Leveraging protein co-evolution for protein characterization in Chlamydomonas

Alan L. Kwan1, Gary D. Stormo2, and Susan K. Dutcher2

1) Department of Computer Science & Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA 2) Department of Genetics, Washington University in St. Louis, St. Louis, MO 63110, USA

Sequence similarity based protein clustering methods organize proteins into families of similar sequences, which is a task that continues to be critical for automated protein characterization. However, many protein families cannot be automatically characterized further because little is known about the function of any protein in a family of similar sequences. We present a novel phylogenetic profile comparison (PPC) method called Automated Protein Annotation by Coordinate Evolution (APACE) that facilitates the automated characterization of proteins beyond their homology to other similar sequences. Our method implements a new approach for the normalization of similarity scores among multiple species and automates the characterization of proteins by their patterns of co-evolution with other proteins that do not necessarily share a similar sequence. We apply our method to the Chlamydomonas proteome along with 28 other eukaryotic organisms. APACE predicts a set of 65 Chlamydomonas proteins that may be necessary for flagellar motility. Forty-five have an existing flagella-related, though not necessarily motility-related, annotations evidenced in previous studies by Pazour, Li, Merchant and colleagues. Fifteen have no annotated function, and the remaining five have annotated functions that are not obviously related to flagellar motility. Preliminary RNA-seq results assaying expression level changes across early time-points in flagellar regeneration support the majority of the novel motility characterizations made by APACE. We are validating a candidate gene that is a known human tumor suppressor, which is expressed primarily in tissues with motile cilia.

e-mail address of presenting author: alan@ural.wustl.edu