The cattle rumen serves as a digestive bioreactor for the dairy cow, yet our knowledge of the microbial contents, ecology and host-selection within the rumen is only cursory. This is despite the knowledge that the volatile fatty acids (VFA) and microbial crude protein (MCP) produced by rumen microbiota serve as the precursors to milk fat and protein, respectively. By creating models that predict rumen microbial population presence and predict the flux of metabolites in the rumen, it may be possible to develop intervention therapies designed to relieve milk fat depression, negative energy balance and/or disease. These therapies will need to be designed with the properties of the cattle rumen in mind, as recent research indicates that the community is dynamic during lactation phases but adopts a profile that is unique to each individual cow. Development of probiotics to elicit permanent changes in the cattle rumen may therefore be difficult as probiotic species tend to be undetectable in the rumen contents after a 24 - 48 h period. Rumen content exchanges between a host and donor cow similarly show a reversion of rumen pH and VFA profiles within a day’s time. This suggests a strong selection of microbial content by the host cow and/or selection by the residual microbial species that remain after rumen content evacuation. This presents an intriguing possibility with respect to the inheritance of milk fat and protein traits in the genetic selection of dairy cattle, as much of the heritability of these traits may be due to the host’s selection and maintenance of microbes in the rumen. It is challenging to test this hypothesis, as we are unable to efficiently genotype dairy cattle rumen microbial communities for use in large population-scale models. Instead, we present the preliminary results of a meta-analysis of publically available, whole genome shotgun (WGS) sequencing of the rumen microbial community. Our intent is to generate a indexable profile of singly-unique microbial reads that would be suitable for rapid genotyping in future WGS sequencing experiments. By using this reference in larger sampling surveys, it may be possible to identify key quantitative trait loci within the cattle genome that select for rumen microbial contents.