• Title/Summary/Keyword: Data Annotation

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Identification of Differentially Expressed Genes in Ducks in Response to Avian Influenza A Virus Infections

  • Ndimukaga, Marc;Won, Kyunghye;Truong, Anh Duc;Song, Ki-Duk
    • Korean Journal of Poultry Science
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    • v.47 no.1
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    • pp.9-19
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    • 2020
  • Avian influenza (AI) viruses are highly contagious viruses that infect many bird species and are zoonotic. Ducks are resistant to the deadly and highly pathogenic avian influenza virus (HPAIV) and remain asymptomatic to the low pathogenic avian influenza virus (LPAIV). In this study, we identified common differentially expressed genes (DEGs) after a reanalysis of previous transcriptomic data for the HPAIV and LPAIV infected duck lung cells. Microarray datasets from a previous study were reanalyzed to identify common target genes from DEGs and their biological functions. A total of 731 and 439 DEGs were identified in HPAIV- and LPAIV-infected duck lung cells, respectively. Of these, 227 genes were common to cells infected with both viruses, in which 193 genes were upregulated and 34 genes were downregulated. Functional annotation of common DEGs revealed that translation related gene ontology (GO) terms were enriched, including ribosome, protein metabolism, and gene expression. REACTOME analyses also identified pathways for protein and RNA metabolism as well as for tissue repair, including collagen biosynthesis and modification, suggesting that AIVs may evade the host defense system by suppressing host translation machinery or may be suppressed before being exported to the cytosol for translation. AIV infection also increased collagen synthesis, showing that tissue lesions by virus infection may be mediated by this pathway. Further studies should focus on these genes to clarify their roles in AIV pathogenesis and their possible use in AIV therapeutics.

Transcriptome profiling and comparative analysis of Panax ginseng adventitious roots

  • Jayakodi, Murukarthick;Lee, Sang-Choon;Park, Hyun-Seung;Jang, Woojong;Lee, Yun Sun;Choi, Beom-Soon;Nah, Gyoung Ju;Kim, Do-Soon;Natesan, Senthil;Sun, Chao;Yang, Tae-Jin
    • Journal of Ginseng Research
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    • v.38 no.4
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    • pp.278-288
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    • 2014
  • Background: Panax ginseng Meyer is a traditional medicinal plant famous for its strong therapeutic effects and serves as an important herbal medicine. To understand and manipulate genes involved in secondary metabolic pathways including ginsenosides, transcriptome profiling of P. ginseng is essential. Methods: RNA-seq analysis of adventitious roots of two P. ginseng cultivars, Chunpoong (CP) and Cheongsun (CS), was performed using the Illumina HiSeq platform. After transcripts were assembled, expression profiling was performed. Results: Assemblies were generated from ~85 million and ~77 million high-quality reads from CP and CS cultivars, respectively. A total of 35,527 and 27,716 transcripts were obtained from the CP and CS assemblies, respectively. Annotation of the transcriptomes showed that approximately 90% of the transcripts had significant matches in public databases.We identified several candidate genes involved in ginsenoside biosynthesis. In addition, a large number of transcripts (17%) with different gene ontology designations were uniquely detected in adventitious roots compared to normal ginseng roots. Conclusion: This study will provide a comprehensive insight into the transcriptome of ginseng adventitious roots, and a way for successful transcriptome analysis and profiling of resource plants with less genomic information. The transcriptome profiling data generated in this study are available in our newly created adventitious root transcriptome database (http://im-crop.snu.ac.kr/transdb/index.php) for public use.

Transcriptome and Flower Color Related Gene Analysis in Angelica gigas Nakai Using RNA-Seq (RNA-seq을 이용한 참당귀의 전사체 분석과 꽃 색 관련 유전자 분석)

  • Kim, Nam Su;Jung, Dae Hui;Park, Hong Woo;Park, Yun mi;Jeon, Kwon Seok;Kim, Mahn Jo
    • Proceedings of the Plant Resources Society of Korea Conference
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    • 2019.10a
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    • pp.73-73
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    • 2019
  • Angelica gigas Nakai (Korean danggui), a member of the Umbelliferae family, is a Korean traditional medicinal plant whose roots have been used for treating gynecological diseases. Transcriptomics is the study of the transcriptome, which is the complete set of RNA transcripts that are produced by the genome, using high-throughput methods, such as microarray analysis. In this study, transcriptome analysis of A.gigas Nakai was carried out. Transcriptome sequencing and assembly was carried out by using Illumina Hiseq 2500, Velvet and Oases. A total of 109,591,555 clean reads of A. gigas Nakai was obtained after trimming adaptors. The obtained reads were assembled with an average length of 1,154 bp, a maximum length of 13,166 bp, a minimum length of 200 pb, and N50 of 1,635 bp. Functional annotation and classification was performed using NCBI NR, InterprotScan, KOG, KEGG and GO. Candidate genes for phenylpropanoid biosynthesis were obtanied from A.gigas transcriptome and the genes and its proteins were confirmed through the NCBI homology BLAST searches, revealing high identity with other othologous genes and proteins from various plants pecies. In RNA sequencing analysis using an Illumina Next-Seq2500 sequencer, we identified a total 94,930 transcripts and annotated 71,281 transcripts, which provide basic information for further research in A.gigas Nakai. Our transcriptome data reveal that several differentially expressed genes related to flower color in A.gigas Nakai. The results of this research provide comprehensive information on the A.gigas Nakai genome and enhance our understanding of the flower color related gene pathways in this plant.

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Korea Brassica Genome Project: Current Status and Prospective (배추 유전체열구의 현황과 전망)

  • Choi, Su-Ryun;Park, Jee-Yong;Park, Beom-Seok;Kim, Ho-Il;Lim, Yong-Pyo
    • Journal of Plant Biotechnology
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    • v.33 no.3
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    • pp.153-160
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    • 2006
  • Brassica rape is an important species used as a vegetable, oil, and fodder worldwide. It is related phylogenically to Arabidopsis thaliana, which has already been fully sequenced as a model plant. The 'Multinational Brassica Genome Project (MBGP)'was launched by the international Brassica community with the aim of sequencing the whole genome of B. rapa in 2003 on account of its value and the fact that it has the smallest genome among the diploid Brassica. The genome study was carried out not only to know the structure of genome but also to understand the function and the evolution of the genes comprehensively. There are two mapping populations, over 1,000 molecular markers and a genetic map, 2 BAC libraries, physical map, a 22 cDHA libraries as suitable genomic materials for examining the genome of B. rapa ssp. pekinensis Chinese cabbage. As the first step for whole genome analysis, 220,000 BAC-end sequences of the KBrH and KBrB BAC library are achieved by cooperation of six countries. The results of BAC-end sequence analysis will provide a clue in understanding the structure of the genome of Brassica rapa by analyzing the gene sequence, annotation and abundant repetitive DHA. The second stage involves sequencing of the genetically mapped seed BACs and identifying the overlapping BACs for complete genome sequencing. Currently, the second stage is comprises of process genetic anchoring using communal populations and maps to identify more than 1,000 seed BACs based on a BAC-to-BAC strategy. For the initial sequencing, 629 seed BACs corresponding to the minimum tiling path onto Arabidopsis genome were selected and fully sequenced. These BACs are now anchoring to the genetic map using the development of SSR markers. This information will be useful for identifying near BAC clones with the seed BAC on a genome map. From the BAC sequences, it is revealed that the Brassica rapa genome has extensive triplication of the DNA segment coupled with variable gene losses and rearrangements within the segments. This article introduces the current status and prospective of Korea Brassica Genome Project and the bioinformatics tools possessed in each national team. In the near future, data of the genome will contribute to improving Brassicas for their economic use as well as in understanding the evolutional process.