From Protein Interactions to Functional Annotation: Graph Alignment in Herpes

TL;DR

This paper introduces a hybrid graph alignment method combining protein interaction networks and sequence similarity to improve functional annotation of herpesviruses, especially in divergent regions.

Contribution

The study presents a novel graph alignment approach that integrates interaction and sequence data, revealing evolutionary relationships and functional insights beyond traditional methods.

Findings

Confirmed evolutionary relationships with low sequence similarity

Identified high interaction similarity without sequence similarity

Functional predictions align with genomic and expression data

Abstract

Sequence alignment forms the basis of many methods for functional annotation by phylogenetic comparison, but becomes unreliable in the `twilight' regions of high sequence divergence and short gene length. Here we perform a cross-species comparison of two herpesviruses, VZV and KSHV, with a hybrid method called graph alignment. The method is based jointly on the similarity of protein interaction networks and on sequence similarity. In our alignment, we find open reading frames for which interaction similarity concurs with a low level of sequence similarity, thus confirming the evolutionary relationship. In addition, we find high levels of interaction similarity between open reading frames without any detectable sequence similarity. The functional predictions derived from this alignment are consistent with genomic position and gene expression data.