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Identifying Sequenced Eukaryotic Genomes and Transcriptomes with diArk

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Eukaryotic Genomic Databases

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1757))

Abstract

The diArk Eukaryotic Genome Database is a manually curated and updated repository of available eukaryotic genome and transcriptome assemblies. diArk is a key resource for researchers interested in comparative eukaryotic genomics, and the entry point to browsing sequenced eukaryotes in general and to find the most closely related species to the own organism of interest in particular. The exponentially increasing number of sequenced species demands sophisticated search and data presentation tools. In this chapter we describe how to navigate the diArk database keeping a first-time user in mind.

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References

  1. Odronitz F, Hellkamp M, Kollmar M (2007) diArk--a resource for eukaryotic genome research. BMC Genomics 8:103. https://doi.org/10.1186/1471-2164-8-103

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Clark AG, Eisen MB, Smith DR et al (2007) Evolution of genes and genomes on the drosophila phylogeny. Nature 450:203–218. https://doi.org/10.1038/nature06341

    Article  PubMed  CAS  Google Scholar 

  3. Lindblad-Toh K, Garber M, Zuk O et al (2011) A high-resolution map of human evolutionary constraint using 29 mammals. Nature 478:476–482. https://doi.org/10.1038/nature10530

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Genome 10K Community of Scientists (2009) Genome 10K: a proposal to obtain whole-genome sequence for 10 000 vertebrate species. J Hered 100:659–674. https://doi.org/10.1093/jhered/esp086

    Article  PubMed Central  CAS  Google Scholar 

  5. Zhang G, Rahbek C, Graves GR et al (2015) Genomics: bird sequencing project takes off. Nature 522:34. https://doi.org/10.1038/522034d

    Article  PubMed  CAS  Google Scholar 

  6. i5K Consortium (2013) The i5K initiative: advancing arthropod genomics for knowledge, human health, agriculture, and the environment. J Hered 104:595–600. https://doi.org/10.1093/jhered/est050

    Article  PubMed Central  Google Scholar 

  7. Kumar S, Schiffer PH, Blaxter M (2012) 959 nematode genomes: a semantic wiki for coordinating sequencing projects. Nucleic Acids Res 40:D1295–D1300. https://doi.org/10.1093/nar/gkr826

    Article  PubMed  CAS  Google Scholar 

  8. Kumar S, Koutsovoulos G, Kaur G, Blaxter M (2012) Toward 959 nematode genomes. WormBook 1:42–50. https://doi.org/10.4161/worm.19046

    Article  Google Scholar 

  9. Matasci N, Hung L-H, Yan Z et al (2014) Data access for the 1,000 plants (1KP) project. GigaScience 3:17. https://doi.org/10.1186/2047-217X-3-17

    Article  PubMed  PubMed Central  Google Scholar 

  10. Keeling PJ, Burki F, Wilcox HM et al (2014) The marine microbial eukaryote Transcriptome sequencing project (MMETSP): illuminating the functional diversity of eukaryotic life in the oceans through transcriptome sequencing. PLoS Biol 12:e1001889. https://doi.org/10.1371/journal.pbio.1001889

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Sun Y, Huang Y, Li X et al (2016) Fish-T1K (Transcriptomes of 1,000 fishes) project: large-scale transcriptome data for fish evolution studies. GigaScience 5:18. https://doi.org/10.1186/s13742-016-0124-7

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Normile D (2017) Plant scientists plan massive effort to sequence 10,000 genomes. In: Sci. AAAS. http://www.sciencemag.org/news/2017/07/plant-scientists-plan-massive-effort-sequence-10000-genomes. Accessed 28 Aug 2017

  13. Kitts PA, Church DM, Thibaud-Nissen F et al (2016) Assembly: a resource for assembled genomes at NCBI. Nucleic Acids Res 44:D73–D80. https://doi.org/10.1093/nar/gkv1226

    Article  PubMed  CAS  Google Scholar 

  14. Hammesfahr B, Odronitz F, Hellkamp M, Kollmar M (2011) diArk 2.0 provides detailed analyses of the ever increasing eukaryotic genome sequencing data. BMC Res Notes 4:338. https://doi.org/10.1186/1756-0500-4-338

    Article  PubMed  PubMed Central  Google Scholar 

  15. Kollmar M, Kollmar L, Hammesfahr B, Simm D (2015) diArk – the database for eukaryotic genome and transcriptome assemblies in 2014. Nucleic Acids Res 43:D1107–D1112. https://doi.org/10.1093/nar/gku990

    Article  PubMed  CAS  Google Scholar 

  16. Federhen S (2012) The NCBI taxonomy database. Nucleic Acids Res 40:D136–D143. https://doi.org/10.1093/nar/gkr1178

    Article  PubMed  CAS  Google Scholar 

  17. Kaye J, Heeney C, Hawkins N et al (2009) Data sharing in genomics — re-shaping scientific practice. Nat Rev Genet 10:331–335. https://doi.org/10.1038/nrg2573

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Author information

Authors and Affiliations

  1. Group Systems Biology of Motor Proteins, Department of NMR-Based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany

    Martin Kollmar & Dominic Simm

  2. Theoretical Computer Science and Algorithmic Methods, Institute of Computer Science, Georg-August-University, Göttingen, Germany

    Dominic Simm

Authors
  1. Martin Kollmar
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  2. Dominic Simm
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Corresponding author

Correspondence to Martin Kollmar .

Editor information

Editors and Affiliations

  1. Group Systems Biology of Motor Proteins, Department of NMR-Based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany

    Martin Kollmar

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Kollmar, M., Simm, D. (2018). Identifying Sequenced Eukaryotic Genomes and Transcriptomes with diArk. In: Kollmar, M. (eds) Eukaryotic Genomic Databases. Methods in Molecular Biology, vol 1757. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7737-6_1

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  • DOI: https://doi.org/10.1007/978-1-4939-7737-6_1

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7736-9

  • Online ISBN: 978-1-4939-7737-6

  • eBook Packages: Springer Protocols

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