminating senescent cells, the effect of the senolytics varies in different cell types, suggesting variations in senescence. Various factors can induce cellular senescence, and the rate of accumulation of senescent cells differ depending on the organ. In addition, since the heterogeneity is due to the spatiotemporal context of senescent cells, in vivo studies are needed to increase the understanding of senescent cells. Since current methods are often unable to distinguish senescent cells from other cells, efforts are being made to find markers commonly expressed in senescent cells using bulk RNA-sequencing. Moreover, single-cell RNA (scRNA) sequencing, which analyzes the transcripts of each cell, has been utilized to understand the in vivo characteristics of the rare senescent cells. Recently, transcriptomic cell atlases for each organ using this technology have been published in various species. Novel senescent cells that do not express previously established marker genes have been discovered in some organs. However, there is still insufficient information on senescent cells due to the limited throughput of the scRNA sequencing technology. Therefore, it is necessary to improve the throughput of the scRNA sequencing technology or develop a way to enrich the rare senescent cells. The in vivo senescent cell atlas that is established using rapidly developing single-cell technologies will contribute to the precise rejuvenation by specifically removing senescent cells in each tissue and individual.

Type-specific Amplification of 5S rRNA from Panax ginseng Cultivars Using Touchdown (TD) PCR and Direct Sequencing

  • Sun, Hun;Wang, Hong-Tao;Kwon, Woo-Saeng;Kim, Yeon-Ju;Yang, Deok-Chun
    • Journal of Ginseng Research
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    • 제33권1호
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    • pp.55-58
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    • 2009
  • Generally, the direct sequencing through PCR is faster, easier, cheaper, and more practical than clone sequencing. Frequently, standard PCR amplification is usually interpreted by mispriming internal or external regions of the target template. Normally, DNA fragments were eluted from the gel using Gel extraction kit and subjected to direct sequencing or cloning sequencing. Cloning sequencing has often troublesome and needs more time to analyze for many samples. Since touchdown (TD) PCR can generate sufficient and highly specific amplification, it reduces unwanted amplicon generation. Accordingly, TD PCR is a good method for direct sequencing due to amplifying wanted fragment. In plants the 5S-rRNA gene is separated by simple spacers. The 5S-rRNA gene sequence is very well-conserved between plant species while the spacer is species-specific. Therefore, the sequence has been used for phylogenetic studies and species identification. But frequent occurrences of spurious bands caused by complex genomes are encountered in the product spectrum of standard PCR amplification. In conclusion, the TD PCR method can be applied easily to amplify main 5S-rRNA and direct sequencing of panax ginseng cultivars.

Integrative Comparison of Burrows-Wheeler Transform-Based Mapping Algorithm with de Bruijn Graph for Identification of Lung/Liver Cancer-Specific Gene

  • Ajaykumar, Atul;Yang, Jung Jin
    • Journal of Microbiology and Biotechnology
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    • 제32권2호
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    • pp.149-159
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    • 2022
  • Cancers of the lung and liver are the top 10 leading causes of cancer death worldwide. Thus, it is essential to identify the genes specifically expressed in these two cancer types to develop new therapeutics. Although many messenger RNA (mRNA) sequencing data related to these cancer cells are available due to the advancement of next-generation sequencing (NGS) technologies, optimized data processing methods need to be developed to identify the novel cancer-specific genes. Here, we conducted an analytical comparison between Bowtie2, a Burrows-Wheeler transform-based alignment tool, and Kallisto, which adopts pseudo alignment based on a transcriptome de Bruijn graph using mRNA sequencing data on normal cells and lung/liver cancer tissues. Before using cancer data, simulated mRNA sequencing reads were generated, and the high Transcripts Per Million (TPM) values were compared. mRNA sequencing reads data on lung/liver cancer cells were also extracted and quantified. While Kallisto could directly give the output in TPM values, Bowtie2 provided the counts. Thus, TPM values were calculated by processing the Sequence Alignment Map (SAM) file in R using package Rsubread and subsequently in python. The analysis of the simulated sequencing data revealed that Kallisto could detect more transcripts and had a higher overlap over Bowtie2. The evaluation of these two data processing methods using the known lung cancer biomarkers concludes that in standard settings without any dedicated quality control, Kallisto is more effective at producing faster and more accurate results than Bowtie2. Such conclusions were also drawn and confirmed with the known biomarkers specific to liver cancer.

단세포 RNA 시퀀싱 데이터를 위한 가중변수 스펙트럼 군집화 기법 (One-step spectral clustering of weighted variables on single-cell RNA-sequencing data)

  • 박민영;박세영
    • 응용통계연구
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    • 제33권4호
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    • pp.511-526
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    • 2020
  • 단세포 RNA 시퀀싱 데이터(single-cell RNA-sequencing data, 이하 단세포 RNA 데이터)는 세포 조직으로부터 추출한 각 단세포 별 유전자의 신호를 기록한 데이터로, 세포 간의 이질성을 파악하는 것을 주요 목적으로 한다. 그러나 단세포 RNA 데이터는 샘플링 및 기술적인 한계로 인해 결측비율이 높고, 노이즈가 크다. 이러한 이유 때문에 기존의 군집화 방법을 적용하는 데에 한계가 존재한다. 본 논문에서는 단세포 RNA 데이터 분석에서 모티브를 얻어 스펙트럼 군집화(spectral clustering) 기반의 방법을 제안한다. 특히 유사도 행렬(similarity matrix) 계산에서 유전자 별로 가중치를 부여하여 기존의 단세포 데이터 분석 방법과 차별화하였다. 제안하는 군집화 방법은 유전자별 가중치를 부여함과 동시에 세포를 군집화한다. 군집화는 반복 알고리즘을 통해 제안하는 비볼록식(non-convex optimization)을 풀어 진행한다. 또한 실데이터 적용과 시뮬레이션을 통해 제안하는 군집화 방법이 기존의 방법보다 군집을 잘 구분하는 것을 보인다.

Identification of Alternative Splicing and Fusion Transcripts in Non-Small Cell Lung Cancer by RNA Sequencing

  • Hong, Yoonki;Kim, Woo Jin;Bang, Chi Young;Lee, Jae Cheol;Oh, Yeon-Mok
    • Tuberculosis and Respiratory Diseases
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    • 제79권2호
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    • pp.85-90
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    • 2016
  • Background: Lung cancer is the most common cause of cancer related death. Alterations in gene sequence, structure, and expression have an important role in the pathogenesis of lung cancer. Fusion genes and alternative splicing of cancer-related genes have the potential to be oncogenic. In the current study, we performed RNA-sequencing (RNA-seq) to investigate potential fusion genes and alternative splicing in non-small cell lung cancer. Methods: RNA was isolated from lung tissues obtained from 86 subjects with lung cancer. The RNA samples from lung cancer and normal tissues were processed with RNA-seq using the HiSeq 2000 system. Fusion genes were evaluated using Defuse and ChimeraScan. Candidate fusion transcripts were validated by Sanger sequencing. Alternative splicing was analyzed using multivariate analysis of transcript sequencing and validated using quantitative real time polymerase chain reaction. Results: RNA-seq data identified oncogenic fusion genes EML4-ALK and SLC34A2-ROS1 in three of 86 normal-cancer paired samples. Nine distinct fusion transcripts were selected using DeFuse and ChimeraScan; of which, four fusion transcripts were validated by Sanger sequencing. In 33 squamous cell carcinoma, 29 tumor specific skipped exon events and six mutually exclusive exon events were identified. ITGB4 and PYCR1 were top genes that showed significant tumor specific splice variants. Conclusion: In conclusion, RNA-seq data identified novel potential fusion transcripts and splice variants. Further evaluation of their functional significance in the pathogenesis of lung cancer is required.

Assessment of the gastrointestinal microbiota using 16S ribosomal RNA gene amplicon sequencing in ruminant nutrition

  • Minseok Kim
    • Animal Bioscience
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    • 제36권2_spc호
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    • pp.364-373
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    • 2023
  • The gastrointestinal (GI) tract of ruminants contains diverse microbes that ferment various feeds ingested by animals to produce various fermentation products, such as volatile fatty acids. Fermentation products can affect animal performance, health, and well-being. Within the GI microbes, the ruminal microbes are highly diverse, greatly contribute to fermentation, and are the most important in ruminant nutrition. Although traditional cultivation methods provided knowledge of the metabolism of GI microbes, most of the GI microbes could not be cultured on standard culture media. By contrast, amplicon sequencing of 16S rRNA genes can be used to detect unculturable microbes. Using this approach, ruminant nutritionists and microbiologists have conducted a plethora of nutritional studies, many including dietary interventions, to improve fermentation efficiency and nutrient utilization, which has greatly expanded knowledge of the GI microbiota. This review addresses the GI content sampling method, 16S rRNA gene amplicon sequencing, and bioinformatics analysis and then discusses recent studies on the various factors, such as diet, breed, gender, animal performance, and heat stress, that influence the GI microbiota and thereby ruminant nutrition.