PhyloPat: an updated version of the phylogenetic pattern database contains gene neighborhood

Properties of human disease genes and the role of genes linked to Mendelian disorders in complex disease aetiology

Do genes presenting variation that has been linked to human disease have different biological properties than genes that have never been related to disease? What is the relationship between disease and fitness? Are the evolutionary pressures that affect genes linked to Mendelian diseases the same to those acting on genes whose variation contributes to complex disorders? The answers to these questions could shed light on the architecture of human genetic disorders and may have relevant implications when designing mapping strategies in future genetic studies. Here we show that, relative to non-disease genes, human disease (HD) genes have specific evolutionary profiles and protein network properties. Additionally, our results indicate that the mutation-selection balance renders an insufficient account of the evolutionary history of some HD genes and that adaptive selection could also contribute to shape their genetic architecture. Notably, several biological features of HD genes depend on the type of pathology (complex or Mendelian) with which they are related. For example, genes harbouring both causal variants for Mendelian disorders and risk factors for complex disease traits (Complex-Mendelian genes), tend to present higher functional relevance in the protein network and higher expression levels than genes associated only with complex disorders. Moreover, risk variants in Complex-Mendelian genes tend to present higher odds ratios than those on genes associated with the same complex disorders but with no link to Mendelian diseases. Taken together, our results suggest that genetic variation at genes linked to Mendelian disorders plays an important role in driving susceptibility to complex disease.

ProtPhylo: identification of protein-phenotype and protein-protein functional associations via phylogenetic profiling

ProtPhylo is a web-based tool to identify proteins that are functionally linked to either a phenotype or a protein of interest based on co-evolution. ProtPhylo infers functional associations by comparing protein phylogenetic profiles (co-occurrence patterns of orthology relationships) for more than 9.7 million non-redundant protein sequences from all three domains of life. Users can query any of 2048 fully sequenced organisms, including 1678 bacteria, 255 eukaryotes and 115 archaea. In addition, they can tailor ProtPhylo to a particular kind of biological question by choosing among four main orthology inference methods based either on pair-wise sequence comparisons (One-way Best Hits and Best Reciprocal Hits) or clustering of orthologous proteins across multiple species (OrthoMCL and eggNOG). Next, ProtPhylo ranks phylogenetic neighbors of query proteins or phenotypic properties using the Hamming distance as a measure of similarity between pairs of phylogenetic profiles. Candidate hits can be easily and flexibly prioritized by complementary clues on subcellular localization, known protein–protein interactions, membrane spanning regions and protein domains. The resulting protein list can be quickly exported into a csv text file for further analyses. ProtPhylo is freely available at http://www.protphylo.org.

ProteinHistorian: tools for the comparative analysis of eukaryote protein origin

The evolutionary history of a protein reflects the functional history of its ancestors. Recent phylogenetic studies identified distinct evolutionary signatures that characterize proteins involved in cancer, Mendelian disease, and different ontogenic stages. Despite the potential to yield insight into the cellular functions and interactions of proteins, such comparative phylogenetic analyses are rarely performed, because they require custom algorithms. We developed ProteinHistorian to make tools for performing analyses of protein origins widely available. Given a list of proteins of interest, ProteinHistorian estimates the phylogenetic age of each protein, quantifies enrichment for proteins of specific ages, and compares variation in protein age with other protein attributes. ProteinHistorian allows flexibility in the definition of protein age by including several algorithms for estimating ages from different databases of evolutionary relationships. We illustrate the use of ProteinHistorian with three example analyses. First, we demonstrate that proteins with high expression in human, compared to chimpanzee and rhesus macaque, are significantly younger than those with human-specific low expression. Next, we show that human proteins with annotated regulatory functions are significantly younger than proteins with catalytic functions. Finally, we compare protein length and age in many eukaryotic species and, as expected from previous studies, find a positive, though often weak, correlation between protein age and length. ProteinHistorian is available through a web server with an intuitive interface and as a set of command line tools; this allows biologists and bioinformaticians alike to integrate these approaches into their analysis pipelines. ProteinHistorian's modular, extensible design facilitates the integration of new datasets and algorithms. The ProteinHistorian web server, source code, and pre-computed ages for 32 eukaryotic genomes are freely available under the GNU public license at http://lighthouse.ucsf.edu/ProteinHistorian/.

Widespread establishment and regulatory impact of Alu exons in human genes

The Alu element has been a major source of new exons during primate evolution. Thousands of human genes contain spliced exons derived from Alu elements. However, identifying Alu exons that have acquired genuine biological functions remains a major challenge. We investigated the creation and establishment of Alu exons in human genes, using transcriptome profiles of human tissues generated by high-throughput RNA sequencing (RNA-Seq) combined with extensive RT-PCR analysis. More than 25% of Alu exons analyzed by RNA-Seq have estimated transcript inclusion levels of at least 50% in the human cerebellum, indicating widespread establishment of Alu exons in human genes. Genes encoding zinc finger transcription factors have significantly higher levels of Alu exonization. Importantly, Alu exons with high splicing activities are strongly enriched in the 5'-UTR, and two-thirds (10/15) of 5'-UTR Alu exons tested by luciferase reporter assays significantly alter mRNA translational efficiency. Mutational analysis reveals the specific molecular mechanisms by which newly created 5'-UTR Alu exons modulate translational efficiency, such as the creation or elongation of upstream ORFs that repress the translation of the primary ORFs. This study presents genomic evidence that a major functional consequence of Alu exonization is the lineage-specific evolution of translational regulation. Moreover, the preferential creation and establishment of Alu exons in zinc finger genes suggest that Alu exonization may have globally affected the evolution of primate and human transcriptomes by regulating the protein production of master transcriptional regulators in specific lineages.

Similarly strong purifying selection acts on human disease genes of all evolutionary ages

A number of studies have showed that recently created genes differ from the genes created in deep evolutionary past in many aspects. Here, we determined the age of emergence and propensity for gene loss (PGL) of all human protein–coding genes and compared disease genes with non-disease genes in terms of their evolutionary rate, strength of purifying selection, mRNA expression, and genetic redundancy. The older and the less prone to loss, non-disease genes have been evolving 1.5- to 3-fold slower between humans and chimps than young non-disease genes, whereas Mendelian disease genes have been evolving very slowly regardless of their ages and PGL. Complex disease genes showed an intermediate pattern. Disease genes also have higher mRNA expression heterogeneity across multiple tissues than non-disease genes regardless of age and PGL. Young and middle-aged disease genes have fewer similar paralogs as non-disease genes of the same age. We reasoned that genes were more likely to be involved in human disease if they were under a strong functional constraint, expressed heterogeneously across tissues, and lacked genetic redundancy. Young human genes that have been evolving under strong constraint between humans and chimps might also be enriched for genes that encode important primate or even human-specific functions.