Blood transcriptome reveals immune and metabolic-related genes involved in growth of pasteurized colostrum-fed calves

Abstract

The quality of colostrum is a key factor contributing to healthy calf growth, and pasteurization of colostrum can effectively reduce the counts of pathogenic microorganisms present in the colostrum. Physiological changes in calves fed with pasteurized colostrum have been well characterized, but little is known about the underlying molecular mechanisms. In this study, key genes and functional pathways through which pasteurized colostrum affects calf growth were identified through whole blood RNA sequencing. Our results showed that calves in the pasteurized group (n = 16) had higher body height and daily weight gain than those in the unpasteurized group (n = 16) in all months tested. Importantly, significant differences in body height were observed at 3 and 4 months of age (p < 0.05), and in daily weight gain at 2, 3, and 6 months of age (p < 0.05) between the two groups. Based on whole blood transcriptome data from 6-months old calves, 630 differentially expressed genes (DEGs), of which 235 were upregulated and 395 downregulated, were identified in the pasteurized compared to the unpasteurized colostrum groups. Most of the DEGs have functions in the immune response (e.g., CCL3, CXCL3, and IL1A) and metabolism (e.g., PTX3 and EXTL1). Protein-protein interaction analyses of DEGs revealed three key subnetworks and fifteen core genes, including UBA52 and RPS28, that have roles in protein synthesis, oxidative phosphorylation, and inflammatory responses. Twelve co-expression modules were identified through weighted gene co-expression network analysis. Among them, 17 genes in the two modules that significantly associated with pasteurization were mainly involved in the tricarboxylic acid cycle, NF-kappa B signaling, and NOD-like receptor signaling pathways. Finally, DEGs that underwent alternative splicing in calves fed pasteurized colostrum have roles in the immune response (SLCO4A1, AKR1C4, and MED13L), indicative of potential roles in immune regulation. Results from multiple analytical methods used suggest that differences in calf growth between the pasteurized and unpasteurized groups may be due to differential immune activity. Our data provide new insights into the impact of pasteurization on calf immune and metabolic-related pathways through its effects on gene expression.

Keywords: Holstein; colostrum; growth traits; immunity; pasteurization.

FIGURE 1

Volcano and circos plots of differentially expressed genes. (A) Volcano plot for expressed genes, it represents the -log10 (p-value) (y-axis) of genome-wide genes in relation to their respective log2 (fold change) (x-axis). Red dots represent up-regulated genes, green dots represent down-regulated genes, and gray dots represent genes with no significant difference in expression (|log2FC|≥0.585 and FDR<0.05). (B) Circos plot for functional enrichment of DEGs. The color gradient from blue to red on the left side of the graph represents the change of genes from down-regulation to up-regulation, and the terms on the right side are represented by different colors.

FIGURE 2

Key subnetworks from PPI networks and their enrichment analysis. (A), (B), and (C) Three key subnetworks. The red and green nodes represent the up- and down-regulated genes in the shapes of “diamond” and “rectangle”, represent core genes and DEGs. (D)The bubble plots of functional enrichment analysis of the three key subnetworks. The size of the dots represents the number of genes in the pathway and the color represents the pathway significance.

FIGURE 3

WGCNA of all expressed genes. (A) The analysis of the scale-free fit index and mean connectivity for diverse soft-thresholding powers. (B)Hierarchical clustering dendrograms showing 12 modules of co-expressed genes. Each branch in the clustering tree represents a gene, while co-expression modules were constructed in different colors. (C) Network heatmap in the co-expression modules (the yellow color scale indicates the degree of overlap between functional modules). (D) Module-trait association heatmap where each row corresponds to a module eigengene and the columns correspond to a trait. Each cell contains the correlation and p-value for the corresponding differentiation stages. The scale bar indicates the color coding for the correlations, with blue to red indicating low to high correlations, respectively.

FIGURE 4

Main pathway enrichment of AS genes. The dot size represents the number of genes in the pathway, the color represents the pathway significance and the vertical coordinate represents the KEGG pathway.