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Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of interfaces to genomic data across the tree of life, including reference genome sequence, gene models, transcriptional data, genetic variation and comparative analysis. Data may be accessed via our website, online tools platform and programmatic interfaces, with updates made four times per year (in synchrony with Ensembl). Here, we provide an overview of Ensembl Genomes, with a focus on recent developments. These include the continued growth, more robust and reproducible sets of orthologues and paralogues, and enriched views of gene expression and gene function in plants. Finally, we report on our continued deeper integration with the Ensembl project, which forms a key part of our future strategy for dealing with the increasing quantity of available genome-scale data across the tree of life.

The Ensembl project (https://www.ensembl.org) makes key genomic data sets available to the entire scientific community without restrictions. Ensembl seeks to be a fundamental resource driving scientific progress by creating, maintaining and updating reference genome annotation and comparative genomics resources. This year we describe our new and expanded gene, variant and comparative annotation capabilities, which led to a 50% increase in the number of vertebrate genomes we support. We have also doubled the number of available human variants and added regulatory regions for many mouse cell types and developmental stages. Our data sets and tools are available via the Ensembl website as well as a through a RESTful webservice, Perl application programming interface and as data files for download.

Ngatiwai Trust Board. et al., The tuatara (Sphenodon punctatus)—the only living member of the reptilian order Rhynchocephalia (Sphenodontia), once widespread across Gondwana1,2—is an iconic species that is endemic to New Zealand2,3. A key link to the now-extinct stem reptiles (from which dinosaurs, modern reptiles, birds and mammals evolved), the tuatara provides key insights into the ancestral amniotes2,4. Here we analyse the genome of the tuatara, which—at approximately 5 Gb—is among the largest of the vertebrate genomes yet assembled. Our analyses of this genome, along with comparisons with other vertebrate genomes, reinforce the uniqueness of the tuatara. Phylogenetic analyses indicate that the tuatara lineage diverged from that of snakes and lizards around 250 million years ago. This lineage also shows moderate rates of molecular evolution, with instances of punctuated evolution. Our genome sequence analysis identifies expansions of proteins, non-protein-coding RNA families and repeat elements, the latter of which show an amalgam of reptilian and mammalian features. The sequencing of the tuatara genome provides a valuable resource for deep comparative analyses of tetrapods, as well as for tuatara biology and conservation. Our study also provides important insights into both the technical challenges and the cultural obligations that are associated with genome sequencing., N.J.G. acknowledges the support of Ngatiwai iwi, Allan Wilson Centre, University of Otago, New Zealand Department of Conservation, New Zealand Genomics and Illumina. J.I.A. was supported by CONICYT National Doctoral Scholarship No. 21130515. M.W. was supported by NIH grant R35 GM124827. Ensembl annotation was supported by the Wellcome Trust (WT108749/Z/15/Z) and the European Molecular Biology Laboratory.

Gene families evolve by the processes of speciation (creating orthologs), gene duplication (paralogs), and horizontal gene transfer (xenologs), in addition to sequence divergence and gene loss. Orthologs in particular play an essential role in comparative genomics and phylogenomic analyses. With the continued sequencing of organisms across the tree of life, the data are available to reconstruct the unique evolutionary histories of tens of thousands of gene families. Accurate reconstruction of these histories, however, is a challenging computational problem, and the focus of the Quest for Orthologs Consortium. We review the recent advances and outstanding challenges in this field, as revealed at a symposium and meeting held at the University of Southern California in 2017. Key advances have been made both at the level of orthology algorithm development and with respect to coordination across the community of algorithm developers and orthology end-users. Applications spanned a broad range, including gene function prediction, phylostratigraphy, genome evolution, and phylogenomics. The meetings highlighted the increasing use of meta-analyses integrating results from multiple different algorithms, and discussed ongoing challenges in orthology inference as well as the next steps toward improvement and integration of orthology resources. We thank the Society for Molecular Biology and Evolution for supporting the SMBE-EGF Symposium, and the University of Southern California for supporting the QFO5 meeting. We wish to acknowledge the following support for attending the meetings and/or writing this manuscript: National Institutes of Health (grant HG002273 for P.D.T.; HG007822 for M.J.M. and A.S.d.S.; GM122480, HD085901, DK110520 for E.M.M.; GM123683 for C.M.), Wellcome Trust (grant WT108749/Z/15/Z for M.M. and M.P.), Swiss National Science Foundation (grant 150654 for C.D.), European Commission (contract 676559 for S.C.G.), Welch Foundation (grant F-1515 for E.M.M.), European Molecular Biology Laboratory (for M.J.M., M.M., M.P.), and National Bioscience Database Center and Japan Science and Technology Agency (for I.U.).

Ensembl (http://www.ensembl.org) is a genomic interpretation system providing the most up-to-date annotations, querying tools and access methods for chordates and key model organisms. This year we released updated annotation (gene models, comparative genomics, regulatory regions and variation) on the new human assembly, GRCh38, although we continue to support researchers using the GRCh37.p13 assembly through a dedicated site (http://grch37.ensembl.org). Our Regulatory Build has been revamped to identify regulatory regions of interest and to efficiently highlight their activity across disparate epigenetic data sets. A number of new interfaces allow users to perform large-scale comparisons of their data against our annotations. The REST server (http://rest.ensembl.org), which allows programs written in any language to query our databases, has moved to a full service alongside our upgraded website tools. Our online Variant Effect Predictor tool has been updated to process more variants and calculate summary statistics. Lastly, the WiggleTools package enables users to summarize large collections of data sets and view them as single tracks in Ensembl. The Ensembl code base itself is more accessible: it is now hosted on our GitHub organization page (https://github.com/Ensembl) under an Apache 2.0 open source license.

Ensembl (www.ensembl.org) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access methods ensure uniform data analysis and distribution for all supported species. Together, these provide a comprehensive solution for large-scale and targeted genomics applications alike. Among many other developments over the past year, we have improved our resources for gene regulation and comparative genomics, and added CRISPR/Cas9 target sites. We released new browser functionality and tools, including improved filtering and prioritization of genome variation, Manhattan plot visualization for linkage disequilibrium and eQTL data, and an ontology search for phenotypes, traits and disease. We have also enhanced data discovery and access with a track hub registry and a selection of new REST end points. All Ensembl data are freely released to the scientific community and our source code is available via the open source Apache 2.0 license.

The Ensembl project (http://www.ensembl.org) is a system for genome annotation, analysis, storage and dissemination designed to facilitate the access of genomic annotation from chordates and key model organisms. It provides access to data from 87 species across our main and early access Pre! websites. This year we introduced three newly annotated species and released numerous updates across our supported species with a concentration on data for the latest genome assemblies of human, mouse, zebrafish and rat. We also provided two data updates for the previous human assembly, GRCh37, through a dedicated website (http://grch37.ensembl.org). Our tools, in particular the VEP, have been improved significantly through integration of additional third party data. REST is now capable of larger-scale analysis and our regulatory data BioMart can deliver faster results. The website is now capable of displaying long-range interactions such as those found in cis-regulated datasets. Finally we have launched a website optimized for mobile devices providing views of genes, variants and phenotypes. Our data is made available without restriction and all code is available from our GitHub organization site (http://github.com/Ensembl) under an Apache 2.0 license.

TreeFam (http://www.treefam.org) is a database of phylogenetic trees inferred from animal genomes. For every TreeFam family we provide homology predictions together with the evolutionary history of the genes. Here we describe an update of the TreeFam database. The TreeFam project was resurrected in 2012 and has seen two releases since. The latest release (TreeFam 9) was made available in March 2013. It has orthology predictions and gene trees for 109 species in 15,736 families covering ∼2.2 million sequences. With release 9 we made modifications to our production pipeline and redesigned our website with improved gene tree visualizations and Wikipedia integration. Furthermore, we now provide an HMM-based sequence search that places a user-provided protein sequence into a TreeFam gene tree and provides quick orthology prediction. The tool uses Mafft and RAxML for the fast insertion into a reference alignment and tree, respectively. Besides the aforementioned technical improvements, we present a new approach to visualize gene trees and alternative displays that focuses on showing homology information from a species tree point of view. From release 9 onwards, TreeFam is now hosted at the EBI.

Inside arthropod's mitochondria the AGG codon is translated differently by distinct species. In some species, AGG is translated as lysine (Lys), whereas in others the typical mitochondrial genetic code of invertebrates operates, and AGG is translated as serine (Ser). There are also arthropods that, instead of translating AGG as Lys or Ser, simply make no use of this codon. The reassignment of the translation of the AGG codon from Ser to Lys has never been observed outside this taxonomic group. The molecular basis of this reassignment lies on point mutations at the anticodons of tRNA (transfer ribonucleic acid)–Ser and tRNA–Lys. Decodification of the AGG codon by the tRNA–Lys (with a CUU anticodon) requires a unique wobble pairing at the second position. The low affinity between the AGG codon and the CUU anticodon most likely explains why tRNA–Ser dominates over tRNA–Lys when both are able to recognise AGG. Ancestral character state reconstruction suggests that the arthropod-specific genetic code variant (AGG=Lys) possibly was already present in the ancestor of arthropods, having reverted to the invertebrate character state (AGG=Ser) multiple times in different arthropod lineages. Key Concepts: The genetic code provides a translation table between the DNA and protein alphabets. A standard genetic code shared by all life domains exists, but there are many variants. Alternative genetic codes are frequently found in metazoan mitochondrial genomes, probably due to their small size and lack of several tRNAs. Arthropods encompass a unique variant in which the AGG codon is translated as lysine, instead of serine, which is the standard meaning of AGG in invertebrates. Some arthropods make no use of the AGG codon. Several events of codon reassignment and reversions have occurred in parallel along the arthropod lineages. The translation of the AGG codon as lysine implies an exceptional wobble pairing with the CUU anticodon at the second position (G::U). Keywords: arthropods; genetic code; mitochondria; parallel evolution; anticodon mutations; ancestral character state reconstruction; AGG codon; lysine; serine; tRNA

At a genomic scale, the patterns that have shaped molecular evolution are believed to be largely heterogeneous. Consequently, comparative analyses should use appropriate probabilistic substitution models that capture the main features under which different genomic regions have evolved. While efforts have concentrated in the development and understanding of model selection techniques, no descriptions of overall relative substitution model fit at the genome level have been reported. Here, we provide a characterization of best-fit substitution models across three genomic data sets including coding regions from mammals, vertebrates, and Drosophila (24,000 alignments). According to the Akaike Information Criterion (AIC), 82 of 88 models considered were selected as best-fit models at least in one occasion, although with very different frequencies. Most parameter estimates also varied broadly among genes. Patterns found for vertebrates and Drosophila were quite similar and often more complex than those found in mammals. Phylogenetic trees derived from models in the 95% confidence interval set showed much less variance and were significantly closer to the tree estimated under the best-fit model than trees derived from models outside this interval. Although alternative criteria selected simpler models than the AIC, they suggested similar patterns. All together our results show that at a genomic scale, different gene alignments for the same set of taxa are best explained by a large variety of different substitution models and that model choice has implications on different parameter estimates including the inferred phylogenetic trees. After taking into account the differences related to sample size, our results suggest a noticeable diversity in the underlying evolutionary process. All together, we conclude that the use of model selection techniques is important to obtain consistent phylogenetic estimates from real data at a genomic scale.

Brazilian poultry industry has reached a high level of development in both meat and egg production as a result of constant technological modernization. Further improvements can be achieved through genomics, but before this can be accomplished, a better understanding of gene expression profiles and nucleotide polymorphisms is necessary. Since animal physiology is directly or indirectly controlled by the pituitary and hypothalamus, the aim of the present work was to identify and analyze genes expressed in these tissues in chicken lines with different growth potential. Two pituitary and hypothalamus cDNA libraries from 21 day broiler (TT) and layer (CC) chickens lines were constructed and allowed identification of 3,074 unique sequences and 77 single nucleotide polymorphisms (SNPs). The collection of expressed sequence tags (ESTs) and SNPs identified in this study represents an important resource for future studies aimed at identifying genes responsible for growth in chicken.

Chicken Expressed Sequence Tags (ESTs) were analyzed to identify genes associated with myogenesis during embryonic development. A total of 6,184 ESTs were generated from three cDNA libraries constructed from whole embryos (Stage 26), somites associated with neural tube (Stage 15), and limb buds (Stages 21, 24 and 26). Clustering and assembly of 4,998 valid ESTs resulted in 2,329 unique sequences with 902 clusters (38.7%) and 1,427 singletons (61.3%). There are more than 400,000 chicken ESTs available at GenBank and we were able to identify 143 novel sequences. From these, 45 sequences found either a human EST homolog or a match with conserved regions among proteins. Most of these sequences were found to be expressed in somites, an important tissue for muscle development and not characterized before. This study revealed the value of micro dissected embryonic libraries for describing gene expression profiles associated with myogenesis and gene discovery.

Background Typical evolutionary events like recombination, hybridization or gene transfer make necessary the use of phylogenetic networks to properly depict the evolution of DNA and protein sequences. Although several theoretical classes have been proposed to characterize these networks, they make stringent assumptions that will likely not be met by the evolutionary process. We have recently shown that the complexity of simulated networks is a function of the population recombination rate, and that at moderate and large recombination rates the resulting networks cannot be categorized. However, we do not know whether these results extend to networks estimated from real data. Results We introduce a web server for the categorization of explicit phylogenetic networks, including the most relevant theoretical classes developed so far. Using this tool, we analyzed statistical parsimony phylogenetic networks estimated from ~5,000 DNA alignments, obtained from the NCBI PopSet and Polymorphix databases. The level of characterization was correlated to nucleotide diversity, and a high proportion of the networks derived from these data sets could be formally characterized. Conclusions We have developed a public web server, NetTest (freely available from the software section at http://darwin.uvigo.es), to formally characterize the complexity of phylogenetic networks. Using NetTest we found that most statistical parsimony networks estimated with the program TCS could be assigned to a known network class. The level of network characterization was correlated to nucleotide diversity and dependent upon the intra/interspecific levels, although no significant differences were detected among genes. More research on the properties of phylogenetic networks is clearly needed.

The Ensembl project has been aggregating, processing, integrating and redistributing genomic datasets since the initial releases of the draft human genome, with the aim of accelerating genomics research through rapid open distribution of public data. Large amounts of raw data are thus transformed into knowledge, which is made available via a multitude of channels, in particular our browser (http://www.ensembl.org). Over time, we have expanded in multiple directions. First, our resources describe multiple fields of genomics, in particular gene annotation, comparative genomics, genetics and epigenomics. Second, we cover a growing number of genome assemblies; Ensembl Release 90 contains exactly 100. Third, our databases feed simultaneously into an array of services designed around different use cases, ranging from quick browsing to genome-wide bioinformatic analysis. We present here the latest developments of the Ensembl project, with a focus on managing an increasing number of assemblies, supporting efforts in genome interpretation and improving our browser.