Journal of Molecular Biology

Journal of Molecular Biology

Volume 283, Issue 4, 6 November 1998, Pages 707-725
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Review
Predicting function: from genes to genomes and back1

https://doi.org/10.1006/jmbi.1998.2144Get rights and content

Abstract

Predicting function from sequence using computational tools is a highly complicated procedure that is generally done for each gene individually. This review focuses on the added value that is provided by completely sequenced genomes in function prediction. Various levels of sequence annotation and function prediction are discussed, ranging from genomic sequence to that of complex cellular processes. Protein function is currently best described in the context of molecular interactions. In the near future it will be possible to predict protein function in the context of higher order processes such as the regulation of gene expression, metabolic pathways and signalling cascades. The analysis of such higher levels of function description uses, besides the information from completely sequenced genomes, also the additional information from proteomics and expression data. The final goal will be to elucidate the mapping between genotype and phenotype.

Section snippets

Genomes and function prediction

Prediction of protein function using computational tools becomes more and more important as the gap between the increasing amount of sequences and the experimental characterization of the respective proteins widens Bork and Koonin 1998, Smith 1998. With the availability of complete genomes we face a new quality in the prediction process (Table 1) as context information can be utilized when analysing particular sequences. This review focuses on the added value of genomic information on the many

What is function?

“Function” is a very loosely defined term that only makes sense in context. Most current efforts aim at predicting protein function, but there are other types of function, e.g. RNA function or organelle function, that also need to be explored. Even to describe “protein function” requires a broad range of attributes and features (Figure 1). Molecular features such as enzymatic activity, interaction partners, and pathway context are currently being predicted, but only qualitatively. Expression

Functional prediction for gene products by annotation transfer from homologous sequences

When homologues of a query are identified in a database search (Bork & Gibson, 1996), the annotated information of the homologue and the taxonomic, biochemical and/or molecular-biological context of the query protein are used to extrapolate possible structural and functional features of the query protein. This approach has proven extremely successful although, from a formal point of view the hypotheses generated must be experimentally verified (Eisenhaber et al., 1995). The information transfer

Sequence and annotation quality in molecular databases

Function transfer by analogy requires knowledge about the quality of sequence data and functional annotation. Concerns have been raised about an accumulation (Bork & Bairoch, 1996) and even an explosion (Bhatia et al., 1997) of errors in sequence databases.

In genome projects, two to tenfold sequence coverage is usually sampled. This is critical as automated raw data acquisition (single read) is less than 99% accurate even when using optimized sequencers and software (Ewing et al., 1998). Most

Annotating genomes

Function prediction usually starts with already assembled genomic or cDNA data: at best a complete genome (Figure 2). Several features intrinsic to DNA can be recognized first, before identification of genes and pathways, although detection of the latter enhances also the annotation of non-coding features in genomes.

Annotating individual proteins

Although homology searches are often already integrated into the gene prediction procedures, they are fully exploited only at the protein level with its higher sensitivity. Database searches are a standard technique for annotating proteins, but should be used in context with other methods (Bork & Koonin, 1998).

Incorporating proteomics data

Proteomics focuses on the protein products of the genome and their interactions rather than on DNA sequences (Humphery-Smith & Blackstock, 1997). It is thus complementary to the genomic and nucleic acid information (Kahn, 1995) exploiting novel tools such as 2D large scale analysis (Vietor & Huber, 1997) and powerful mass-spectrometry applications (Yates, 1998).

Predicting function in higher order processes

Having predicted or determined functions for as many genes as possible and having assigned their interactions as well as their expression levels, it is a challenging task to put all the information into the context of cellular processes (Figure 1). A variety of databases and tools are emerging to support this procedure.

Robustness, modularity and interdependence

When considering all the levels discussed there seems to be a discrepancy between the complex nature of the networks of genes and their interdependence (e.g. via regulation) on the one hand and the surprising robustness (e.g. horizontal gene transfer or gene loss) on the other. One way in which such robustness might be achieved is a highly modular organisation, the interdependencies of genes would then be limited to small sets. As yet we do not have a quantitative understanding of the

Acknowledgements

The order of the authors is alphabetically. This work was supported by Deutsche Forschungsgemeinschaft (Bo 1099/3-1) and BMBF (grants 01KW9602/6; 0311748; 0311617). We thank Enrique Morrett and Shamil Sunyaev for critical reading of the manuscript and David Thomas for stylistic corrections. Most of all we acknowledge the work and efforts of all our colleagues who could not be mentioned in this review due to limitations of space and time and the limited selection such a review necessarily has to

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    Edited by P. E. Wright

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    Present address: Y. Diaz-Lazcoz, Laboratoire Genome et Informatique; Batiment BUFFON, Universite de Versailles-Saint Quentin, 45, avenue des Etats-Unis, 78035 Versailles Cedex, France.

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