Update README.md

README.md

@@ -20,15 +20,22 @@ Some guidelines and tips:
 
 OK, here we go.
 
-# Title of my project
+# Comparing Evolution Rates of Protein Quality Control Genes
 
 ## Introduction and Goals
 
-The goal of my project is to answer the question, What is...?
+The goal of my project is to answer the question, "Do proteases and chaperones evolve at a similar rate?"
+This question is prompted by a recent study available on bioRxiv on proteome expansion across the tree of life (Rebeaud et al., 2020). They write extensively about the evolution of chaperones and co-chaperones, but say little about proteases. However, it has been well-catalogued that chaperones and proteases play different (but arguably equally important) roles in maintaining proteostasis in a cell (Gottesman et al., 1997). Furthermore, the network of chaperones and proteases that make up protein quality control (PQC) networks are necessary for cell tolerance of perturbations, and, acting as a mechanism of robustness are thus a driving force of evolution. 
+
+https://www.biorxiv.org/content/10.1101/2020.06.08.140319v2
+http://genesdev.cshlp.org/content/11/7/815.full.pdf
 
 The methods I will use to do this are...
+I will need to download sequence data for certain PQC genes, align them, and construct a phylogenetic tree. I'm wondering if I can create a tree where each edge represents a specific PQC protein gene. I imagine I would have to collect a lot of sequences of orthologous PQC genes across species and then create some kind of average estimate of its placement with respect to other proteins. I can create the tree using R and iqtree with the methods we have used in class thus far. I can also use R to estimate and compare evolutionary rates of time based on the phylogenies I create. However, I'm not sure yet how I will organize my collection of homologous protein sequences into one input to map on a tree. 
+
+For the purpose of this project, the data I will use are publicly available at NCBI. Some of the most well-studied PQC systems are in E. coli (GroEL, GroES, Lon) so I think that would be a good place to start. However, I would love some input on how far I should expand this question (to other bacteria, other microbes, all animals?) I think it would be really cool to include archaea, since I imagine many extremophiles rely heavily on PQC proteins to keep them alive in gnarly environments! If my study focused on bacteria, maybe archaea could be an outgroup?
 
-The data I will use are (my own data/ data publicly available at YYY/ simulations)
+I will be limited by what is publicly available, but I hope to implement the methods I learn in this project on my own sequence data as my thesis progresses. This will ultimately be sequence data from nearshore bacterial communities in the Long Island Sound. 
 
 ## Methods