Skip to main content
SpringerLink
Log in

The FANTOM5 Computation Ecosystem: Genomic Information Hub for Promoters and Active Enhancers

  • Protocol
  • First Online:
Protein Function Prediction

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1611))

Abstract

The Functional Annotation of the Mammalian Genome 5 (FANTOM5) project conducted transcriptome analysis of various mammalian cell types and provided a comprehensive resource to understand transcriptome and transcriptional regulation in individual cellular states encoded in the genome.

FANTOM5 used cap analysis of gene expression (CAGE) with single-molecule sequencing to map transcription start sites (TSS) and measured their expression in a diverse range of samples. The main results from FANTOM5 were published as a promoter-level mammalian expression atlas and an atlas of active enhancers across human cell types. The FANTOM5 dataset is composed of raw experimental data and the results of bioinformatics analyses. In this chapter, we give a detailed description of the content of the FANTOM5 dataset and elaborate on different computing applications developed to publish the data and enable reproducibility and discovery of new findings. We present use cases in which the FANTOM5 dataset has been reused, leading to new findings.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Wang Z, Gerstein M, Snyder M (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10(1):57–63. doi:10.1038/nrg2484

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Yu NY, Hallstrom BM, Fagerberg L et al (2015) Complementing tissue characterization by integrating transcriptome profiling from the human protein atlas and from the FANTOM5 consortium. Nucleic Acids Res 43(14):6787–6798. doi:10.1093/nar/gkv608

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Murata M, Nishiyori-Sueki H, Kojima-Ishiyama M et al (2014) Detecting expressed genes using CAGE. In: Miyamoto-Sato E, Ohashi H, Sasaki H, Nishikawa J-I, Yanagawa H (eds) Transcription factor regulatory networks: methods and protocols. Springer, New York, NY, pp 67–85. doi:10.1007/978-1-4939-0805-9_7

    Google Scholar 

  4. Kanamori-Katayama M, Itoh M, Kawaji H et al (2011) Unamplified cap analysis of gene expression on a single-molecule sequencer. Genome Res 21(7):1150–1159. doi:10.1101/gr.115469.110

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Takahashi H, Lassmann T, Murata M et al (2012) 5[prime] end-centered expression profiling using cap-analysis gene expression and next-generation sequencing. Nat Protoc 7(3):542–561

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Haberle V, Li N, Hadzhiev Y et al (2014) Two independent transcription initiation codes overlap on vertebrate core promoters. Nature 507(7492):381–385. doi:10.1038/nature12974

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Carninci P, Kasukawa T, Katayama S et al (2005) The transcriptional landscape of the mammalian genome. Science 309(5740):1559–1563. doi:10.1126/science.1112014

    Article  CAS  PubMed  Google Scholar 

  8. The ENCODE project consurtium (2012) An integrated encyclopedia of DNA elements in the human genome. Nature 489(7414):57–74

    Article  Google Scholar 

  9. Celniker SE, Dillon LAL, Gerstein MB et al (2009) Unlocking the secrets of the genome. Nature 459(7249):927–930

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. De Hoon M, Shin JW, Carninci P (2015) Paradigm shifts in genomics through the FANTOM projects. Mamm Genome 26(9–10):391–402. doi:10.1007/s00335-015-9593-8

    Article  PubMed  PubMed Central  Google Scholar 

  11. Forrest AR, Kawaji H, Rehli M et al (2014) A promoter-level mammalian expression atlas. Nature 507(7493):462–470. doi:10.1038/nature13182

    Article  CAS  PubMed  Google Scholar 

  12. Andersson R, Gebhard C, Miguel-Escalada I et al (2014) An atlas of active enhancers across human cell types and tissues. Nature 507(7493):455–461. doi:10.1038/nature12787

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Arner E, Daub CO, Vitting-Seerup K et al (2015) Gene regulation. Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells. Science 347(6225):1010–1014. doi:10.1126/science.1259418

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Lizio M, Harshbarger J, Shimoji H et al (2015) Gateways to the FANTOM5 promoter level mammalian expression atlas. Genome Biol 16:22. doi:10.1186/s13059-014-0560-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. The Functional Genomics Data Society (FGED), TFGDS MAGE-TAB Specification. http://www.mged.org/mage-tab/

    Google Scholar 

  16. Pearson WR, Lipman DJ (1988) Improved tools for biological sequence comparison. Proc Natl Acad Sci U S A 85(8):2444–2448

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Kodama Y, Mashima J, Kaminuma E et al (2012) The DNA data Bank of Japan launches a new resource, the DDBJ Omics archive of functional genomics experiments. Nucleic Acids Res 40(Database issue):D38–D42. doi:10.1093/nar/gkr994

    Article  CAS  PubMed  Google Scholar 

  18. Bard J, Rhee SY, Ashburner M (2005) An ontology for cell types. Genome Biol 6(2):R21. doi:10.1186/gb-2005-6-2-r21

    Article  PubMed  PubMed Central  Google Scholar 

  19. Kibbe WA, Arze C, Felix V et al (2015) Disease ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data. Nucleic Acids Res 43(Database issue):D1071–D1078. doi:10.1093/nar/gku1011

    Article  CAS  PubMed  Google Scholar 

  20. Druzinsky R, Mungall C, Haendel M et al (2013) What is an anatomy ontology? Anat Rec (Hoboken) 296(12):1797–1799. doi:10.1002/ar.22805

    Article  Google Scholar 

  21. Severin J, Lizio M, Harshbarger J et al (2014) Interactive visualization and analysis of large-scale sequencing datasets using ZENBU. Nat Biotechnol 32(3):217–219. doi:10.1038/nbt.2840

    Article  CAS  PubMed  Google Scholar 

  22. Abugessaisa I, Shimoji H, Sahin S et al (2016) FANTOM5 transcriptome catalog of cellular states based on Semantic MediaWiki. Database (Oxford) 2016. doi:10.1093/database/baw105

  23. Krötzsch M, Vrandečić D, Völkel M (2006) Semantic MediaWiki. In: Cruz I, Decker S, Allemang D et al (eds) The semantic web-ISWC 2006, Lecture notes in computer science, vol 4273. Springer, Berlin Heidelberg, pp 935–942. doi:10.1007/11926078_68

    Chapter  Google Scholar 

  24. Smedley D, Haider S, Durinck S et al (2015) The BioMart community portal: an innovative alternative to large, centralized data repositories. Nucleic Acids Res 43(W1):W589–W598. doi:10.1093/nar/gkv350

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Theocharidis A, van Dongen S, Enright AJ et al (2009) Network visualization and analysis of gene expression data using BioLayout express(3D). Nat Protoc 4(10):1535–1550. doi:10.1038/nprot.2009.177

    Article  CAS  PubMed  Google Scholar 

  26. Abugessaisa I (2010) Geospatial metadata extraction from product description document applying methods from ontology engineering. Int J Metadata Semant Ontologies 5(4):321–332. doi:10.1504/ijmso.2010.035554

    Article  Google Scholar 

  27. Patrinos GP, Cooper DN, van Mulligen E et al (2012) Microattribution and nanopublication as means to incentivize the placement of human genome variation data into the public domain. Hum Mutat 33(11):1503–1512. doi:10.1002/humu.22144

    Article  PubMed  Google Scholar 

  28. Speir ML, Zweig AS, Rosenbloom KR et al (2016) The UCSC genome browser database: 2016 update. Nucleic Acids Res 44(D1):D717–D725. doi:10.1093/nar/gkv1275

    Article  CAS  PubMed  Google Scholar 

  29. Finucane HK, Bulik-Sullivan B, Gusev A et al (2015) Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat Genet 47(11):1228–1235

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Kaczkowski B, Tanaka Y, Kawaji H et al (2016) Transcriptome analysis of recurrently deregulated genes across multiple cancers identifies new pan-cancer biomarkers. Cancer Res 76(2):216–226. doi:10.1158/0008-5472.CAN-15-0484

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgment

FANTOM5 was made possible by a Research Grant for RIKEN Omics Science Center from MEXT to Yoshihide Hayashizaki and a Grant of the Innovative Cell Biology by Innovative Technology (Cell Innovation Program) from the MEXT, Japan to Yoshihide Hayashizaki and to the RIKEN Center for Life Science Technologies. This study is also supported by Research Grants from the Japanese Ministry of Education, Culture, Sports, Science and Technology through RIKEN Centre for Life Science Technologies, Division of Genomic Technologies. We would like to thank all the members of the FANTOM5 consortium for contributing to the generation of samples and analysis of the data-set and thank GeNAS for data production.

Author information

Authors and Affiliations

  1. Division of Genomic Technologies, RIKEN Center for Life Science Technologies, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan

    Imad Abugessaisa, Shuhei Noguchi, Piero Carninci & Takeya Kasukawa

Authors
  1. Imad Abugessaisa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shuhei Noguchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Piero Carninci
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Takeya Kasukawa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Piero Carninci or Takeya Kasukawa .

Editor information

Editors and Affiliations

  1. Department of Biological Sciences and Computer Science, Purdue University, West Lafayette, Indiana, USA

    Daisuke Kihara

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media LLC

About this protocol

Cite this protocol

Abugessaisa, I., Noguchi, S., Carninci, P., Kasukawa, T. (2017). The FANTOM5 Computation Ecosystem: Genomic Information Hub for Promoters and Active Enhancers. In: Kihara, D. (eds) Protein Function Prediction. Methods in Molecular Biology, vol 1611. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7015-5_15

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-7015-5_15

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7013-1

  • Online ISBN: 978-1-4939-7015-5

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation