• Title/Summary/Keyword: RNA-sequencing

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No excessive mutations in transcription activator-like effector nuclease-mediated α-1,3-galactosyltransferase knockout Yucatan miniature pigs

  • Choi, Kimyung;Shim, Joohyun;Ko, Nayoung;Park, Joonghoon
    • Asian-Australasian Journal of Animal Sciences
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    • v.33 no.2
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    • pp.360-372
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    • 2020
  • Objective: Specific genomic sites can be recognized and permanently modified by genome editing. The discovery of endonucleases has advanced genome editing in pigs, attenuating xenograft rejection and cross-species disease transmission. However, off-target mutagenesis caused by these nucleases is a major barrier to putative clinical applications. Furthermore, off-target mutagenesis by genome editing has not yet been addressed in pigs. Methods: Here, we generated genetically inheritable α-1,3-galactosyltransferase (GGTA1) knockout Yucatan miniature pigs by combining transcription activator-like effector nuclease (TALEN) and nuclear transfer. For precise estimation of genomic mutations induced by TALEN in GGTA1 knockout pigs, we obtained the whole-genome sequence of the donor cells for use as an internal control genome. Results: In-depth whole-genome sequencing analysis demonstrated that TALEN-mediated GGTA1 knockout pigs had a comparable mutation rate to homologous recombination-treated pigs and wild-type strain controls. RNA sequencing analysis associated with genomic mutations revealed that TALEN-induced off-target mutations had no discernable effect on RNA transcript abundance. Conclusion: Therefore, TALEN appears to be a precise and safe tool for generating genomeedited pigs, and the TALEN-mediated GGTA1 knockout Yucatan miniature pigs produced in this study can serve as a safe and effective organ and tissue resource for clinical applications.

Reverse Transcription and Amplification of Halobacterial gvp Genes with Polymerase Chain Reaction Method (Polymerase Chain Reaction 방법에 의한 Halobacteria gvp 유전자의 역전사 및 증폭)

  • 윤병수;이상섭
    • Korean Journal of Microbiology
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    • v.30 no.6
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    • pp.456-459
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    • 1992
  • The genes of Halohacteria. gvpD and gvpE. take part in formation of gas vesicle. These mRNA cause a lot of experimental prohlems due to its eharacteristic instahility in the analysis of transcripts. This study allowed easy cloning and sequencing of RNA hy substituting a stable complementary DNA for the mRNA of the genes for an analysis. The weak 111 RNA was reverse transcribed to DNA using reverse transcriptase. and was amplified using PCR method. The transcripts confirmed in this ~,tudy have not heen round in the northern hybridization covering almost all ranges of ORF of the gene. gvpD.

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Effects of antibacterial mouth rinses on multiple oral biofilms model (구강세정제가 다중 구강 바이오필름 모델에 미치는 영향)

  • Soo-Kyung Jun;Young-Suk Choi
    • Journal of Korean society of Dental Hygiene
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    • v.23 no.4
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    • pp.209-218
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    • 2023
  • Objectives: To confirm the antibacterial effects of each mouth rinse on multiple oral biofilms in vitro. Methods: The antibacterial effects of different mouth rinses were examined by ATP and counted colony forming units (CFU). Preformed oral biofilms on saliva coated hydroxyapatite (sHA) disks were treated with essential oil and saline; then, the multiple oral biofilms were observed by Scanning electron microscope (SEM). RNA sequencing analysis was performed on total RNA isolated from old biofilms of P. intermedia ATCC 49046. Results: In the CFU measured result compared to controls, preformed multiple oral biofilms were reduced from a low of 39.0% to 95.7% (p<0.05). The size of bacterial cells changed after treatment with the essential oil, and some of the cells ruptured into small pieces of cell debris. Gene expression in P. intermedia ATCC 49046 significantly altered in RNA transcribed and protein translated genes after exposure to essential oil. Conclusions: Mouth rinse solutions with different ingredients had different antibacterial effects and may alter surface structure and gene expression as determined by RNA sequencing.

Analysis of Varietal Differences in Pre-harvest Sprouting of Rice using RNA-Sequencing (RNA-Sequencing을 이용한 벼 품종간 수발아 차이 분석)

  • Choi, Myoung-Goo;Lee, Hyen-Seok;Hwang, Woon-Ha;Yang, Seo-Yeong;Lee, Yun-Ho;Lee, Chung-gun;Yun, Song Joong;Jeong, Jae-Hyeok
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.65 no.4
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    • pp.274-283
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    • 2020
  • Seed dormancy is an adaptive trait in which seeds do not germinate under unfavorable environmental conditions. Low dormancy seeds are easily germinated under optimal environmental conditions, and these characteristics greatly reduce the yield and quality of crops. In the present study, we compared the pre-harvest sprouting (PHS) rate of two cultivars, Joun and Jopyeong, using the Winkler scale after heading day and temperature of the test. The PHS rate increased as the Winkler scale after heading day increased from 700℃ to 1100℃ and the temperature of the test increased. In all conditions, the PHS rate of Jopyeong was higher than that of Joun. RNA-sequencing was used to analyze the cause of the high PHS rate. We analyzed the biological metabolic processes related to the abscisic acid (ABA) metabolite pathway using the KEGG mapper with selected differentially expressed genes in PHS seeds. We found that the expression of ABA biosynthesis genes (OsNCEDs) was down-regulated and that ABA catabolic genes (OsCYP707As) was up-regulated in PHS seeds. However, the quantitative real-time PCR results showed that Joun had a higher expression of OsNCEDs than that of Jopyeong, but OsCYP707As did not yield a significant result. Joun displayed higher ABA content than that of Jopyeong not only during ripeness time but also during PHS treatment. Taken together, we provided evidence that the ABA content remaining in the seed is important to the PHS rate, which is determined by the expression level of the ABA biosynthesis gene OsNCEDs.

Recent advances in spatially resolved transcriptomics: challenges and opportunities

  • Lee, Jongwon;Yoo, Minsu;Choi, Jungmin
    • 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.

First complete mitogenome sequence of Korean Gloydius ussuriensis (Viperidae: Crotalinae)

  • Hye Sook Jeon;Min Seock Do;Jung A Kim;Yoonjee Hong;Chae Eun Lim;Jae-Hwa Suh;Junghwa An
    • Journal of Species Research
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    • v.13 no.2
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    • pp.127-130
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    • 2024
  • The first complete mitogenome sequence of the Red-tongue Pit Viper (Gloydius ussuriensis) from Korea was characterized using next-generation sequencing. The mitogenome is a circular molecule (17,209 bp) with a typical vertebrate mitogenome arrangement, which consists of 2 ribosomal RNA genes (rRNA), 22 transfer RNA genes (tRNA), two non-coding regions (D-loop), and 13 protein-coding genes (PCGs). The base composition of the mitogenome is 32.7% of A, 27.5% of C, 13.9% of G, and 25.9% of T, with a slight AT bias(58.6%). This phylogenetic analysis infers that G. ussuriensis is in the same group as the Chinese G. ussuriensis (Accession No. KP262412) and is closely related to G. blomhoffi and other species of the genus Gloydius. In our study, the complete mitogenome sequence of Korean G. ussuriensis was characterized and we provided basic genetic information on this species.

TRAPR: R Package for Statistical Analysis and Visualization of RNA-Seq Data

  • Lim, Jae Hyun;Lee, Soo Youn;Kim, Ju Han
    • Genomics & Informatics
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    • v.15 no.1
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    • pp.51-53
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    • 2017
  • High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.

A MA-plot-based Feature Selection by MRMR in SVM-RFE in RNA-Sequencing Data

  • Kim, Chayoung
    • The Journal of Korean Institute of Information Technology
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    • v.16 no.12
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    • pp.25-30
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    • 2018
  • It is extremely lacking and urgently required that the method of constructing the Gene Regulatory Network (GRN) from RNA-Sequencing data (RNA-Seq) because of Big-Data and GRN in Big-Data has obtained substantial observation as the interactions among relevant featured genes and their regulations. We propose newly the computational comparative feature patterns selection method by implementing a minimum-redundancy maximum-relevancy (MRMR) filter the support vector machine-recursive feature elimination (SVM-RFE) with Intensity-dependent normalization (DEGSEQ) as a preprocessor for emphasizing equal preciseness in RNA-seq in Big-Data. We found out the proposed algorithm might be more scalable and convenient because of all libraries in R package and be more improved in terms of the time consuming in Big-Data and minimum-redundancy maximum-relevancy of a set of feature patterns at the same time.

The Workflow for Computational Analysis of Single-cell RNA-sequencing Data (단일 세포 RNA 시퀀싱 데이터에 대한 컴퓨터 분석의 작업과정)

  • Sung-Hun WOO;Byung Chul JUNG
    • Korean Journal of Clinical Laboratory Science
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    • v.56 no.1
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    • pp.10-20
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    • 2024
  • RNA-sequencing (RNA-seq) is a technique used for providing global patterns of transcriptomes in samples. However, it can only provide the average gene expression across cells and does not address the heterogeneity within the samples. The advances in single-cell RNA sequencing (scRNA-seq) technology have revolutionized our understanding of heterogeneity and the dynamics of gene expression at the single-cell level. For example, scRNA-seq allows us to identify the cell types in complex tissues, which can provide information regarding the alteration of the cell population by perturbations, such as genetic modification. Since its initial introduction, scRNA-seq has rapidly become popular, leading to the development of a huge number of bioinformatic tools. However, the analysis of the big dataset generated from scRNA-seq requires a general understanding of the preprocessing of the dataset and a variety of analytical techniques. Here, we present an overview of the workflow involved in analyzing the scRNA-seq dataset. First, we describe the preprocessing of the dataset, including quality control, normalization, and dimensionality reduction. Then, we introduce the downstream analysis provided with the most commonly used computational packages. This review aims to provide a workflow guideline for new researchers interested in this field.

Development of Contig Assembly Program for Nucleotide Sequencing (염기서열 해독작업을 위한 핵산 단편 조립 프로그램의 개발)

  • 이동훈
    • Korean Journal of Microbiology
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    • v.35 no.2
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    • pp.121-127
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    • 1999
  • An effective computer program for assembling fragments in DNA sequencing has been developed. The program, called SeqEditor (Sequence Editor), is usable on the pcrsonal computer systems of MS-Widows which is the mosl popular operating system in Korea. It c'm recd several sequence file formats such as GenBak, FASTA, and ASCII. In the SeqEditor program, a dynamic programming algorihm is applied to compute the maximalscoring overlapping alignment between each pjlr of fragments. A novel feature of the program is that SeqEdilor implemnents interaclive operation with a graphical user interface. The performance lests of the prograln 011 fragmen1 data from 16s and 18s rDNA sequencing pi-ojects produced saiisIactory results. This program may be useful to a person who has work of time with large-scale DNA sequencing projects.

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