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. 2023 Jan 26;7(3):414–423. doi: 10.1038/s41559-022-01975-w

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© The Author(s) 2023

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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Extended Data Fig. 2 — Within-control variation of counts transformed with a variance-stabilising transform of all genes included in differential expression analysis, for all populations in control treatments, are displayed. A + B) Principal components analysis (PCA), point fill corresponds to population zinc tolerance (orange = tolerant, blue = sensitive), point border corresponds to geographic pair (red = Wales [T1/S1], dark blue = England [T2/S2]). The third and fourth (A), and fifth and sixth (B) principal components are displayed. (C) A heatmap and hierarchical clustering of all individuals in the control treatment based on a matrix of transformed counts. Each individual (i-iii) from each population (S1, S2, T1, T2) is displayed as a row/column. Box colours indicate sample-to-sample distances based on the R dist() function.