‘‘susceptible’’, ‘‘wild-type’’ and/or ‘‘reversion’’ forms. We will endeavour to use the ‘‘adapted/nonadapted’’ nomenclature in all future studies of this type. HIV covariation-corrected analysis: a point to consider HIV proteins often contain multiple epitopes restricted by the same HLA allele (B*57 TW10 and IW9 in Gag, for example). On occasion, we have observed that the covariation-corrected analysis identifies mutations in epitopes restricted by the same HLA allele as being ‘‘linked’’, when in fact a more likely explanation is that that they arise due to HLA-restricted targeting and escape within multiple epitopes, either simultaneously or sequentially over the disease course [27,32,44,45,46,47]. In order to not exclude any potentially important escape mutations from our figures, we ran the analysis with and without the covariation correction, and included all HLA-associated polymorphisms identified by either method in the escape maps. In the escape maps, the covariation- corrected and uncorrected associations are differentiated by the use of uppercase and lowercase letters, respectively. Results HLA-associated polymorphisms were identified in HIV-1 Gag, Pol and Nef in a multicenter cohort of .1500 chronically-infected, treatment-na¨ıve individuals using published methods featuring a correction for HIV phylogeny, HLA linkage disequilibrium and HIV codon covariation [27]. The false discovery rate [43] was used to account for multiple tests. At the conservative threshold of q#0.05, 282 HIV codons commonly mutating under HLA-associated immune pressure in Gag, Pol and Nef were identified. These polymorphisms were observed at 74 (of 206; 36%) Nef codons, 80 (of 500; 16%) Gag codons, and 128 (of 947; 14%) codons in Pol. At a more liberal threshold of q#0.2, the total number of observed codons harboring HLA-associated polymorphisms increased to 442, which included 113 (55%), 130 (26%), 199 (21%) of codons in Nef, Gag and Pol, respectively. These data confirm the results of previous population-based studies reporting greater density of HLA-associated polymorphisms in Nef than in Gag or Pol [15,29,41,48]. Moreover results underscore the observation that the effects of HLA-associated selection pressures on HIV-1 evolution are extensive and predictable. All HLA-associated polymorphisms at q#0.05 were organized into gene-wide ‘‘immune escape maps’’ (Figures 1, 2, 3, 4, 5) indicating their location, HLA restriction, specific amino acids, and their direction of association (‘‘adapted’’ vs. ‘‘non-adapted’’) with respect to the current HIV subtype B consensus sequence (http://www.hiv.lanl.gov). Published, optimally-described CTL epitopes [49] containing HLA-associated polymorphisms are also shown. In addition, the maps discriminate between HLA- associated polymorphisms directly attributable to selection pres- sure by the allele (meaning that they survive correction for HIV covariation), from those that may be better explained indirectly (meaning that their occurrence may be better explained by the presence of an HLA-associated covarying residue, rather than the allele itself). The full list of direct (covariation-corrected) plus indirect (covariation uncorrected) HLA-associated polymorphisms within each viral protein at q#0.2 is provided in Table S1. As described in the methods, we also undertook an HIV codon-covariation analysis that, besides identifying direct HLA- associated polymorphisms, also identified all pairwise amino acid-amino acid (aa-aa) associations within a given HIV protein [27]. The HIV codon covariation analysis can be used to identify linked pathways of immune escape, as well as putative secondary HIV-1 Immune Escape Maps and/or compensatory mutations associated with a primary escape site. The codon covariation analysis identified .7000 intra-protein aa-aa correlations occurring at .4500 codon pairs, illustrating the dense and complex networks of covarying amino acids in HIV (Table S2). Indeed, if one sums up the total number of codons harboring HLA-associated polymorphisms, plus the co-varying sites immediately associated with them, the total proportion of codons in Nef that are either directly or indirectly associated with HLA selection pressures reaches 77%. For Gag and Pol, the corresponding proportions are 55% and 44%, respectively. The sheer density of the intraprotein codon covariation network renders the task of displaying these data rather challenging, but Carlson et al have developed an elegant tool for data visualization that is freely available [27]. Here, the amino acid sequence of a protein is displayed in a counterclockwise circle starting at the 3 o’clock position (Figures 6 and 7). Any HLA alleles associated with variation at those sites are indicated at the corresponding positions outside the circle, while covarying amino acids are joined together by arcs within the circle. The strength of the association (q-value) is indicated by the color of the arc. HLA-associated intraprotein codon networks in Gag for HLA- B*57 and HLA-B*27 are shown in Figures 6 and 7, respectively. These two alleles were chosen as examples due to their association with slower HIV disease progression in numerous epidemiologic studies [5,34,50]. Similarly, Gag was chosen in light of accumulating evidence that Gag-specific CD8 T-cell responses may contribute substantially to HIV immune containment [51,52,53] as well as the observation that B*57 and B*27- associated escape mutations in Gag are associated with measurable costs to viral replication capacity [35,36,54], which may be partially rescued by compensatory mutations at secondary sites [35,36]. All direct (covariation-corrected) and indirect (covariation uncorrected) B*57-associated Gag polymorphisms at q#0.2 are identified at their respective positions along the circle’s circumfer- ence: For B*57 (figure 6), this corresponds to codons 146, 147, 163, 173, 242, 248, 315, 340, 435 and 449. Within the circle, all q#0.2 ‘‘one-hop’’ associations with these codons (meaning, Gag codons identified as covarying with them) are connected via arcs. For example, if the B*57-associated polymorphism at Gag position 242 is considered the ‘‘predictor variable’’ (see Table S2), then the residues positively associated with it (‘‘adapted’’ associations) and/ or negatively associated with it (‘‘nonadapted’’ associations) are located at codons 146, 147, 215, 228, 230, 241, 243, 248, 256, 310, 340 and 373. If position 242 is considered the ‘‘target variable’’, then the covarying residues positively and negatively associated with it are located at codons 109, 219, 292, 373, 469 and 473. It is important to note in the case of aa-aa associations, the use of ‘‘predictor’’ and ‘‘target’’ terminology should not be interpreted as suggesting a directional association between these polymorphisms or a specific temporal order of selection; rather, it is more appropriate to simply interpret these as codon-codon pairs. Therefore, if one is interested using Table S2 to look up all codons positively and/or negatively associated with Gag codon 242, one should investigate all ‘‘target’’ codons that appear when 242 is set as the ‘‘predictor’’ variable, and vice versa. The union of these two queries will provide a list of specific codons and residues that are positively and/or negatively associated with variation at codon 242. Note that our analysis also identifies ‘‘two-hop’’ associations (meaning, codons that positively and/or negatively covary with the ‘‘one-hop’’ sites), however these are not shown on the figure due to the high density of the resulting networks. The full list of intraprotein covarying codons is provided in Table S2. PLoS ONE | www.plosone.org 4 August 2009 | Volume 4 | Issue 8 | e6687