An increasing number of evidences show that genes are not distributed randomly across eukaryotic chromosomes, but rather in functional neighborhoods. Nevertheless, the driving force that originated and maintains such neighborhoods is still a matter of controversy. We present the first detailed multispecies cartography of genome regions enriched in genes with related functions and study the evolutionary implications of such clustering. Our results indicate that the chromosomes of higher eukaryotic genomes contain up to 12% of genes arranged in functional neighborhoods, with a high level of gene co-expression, which are consistently distributed in phylogenies. Unexpectedly, neighborhoods with homologous functions are formed by different (non-orthologous) genes in different species. Actually, instead of being conserved, functional neighborhoods present a higher degree of synteny breaks than the genome average. This scenario is compatible with the existence of selective pressures optimizing the coordinated transcription of blocks of functionally related genes. If these neighborhoods were broken by chromosomal rearrangements, selection would favor further rearrangements reconstructing other neighborhoods of similar function. The picture arising from this study is a dynamic genomic landscape with a high level of functional organization.

UNLABELLED: Single nucleotide polymorphisms (SNPs) are the most widely used marker in studies to assess associations between genetic variants and complex traits or diseases. They are also becoming increasingly important in the study of the evolution and history of humans and other species. The analysis and processing of SNPs obtained thanks to high-throughput technologies imply the time consuming and costly use of different, complex and usually format-incompatible software. SNPator is a user-friendly web-based SNP data analysis suite that integrates, among many other algorithms, the most common steps of a SNP association study. It frees the user from the need to have large computer facilities and an in depth knowledge of genetic software installation and management. Genotype data is directly read from the output files of the usual genotyping platforms. Phenotypic data on the samples can also be easily uploaded. Many different quality control and analysis procedures can be performed either by using built-in SNPator algorithms or by calling standard genetic software. AVAILABILITY: Access is granted from the SNPator webpage http://www.snpator.org.