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. 2022 Feb 28;12:3268. doi: 10.1038/s41598-022-07238-9

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© The Author(s) 2022

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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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Integration analysis highlights gene-metabolite pathway relationships. (A) Modulated Modularity Clustering (MMC) analysis in which a smooth correlation ordering is performed in order to differentiate blocks of metabolites with the same behavior. Metabolites were grouped into 9 different modules. Blue is positively correlated and red is negatively correlated. (B,C) Heatmaps²⁸ of Modules 6 (B) and 9 (C) after a sparse PLS (sPLS) analysis was performed with the Gene/Metabolite Integration Tool²⁸. Metagenes were estimated from the PANA approach⁹. (D) Representations of C. elegans fatty acid metabolic pathways in KEGG³¹. Genes significantly downregulated in bcat-1(RNAi) worms are blue, and genes significantly upregulated in bcat-1(RNAi) worms are red.