SigniSite: Identification of residue-level genotype-phenotype correlations in protein multiple sequence alignments

Abstract

Identifying which mutation(s) within a given genotype is responsible for an observable phenotype is important in many aspects of molecular biology. Here, we present SigniSite, an online application for subgroup-free residue-level genotype-phenotype correlation. In contrast to similar methods, SigniSite does not require any pre-definition of subgroups or binary classification. Input is a set of protein sequences where each sequence has an associated real number, quantifying a given phenotype. SigniSite will then identify which amino acid residues are significantly associated with the data set phenotype. As output, SigniSite displays a sequence logo, depicting the strength of the phenotype association of each residue and a heat-map identifying 'hot' or 'cold' regions. SigniSite was benchmarked against SPEER, a state-of-the-art method for the prediction of specificity determining positions (SDP) using a set of human immunodeficiency virus protease-inhibitor genotype-phenotype data and corresponding resistance mutation scores from the Stanford University HIV Drug Resistance Database, and a data set of protein families with experimentally annotated SDPs. For both data sets, SigniSite was found to outperform SPEER. SigniSite is available at: http://www.cbs.dtu.dk/services/SigniSite/.

Figure 1.

Sequence logo. Example of sequence logo (13) output from SigniSite from the analysis of the ATV ∼Antivirogram multiple sequence alignment (MSA), truncated to p₁ – p₃₅ for the purpose of illustration (see ‘Materials and Methods’ section). The analysis was performed with default settings. On the x-axis are the MSA positions p and on the y-axis the Z-scores for each amino acid residue a (). The height of each letter representing the residues is proportional to , i.e. the strength of the statistical association between the residue and the data set-phenotype. Residues above the Z = 0 line have a , i.e. enhances the phenotype, whereas residues below the Z = 0 line have a , i.e. inhibits the phenotype, e.g. the presence of a certain residue with favourable chemical properties may enhance binding (), whereas a residue with unfavourable properties may inhibit binding (). Colour-coding: acidic [DE]: red, basic [HKR]: blue, hydrophobic [ACFILMPVW]: black and neutral [GNQSTY]: green (14).

Figure 2.

SigniSite heatmap from the analysis of the ATV ∼Antivirogram multiple sequence alignment (MSA), truncated to p₁ – p₃₅ for the purpose of illustration (see ‘Materials and Methods’ section). The analysis was performed with default settings. On the x-axis are the 20 proteogenic amino acids a and on the y-axis the positions p in the analysed MSA. The colour coding of the fields is such that fields reflecting are blue, whereas results in a red field. For , nuances in between are used. If a residue has a of 0, the cell is coloured grey. Absent residues are coloured black. If only one grey cell is present at a given position, this implies that the position is fully conserved, harbouring only this residue. If more grey cells are present, their associated P-values have become after correction for multiple testing.

Figure 3.

Measures are mean (AUC) ± SE. Columns are: HIV [SPEER/SIGNI], SPEER and SigniSite’s predictions on the HIVdb data set. SDP [SPEER/SIGNI] SPEER and SigniSite’s predictions on the SDP data set. P-values quantifying the significance of the difference in performance were obtained using a two-tailed paired t-test.