NCycDB: a curated integrative database for fast and accurate metagenomic profiling of nitrogen cycling genes
By Qichao Tu, Lu Lin, Lei Cheng, Ye Deng, Zhili He. Bioinform., 2018
387 citations recorded by the source corpus.
Motivation The nitrogen (N) cycle is a collection of important biogeochemical pathways in the Earth ecosystem and has gained extensive foci in ecology and environmental studies. Currently, shotgun metagenome sequencing has been widely applied to explore gene families responsible for N cycle processes. However, there are problems in applying publically available orthology databases to profile N cycle gene families in shotgun metagenomes, such as inefficient database searching, unspecific orthology groups and low coverage of N cycle genes and/or gene (sub)families. Results To solve these issues, this study built a manually curated integrative database (NCycDB) for fast and accurate profiling of N cycle gene (sub)families from shotgun metagenome sequencing data. NCycDB contains a total of 68 gene (sub)families and covers eight N cycle processes with 84 759 and 219 146 representative sequences at 95 and 100% identity cutoffs, respectively. We also identified 1958 homologous orthology groups and included corresponding sequences in the database to avoid false positive assignments due to ‘small database’ issues. We applied NCycDB to characterize N cycle gene (sub)families in 52 shotgun metagenomes from the Global Ocean Sampling expedition. Further analysis showed that the structure and composition of N cycle gene families were most strongly correlated with latitude and temperature. NCycDB is expected to facilitate N cycle studies via shotgun metagenome sequencing approaches in various environments. The framework developed in this study can be served as a good reference to build similar knowledge‐based functional gene databases in various processes and pathways. Availability and implementation NCycDB database files are available at https://github.com/qichao1984/NCyc. Supplementary information Supplementary data are available at Bioinformatics online.
Subfields: Ecology, Molecular Biology, Oceanography
View Paper: https://www.semanticscholar.org/paper/aeccda1f1e20a253138806d3c949682df3e14b24
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Citations in the corpus
- SCycDB: A curated functional gene database for metagenomic profiling of sulphur cycling pathways (2020, methodology): “…databases present several limitations for analysis of S cycling microbial communities, such as low coverage of S cycling genes (Baker et al., 2015; Vavourakis et al., 2019), difficulties in distinguishing homologous genes (e.g., sat vs. cysC, sbp vs. cysP, or psrA vs. phsA) (Marietou et al.,…”