Project description:Exploration of the bioactive components of bovine milk has gained global interest due to their potential applications in human nutrition and health promotion. Despite advances in proteomics profiling, limited studies have been carried out to fully characterize the bovine milk proteome. This study explored the milk proteome of Jersey and Kashmiri cattle at day 90 of lactation using high-resolution mass spectrometry based quantitative proteomics nano-scale LC-MS/Q-TOF technique.
Project description:Background : Although the chemical, physical, and nutritional properties of bovine milk have been extensively studied, few studies have attempted to characterize the milk synthesizing genes associated with milk yielding traits. In addition, no previous attempts have been made to detect quantitative traits such as milk production related traits, associated genes on RNA-seq experiment with several biological replicates. Research in this field is necessary as bovine milk is a primary source of nutrition for humans. Results : We investigated advantages of using linear models with continuous response variables over converted group variables in a Holsteins’ milk. Suggested methods were more suitable in detection of significant genes in our analysis; the proportion of false discoveries to total significant genes was observed to be much lower compared to the precedent approaches we employed. These were observed through mock comparison studies and quantitative real time PCR (qRT-PCR). Conclusion : Several milk production related genes and pathways were identified from the suggested methods. Given the current trend in RNA-seq pricing, we expect our methods to be successfully applied in various RNA-seq studies with numerous biological replicates that handle continuous response traits.
