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. 2021 Apr 21;22:288. doi: 10.1186/s12864-021-07595-1

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© The Author(s) 2021

Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 4 — WGCNA of postnatal rumen development metagenomes. a Relationship of modules among microbial abundance at genus level (modules are named by colors). b Rumen microbial modules at the genus level (M7) showed increasing during early rumen development. c Rumen microbial modules at the genus level (M18) showed increasing in immune phase and decreasing in metabolic phase during early rumen development. d Rumen microbial modules at the genus level (M1) showed declining in immune phase during early rumen development. In each module, the expression regression line was generated using the Loess curve-fitting method. The eigengene is a central rumen microbial genus whose dynamic abundance pattern can represent the whole module. The networks indicate the correlation between genera by calculating the Pearson correlation coefficient