Repeat Conservation Mapping Figure 5. Functional testing of double-alanine mutagenesis alleles of EFR reveals that function-blocking mutations map to sites that RCM scores as conserved sites. A series of EFR alleles that each encode two alanine mutations within the b-strand/b-turn region of a single repeat (locations shown in Figure 4) were introduced into efr2 plants and transgenic T1 seedlings were tested for their ability to respond to 100 nM elf18 in a seedling growth inhibition assay. Y-axis: Average weight of seedlings (+/2 standard error), as compared to a no- peptide control for each line, for at least three replicate experiments with at least eight transgenic seedlings per genotype per treatment. Controls are weight (mean +/2 standard error) of efr2 seedlings transformed with wild-type EFR (WT, lower grey band) or empty vector (EV, upper grey band), as determined within the same experiments. X- axis: The average RCM regional conservation score for the two positions mutated in any given construct (x-axis bar ends for each symbol are at the RCM scores for the two positions mutated in each construct). doi:10.1371/journal.pone.0021614.g005 A similar exercise was performed using FLS2 sequences from seven closely or distantly related Brassicaceae species (Figure S6). The maps of functionally similar LRRs from very closely related sequences (Figures 8 and S6) emphasize amino acid clusters containing less common amino acid residues that score highly in Blosum matrices, whether or not they reside at functional sites. The maps made from seven or ten functionally confirmed sequences more reliably emphasize evolutionary conservation of residue clusters. These latter maps also offer better resolution of conserved and diversified areas, but maps made from just two sequences from more distantly related species were sufficient to highlight the main features also present on the maps made from larger numbers of proteins (Figures 8 and S6, see also Figure 4). As with the map of Arabidopsis EFR and its paralogs, these ortholog maps also highlight regions outside of the concave face that have been conserved, presumably due to their functional significance. Comparison of conservation mapping to other computational methods Other methods that predict important amino acid residues within a protein, beyond the BLAST or Pfam-like methods that identify conserved motifs in the primary sequence, include positive/purifying selection analysis [46], optimal docking area (ODA) calculation [55], and Consurf [49]. Because these three approaches employ different criteria for identifying functionally significant residues, we searched for important residues of EFR, FLS2 and PGIP using these three methods and compared their results to those generated by RCM (Figures 9 and S7). When a method required multiple sequences as input, we used the same sequences for each analysis (the Brassicaceae orthologs described above for EFR and FLS2, or the Fabaceae PGIP sequences from Figure 6. Site-directed, randomizing mutagenesis of EFR sites that are divergent in EFR paralogs reveals many partial-impact LRR sites. Seedling growth inhibition assays for EFR function were performed as in Figure 5 except that seedlings were treated with 1 uM elf18. A minimum of 65 T1 seedlings were tested for each allele library. Plants were classified as elf18-sensitive if their response was in the range of 95% of positive controls transformed with wild-type EFR, as elf18-insensitive if response was in the range of 95% of negative controls transformed with empty vector, or as partially sensitive if they fell within both ranges. WT: wild-type; EV: empty vector; allele number codes reflect the repeat number and the b-strand/b-turn position of the mutagenized amino acid (for example, 2.3 is the third x position of LxxLxLxxN in the second repeat), and parentheses enclose the amino acid number and letter. doi:10.1371/journal.pone.0021614.g006 [55]). Homology models of EFR and FLS2 were created using the crystal structure of PGIP as template [56]. To allow comparison, the RCM results of Figure 4A are also presented on a homology model of EFR (Figure 9D). As previously reported, integration of positive selection analysis and ODA identified several residues on the surface of PGIP that were important for specificity toward different PG’s [55]. Unsurprisingly, most surface residues of EFR and FLS2, when compared to functional Brassicacea orthologs, were under purifying selection (2log(v).0). Only two residues of the LRR of EFR showed evidence of positive selection, neither of which is predicted to be on the concave face of the receptor (although both are on the surface of the protein) (Figure 9A). Similarly, two residues of the LRR of FLS2 are under positive selection, predicted to be on the side of the LRR and solvent-exposed (Figure S7). Using ODA, a patch of potential ligand binding residues for EFR was identified on the b-strand, b-turn region of LRRs 17–18 (Figure 9B), overlapping with a region strongly identified by RCM. Two patches of predicted binding sites were detected for FLS2: a patch three to five surface residues wide in LRRs 1–5 occurring partially on the convex face and partially on the side of the LRR; and a patch primarily in the b-strand region of LRRs 10–15 (Figure S7). This second patch was previously shown to be important for flg22 recognition [35]. Consurf analysis of EFR highlighted many conserved areas; the most highly conserved residues were found in the second and third columns of the surface of the repeats as shown in Figure 4, and in the b-strand b-turn region (Figure 9C). Because the similarity of the Brassicacea FLS2 sequences is high (greater than 80%), Consurf ranked almost all residues as either highly conserved or highly divergent (Figure S7). PLoS ONE | www.plosone.org 8 July 2011 | Volume 6 | Issue 7 | e21614