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Meta-analysis of mammary RNA seq datasets reveals the molecular understanding of bovine lactation biology.

08:00 EDT 9th May 2019 | BioPortfolio

Summary of "Meta-analysis of mammary RNA seq datasets reveals the molecular understanding of bovine lactation biology."

The understanding of lactation biology at the gene expression level and the identification of candidate genes for milk synthesis and milk components are possible using recent advanced RNA seq technology. The purpose of this study is to understand the milk constituents synthesis, the molecular pathways responsible for milk synthesis and identification of candidate genes for milk production traits using whole mammary transcriptome dataset. We performed a meta-analysis of publically available RNA seq transcriptomics dataset of mammary tissue/milk somatic cells. Totally 11562 genes were commonly identified from all RNA seq based mammary gland transcriptomes. Functional annotation of commonly expressed genes revealed the molecular understanding of milk fat, protein and lactose synthesis process in mammary secretory cells and molecular pathways responsible for milk synthesis. Further, we identified several candidate genes responsible for milk production traits and constructed the gene regulatory network for RNA seq datasets. In conclusion, this study provides a basic understanding of lactation biology of cows at the gene expression level.

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Name: Genome
ISSN: 1480-3321
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Meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions that may or may not have been evaluated directly against each other. Common considerations in network meta-analysis include conceptual and statistical heterogeneity and incoherence.

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