PhyloPat: phylogenetic pattern analysis of eukaryotic genes

Relaxed purifying selection and possibly high rate of adaptation in primate lineage-specific genes

Genes in the same organism vary in the time since their evolutionary origin. Without horizontal gene transfer, young genes are necessarily restricted to a few closely related species, whereas old genes can be broadly distributed across the phylogeny. It has been shown that young genes evolve faster than old genes; however, the evolutionary forces responsible for this pattern remain obscure. Here, we classify human–chimp protein-coding genes into different age classes, according to the breath of their phylogenetic distribution. We estimate the strength of purifying selection and the rate of adaptive selection for genes in different age classes. We find that older genes carry fewer and less frequent nonsynonymous single-nucleotide polymorphisms than younger genes suggesting that older genes experience a stronger purifying selection at the protein-coding level. We infer the distribution of fitness effects of new deleterious mutations and find that older genes have proportionally more slightly deleterious mutations and fewer nearly neutral mutations than younger genes. To investigate the role of adaptive selection of genes in different age classes, we determine the selection coefficient (γ = 2N_es) of genes using the MKPRF approach and estimate the ratio of the rate of adaptive nonsynonymous substitution to synonymous substitution (ω_A) using the DoFE method. Although the proportion of positively selected genes (γ > 0) is significantly higher in younger genes, we find no correlation between ω_A and gene age. Collectively, these results provide strong evidence that younger genes are subject to weaker purifying selection and more tenuous evidence that they also undergo adaptive evolution more frequently.

Genomics and bioinformatics resources for crop improvement

Recent remarkable innovations in platforms for omics-based research and application development provide crucial resources to promote research in model and applied plant species. A combinatorial approach using multiple omics platforms and integration of their outcomes is now an effective strategy for clarifying molecular systems integral to improving plant productivity. Furthermore, promotion of comparative genomics among model and applied plants allows us to grasp the biological properties of each species and to accelerate gene discovery and functional analyses of genes. Bioinformatics platforms and their associated databases are also essential for the effective design of approaches making the best use of genomic resources, including resource integration. We review recent advances in research platforms and resources in plant omics together with related databases and advances in technology.

Testicular cell adhesion molecule 1 (TCAM1) is not essential for fertility

Testicular cell adhesion molecule 1 (Tcam1) is a testis-expressed gene that is evolutionarily conserved in most mammalian species. The putative location of TCAM1 on the cell surface makes it an attractive contraceptive target to study. We found that Tcam1 transcription is enriched in the adult testis, and in situ hybridization revealed that Tcam1 is expressed in pachytene to secondary spermatocytes. Immunofluorescence for TCAM1 protein showed strong expression along cell membranes of spermatocytes and weak localization to round spermatids. In light of this evidence, we hypothesized that TCAM1 interacts with an unknown receptor on the surface of Sertoli cells and that this interaction is important for germ cell-Sertoli cell interactions. However, Tcam1 knockout mice that we generated are fertile, and testis weights and sperm counts were not significantly altered. Therefore, we conclude that TCAM1 is not essential for male fertility or germ cell function in Mus musculus.

Dynamism in gene expression across multiple studies

In this study we develop methods of examining gene expression dynamics, how and when genes change expression, and demonstrate their application in a meta-analysis involving over 29,000 microarrays. By defining measures across many experimental conditions, we have a new way of characterizing dynamics, complementary to measures looking at changes in absolute variation or breadth of tissues showing expression. We show conservation in overall patterns of dynamism across three species (human, mouse, and rat) and show associations with known disease-related genes. We discuss the enriched functional properties of the sets of genes showing different patterns of dynamics and show that the differences in expression dynamics is associated with the variety of different transcription factor regulatory sites. These results can influence thinking about the selection of genes for microarray design and the analysis of measurements of mRNA expression variation in a global context of expression dynamics across many conditions, as genes that are rarely differentially expressed between experimental conditions may be the subject of increased scrutiny when they significantly vary in expression between experimental subsets.

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.

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

Phylogenetic patterns show the presence or absence of certain genes in a set of full genomes derived from different species. They can also be used to determine sets of genes that occur only in certain evolutionary branches. Previously, we presented a database named PhyloPat which allows the complete Ensembl gene database to be queried using phylogenetic patterns. Here, we describe an updated version of PhyloPat which can be queried by an improved web server. We used a single linkage clustering algorithm to create 241,697 phylogenetic lineages, using all the orthologies provided by Ensembl v49. PhyloPat offers the possibility of querying with binary phylogenetic patterns or regular expressions, or through a phylogenetic tree of the 39 included species. Users can also input a list of Ensembl, EMBL, EntrezGene or HGNC IDs to check which phylogenetic lineage any gene belongs to. A link to the FatiGO web interface has been incorporated in the HTML output. For each gene, the surrounding genes on the chromosome, color coded according to their phylogenetic lineage can be viewed, as well as FASTA files of the peptide sequences of each lineage. Furthermore, lists of omnipresent, polypresent, oligopresent and anticorrelating genes have been included. PhyloPat is freely available at http://www.cmbi.ru.nl/phylopat.

BioVenn - a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams

BACKGROUND

In many genomics projects, numerous lists containing biological identifiers are produced. Often it is useful to see the overlap between different lists, enabling researchers to quickly observe similarities and differences between the data sets they are analyzing. One of the most popular methods to visualize the overlap and differences between data sets is the Venn diagram: a diagram consisting of two or more circles in which each circle corresponds to a data set, and the overlap between the circles corresponds to the overlap between the data sets. Venn diagrams are especially useful when they are 'area-proportional' i.e. the sizes of the circles and the overlaps correspond to the sizes of the data sets. Currently there are no programs available that can create area-proportional Venn diagrams connected to a wide range of biological databases.

RESULTS

We designed a web application named BioVenn to summarize the overlap between two or three lists of identifiers, using area-proportional Venn diagrams. The user only needs to input these lists of identifiers in the textboxes and push the submit button. Parameters like colors and text size can be adjusted easily through the web interface. The position of the text can be adjusted by 'drag-and-drop' principle. The output Venn diagram can be shown as an SVG or PNG image embedded in the web application, or as a standalone SVG or PNG image. The latter option is useful for batch queries. Besides the Venn diagram, BioVenn outputs lists of identifiers for each of the resulting subsets. If an identifier is recognized as belonging to one of the supported biological databases, the output is linked to that database. Finally, BioVenn can map Affymetrix and EntrezGene identifiers to Ensembl genes.

CONCLUSION

BioVenn is an easy-to-use web application to generate area-proportional Venn diagrams from lists of biological identifiers. It supports a wide range of identifiers from the most used biological databases currently available. Its implementation on the World Wide Web makes it available for use on any computer with internet connection, independent of operating system and without the need to install programs locally. BioVenn is freely accessible at http://www.cmbi.ru.nl/cdd/biovenn/.

BioVenn - a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams

BACKGROUND

In many genomics projects, numerous lists containing biological identifiers are produced. Often it is useful to see the overlap between different lists, enabling researchers to quickly observe similarities and differences between the data sets they are analyzing. One of the most popular methods to visualize the overlap and differences between data sets is the Venn diagram: a diagram consisting of two or more circles in which each circle corresponds to a data set, and the overlap between the circles corresponds to the overlap between the data sets. Venn diagrams are especially useful when they are 'area-proportional' i.e. the sizes of the circles and the overlaps correspond to the sizes of the data sets. Currently there are no programs available that can create area-proportional Venn diagrams connected to a wide range of biological databases.

RESULTS

We designed a web application named BioVenn to summarize the overlap between two or three lists of identifiers, using area-proportional Venn diagrams. The user only needs to input these lists of identifiers in the textboxes and push the submit button. Parameters like colors and text size can be adjusted easily through the web interface. The position of the text can be adjusted by 'drag-and-drop' principle. The output Venn diagram can be shown as an SVG or PNG image embedded in the web application, or as a standalone SVG or PNG image. The latter option is useful for batch queries. Besides the Venn diagram, BioVenn outputs lists of identifiers for each of the resulting subsets. If an identifier is recognized as belonging to one of the supported biological databases, the output is linked to that database. Finally, BioVenn can map Affymetrix and EntrezGene identifiers to Ensembl genes.

CONCLUSION

BioVenn is an easy-to-use web application to generate area-proportional Venn diagrams from lists of biological identifiers. It supports a wide range of identifiers from the most used biological databases currently available. Its implementation on the World Wide Web makes it available for use on any computer with internet connection, independent of operating system and without the need to install programs locally. BioVenn is freely accessible at http://www.cmbi.ru.nl/cdd/biovenn/.

Preservation of genes involved in sterol metabolism in cholesterol auxotrophs: facts and hypotheses

Background

It is known that primary sequences of enzymes involved in sterol biosynthesis are well conserved in organisms that produce sterols de novo. However, we provide evidence for a preservation of the corresponding genes in two animals unable to synthesize cholesterol (auxotrophs): Drosophila melanogaster and Caenorhabditis elegans.

Principal Findings

We have been able to detect bona fide orthologs of several ERG genes in both organisms using a series of complementary approaches. We have detected strong sequence divergence between the orthologs of the nematode and of the fruitfly; they are also very divergent with respect to the orthologs in organisms able to synthesize sterols de novo (prototrophs). Interestingly, the orthologs in both the nematode and the fruitfly are still under selective pressure. It is possible that these genes, which are not involved in cholesterol synthesis anymore, have been recruited to perform different new functions. We propose a more parsimonious way to explain their accelerated evolution and subsequent stabilization. The products of ERG genes in prototrophs might be involved in several biological roles, in addition to sterol synthesis. In the case of the nematode and the fruitfly, the relevant genes would have lost their ancestral function in cholesterogenesis but would have retained the other function(s), which keep them under pressure.

Conclusions

By exploiting microarray data we have noticed a strong expressional correlation between the orthologs of ERG24 and ERG25 in D. melanogaster and genes encoding factors involved in intracellular protein trafficking and folding and with Start1 involved in ecdysteroid synthesis. These potential functional connections are worth being explored not only in Drosophila, but also in Caenorhabditis as well as in sterol prototrophs.

Conservation of key members in the course of the evolution of the insulin signaling pathway

Our understanding of the evolution of the insulin signaling pathway (ISP) is still incomplete. One intriguing unanswered question is the explanation of the emergence of the glucostatic role of insulin in mammals. To find out whether this is due to the development of new sets of signaling transduction elements in these organisms, or to the establishment of new interactions between pre-existing proteins, we rebuilt putative orthologous ISPs in 17 eukaryotic organisms. Then, we computed the conservation of orthologous ISPs at different levels, from sequence similarity of orthologous proteins to co-evolution of interacting domains. We found that the emergence of glucostatic role in mammals can neither be explained by the development of new sets of signaling elements, nor by the establishment of new interactions between pre-existing proteins. The comparison of orthologous IRS molecules indicates that only in mammals have they acquired their complete functionality as efficient recruiters of effector sub-pathways.

Evolutionary origin of sex-related genes in the mouse brain

With the aim of elucidating the evolutionary process of sexual dimorphism in the brain at the molecular level, we conducted genomic comparisons of a set of genes expressed in a sexually different manner in the mouse brain with all genes from other species of eukaryotes. First, seventeen protein-coding genes whose levels of mRNA expression in the brain differed between male and female mice have been known according to the currently available microarray data, and we designated these genes operationally as "sex-related genes in the mouse brain". Next, we estimated the time when these sex-related genes in the mouse brain emerged in the evolutionary process of eukaryotes by examining the presence or absence of the orthologues in the 26 eukaryotic species whose genome sequences are available. As a result, we found that the ten sex-related genes in the mouse brain emerged after the divergence of urochordates and mammals whereas the other seven sex-related genes in the mouse brain emerged before the divergence of urochordates and mammals. In particular, five sex-related genes out of the ten genes in the mouse brain emerged just before the appearance of bony fish which have phenotypic sexual dimorphism in the brain. Interestingly, three of these five sex-related genes that emerged during this period were classified into the "protein binding" function category. Moreover, all of these three genes were expected to have the functions that are related to cell-cell communications in the brain according to the gene expression patterns and/or functional information of these genes. These findings suggest that the orthologues of the sex-related genes in the mouse brain that emerged just before the divergence of bony fish might have essential roles in the evolution of the sexual dimorphism in the brain forming protein-protein interactions.