Biases in the Experimental Annotations of Protein Function and Their Effect on Our Understanding of Protein Function Space

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.

Protein function annotation using protein domain family resources

“…A function annotation method using family resources is often limited by the scope of the family resources and their ability to provide functional information only for certain aspects. Moreover, bias in protein function annotations [74] or mis-annotations affects our understanding of protein function space [11]. As a result, sometimes correct and highly specific predictions may be misinterpreted as incorrect or erroneous if they have only been experimentally annotated in a generic manner.…”

Gene Ontology: Pitfalls, Biases, and Remedies

“…Schnoes et al [ 32 ] reported that annotations deriving from high-throughput experiments tend to consist of high-level GO terms, and tend to represent a limited number of functions. This artifi cially decreases the information content of these terms, since they are frequently annotated, and artifi cially decreased information content affects similarity analyses.…”

Evaluating Computational Gene Ontology Annotations

“…However, at the time of writing, a small number of experimental studies contribute much of the functional protein annotations collected in the databases, thereby biasing the available experimental annotations [ 8 ]. Indeed, DNA sequencing did not achieve its dramatic cost reductions and increases in throughput fortuitously, but rather was the result of the systematic investment of hundreds of millions of dollars in technology development over two decades.…”

“…Manual curation may be thought of as more cautious, as there is typically a single protein being labeled at a time [ 8 ], whereas the goal of computational prediction is typically more ambitious: labeling a large number of proteins-possibly ignoring subtle aspects of the biological reality.…”