Page 205 - Microbial methane cycling in a warming world From biosphere to atmosphere Michiel H in t Zandt

al. 2019]). Annotations on functional and taxonomic guilds of quality-controlled contigs were mainly performed with eggNOG-mapper (v1.0.3) (Huerta-Cepas et al. 2017) and DIAMOND (v0.8.22.84) (Buchfink, Xie and Huson 2015), respectively. The KEGG (Kyoto Encyclopedia of Genes and Genomes) (i.e., KO identifiers) and COG annotations were obtained from the EggNOG reference database (v5.0) (Huerta-Cepas et al. 2018).
During downstream analysis, we reconstructed the relative abundances of the functional categories of methanogenesis, carbon fixation, nitrogen cycling and sulfur cycling at whole community level. All related functional components were extracted according the KO identifiers of major pathways from the KEGG database by using custom Python, R, and shell scripts. The gene abundances were normalized to transcripts per kilobase million (TPM) by taking account of both the gene length and coverage according to Equation 1. To identify the functional components of carbon degradation pathways, the subsets of the carbohydrate-active enzyme (CAZy) annotations were extracted from the output of eggNOG-mapper (v1.0.3). Subsequently, the abundance of each functional category was normalized to TPM within this CAZy subset. In addition, all the CAZy-affiliated protein sequences were taxonomically assigned against UniRef90 database (Suzek et al. 2014) by using DIAMOND (v0.8.22.84) to identify the major microbial players.
Ai / ∑(Ai) ×106
where Ai = total reads mapped to genei/(length of genei/1000) [Equation 1] 9
To obtain an overall picture of the taxonomic differentiation at community level, we also assigned taxonomic labels to the merged paired-end QC short reads by mapping against the SILVA 132 SSU non-redundant reference database (Quast et al. 2012). The taxonomy was reported maximally at family level due to the relatively short sequence fragment lengths (which are 203, 243, and 269 bp at 25, 50, and 75% quantiles for the merged paired-end reads, respectively). In addition, the taxonomic composition was assigned based on the annotated ribosomal protein S3 (rpS3, which was also recently proposed as “uS3” according to the Ban Lab https://bangroup.ethz.ch/research/nomenclature-of-ribosomal-proteins.html). The rpS3 marker has advantages to detect organisms with incomplete or unavailable SSU rRNA gene sequences and more strongly resolves the evolutionary deeper radiations (Hug et al. 2016).
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