Collaborative environmental DNA sampling from petal surfaces of flowering cherry Cerasus × yedoensis ‘Somei-yoshino’ across the Japanese archipelago

  • Tazro Ohta
  • Takeshi Kawashima
  • Natsuko O. Shinozaki
  • Akito Dobashi
  • Satoshi Hiraoka
  • Tatsuhiko Hoshino
  • Keiichi Kanno
  • Takafumi Kataoka
  • Shuichi Kawashima
  • Motomu Matsui
  • Wataru Nemoto
  • Suguru Nishijima
  • Natsuki Suganuma
  • Haruo Suzuki
  • Y-h. Taguchi
  • Yoichi Takenaka
  • Yosuke Tanigawa
  • Momoka Tsuneyoshi
  • Kazutoshi Yoshitake
  • Yukuto Sato
  • Riu Yamashita
  • Kazuharu Arakawa
  • Wataru Iwasaki
Technical Note

Abstract

Recent studies have shown that environmental DNA is found almost everywhere. Flower petal surfaces are an attractive tissue to use for investigation of the dispersal of environmental DNA in nature as they are isolated from the external environment until the bud opens and only then can the petal surface accumulate environmental DNA. Here, we performed a crowdsourced experiment, the “Ohanami Project”, to obtain environmental DNA samples from petal surfaces of Cerasus × yedoensis ‘Somei-yoshino’ across the Japanese archipelago during spring 2015. C. × yedoensis is the most popular garden cherry species in Japan and clones of this cultivar bloom simultaneously every spring. Data collection spanned almost every prefecture and totaled 577 DNA samples from 149 collaborators. Preliminary amplicon-sequencing analysis showed the rapid attachment of environmental DNA onto the petal surfaces. Notably, we found DNA of other common plant species in samples obtained from a wide distribution; this DNA likely originated from the pollen of the Japanese cedar. Our analysis supports our belief that petal surfaces after blossoming are a promising target to reveal the dynamics of environmental DNA in nature. The success of our experiment also shows that crowdsourced environmental DNA analyses have considerable value in ecological studies.

Keywords

Crowdsourcing Cherry blossom Environmental DNA Amplicon sequencing 

Notes

Acknowledgements

We thank all the Ohanami Project collaborators (Supplementary material 5) for their help with sampling. We also thank the NGS Field 4th Meeting organizers who encouraged us to publish this manuscript. We thank Dr. Hiroshi Mori of National Institute of Genetics for helpful comments. We would also like to show our gratitude to Halna Tsunekawa for graphical design of the project website and the logo. Computations were partially performed on the NIG supercomputer at ROIS National Institute of Genetics.

Author contributions

TO, TK, YS, RY, KA, and WI led the project. NS, YS, and RY performed library construction and sequencing. TO, TK, AD, SH, TH, KK, TK, SK, MM, WN, SN, NS, HS, Y-hT, YT, YT, MT, KY, YS, and KA performed data analysis. TO developed the data management system and submitted data to the public repository. TK, TO, and WI wrote the manuscript.

Funding

This work was supported by the NGS Field 4th Meeting.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest associated with this manuscript.

Supplementary material

10265_2018_1017_MOESM1_ESM.pdf (257 kb)
Supplementary material 1 Sampling protocol handout for participants of the sampling campaign held in 2015. The instructions in the sampling protocol were provided to participants in the text and embedded photographs. The instructions also state the protocol for storage and transfer of the collected samples (PDF 257 KB)
10265_2018_1017_MOESM2_ESM.pdf (3.6 mb)
Supplementary material 2 Figs. S1–S3, Tables S1–S4 (PDF 3699 KB)
10265_2018_1017_MOESM3_ESM.csv (19 kb)
Supplementary material 3 Index sequences used for the 1st sequence run. The data submitted to the DDBJ Sequence Read Archive are already demultiplexed and do not contain the index sequences (CSV 18 KB)
10265_2018_1017_MOESM4_ESM.csv (18 kb)
Supplementary material 4 Index sequences used for the 2nd sequence run. The data submitted to the DDBJ Sequence Read Archive are already demultiplexed and do not contain the index sequences (CSV 18 KB)
10265_2018_1017_MOESM5_ESM.pdf (62 kb)
Supplementary material 5 The Ohanami project collaborators (PDF 62 KB)

References

  1. Afshinnekoo E, Meydan C, Chowdhury S et al (2015) Geospatial resolution of human and bacterial diversity with city-scale metagenomics. Cell Syst 1:72–87.  https://doi.org/10.1016/j.cels.2015.01.001 CrossRefPubMedPubMedCentralGoogle Scholar
  2. Andrews S (2010) FastQC: a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc Accessed 17 Feb 2017
  3. Cox MP, Peterson DA, Biggs PJ (2010) SolexaQA: at-a-glance quality assessment of Illumina second-generation sequencing data. BMC Bioinform 11:485.  https://doi.org/10.1186/1471-2105-11-485 CrossRefGoogle Scholar
  4. Feng L, Zhang Y, Xi J, Zhu Y, Wang N, Xia F, Jiang L (2008) Petal effect: a superhydrophobic state with high adhesive force. Langmuir 24:4114–4119.  https://doi.org/10.1021/la703821h CrossRefPubMedGoogle Scholar
  5. Howe J (2006) The rise of Crowdsourcing. Wired 2006. https://www.wired.com/2006/06/crowds/. Accessed 17 Feb 2017
  6. Iketani H, Ohta S, Kawahara T, Katsuki T, Mase N, Sato Y, Yamamoto T (2007) Analyses of clonal status in ‘Somei-yoshino’and confirmation of genealogical record in other cultivars of Prunus × yedoensis by microsatellite markers. Breed Sci 57:1–6.  https://doi.org/10.1270/jsbbs.57.1 CrossRefGoogle Scholar
  7. Innan H, Terauchi R, Miyashita NT, Tsunewaki K (1995) DNA fingerprinting study on the intraspecific variation and the origin of Prunus yedoensis (Someiyoshino). Jap J Genet 70:185–196.  https://doi.org/10.1266/jjg.70.185 CrossRefGoogle Scholar
  8. Japan Meteorological Agency (2015) Forecast of cherry blossom blooming date. http://www.data.jma.go.jp/sakura/data/sakura004_03.html. Accessed 17 Feb 2017
  9. Kato S, Matsumoto A, Yoshimura K, Katsuki T, Iwamoto K, Tsuda Y, Ishio S, Nakamura K, Moriwaki K, Shiroishi T, Gojobori T, Yoshimaru H (2012) Clone identification in Japanese flowering cherry (Prunus subgenus Cerasus) cultivars using nuclear SSR markers. Breed Sci 62:248–255.  https://doi.org/10.1270/jsbbs.62.248 CrossRefPubMedPubMedCentralGoogle Scholar
  10. Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD (2013) Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 79:5112–5120.  https://doi.org/10.1128/AEM.01043-13 CrossRefPubMedPubMedCentralGoogle Scholar
  11. Lindstrom K (2007) From experimental to chronometric seasonality—the establishment of seasons as a national symbol in modern Japan. In: Palang H, Sooväli H, Printsmann A (eds) Seasonal landscapes. Springer, Dordrecht, pp 225–229.  https://doi.org/10.1007/1-4020-4990-0_9
  12. Magoč T, Salzberg SL (2011) FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27:2957–2963.  https://doi.org/10.1093/bioinformatics/btr507 CrossRefPubMedPubMedCentralGoogle Scholar
  13. MetaSUB International Consortium (2016) The metagenomics and metadesign of the subways and urban biomes (MetaSUB) international consortium inaugural meeting report. Microbiome 4:1–14.  https://doi.org/10.1186/s40168-016-0168-z CrossRefGoogle Scholar
  14. Morgulis A, Coulouris G, Raytselis Y, Madden TL, Agarwala R, Schäffer AA (2008) Database indexing for production MegaBLAST searches. Bioinformatics 24:1757–1764.  https://doi.org/10.1093/bioinformatics/btn322 CrossRefPubMedPubMedCentralGoogle Scholar
  15. Rosario K, Breitbart M (2011) Exploring the viral world through metagenomics. Curr Opin Virol 1:289–297.  https://doi.org/10.1016/j.coviro.2011.06.004 CrossRefPubMedGoogle Scholar
  16. Schmieder R, Lim YW, Rohwer F, Edwards R (2010) TagCleaner: Identification and removal of tag sequences from genomic and metagenomic datasets. BMC Bioinform 11:341.  https://doi.org/10.1186/1471-2105-11-341 CrossRefGoogle Scholar
  17. Shirahata Y (2000) Hanami to sakura: Nihon teki naru mono saikō [Hanami and Sakura: Reconsideration of what Japanese style is]. PHP Institute, KyotoGoogle Scholar
  18. Wolfsberg TG, Schafer S, Tatusov RL, Tatusova TA (2001) Organelle genome resources at NCBI. Trends Biochem Sci 26:199–202.  https://doi.org/10.1016/S0968-0004(00)01773-4 CrossRefPubMedGoogle Scholar
  19. Yamagishi J, Sato Y, Shinozaki N, Ye B, Tsuboi A, Nagasaki M, Yamashita R (2016) Comparison of boiling and robotics automation method in DNA extraction for metagenomic sequencing of human oral microbes. PloS One 11:e0154389.  https://doi.org/10.1371/journal.pone.0154389 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© The Botanical Society of Japan and Springer Japan KK, part of Springer Nature 2018

Authors and Affiliations

  • Tazro Ohta
    • 1
  • Takeshi Kawashima
    • 2
  • Natsuko O. Shinozaki
    • 3
  • Akito Dobashi
    • 4
  • Satoshi Hiraoka
    • 5
  • Tatsuhiko Hoshino
    • 6
  • Keiichi Kanno
    • 7
  • Takafumi Kataoka
    • 8
  • Shuichi Kawashima
    • 9
  • Motomu Matsui
    • 10
  • Wataru Nemoto
    • 11
  • Suguru Nishijima
    • 12
    • 13
    • 14
  • Natsuki Suganuma
    • 15
  • Haruo Suzuki
    • 16
  • Y-h. Taguchi
    • 17
  • Yoichi Takenaka
    • 18
  • Yosuke Tanigawa
    • 19
  • Momoka Tsuneyoshi
    • 20
  • Kazutoshi Yoshitake
    • 21
  • Yukuto Sato
    • 22
  • Riu Yamashita
    • 22
  • Kazuharu Arakawa
    • 23
  • Wataru Iwasaki
    • 10
  1. 1.Database Center for Life Science (DBCLS), Joint Support-Center for Data Science ResearchResearch Organization of Information and Systems (ROIS)MishimaJapan
  2. 2.National Institute of GeneticsMishimaJapan
  3. 3.Division of Biomedical Information AnalysisTohoku University Graduate School of MedicineSendaiJapan
  4. 4.Pathology Project for Molecular Targets, The Cancer InstituteJapanese Foundation for Cancer ResearchTokyoJapan
  5. 5.Department of Computational Biology and Medical Sciences, Graduate School of Frontier SciencesThe University of TokyoKashiwaJapan
  6. 6.Geomicrobiology Group, Kochi Institute for Core Sample ResearchJapan Agency for Marine-Earth Science and Technology (JAMSTEC)NankokuJapan
  7. 7.Graduate School of Agricultural ScienceTohoku UniversitySendaiJapan
  8. 8.Center for Environmental Biology and Ecosystem StudiesNational Institute for Environmental StudiesTsukubaJapan
  9. 9.Database Center for Life Science (DBCLS), Joint Support-Center for Data Science ResearchResearch Organization of Information and Systems (ROIS)KashiwaJapan
  10. 10.Department of Biological Sciences, Graduate School of ScienceThe University of TokyoTokyoJapan
  11. 11.Division of Life Science and Engineering, School of Science and EngineeringTokyo Denki University (TDU)SaitamaJapan
  12. 12.Computational Bio-Big Data Open Innovation Lab.National Institute of Advanced Industrial Science and TechnologyTokyoJapan
  13. 13.Computational Biology and Medical Sciences, Graduate School of Frontier SciencesThe University of TokyoKashiwaJapan
  14. 14.Research Organization for Nano & Life InnovationWaseda UniversityTokyoJapan
  15. 15.Institute of Health SciencesEzaki Glico Co. Ltd.OsakaJapan
  16. 16.Institute for Advanced BiosciencesKeio UniversityFujisawaJapan
  17. 17.Department of PhysicsChuo UniversityTokyoJapan
  18. 18.Faculty of InformaticsKansai UniversityTakatsukiJapan
  19. 19.Department of Bioinformatics and Systems Biology, Faculty of ScienceThe University of TokyoTokyoJapan
  20. 20.Advanced Microbiological Functions Research Group, Frontier Research Labs, Institute For InnovationAjinomoto Co., Inc.KawasakiJapan
  21. 21.Japan Software Management Co., Ltd.YokohamaJapan
  22. 22.Division of Biomedical Information Analysis, Department of Integrative Genomics, Tohoku Medical Megabank OrganizationTohoku UniversitySendaiJapan
  23. 23.Institute for Advanced BiosciencesKeio UniversityTsuruokaJapan

Personalised recommendations