Additional file 2 of Microbial hydrocarbon degradation potential of the Baltic Sea ecosystem

Additional file 2: Supplementary Table S1 Metagenomics sample information and environmental factors. Metagenomics sequencing data were obtained from the European Nucleotide Archive (ENA) database: accession numbers PRJEB41834 (Broman et al., 2022; Rodríguez-Gijón et al., 2023), PRJEB22997 (Alneberg et al., 2018), and PRJEB34883 (Alneberg et al., 2020). The environmental parameters, i.e., depth (m), salinity (PSU), and temperature (°C), compiled by Rodríguez-Gijón et al. (2023) were used in this study. Table S2 Metagenomics data processing information: Sequence codes, read processing counts (from quality-filtering to contig assembly), prodigal annotations and binning stat values. The Calgary approach to ANnoTating HYDrocarbon degradation genes (CANT-HYD; Khot et al., 2022) counts highlighted in blue. Table S3 Metagenome-assembled genome (MAG) stats and taxonomic classification based on using GTDB-Tk v2.4.0 with R220 (Chaumeil et al., 2022). Table S4 The Calgary approach to ANnoTating HYDrocarbon degrading enzymes database (CANT-HYD) annotations (Khot et al. 2022). Table S5 Count and annotation table of the annotated hydrocarbon degradation genes (HDGs). Reads per kilobase million (RPKM) absolute counts. Table S6. The annual average of total oil spills during the assessment period 2016-2021 (m³) values (Supplementary Table S6) from HELCOM (2023b). Table S7 Average metagenome-assembled genome (MAG) quality stats per environment. Table S8 Total metagenome-assembled genome (MAG) counts per environment and relative abundance based on species-level classification.Table S9 Statistical results of the permutation test for homogeneity of multivariate dispersions and permutation test for adonis under a reduced model of the hydrocarbon degradation genes (HDG) dataset. Table S10 Differential abundance test by Random Forests for the HDGs per environment and per subbasin. Table S11 Statistical results of the permutation test for distance-based redundancy analysis (dbRDA) analyses in R of the ARG composition and environmental factors. Table S12 Spearman rank correlations between environmental variables and the RPKM abundance of the hydrocarbon degradation genes (HDG)