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. 2022 Aug 19;12:14162. doi: 10.1038/s41598-022-18422-2

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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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RNA-seq data analysis of seabream HGC and SPZ_EJ. (a) Principal component analysis (PCA) using the top 500 most variable genes between HGC and SPZ_EJ (n = 4 pools) and the 'rlog' transformation of the counts. (b) Heatmap generated by unsupervised hierarchical clustering of RNAseq expression z-scores computed for the 7286 differentially expressed genes (DEGs) (p-adj < 0.01; Log2 fold change > 1) between HGC and SPZ_EJ. The heatmap was generated with the ‘pheatmap’ R package (https://CRAN.R-project.org/package=pheatmap). (c) Volcano plot representation of DEGs in the SPZ_EJ versus HGC comparison. The x-axis shows Log2 fold changes in expression and the y-axis the negative logarithm of their p-value to base 10. Red and green points mark the genes with significantly increased or decreased expression respectively in SPZ_EJ compared to HGC (FDR < 0.01). (d) Venn diagrams showing the number of HGCs- and SPZ_EJ-specific and common mRNAs and lncRNAs (in intersect region) which are differentially expressed between the two stages. The Venn diagrams and volcano plots were performed with the ‘VenDiagramm’ R package (https://CRAN.R-project.org/package=VennDiagram) and ‘ggplot2’ R package (https://ggplot2.tidyverse.org), respectively. (e) Validation of the RNAseq data by qRT-PCR. The plot represents the Pearson's correlation analysis of DEGs in HGC and SPZ_EJ determined by RNAseq and qRT-PCR. The Pearson’s correlation coefficient (PCC) of the Log2 fold change analyzed by RNAseq (x-axis) and using qRT-PCR (y-axis), the p-value, and the number of DEGs analyzed are indicated. Plots in a, d and e were generated using the GraphPad Prism v8.4.3 (686) software (https://www.graphpad.com/).