It is of fundamental importance to understand the determinants of the rate of protein evolution. Eukaryotic extracellular proteins are known to evolve faster than intracellular proteins. Although this rate difference appears to be due to the lower essentiality of extracellular proteins than intracellular proteins in yeast, we here show that, in mammals, the impact of extracellularity is independent from the impact of gene essentiality. Our partial correlation analysis indicated that the impact of extracellularity on mammalian protein evolutionary rate is also independent from those of tissue-specificity, expression level, gene compactness, and the number of protein-protein interactions and, surprisingly, is the strongest among all the factors we examined. Similar results were also found from principal component regression analysis. Our findings suggest that different rules govern the pace of protein sequence evolution in mammals and yeasts.

Although gene duplication plays a major role in organismal evolution, it may also lead to gene dosage imbalance, thereby having an immediate adverse effect on an organism’s fitness. Investigating the evolution of the expression patterns of genes that duplicated after the divergence of rodents and primates, we confirm that adaptive evolution has been involved in dosage rebalance after gene duplication. To understand mechanisms underlying this process, we examined 1) microRNA (miRNA)-mediated gene regulation, 2) cis-regulatory sequence modifications, and 3) DNA methylation. Neither miRNA-mediated regulation nor cis-regulatory changes was found to be associated with expression reduction of duplicate genes. By contrast, duplicate genes, especially lowly expressed copies, were heavily methylated in the upstream region. However, for duplicate genes encoding proteins that are members of macromolecular complexes, heavy methylation in the genic region was not consistently observed. This result held after controlling potential confounding factors, such as enrichment in functional categories. Our results suggest that during mammalian evolution, DNA methylation plays a dominant role in dosage rebalance after gene duplication by inhibiting transcription initiation of duplicate genes.

The relative importance of protein function change and gene expression change in phenotypic evolution is a contentious, yet central topic in evolutionary biology. Analyzing 5,199 mouse genes with recorded mutant phenotypes, we find that genes exclusively affecting morphological traits when mutated (dubbed “morphogenes”) are grossly enriched with transcriptional regulators, whereas those exclusively affecting physiological traits (dubbed “physiogenes”) are enriched with channels, transporters, receptors, and enzymes. Compared to physiogenes, morphogenes are more likely to be essential and pleiotropic and less likely to be tissue specific. Morphogenes evolve faster in expression profile, but slower in protein sequence and gene gain/loss than physiogenes. Thus, morphological and physiological changes have a differential molecular basis; separating them helps discern the genetic mechanisms of phenotypic evolution.

Genome-scale phenotypic data are available for many model organisms, yet existing tools to functionally interpret gene sets from these phenotypic data are largely based on mutagenesis-derived phenotypes observed in mouse or human. Data from both mutagenesis and knockdown experiments are incorporated into modPhEA to allow users to perform enrichment analyses based on phenotypes observed in budding yeast (Saccharomyces cerevisiae), roundworm (Caenorhabditis elegans), fruit fly (Drosophila melanogaster), zebrafish (Danio rerio), mouse (Mus musculus) and humans (Homo sapiens). The phenotypes analysed can be customized to investigate complex traits and gene sets from any fully sequenced animal or fungal genome are also supported by modPhEA. Freely available on the web at http://evol.nhri.org.tw/modPhEA/. Supplementary data are available at Bioinformatics online.

Microbial diversity and community structures in acidic hot springs have been characterized by 16S rRNA gene-based diversity surveys. However, our understanding regarding the interactions among microbes, or between microbes and environmental factors, remains limited. In the present study, a metagenomic approach, followed by bioinformatics analyses, were used to predict interactions within the microbial ecosystem in Shi-Huang-Ping (SHP), an acidic hot spring in northern Taiwan. Characterizing environmental parameters and potential metabolic pathways highlighted the importance of carbon assimilatory pathways. Four distinct carbon assimilatory pathways were identified in five dominant genera of bacteria. Of those dominant carbon fixers, Hydrogenobaculum bacteria outcompeted other carbon assimilators and dominated the SHP, presumably due to their ability to metabolize hydrogen and to withstand an anaerobic environment with fluctuating temperatures. Furthermore, most dominant microbes were capable of metabolizing inorganic sulfur-related compounds (abundant in SHP). However, Acidithiobacillus ferrooxidans was the only species among key rare microbes with the capability to fix nitrogen, suggesting a key role in nitrogen cycling. In addition to potential metabolic interactions, based on the 16S rRNAs gene sequence of Nanoarchaeum-related and its potential host Ignicoccus-related archaea, as well as sequences of viruses and CRISPR arrays, we inferred that there were complex microbe-microbe interactions. Our study provided evidence that there were numerous microbe-microbe and microbe-environment interactions within the microbial community in an acidic hot spring. We proposed that Hydrogenobaculum bacteria were the dominant microbial genus, as they were able to metabolize hydrogen, assimilate carbon and live in an anaerobic environment with fluctuating temperatures.

Summary: MamPhEA is a web application dedicated to understanding functional properties of mammalian gene sets based on mouse-mutant phenotypes. It allows users to conduct enrichment analysis on predefined or user-defined phenotypes, gives users the option to specify phenotypes derived from null mutations, produces easily comprehensible results and supports analyses on genes of all mammalian species with a fully sequenced genome. Availability:http://evol.nhri.org.tw/MamPhEA/ Contact:liaoby@nhri.org.tw Supplementary information: Supplementary data are available at Bioinformatics online.