TY - JOUR
T1 - Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan
AU - Yoshitake, Kazutoshi
AU - Kimura, Gaku
AU - Sakami, Tomoko
AU - Watanabe, Tsuyoshi
AU - Taniuchi, Yukiko
AU - Kakehi, Shigeho
AU - Kuwata, Akira
AU - Yamaguchi, Haruyo
AU - Kataoka, Takafumi
AU - Kawachi, Masanobu
AU - Ikeo, Kazuho
AU - Tan, Engkong
AU - Igarashi, Yoji
AU - Ohtsubo, Masafumi
AU - Watabe, Shugo
AU - Suzuki, Yutaka
AU - Asakawa, Shuichi
AU - Ishino, Sonoko
AU - Tashiro, Kosuke
AU - Ishino, Yoshizumi
AU - Kobayashi, Takanori
AU - Mineta, Katsuhiko
AU - Gojobori, Takashi
N1 - KAUST Repository Item: Exported on 2021-06-15
Acknowledgements: This work was supported by CREST, the Japanese Science and Technology Agency. Computations were partially performed using the NIG supercomputer at ROIS National Institute of Genetics as well as the computational resources at Computational Bioscience Research Center, King Abdullah University of Science and Technology.
PY - 2021/6/9
Y1 - 2021/6/9
N2 - AbstractAlthough 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 (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), 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.
AB - AbstractAlthough 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 (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), 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.
UR - http://hdl.handle.net/10754/669576
UR - http://www.nature.com/articles/s41598-021-91615-3
U2 - 10.1038/s41598-021-91615-3
DO - 10.1038/s41598-021-91615-3
M3 - Article
C2 - 34108585
SN - 2045-2322
VL - 11
JO - Scientific Reports
JF - Scientific Reports
IS - 1
ER -