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. 2021 Jul 28;16(1):284–295. doi: 10.1038/s41396-021-01067-w

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 3 — (a) A heatmap of functional gene abundances in shotgun metagenome data; genes are color-coded by element cycle and pathway, and selected genes are shown, where correlations with methane had Spearman’s r > 0.5 from 149 unique CNPS genes. Correlations with CH₄ fluxes and salinity across all sites are shown in the leftmost heatmap. The central heatmap shows the relative abundance of these genes across sites (values in the heatmap had a step of z-transformation for a better visualization by Seaborn Python package (https://seaborn.pydata.org/), with site type indicated by the bars at the top. The function names of genes were truncated to save space; full names are in Table S3. Scatterplots in (b) show relationships between CH₄ flux and key genes for methanogenesis (mcrA), demethylation of phosphonate (phnJ) and ammonia/methane oxidation (amo/pmoA) (DESeq2 normalized and log2 transformed). Note the logarithmic y-axis scale in panel (b).