Abstract

The ongoing functional annotation of proteins relies upon the work of curators to capture experimental findings from scientific literature and apply them to protein sequence and structure data. However, with the increasing use of high-throughput experimental assays, a small number of experimental studies dominate the functional protein annotations collected in databases. Here, we investigate just how prevalent is the “few articles - many proteins” phenomenon. We examine the experimentally validated annotation of proteins provided by several groups in the GO Consortium, and show that the distribution of proteins per published study is exponential, with 0.14% of articles providing the source of annotations for 25% of the proteins in the UniProt-GOA compilation. Since each of the dominant articles describes the use of an assay that can find only one function or a small group of functions, this leads to substantial biases in what we know about the function of many proteins. Mass-spectrometry, microscopy and RNAi experiments dominate high throughput experiments. Consequently, the functional information derived from these experiments is mostly of the subcellular location of proteins, and of the participation of proteins in embryonic developmental pathways. For some organisms, the information provided by different studies overlap by a large amount. We also show that the information provided by high throughput experiments is less specific than those provided by low throughput experiments. Given the experimental techniques available, certain biases in protein function annotation due to high-throughput experiments are unavoidable. Knowing that these biases exist and understanding their characteristics and extent is important for database curators, developers of function annotation programs, and anyone who uses protein function annotation data to plan experiments.

Highlights

  • Functional annotation of proteins is an open problem and a primary challenge in molecular biology today [1,2,3,4]

  • The three ontologies are Molecular Function (MF), Biological Process (BP) and Cellular Component (CC). These are separate ontologies within GO, describing different aspects of function as detailed in [8]. For some species this means that a single functional aspect (MF, BP or CC) of a species can be dominated by a single study

  • Taken together, the annotation trends in high-throughput studies affect our understanding of protein function space

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Summary

Introduction

Functional annotation of proteins is an open problem and a primary challenge in molecular biology today [1,2,3,4]. To aid current annotation procedures and improve computational function prediction algorithms, high-quality, experimentally derived data are necessary. One of the few repositories of such data is the UniProt-GOA database [7], which is a compilation of data contributed by several member groups of the GO consortium. UniProt-GOA contains functional information derived from literature, and by computational means. The information derived from literature is extracted by human curators who capture functional data from publications, assign the data to their appropriate place in the Gene Ontology hierarchy [8], and label them with appropriate functional evidence codes. UniProtGOA is compiled from annotations made by several member groups of the GO consortium, and as such presents the current state of our view of protein function space. It is important to understand any trends and biases that are encapsulated in UniProt-GOA, as those impact well-used sister databases and a large number of users worldwide

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