Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan

Kazutoshi Yoshitake, Gaku Kimura, Tomoko Sakami, Tsuyoshi Watanabe, Yukiko Taniuchi, Shigeho Kakehi, Akira Kuwata, Haruyo Yamaguchi, Takafumi Kataoka, Masanobu Kawachi, Kazuho Ikeo, Engkong Tan, Yoji Igarashi, Masafumi Ohtsubo, Shugo Watabe, Yutaka Suzuki, Shuichi Asakawa, Sonoko Ishino, Kosuke Tashiro, Yoshizumi IshinoTakanori Kobayashi, Katsuhiko Mineta, Takashi Gojobori

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


Although numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data (, which provides a three-dimensional bird’s-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research.

Original languageEnglish
Article number12222
JournalScientific reports
Issue number1
Publication statusPublished - 2021 Dec

All Science Journal Classification (ASJC) codes

  • General


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