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. 2021 Jun 5;22:413. doi: 10.1186/s12864-021-07731-x

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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. 3 — Identification of key module based on WGCNA. a Correlation between co-expressed WGCNA module eigengenes and phenotypic traits. Depth of color corresponds to depth of correlation. Positive correlation indicated in red and negative correlation indicated in blue. Significance (P-value) of each module to each external factor presented in parentheses (). b Enrichment map of 438 genes. c Modules found by MCODE in the network related to erythropoiesis. The edge width was proportional to the score of protein-protein interaction based on the STRING database, The color of edge was weight acquired from WGCNA. d The heatmap of erythropoiesis-related gene expression in RNA-seq. e qRT-PCR analysis. The mRNA expression levels of 10 selected genes were normalized with the external control gene (Gapdh) and were calculated with 2^−ΔΔCt