Identifying functional links between genes using conserved chromosomal proximity

doi:10.1016/S0168-9525(01)02621-X

Trends in Genetics

Volume 18, Issue 4, 1 April 2002, Pages 176-179

https://doi.org/10.1016/S0168-9525(01)02621-X Get rights and content

Abstract

Conservation of proximity of a pair of genes across multiple genomes generally indicates that their functions could be linked. Here, we present a systematic evaluation using 42 complete microbial genomes from 25 phylogenetic groups to test the reliability of this observation in predicting function for genes. We find a relationship between the number of phylogenetic groups in which a gene pair is proximate and the probability that the pair belongs to a common pathway. Our method produces 1586 links between ortholog families substantiated by observed proximity in genomes representing at least three phylogenetic groups. Of the pairs annotated in the KEGG database, 80% are in the same biological pathway in KEGG.

Section snippets

Finding proximate genes and constructing profiles of conservation

We define genes as proximate if they are on the same strand and within 300 base pairs [13], or if their respective paralogs are within 300 bp (Fig. 1), with paralogs and orthologs defined according to the Clusters of Orthologous Groups database (COG; Box 1) 15., 16.. Because the complete genome sequences available are not evenly distributed phylogenetically (e.g. two strains of Helicobacter pylori), we adopt the COG categorization of the 42 microbial genomes into 25 major phylogenetic groups

How reliable is this method?

To estimate the ability of our method to detect links between functionally related genes, we identify the subset of links where both ortholog families are annotated and assigned to a pathway in the KEGG database [20], or to a functional category in the COG database [15] (Box 1). We then calculate the fractions of these that are in the same KEGG pathway and of the same COG functional category. As Fig. 3a shows, the functional correspondence is positively correlated to the minimal number of

Acknowledgements

We would like to thank Adnan Derti for a critical reading of this manuscript. This work was supported in part by a National Science Foundation Integrative Graduate Education and Research Traineeship Program grant to JCM. IY is supported by a Whitaker Fellowship.

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The idea for expanding predictions beyond those produced within a single genome works as follows (Fig. 4A): genes separated in a genome of interest (or target genome), could be inferred to functionally interact if their orthologs were found to be in the same operon in some other genomes (the informative genomes). This idea has been implemented on the basis of operons predicted by conservation of gene order [37–39], and was later expanded to include operons predicted by intergenic distances [40]. It is to be expected that operon rearrangements increase the number of available predicted functional associations.
In this mini-review I aim to make the case that operons might be the most powerful source for predicted associations among gene products. Such associations can help identify potential processes where the products of unannotated genes might play a role. The power of the operon for providing insight into functional associations stems from four features: (1) on average, around 60% of the genes in prokaryotes are associated into operons; (2) the functional associations between genes in operons tend to be highly conserved; (3) operons can be predicted with high accuracy by conservation of gene order and by the distances between adjacent genes in the same DNA strand; and (4) operons frequently reorganize, providing further insight into functional associations that would not be evident without these reorganization events.
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The analysis of expression data for yeast, fruit fly, worm, rat, mouse and human indicated that neighboring genes are likely co-expressed (Fukuoka et al., 2004). The proximity of a pair of genes has been used to predict gene functions (Raghupathy and Durand, 2009; Yanai et al., 2002). In bacteria, gene essentiality determines chromosome organization (Rocha and Danchin, 2003), and essential genes occur more frequently and are conserved in the leading replicating strand as compared with the expected average frequency for all genes.
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Over 3000 genomes, including numerous plant genomes, are now sequenced. However, their annotation remains problematic as illustrated by the many conserved genes with no assigned function, vague annotations such as ‘kinase’, or even wrong ones. Around 40% of genes of unknown function that are conserved between plants and microbes are probably metabolic enzymes or transporters; finding functions for these genes is a major challenge. Comparative genomics has correctly predicted functions for many such genes by analyzing genomic context, and gene fusions, distributions and co-expression. Comparative genomics complements genetic and biochemical approaches to dissect metabolism, continues to increase in power and decrease in cost, and has a pivotal role in modeling and engineering by helping identify functions for all metabolic genes.
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Trends in Genetics

Research updateIdentifying functional links between genes using conserved chromosomal proximity

Abstract

Section snippets

Finding proximate genes and constructing profiles of conservation

How reliable is this method?

Acknowledgements

Trends Genet.

Trends Biochem. Sci.

Adv. Protein Chem.

J. Biotechnol.

Trends Genet.

Trends Biochem. Sci.

C. R. Acad. Sci. Ser. III

Trends Microbiol.

Genome alignment, evolution of prokaryotic genome organization, and prediction of gene function using genomic context

Genome Res.

Mapping the bacterial cell architecture into the chromosome

Philos. Trans. R. Soc. London Biol. Sci.

Behavior of restriction-modification systems as selfish mobile elements and their impact on genome evolution

Nucleic Acids Res.

Research update
Identifying functional links between genes using conserved chromosomal proximity