Coexpression of neighboring genes in the genome of Arabidopsis thaliana.

Large-scale analyses of expression data of eukaryotic organisms are now becoming increasingly routine. The data sets are revealing interesting and novel patterns of genomic organization, which provide insight both into molecular evolution and how structure and function of a genome interrelate. Our study investigates, for the first time, how genome organization affects expression of a gene in the Arabidopsis genome. The analyses show that neighboring genes are coexpressed. This pattern has been found for all eukaryotic genomes studied so far, but as yet, it remains unclear whether it is due to selective or nonselective influences. We have investigated reasons for coexpression of neighboring genes in Arabidopsis, and our evidence suggests that orientation of gene pairs plays a significant role, with potential sharing of regulatory elements in divergently transcribed genes. Using the data available in the KEGG database, we find evidence that genes in the same pathway are coexpressed, although this is not a major cause for the coexpression of neighboring genes.

Natural selection promotes the conservation of linkage of co-expressed genes.

Although there is increasing evidence that eukaryotic gene order is not always random, there is no evidence that putatively favourable gene arrangements are preserved by selection more than expected by chance. In yeast (Saccharomyces cerevisiae), for example, co-expressed genes tend to be linked, but whether such gene pairs tend to remain linked more often than expected under null neutral expectations is not known. We show using gene pairs in the S. cerevisiae-Candida albicans comparison that highly co-expressed gene pairs are conserved as pairs at about twice the average rate. However, co-expressed genes also tend to be in close physical proximity and, as expected from a null neutral model, genes (be they co-expressed or not) that are physically close together tend to be retained more often. This physical proximity, however, only accounts for a small proportion of the enhanced degree of conservation of co-expressed gene pairs. These results demonstrate that purely neutralist models of gene order evolution are not realistic.

Clustering of tissue-specific genes underlies much of the similarity in rates of protein evolution of linked genes.

Are genes nonrandomly distributed around the genome and might this explain why it was found that, in the mouse genome, proteins of linked genes evolve at similar rates? Anecdotal evidence suggests that the similarity of expression of linked genes might, in part, explain the similarity in their rates of evolution. Immune system genes, for example, are known to evolve at a high rate and sometimes cluster in the genome. Here we develop methods for statistical tests of similarity of expression of linked genes and report that there is a significant tendency for genes of similar expression breadth to be linked. Significantly, when we exclude tissue specific genes from our sample, the similarity in rates of protein evolution of linked genes is greatly diminished, if not abolished. This diminution is not a sampling artifact. In contrast, while half of the immune genes in our sample reside in 1 of 10 immune clusters in the mouse genome, this clustering appears not to affect the extent of local similarity in rates of evolution. The distribution of placentally expressed genes, in contrast, does have an effect.