Reconstruction, analysis and comparison of gene networks topology based on RNA-Seq data involved in reproductive and fertility complex traits.

In spite of the importance of fertility in different species, there has been little success dissecting the levels of OMICS. To better understand the molecular basis of fertility, we study transcriptome profiling of different tissues.   Materials and methods  liver, muscle, endometrium and corpus luteum tissues between cows with either good or poor genetic merit for fertility using RNA-Seq data sets. We first compiled a master list of genes related to corpus luteum that change with level of fertility and then reconstructed the network.  

A few genes were identified in liver, muscle and endometrium between high and low fertile cows but in corpus luteum circumstance was different. 264 genes and 6 key modules were disclosed through clustering for mRNA master list for corpus luteum. All these genes, being involved in at least one of the biological process, namely proteolysis, actin cytoskeleton organization, immune system process, biological adhesion, cell differentiation and lipid metabolic process, have an overexpression pattern (P < 0.01).

Finally, the identification of genes and the construction of their regulatory networks may give new insights into biological procedures. As well as, this study increases our understanding of the contribution of different tissues transcriptome to phenotypic fertility in dairy cattle.