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PLAST Protein Localization Analysis and Search Tools (version 1.0)

Quantitative Protein Localization Signatures Reveal an Association between Spatial and Functional Divergences of Proteins

Lit-Hsin Loo, Danai Laksameethanasan, Yi-Ling Tung

Bioinformatics Institute, A*STAR, Singapore

Abstract:

Protein subcellular localization is a major determinant of protein function. However, this important protein feature is often described in terms of discrete and qualitative categories of subcellular compartments, and therefore it has limited applications in quantitative protein function analyses. Here, we present Protein Localization Analysis and Search Tools (PLAST), an automated analysis framework for constructing and comparing quantitative signatures of protein subcellular localization patterns based on microscopy images. PLAST produces human-interpretable protein localization maps that quantitatively describe the similarities in the localization patterns of proteins and major subcellular compartments, without requiring manual assignment or supervised learning of these compartments. Using the budding yeast Saccharomyces cerevisiae as a model system, we show that PLAST is more accurate than existing, qualitative protein localization annotations in identifying known co-localized proteins. Furthermore, we demonstrate that PLAST can reveal protein localization-function relationships that are not obvious from these annotations. First, we identified proteins that have similar localization patterns and participate in closely-related biological processes, but do not necessarily form stable complexes with each other or localize at the same organelles. Second, we found an association between spatial and functional divergences of proteins during evolution. Surprisingly, as proteins with common ancestors evolve, they tend to develop more diverged subcellular localization patterns, but still occupy similar numbers of compartments. This suggests that divergence of protein localization might be more frequently due to the development of more specific localization patterns over ancestral compartments than the occupation of new compartments. PLAST enables systematic and quantitative analyses of protein localization-function relationships, and will be useful to elucidate protein functions and how these functions were acquired in cells from different organisms or species. A public web interface of PLAST is available at http://plast.bii.a-star.edu.sg.

Supplementary data:

File name (file size)Description
yeast_localization_map.csv (5.2MB) Supplementary Data 1: Global subcellular localization map of the budding yeast Saccharomyces cerevisiae proteome
proteome_assignment.csv (40KB) Supplementary Data 2: List of proteins assigned with selected subcellular compartments
duplicate_genes.csv (271KB) Supplementary Data 3: P-profile dissimilarity scores and numbers of subcellular compartments localized by WGD duplicate genes

Source code and raw data:

File name (file size)Description
README.TXT (6.1KB) Instructions for installing and running the P-profile construction code.
PLAST-Yeast_analysis_v1.zip (596MB) All the R scripts used to construct P-profiles and generate the figures in the manuscript. The project and image data files are not required to run these R scripts.
PLAST-Yeast_project_v1.zip (448MB) (Optional:) cellXpress project files, including all the configurations, computed segmentation masks, and extracted features. This is only required if you want to re-run the segmentation and feature extraction steps.
PLAST-Yeast_plate_v1.zip (2.8GB) (Optional:) cellXpress image data files. This is only required if you want to re-run the segmentation and feature extraction steps.

Last updated: 24 December 2014