Goat mammary gland metabolism: An integrated Omics analysis to unravel seasonal weight loss tolerance

Abstract

Seasonal weight loss (SWL), is a major limitation to animal production. In the Canary Islands, there are two dairy goat breeds with different levels of tolerance to SWL: Majorera (tolerant) and Palmera (susceptible). Our team has studied the response of these breeds to SWL using different Omics tools. The objective of this study was to integrate such results in a data driven approach and using dedicated tools, namely the DIABLO method. The outputs of our analysis mainly separate unrestricted from restricted goats. Metabolites behave as “hub” molecules, grouping interactions with several genes and proteins. Unrestricted goats upregulated protein synthesis, along with arginine catabolism and adipogenesis pathways, which are related with higher anabolic rates and a larger proportion of secretory tissue, in agreement with their higher milk production. Contrarily, restricted goats seemingly increased the synthesis of acetyl-CoA through serine and acetate conversion into pyruvate. This may have occurred to increase fatty acid synthesis and/or to use them as an energy source in detriment to glucose, which was more available in the diet of unrestricted goats. Lastly, restricted Palmera upregulated the expression of PEBP4 and GPD1 genes compared to all other groups, which might support their use as putative biomarkers for SWL susceptibility. Significance: Seasonal weight loss (SWL) is a major issue influencing animal production in the tropics and Mediterranean. By studying its impact on the mammary gland of tolerant and susceptible dairy goat breeds, using Omics, we aim at surveying the tissue for possible biomarkers that reflect these traits. In this study, data integration of three Omics (transcriptomics, proteomics and metabolomics) was performed using bioinformatic tools, to relate putative biomarkers and evaluate all three levels of information; in a novel approach. This information can enhance selection programs, lowering the impact of SWL on food production systems.