Case study
We
applied AsgeneDB and the orthology databases
(KEGG,
eggNOG, COG, arCOG and KOG) to analyze microbial
As
metabolism from four distinct habitats: freshwater, hot spring, marine
sediment and soil.
Forty
metagenome sequencing data files were downloaded from the NCBI SRA
database (https://www.ncbi.nlm.nih.gov/sra) (Table S2). Raw reads were
quality-controlled using Trimmomatic v2.39 (Bolger, Lohse, & Usadel,
2014) to trim adaptors and primers, and to filter short (< 50
bp) and low-quality reads (< 20 bases).
The
forward and reverse quality-controlled reads were merged by the program
idba (Peng, Leung, Yiu, & Chin, 2012). Merged shotgun metagenome
sequences were searched against KEGG, eggNOG, COG, arCOG, KOG and
AsgeneDB databases using DIAMOND
(parameters: -k 1 1e-10 -p 20
–query-cover 80 –id 50) (Buchfink, Xie, & Huson,
2015).
Subsequent
standardization of
gene
abundance between samples and statistics of gene abundance and As
metabolic microbial communities were performed with R studio.
We
assessed significant differences for the number and abundance (RPKM) of
key As metabolic gene families in environmental samples detected by
KEGG, eggNOG, COG, arCOG, KOG and AsgeneDB using one-way analysis of
variance
(ANOVA)
and Tukey’s Honest Significant Difference
(HSD).