eggNOG v4.0: nested orthology inference across 3686 organisms.

With the increasing availability of various 'omics data, high-quality orthology assignment is crucial for evolutionary and functional genomics studies. We here present the fourth version of the eggNOG database (available at http://eggnog.embl.de) that derives nonsupervised orthologous groups (NOGs) from complete genomes, and then applies a comprehensive characterization and analysis pipeline to the resulting gene families. Compared with the previous version, we have more than tripled the underlying species set to cover 3686 organisms, keeping track with genome project completions while prioritizing the inclusion of high-quality genomes to minimize error propagation from incomplete proteome sets. Major technological advances include (i) a robust and scalable procedure for the identification and inclusion of high-quality genomes, (ii) provision of orthologous groups for 107 different taxonomic levels compared with 41 in eggNOGv3, (iii) identification and annotation of particularly closely related orthologous groups, facilitating analysis of related gene families, (iv) improvements of the clustering and functional annotation approach, (v) adoption of a revised tree building procedure based on the multiple alignments generated during the process and (vi) implementation of quality control procedures throughout the entire pipeline. As in previous versions, eggNOGv4 provides multiple sequence alignments and maximum-likelihood trees, as well as broad functional annotation. Users can access the complete database of orthologous groups via a web interface, as well as through bulk download.

Consistent mutational paths predict eukaryotic thermostability.

BACKGROUND: Proteomes of thermophilic prokaryotes have been instrumental in structural biology and successfully exploited in biotechnology, however many proteins required for eukaryotic cell function are absent from bacteria or archaea. With Chaetomium thermophilum, Thielavia terrestris and Thielavia heterothallica three genome sequences of thermophilic eukaryotes have been published. RESULTS: Studying the genomes and proteomes of these thermophilic fungi, we found common strategies of thermal adaptation across the different kingdoms of Life, including amino acid biases and a reduced genome size. A phylogenetics-guided comparison of thermophilic proteomes with those of other, mesophilic Sordariomycetes revealed consistent amino acid substitutions associated to thermophily that were also present in an independent lineage of thermophilic fungi. The most consistent pattern is the substitution of lysine by arginine, which we could find in almost all lineages but has not been extensively used in protein stability engineering. By exploiting mutational paths towards the thermophiles, we could predict particular amino acid residues in individual proteins that contribute to thermostability and validated some of them experimentally. By determining the three-dimensional structure of an exemplar protein from C. thermophilum (Arx1), we could also characterise the molecular consequences of some of these mutations. CONCLUSIONS: The comparative analysis of these three genomes not only enhances our understanding of the evolution of thermophily, but also provides new ways to engineer protein stability.

Visualization of multiple alignments, phylogenies and gene family evolution.

Software for visualizing sequence alignments and trees are essential tools for life scientists. In this review, we describe the major features and capabilities of a selection of stand-alone and web-based applications useful when investigating the function and evolution of a gene family. These range from simple viewers, to systems that provide sophisticated editing and analysis functions. We conclude with a discussion of the challenges that these tools now face due to the flood of next generation sequence data and the increasingly complex network of bioinformatics information sources.

RNA-seq analysis of differential gene expression in liver from lactating dairy cows divergent in negative energy balance.

BACKGROUND: The liver is central to most economically important metabolic processes in cattle. However, the changes in expression of genes that drive these processes remain incompletely characterised. RNA-seq is the new gold standard for whole transcriptome analysis but so far there are no reports of its application to analysis of differential gene expression in cattle liver. We used RNA-seq to study differences in expression profiles of hepatic genes and their associated pathways in individual cattle in either mild negative energy balance (MNEB) or severe negative energy balance (SNEB). NEB is an imbalance between energy intake and energy requirements for lactation and body maintenance. This aberrant metabolic state affects high-yielding dairy cows after calving and is of considerable economic importance because of its negative impact on fertility and health in dairy herds. Analysis of changes in hepatic gene expression in SNEB animals will increase our understanding of NEB and contribute to the development of strategies to circumvent it. RESULTS: RNA-seq analysis was carried out on total RNA from liver from early post partum Holstein Friesian cows in MNEB (n = 5) and SNEB (n = 6). 12,833 genes were deemed to be expressed (>4 reads per gene per animal), 413 of which were shown to be statistically significantly differentially expressed (SDE) at a false discovery rate (FDR) of 0.1% and 200 of which were SDE (FDR of 0.1%) with a ≥ 2-fold change between MNEB and SNEB animals. GOseq/KEGG pathway analysis showed that SDE genes with ≥ 2- fold change were associated (P <0.05) with 9 KEGG pathways. Seven of these pathways were related to fatty acid metabolism and unexpectedly included 'Steroid hormone biosynthesis', a process which mainly occurs in the reproductive organs rather than the liver. CONCLUSIONS: RNA-seq analysis showed that the major changes at the level of transcription in the liver of SNEB cows were related to fat metabolism. 'Steroid hormone biosynthesis', a process that normally occurs in reproductive tissue, was significantly associated with changes in gene expression in the liver of SNEB cows. Changes in gene expression were found in this pathway that have not been previously been identified in SNEB cows.

Resistome Analysis of Global Livestock and Soil Microbiomes.

Antimicrobial resistance (AMR) is a serious threat to public health globally; it is estimated that AMR bacteria caused 1.27 million deaths in 2019, and this is set to rise to 10 million deaths annually. Agricultural and soil environments act as antimicrobial resistance gene (ARG) reservoirs, operating as a link between different ecosystems and enabling the mixing and dissemination of resistance genes. Due to the close interactions between humans and agricultural environments, these AMR gene reservoirs are a major risk to both human and animal health. In this study, we aimed to identify the resistance gene reservoirs present in four microbiomes: poultry, ruminant, swine gastrointestinal (GI) tracts coupled with those from soil. This large study brings together every poultry, swine, ruminant, and soil shotgun metagenomic sequence available on the NCBI sequence read archive for the first time. We use the ResFinder database to identify acquired antimicrobial resistance genes in over 5,800 metagenomes. ARGs were diverse and widespread within the metagenomes, with 235, 101, 167, and 182 different resistance genes identified in the poultry, ruminant, swine, and soil microbiomes, respectively. The tetracycline resistance genes were the most widespread in the livestock GI microbiomes, including tet(W)_1, tet(Q)_1, tet(O)_1, and tet(44)_1. The tet(W)_1 resistance gene was found in 99% of livestock GI tract microbiomes, while tet(Q)_1 was identified in 93%, tet(O)_1 in 82%, and finally tet(44)_1 in 69%. Metatranscriptomic analysis confirmed these genes were "real" and expressed in one or more of the livestock GI tract microbiomes, with tet(40)_1 and tet(O)_1 expressed in all three livestock microbiomes. In soil, the most abundant ARG was the oleandomycin resistance gene, ole(B)_1. A total of 55 resistance genes were shared by the four microbiomes, with 11 ARGs actively expressed in two or more microbiomes. By using all available metagenomes we were able to mine a large number of samples and describe resistomes in 37 countries. This study provides a global insight into the diverse and abundant antimicrobial resistance gene reservoirs present in both livestock and soil microbiomes.

STRING 8--a global view on proteins and their functional interactions in 630 organisms.

Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein-protein interactions, including both physical and functional interactions. It weights and integrates information from numerous sources, including experimental repositories, computational prediction methods and public text collections, thus acting as a meta-database that maps all interaction evidence onto a common set of genomes and proteins. The most important new developments in STRING 8 over previous releases include a URL-based programming interface, which can be used to query STRING from other resources, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures. Version 8.0 of STRING covers about 2.5 million proteins from 630 organisms, providing the most comprehensive view on protein-protein interactions currently available. STRING can be reached at http://string-db.org/.

The shape of supertrees to come: tree shape related properties of fourteen supertree methods.

Using a simple example and simulations, we explore the impact of input tree shape upon a broad range of supertree methods. We find that input tree shape can affect how conflict is resolved by several supertree methods and that input tree shape effects may be substantial. Standard and irreversible matrix representation with parsimony (MRP), MinFlip, duplication-only Gene Tree Parsimony (GTP), and an implementation of the average consensus method have a tendency to resolve conflict in favor of relationships in unbalanced trees. Purvis MRP and the average dendrogram method appear to have an opposite tendency. Biases with respect to tree shape are correlated with objective functions that are based upon unusual asymmetric tree-to-tree distance or fit measures. Split, quartet, and triplet fit, most similar supertree, and MinCut methods (provided the latter are interpreted as Adams consensus-like supertrees) are not revealed to have any bias with respect to tree shape by our example, but whether this holds more generally is an open problem. Future development and evaluation of supertree methods should consider explicitly the undesirable biases and other properties that we highlight. In the meantime, use of a single, arbitrarily chosen supertree method is discouraged. Use of multiple methods and/or weighting schemes may allow practical assessment of the extent to which inferences from real data depend upon methodological biases with respect to input tree shape or size.