|We identified diversity generating retroelements as a|
potential mechanism driving targeted genomic diversity.
A few weeks ago some colleagues and myself published a new manuscript looking at the diversity of the human skin virome. In our previous previous work, we evaluated the diversity of viruses on the skin. Other groups have looked at virus diversity at other body sites including the gut, lungs, and oral cavity. Our new paper focused on the diversity within viruses on the skin. It provided initial insight into the genomic variability associated with major viruses in the skin virome. In other words, it was a "high resolution" study of the virome.
One of the highlights of the manuscript was identifying numerous hyper-variable loci within the skin virus genomes that we investigated. We did this using a SNP geometric distribution approach instead of a sliding window because it allowed us to establish regions that were more variable than would be expected by random chance, and did not require us to arbitrarily establish a window size for the loci. The loci identified using this approach were associated with stronger evolutionary pressure than their adjacent regions, suggesting they are functionally important. We followed up with this, but I will let you get the details from the manuscript.
A methodological highlight was the validation of our findings using an existing dataset from a different lab. We performed our analytical workflow a second time using another skin metagenomic dataset from a different skin microbiome lab. Even though the second dataset did not undergo virus purification, we were still able to pull out enough viral reads to perform our targeted analysis. We replicated our findings in the second dataset, thereby supporting the strength and biological ubiquity of our findings. My hope is that more groups will perform this type of validation in their future studies, especially since there is so much archived data just waiting to be utilized.
The challenge with this study was writing the analytical tools that I needed to answer our questions. In the end, I built a lot of tools that allowed me to answer evolutionary and functional virome questions. I think these are pretty easy to use, and made them freely available on GitHub. If you are interested in performing similar evolutionary analyses on your virome datasets, check the code out here and let me know if you have any questions.
In the end, I think this is a pretty cool study and I really enjoyed working on it. If this summary sounds interesting, I suggest you check out the paper. It is freely available online and easy to download.
As always, if you have any questions, comments, or concerns, please let me know in the comments section below, shoot me an email, or find me on twitter (links are to the right). I always love to hear from readers!
Hannigan GD, Zheng Q, Meisel JS, Minot SS, Bushman FD, & Grice EA (2017). Evolutionary and functional implications of hypervariable loci within the skin virome. PeerJ, 5 PMID: 28194314