Even though automated functional annotation of genes represents a fundamental step in most genomic and metagenomic workflows, it remains challenging at large scales. Here, we describe a major upgrade to eggNOG-mapper, a tool for functional annotation based on precomputed orthology assignments, now optimized for vast (meta)genomic data sets. Improvements in version 2 include a full update of both the genomes and functional databases to those from eggNOG v5, as well as several efficiency enhancements and new features. Most notably, eggNOG-mapper v2 now allows for: (i) de novo gene prediction from raw contigs, (ii) built-in pairwise orthology prediction, (iii) fast protein domain discovery, and (iv) automated GFF decoration. eggNOG-mapper v2 is available as a standalone tool or as an online service at http://eggnog-mapper.embl.de.

Phylogenetic trees are routinely visualized to present and interpret the evolutionary relationships of species. Most empirical evolutionary data studies contain a visualization of the inferred tree with branch support values. Ambiguous semantics in tree file formats can lead to erroneous tree visualizations and therefore to incorrect interpretations of phylogenetic analyses. Here, we discuss problems that arise when displaying branch values on trees after rerooting. Branch values are typically stored as node labels in the widely-used Newick tree format. However, such values are attributes of branches. Storing them as node labels can therefore yield errors when rerooting trees. This depends on the mostly implicit semantics that tools deploy to interpret node labels. We reviewed ten tree viewers and ten bioinformatics toolkits that can display and reroot trees. We found that 14 out of 20 of these tools do not permit users to select the semantics of node labels. Thus, unaware users might obtain incorrect results when rooting trees. We illustrate such incorrect mappings for several test cases and real examples taken from the literature. This review has already led to improvements in eight tools. We suggest tools should provide options that explicitly force users to define the semantics of node labels.

Orthology assignment is ideally suited for functional inference. However, because predicting orthology is computationally intensive at large scale, and most pipelines are relatively inaccessible (e.g. new assignments only available through database updates), less precise homology-based functional transfer is still the default for (meta-)genome annotation. We therefore developed eggNOG-mapper, a tool for functional annotation of large sets of sequences based on fast orthology assignments using precomputed clusters and phylogenies from the eggNOG database. To validate our method, we benchmarked Gene Ontology predictions against two widely used homology-based approaches: BLAST and InterProScan. Orthology filters applied to BLAST results reduced the rate of false positive assignments by 11%, and increased the ratio of experimentally validated terms recovered over all terms assigned per protein by 15%. Compared to InterProScan, eggNOG-mapper achieved similar proteome coverage and precision while predicting, on average, 41 more terms per protein and increasing the rate of experimentally validated terms recovered over total term assignments per protein by 35%. EggNOG-mapper predictions scored within the top-5 methods in the three Gene Ontology categories using the CAFA2 NK-partial benchmark. Finally, we evaluated eggNOG-mapper for functional annotation of metagenomics data, yielding better performance than interProScan. eggNOG-mapper runs ∼15x faster than BLAST and at least 2.5x faster than InterProScan. The tool is available standalone and as an online service at http://eggnog-mapper.embl.de.

The Environment for Tree Exploration (ETE) is a computational framework that simplifies the reconstruction, analysis and visualization of phylogenetic trees and multiple sequence alignments. Here we present ETE v3, featuring numerous improvements in the underlying library of methods, and providing a novel set of standalone tools to perform common tasks in comparative genomics and phylogenetics. The new features include i) building gene-based and supermatrix-based phylogenies using a single command, ii) testing and visualizing evolutionary models, iii) calculating distances between trees of different size or including duplications, and iv) providing seamless integration with the NCBI taxonomy database. ETE is freely available at http://etetoolkit.org.

Recently duplicated genes are believed to often overlap in function and expression. A priori, they are thus less likely to be essential. While this was indeed observed in yeast, mouse singletons and duplicates were reported to be equally often essential. This contradiction can only partly be explained by experimental biases. We herein show that older genes (i.e., genes with earlier phyletic origin) are more likely to be essential, regardless of their duplication status. At a given phyletic gene age, duplicates are always less likely to be essential compared to singletons. The 'paradoxical' high essentiality among mouse gene duplicates is then caused by different age profiles of singletons and duplicates, with the latter tending to be derived from older genes.

The principle of heterotachy states that the substitution rate of sites in a gene can change through time. In this article, we propose a powerful statistical test to detect sites that evolve according to the process of heterotachy. We apply this test to an alignment of 1289 eukaryotic rRNA molecules to 1) determine how widespread the phenomenon of heterotachy is in ribosomal RNA, 2) to test whether these heterotachous sites are nonrandomly distributed, that is, linked to secondary structure features of ribosomal RNA, and 3) to determine the impact of heterotachous sites on the bootstrap support of monophyletic groupings. Our study revealed that with 21 monophyletic taxa, approximately two-thirds of the sites in the considered set of sequences is heterotachous. Although the detected heterotachous sites do not appear bound to specific structural features of the small subunit rRNA, their presence is shown to have a large beneficial influence on the bootstrap support of monophyletic groups. Using extensive testing, we show that this may not be due to heterotachy itself but merely due to the increased substitution rate at the detected heterotachous sites.

We compare the frequency distribution of gene family sizes in the complete genomes of six bacteria (Escherichia coli, Haemophilus influenzae, Helicobacter pylori, Mycoplasma genitalium, Mycoplasma pneumoniae, and Synechocystis sp. PCC6803), two Archaea (Methanococcus jannaschii and Methanobacterium thermoautotrophicum), one eukaryote (Saccharomyces cerevisiae), the vaccinia virus, and the bacteriophage T4. The sizes of the gene families versus their frequencies show power-law distributions that tend to become flatter (have a larger exponent) as the number of genes in the genome increases. Power-law distributions generally occur as the limit distribution of a multiplicative stochastic process with a boundary constraint. We discuss various models that can account for a multiplicative process determining the sizes of gene families in the genome. In particular, we argue that, in order to explain the observed distributions, gene families have to behave in a coherent fashion within the genome; i.e., the probabilities of duplications of genes within a gene family are not independent of each other. Likewise, the probabilities of deletions of genes within a gene family are not independent of each other.