Nearly 170 million people worldwide are chronically infected with hepatitis C virus (HCV) 
. In the US, HCV is the leading cause of hepatocellular carcinoma and the leading indication for liver transplantation 
. The standard of care for the treatment of chronic hepatitis C is combination therapy with pegylated interferon and ribavirin. Pegylated interferon (PEG-IFN) is a synthetic variant of interferon-α, a naturally occurring cytokine whose endogenous role is to activate the innate immune response. Injected PEG-IFN is hypothesized to function by mimicking this natural cytokine. Ribavirin (RBV) is a nucleoside analog. It is thought to act through a combination of modalities (as reviewed in 
Large clinical trials of PEG-IFN/RBV therapy have revealed significantly different response rates for the various HCV genotypes. There are six major HCV genotypes, numbered 1 to 6. Genotype 2 is the most responsive, with a sustained virologic response (SVR) rate of greater than 80%. Studies also suggest that it is reasonable to treat some patients infected with this genotype for only 12–16 weeks 
. Conversely, the most prevalent genotype worldwide, genotype 1, is the least responsive. The SVR rate for patients infected with genotype 1 is less than 50%. Current guidelines recommend 48 weeks of therapy for this genotype; shorter courses of therapy have been demonstrated to be sub-optimal 
There currently exists no systematic explanation for these genotype-specific differences in clinical outcome 
. It is assumed that genotype-specific clinical response rates are the result of a confluence of host and viral factors. What specific host factors, human demographics/geographic patterns, and/or viral factors determine interferon response rates remains a challenging area of inquiry. Furthermore, whether factors that govern outcome for one genotype play a similar role in other genotypes remains to be more fully explored.
Numerous laboratory studies suggest that certain viral factors are able to inhibit aspects of the innate immune response (as reviewed in 
). These cell culture studies, however, highlight the gap that currently exists between laboratory models and the human host. For example, the HCV replicon system allows for the study of HCV RNA replication in cell culture. Using this system, it was observed that genotype 2 replicons were more resistant to interferon than genotype 1 replicons, the opposite of what is observed clinically 
. Thus, this observation may be a culture system artifact 
that highlights the challenge of ascertaining the clinical relevance of findings first discovered in laboratory models.
Humans are the only known natural hosts for HCV, a virus that is estimated to be hundreds and possibly thousands of years old 
. This lengthy relationship may have allowed HCV to accumulate adaptive mutations that confer increasing resistance to the human immune system. Interferon therapy functions by activating the innate immune response, which is comprised of direct intracellular defenses such as the PKR, Mx and RNaseL proteins, and innate immune cells, including NK, dendritic, monocyte, macrophage, and NKT cells. Once activated, the innate immune system also plays a critical role in the proper stimulation and coordination of the adaptive immune response 
We therefore hypothesize that genotype-specific clinical response rates to interferon-based therapies are a reflection of HCV evolutionary adaptations to the immune system. We do not hypothesize that modern interferon therapy itself selected for the various HCV genotypes. Instead, we are hypothesizing that the immune system that is activated by interferon therapy has co-evolved with HCV.
One evolutionary pattern that would strongly indicate that a selective pressure was favoring adaptations to the immune system would be a strict correlation of increasing non-response to treatment with the relative ages of the genotypes—such that, as each new genotype emerged it would have a more resistant phenotype than its ancestor.
HCV was first divided into genotypes by the seminal work of Simmonds and others in 1993 
, based on an analysis of one segment of the HCV genome from 76 different patients (). Evolutionary analysis limited to only portions of a genome, however, can be misleading 
. For instance, by analyzing 27 full-length HCV genomes Salemi and colleagues 
() found a different phylogenetic pattern for the relationships amongst the six HCV genotypes. Also of note is that neither analysis determined the relative evolutionary ages of the various genotypes.
Unrooted HCV Cladograms From Previous Studies.
Determining the relative ages of the major HCV genotypes is critical to testing our hypothesis that a correlation exists between genotype age and clinical resistance. Relative ages can be determined through the use of an outgroup, which roots the phylogeny and establishes the direction of time. In the analysis presented here, we used GB Virus B (GBV-B) as an outgroup. This allowed us to root our HCV phylogeny and establish for the first time the relative ages of the major HCV genotypes. GBV-B was chosen as the outgroup for two reasons: first, GBV-B, a virus that causes hepatitis in New World monkeys, is the closest viral relative of HCV and the only other member of the hepacivirus
genus. Second, biochemical evidence suggests that proteins in GBV-B share highly-specific functionality with their homologs in HCV 
The evolutionary analyses of HCV that have been performed to date have also been based on a limited number of genomic sequences. A prime reason for this is that reliable methods of tree construction, such as maximum likelihood (ML) and maximum parsimony (MP), require considerable amounts of computational power. Thus, often only a subset of available sequences is actually analyzed. For this reason, Salemi et al. limited their analysis to 27 genomes.
In this work, we perform a comprehensive analysis of all the >300 genomes found in the European HCV database. This order of magnitude increase in the number of genomes analyzed was made possible by the NSF-funded Cyberinfrastructure for Phylogenetic Research (CIPRES) Project, which allows for web-based access to the San Diego Super Computer facility and newly developed evolutionary algorithms that dramatically reduce computational time.
We thus sought to construct the first evolutionary tree of HCV that incorporated all known genomic sequences and would allow for the relative ages of all HCV genotypes to be determined. We then used this tree to test our hypothesis that clinical resistance to interferon correlates with HCV genotype age. Finally, we used ancestral sequence reconstruction to identify HCV loci that potentially play a role in determining genotype-specific clinical outcomes.