Quality assessment of gene repertoire annotations with OMArk.

In the era of biodiversity genomics, it is crucial to ensure that annotations of protein-coding gene repertoires are accurate. State-of-the-art tools to assess genome annotations measure the completeness of a gene repertoire but are blind to other errors, such as gene overprediction or contamination. We introduce OMArk, a software package that relies on fast, alignment-free sequence comparisons between a query proteome and precomputed gene families across the tree of life. OMArk assesses not only the completeness but also the consistency of the gene repertoire as a whole relative to closely related species and reports likely contamination events. Analysis of 1,805 UniProt Eukaryotic Reference Proteomes with OMArk demonstrated strong evidence of contamination in 73 proteomes and identified error propagation in avian gene annotation resulting from the use of a fragmented zebra finch proteome as a reference. This study illustrates the importance of comparing and prioritizing proteomes based on their quality measures.

OMA orthology in 2024: improved prokaryote coverage, ancestral and extant GO enrichment, a revamped synteny viewer and more in the OMA Ecosystem.

In this update paper, we present the latest developments in the OMA browser knowledgebase, which aims to provide high-quality orthology inferences and facilitate the study of gene families, genomes and their evolution. First, we discuss the addition of new species in the database, particularly an expanded representation of prokaryotic species. The OMA browser now offers Ancestral Genome pages and an Ancestral Gene Order viewer, allowing users to explore the evolutionary history and gene content of ancestral genomes. We also introduce a revamped Local Synteny Viewer to compare genomic neighborhoods across both extant and ancestral genomes. Hierarchical Orthologous Groups (HOGs) are now annotated with Gene Ontology annotations, and users can easily perform extant or ancestral GO enrichments. Finally, we recap new tools in the OMA Ecosystem, including OMAmer for proteome mapping, OMArk for proteome quality assessment, OMAMO for model organism selection and Read2Tree for phylogenetic species tree construction from reads. These new features provide exciting opportunities for orthology analysis and comparative genomics. OMA is accessible at https://omabrowser.org.

Bringing science to the public in the light of evolution.

Evolution stands as a foundational pillar within modern biology, shaping our understanding of life. Studies related to evolution, for example constructing phylogenetic trees, are often carried out using DNA or protein sequences. These data, readily accessible from public databases, represent a treasure trove of resources that can be harnessed to create engaging activities with the public. At the heart of our project lies a collection of "stories" about evolution, each rooted in genuine scientific publications that furnish both biological context and supporting evidence. These narratives serve as the focal point of our LightOfEvolution.org website. Each story is accompanied by a dedicated "Your Turn to Play" section. Within this section, we furnish user-friendly activities and step-by-step guidelines, equipping visitors with the means to replicate analyses showcased in the highlighted publications. For example, the website OhMyGenes.org, relying on authentic scientific data, provides the capability to compute the proportion of shared genes across different species. Here, visitors can address the captivating question: "How many genes do we share with a banana?" To extend the educational reach, we have developed a series of modular activities, also related to the stories. These activities have been thoughtfully designed to be adaptable for face-to-face workshops held in classrooms or presented during public events. We aim to create stories and activities that resonate with participants, offering a tangible and enjoyable experience. By providing opportunities that reflect real-world scientific practices, we seek to offer participants valuable insights into the current workings of scientists "in the light of evolution."

Protein length distribution is remarkably uniform across the tree of life.

BACKGROUND: In every living species, the function of a protein depends on its organization of structural domains, and the length of a protein is a direct reflection of this. Because every species evolved under different evolutionary pressures, the protein length distribution, much like other genomic features, is expected to vary across species but has so far been scarcely studied. RESULTS: Here we evaluate this diversity by comparing protein length distribution across 2326 species (1688 bacteria, 153 archaea, and 485 eukaryotes). We find that proteins tend to be on average slightly longer in eukaryotes than in bacteria or archaea, but that the variation of length distribution across species is low, especially compared to the variation of other genomic features (genome size, number of proteins, gene length, GC content, isoelectric points of proteins). Moreover, most cases of atypical protein length distribution appear to be due to artifactual gene annotation, suggesting the actual variation of protein length distribution across species is even smaller. CONCLUSIONS: These results open the way for developing a genome annotation quality metric based on protein length distribution to complement conventional quality measures. Overall, our findings show that protein length distribution between living species is more uniform than previously thought. Furthermore, we also provide evidence for a universal selection on protein length, yet its mechanism and fitness effect remain intriguing open questions.

Deep Divergence and Genomic Diversification of Gut Symbionts of Neotropical Stingless Bees.

Social bees harbor conserved gut microbiotas that may have been acquired in a common ancestor of social bees and subsequently codiversified with their hosts. However, most of this knowledge is based on studies on the gut microbiotas of honey bees and bumblebees. Much less is known about the gut microbiotas of the third and most diverse group of social bees, the stingless bees. Specifically, the absence of genomic data from their microbiotas presents an important knowledge gap in understanding the evolution and functional diversity of the social bee microbiota. Here, we combined community profiling with culturing and genome sequencing of gut bacteria from six neotropical stingless bee species from Brazil. Phylogenomic analyses show that most stingless bee gut isolates form deep-branching sister clades of core members of the honey bee and bumblebee gut microbiota with conserved functional capabilities, confirming the common ancestry and ecology of their microbiota. However, our bacterial phylogenies were not congruent with those of the host, indicating that the evolution of the social bee gut microbiota was not driven by strict codiversification but included host switches and independent symbiont gain and losses. Finally, as reported for the honey bee and bumblebee microbiotas, we found substantial genomic divergence among strains of stingless bee gut bacteria, suggesting adaptation to different host species and glycan niches. Our study offers first insights into the genomic diversity of the stingless bee microbiota and highlights the need for broader samplings to understand the evolution of the social bee gut microbiota. IMPORTANCE Stingless bees are the most diverse group of the corbiculate bees and represent important pollinator species throughout the tropics and subtropics. They harbor specialized microbial communities in their gut that are related to those found in honey bees and bumblebees and that are likely important for bee health. Few bacteria have been cultured from the gut of stingless bees, which has prevented characterization of their genomic diversity and functional potential. Here, we established cultures of major members of the gut microbiotas of six stingless bee species and sequenced their genomes. We found that most stingless bee isolates belong to novel bacterial species distantly related to those found in honey bees and bumblebees and encoding similar functional capabilities. Our study offers a new perspective on the evolution of the social bee gut microbiota and presents a basis for characterizing the symbiotic relationships between gut bacteria and stingless bees.

Protein S-acylation controls the subcellular localization and biological activity of PHYTOCHROME KINASE SUBSTRATE.

PHYTOCHROME KINASE SUBSTRATE (PKS) proteins are involved in light-modulated changes in growth orientation. They act downstream of phytochromes to control hypocotyl gravitropism in the light and act early in phototropin signaling. Despite their importance for plant development, little is known about their molecular mode of action, except that they belong to a protein complex comprising phototropins at the plasma membrane (PM). Identifying evolutionary conservation is one approach to revealing biologically important protein motifs. Here, we show that PKS sequences are restricted to seed plants and that these proteins share 6 motifs (A to F from the N to the C terminus). Motifs A and D are also present in BIG GRAIN, while the remaining 4 are specific to PKSs. We provide evidence that motif C is S-acylated on highly conserved cysteines, which mediates the association of PKS proteins with the PM. Motif C is also required for PKS4-mediated phototropism and light-regulated hypocotyl gravitropism. Finally, our data suggest that the mode of PKS4 association with the PM is important for its biological activity. Our work, therefore, identifies conserved cysteines contributing to PM association of PKS proteins and strongly suggests that this is their site of action to modulate environmentally regulated organ positioning.

DrosOMA: the Drosophila Orthologous Matrix browser.

Background: Comparative genomic analyses to delineate gene evolutionary histories inform the understanding of organismal biology by characterising gene and gene family origins, trajectories, and dynamics, as well as enabling the tracing of speciation, duplication, and loss events, and facilitating the transfer of gene functional information across species. Genomic data are available for an increasing number of species from the genus Drosophila, however, a dedicated resource exploiting these data to provide the research community with browsable results from genus-wide orthology delineation has been lacking. Methods: Using the OMA Orthologous Matrix orthology inference approach and browser deployment framework, we catalogued orthologues across a selected set of Drosophila species with high-quality annotated genomes. We developed and deployed a dedicated instance of the OMA browser to facilitate intuitive exploration, visualisation, and downloading of the genus-wide orthology delineation results. Results: DrosOMA - the Drosophila Orthologous Matrix browser, accessible from https://drosoma.dcsr.unil.ch/ - presents the results of orthology delineation for 36 drosophilids from across the genus and four outgroup dipterans. It enables querying and browsing of the orthology data through a feature-rich web interface, with gene-view, orthologous group-view, and genome-view pages, including comprehensive gene name and identifier cross-references together with available functional annotations and protein domain architectures, as well as tools to visualise local and global synteny conservation. Conclusions: The DrosOMA browser demonstrates the deployability of the OMA browser framework for building user-friendly orthology databases with dense sampling of a selected taxonomic group. It provides the Drosophila research community with a tailored resource of browsable results from genus-wide orthology delineation.

Homoeolog Inference Methods Requiring Bidirectional Best Hits or Synteny Miss Many Pairs.

Homoeologs are pairs of genes or chromosomes in the same species that originated by speciation and were brought back together in the same genome by allopolyploidization. Bioinformatic methods for accurate homoeology inference are crucial for studying the evolutionary consequences of polyploidization, and homoeology is typically inferred on the basis of bidirectional best hit (BBH) and/or positional conservation (synteny). However, these methods neglect the fact that genes can duplicate and move, both prior to and after the allopolyploidization event. These duplications and movements can result in many-to-many and/or nonsyntenic homoeologs-which thus remain undetected and unstudied. Here, using the allotetraploid upland cotton (Gossypium hirsutum) as a case study, we show that conventional approaches indeed miss a substantial proportion of homoeologs. Additionally, we found that many of the missed pairs of homoeologs are broadly and highly expressed. A gene ontology analysis revealed a high proportion of the nonsyntenic and non-BBH homoeologs to be involved in protein translation and are likely to contribute to the functional repertoire of cotton. Thus, from an evolutionary and functional genomics standpoint, choosing a homoeolog inference method which does not solely rely on 1:1 relationship cardinality or synteny is crucial for not missing these potentially important homoeolog pairs.

Ten Years of Collaborative Progress in the Quest for Orthologs.

Accurate determination of the evolutionary relationships between genes is a foundational challenge in biology. Homology-evolutionary relatedness-is in many cases readily determined based on sequence similarity analysis. By contrast, whether or not two genes directly descended from a common ancestor by a speciation event (orthologs) or duplication event (paralogs) is more challenging, yet provides critical information on the history of a gene. Since 2009, this task has been the focus of the Quest for Orthologs (QFO) Consortium. The sixth QFO meeting took place in Okazaki, Japan in conjunction with the 67th National Institute for Basic Biology conference. Here, we report recent advances, applications, and oncoming challenges that were discussed during the conference. Steady progress has been made toward standardization and scalability of new and existing tools. A feature of the conference was the presentation of a panel of accessible tools for phylogenetic profiling and several developments to bring orthology beyond the gene unit-from domains to networks. This meeting brought into light several challenges to come: leveraging orthology computations to get the most of the incoming avalanche of genomic data, integrating orthology from domain to biological network levels, building better gene models, and adapting orthology approaches to the broad evolutionary and genomic diversity recognized in different forms of life and viruses.

Gene Duplication and Gain in the Trematode Atriophallophorus winterbourni Contributes to Adaptation to Parasitism.

Gene duplications and novel genes have been shown to play a major role in helminth adaptation to a parasitic lifestyle because they provide the novelty necessary for adaptation to a changing environment, such as living in multiple hosts. Here we present the de novo sequenced and annotated genome of the parasitic trematode Atriophallophorus winterbourni and its comparative genomic analysis to other major parasitic trematodes. First, we reconstructed the species phylogeny, and dated the split of A. winterbourni from the Opisthorchiata suborder to approximately 237.4 Ma (±120.4 Myr). We then addressed the question of which expanded gene families and gained genes are potentially involved in adaptation to parasitism. To do this, we used hierarchical orthologous groups to reconstruct three ancestral genomes on the phylogeny leading to A. winterbourni and performed a GO (Gene Ontology) enrichment analysis of the gene composition of each ancestral genome, allowing us to characterize the subsequent genomic changes. Out of the 11,499 genes in the A. winterbourni genome, as much as 24% have arisen through duplication events since the speciation of A. winterbourni from the Opisthorchiata, and as much as 31.9% appear to be novel, that is, newly acquired. We found 13 gene families in A. winterbourni to have had more than ten genes arising through these recent duplications; all of which have functions potentially relating to host behavioral manipulation, host tissue penetration, and hiding from host immunity through antigen presentation. We identified several families with genes evolving under positive selection. Our results provide a valuable resource for future studies on the genomic basis of adaptation to parasitism and point to specific candidate genes putatively involved in antagonistic host-parasite adaptation.

OMA orthology in 2021: website overhaul, conserved isoforms, ancestral gene order and more.

OMA is an established resource to elucidate evolutionary relationships among genes from currently 2326 genomes covering all domains of life. OMA provides pairwise and groupwise orthologs, functional annotations, local and global gene order conservation (synteny) information, among many other functions. This update paper describes the reorganisation of the database into gene-, group- and genome-centric pages. Other new and improved features are detailed, such as reporting of the evolutionarily best conserved isoforms of alternatively spliced genes, the inferred local order of ancestral genes, phylogenetic profiling, better cross-references, fast genome mapping, semantic data sharing via RDF, as well as a special coronavirus OMA with 119 viruses from the Nidovirales order, including SARS-CoV-2, the agent of the COVID-19 pandemic. We conclude with improvements to the documentation of the resource through primers, tutorials and short videos. OMA is accessible at https://omabrowser.org.

Making the most of genomic data with OMA.

The OMA Collection is a resource for users of Orthologous Matrix. In this collection, we provide tutorials and protocols on how to leverage the tools provided by OMA to analyse your data. Here, I explain the motivation for this collection and its published works thus far.

Genetic interactions regulating seed phytate and oligosaccharides in soybean (Glycine max L.).

Two low-phytate soybean (Glycine max (L.) Merr.) mutant lines- V99-5089 (mips mutation on chromosome 11) and CX-1834 (mrp-l and mrp-n mutations on chromosomes 19 and 3, respectively) have proven to be valuable resources for breeding of low-phytate, high-sucrose, and low-raffinosaccharide soybeans, traits that are highly desirable from a nutritional and environmental standpoint. A recombinant inbred population derived from the cross CX1834 x V99-5089 provides an opportunity to study the effect of different combinations of these three mutations on soybean phytate and oligosaccharides levels. Of the 173 recombinant inbred lines tested, 163 lines were homozygous for various combinations of MIPS and two MRP loci alleles. These individuals were grouped into eight genotypic classes based on the combination of SNP alleles at the three mutant loci. The two genotypic classes that were homozygous mrp-l/mrp-n and either homozygous wild-type or mutant at the mips locus (MIPS/mrp-l/mrp-n or mips/mrp-l/mrp-n) displayed relatively similar ~55% reductions in seed phytate, 6.94 mg g -1 and 6.70 mg g-1 respectively, as compared with 15.2 mg g-1 in the wild-type MIPS/MRP-L/MRP-N seed. Therefore, in the presence of the double mutant mrp-l/mrp-n, the mips mutation did not cause a substantially greater decrease in seed phytate level. However, the nutritionally-desirable high-sucrose/low-stachyose/low-raffinose seed phenotype originally observed in soybeans homozygous for the mips allele was reversed in the presence of mrp-l/mrp-n mutations: homozygous mips/mrp-l/mrp-n seed displayed low-sucrose (7.70%), high-stachyose (4.18%), and the highest observed raffinose (0.94%) contents per gram of dry seed. Perhaps the block in phytic acid transport from its cytoplasmic synthesis site to its storage site, conditioned by mrp-l/mrp-n, alters myo-inositol flux in mips seeds in a way that restores to wild-type levels the mips conditioned reductions in raffinosaccharides. Overall this study determined the combinatorial effects of three low phytic acid causing mutations on regulation of seed phytate and oligosaccharides in soybean.

The Quest for Orthologs benchmark service and consensus calls in 2020.

The identification of orthologs-genes in different species which descended from the same gene in their last common ancestor-is a prerequisite for many analyses in comparative genomics and molecular evolution. Numerous algorithms and resources have been conceived to address this problem, but benchmarking and interpreting them is fraught with difficulties (need to compare them on a common input dataset, absence of ground truth, computational cost of calling orthologs). To address this, the Quest for Orthologs consortium maintains a reference set of proteomes and provides a web server for continuous orthology benchmarking (http://orthology.benchmarkservice.org). Furthermore, consensus ortholog calls derived from public benchmark submissions are provided on the Alliance of Genome Resources website, the joint portal of NIH-funded model organism databases.

Identifying orthologs with OMA: A primer.

The Orthologous Matrix (OMA) is a method and database that allows users to identify orthologs among many genomes. OMA provides three different types of orthologs: pairwise orthologs, OMA Groups and Hierarchical Orthologous Groups (HOGs). This Primer is organized in two parts. In the first part, we provide all the necessary background information to understand the concepts of orthology, how we infer them and the different subtypes of orthology in OMA, as well as what types of analyses they should be used for. In the second part, we describe protocols for using the OMA browser to find a specific gene and its various types of orthologs. By the end of the Primer, readers should be able to (i) understand homology and the different types of orthologs reported in OMA, (ii) understand the best type of orthologs to use for a particular analysis; (iii) find particular genes of interest in the OMA browser; and (iv) identify orthologs for a given gene.  The data can be freely accessed from the OMA browser at https://omabrowser.org.

How to build phylogenetic species trees with OMA.

Knowledge of species phylogeny is critical to many fields of biology. In an era of genome data availability, the most common way to make a phylogenetic species tree is by using multiple protein-coding genes, conserved in multiple species. This methodology is composed of several steps: orthology inference, multiple sequence alignment and inference of the phylogeny with dedicated tools. This can be a difficult task, and orthology inference, in particular, is usually computationally intensive and error prone if done ad hoc. This tutorial provides protocols to make use of OMA Orthologous Groups, a set of genes all orthologous to each other, to infer a phylogenetic species tree. It is designed to be user-friendly and computationally inexpensive, by providing two options: (1) Using only precomputed groups with species available on the OMA Browser, or (2) Computing orthologs using OMA Standalone for additional species, with the option of using precomputed orthology relations for those present in OMA. A protocol for downstream analyses is provided as well, including creating a supermatrix, tree inference, and visualization. All protocols use publicly available software, and we provide scripts and code snippets to facilitate data handling. The protocols are accompanied with practical examples.

Inferring Orthology and Paralogy.

The distinction between orthologs and paralogs, genes that started diverging by speciation versus duplication, is relevant in a wide range of contexts, most notably phylogenetic tree inference and protein function annotation. In this chapter, we provide an overview of the methods used to infer orthology and paralogy. We survey both graph-based approaches (and their various grouping strategies) and tree-based approaches, which solve the more general problem of gene/species tree reconciliation. We discuss conceptual differences among the various orthology inference methods and databases and examine the difficult issue of verifying and benchmarking orthology predictions. Finally, we review typical applications of orthologous genes, groups, and reconciled trees and conclude with thoughts on future methodological developments.

Advances and Applications in the Quest for Orthologs.

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.

OMA standalone: orthology inference among public and custom genomes and transcriptomes.

Genomes and transcriptomes are now typically sequenced by individual laboratories but analyzing them often remains challenging. One essential step in many analyses lies in identifying orthologs-corresponding genes across multiple species-but this is far from trivial. The Orthologous MAtrix (OMA) database is a leading resource for identifying orthologs among publicly available, complete genomes. Here, we describe the OMA pipeline available as a standalone program for Linux and Mac. When run on a cluster, it has native support for the LSF, SGE, PBS Pro, and Slurm job schedulers and can scale up to thousands of parallel processes. Another key feature of OMA standalone is that users can combine their own data with existing public data by exporting genomes and precomputed alignments from the OMA database, which currently contains over 2100 complete genomes. We compare OMA standalone to other methods in the context of phylogenetic tree inference, by inferring a phylogeny of Lophotrochozoa, a challenging clade within the protostomes. We also discuss other potential applications of OMA standalone, including identifying gene families having undergone duplications/losses in specific clades, and identifying potential drug targets in nonmodel organisms. OMA standalone is available under the permissive open source Mozilla Public License Version 2.0.

Genomic changes underlying host specialization in the bee gut symbiont Lactobacillus Firm5.

Bacteria that engage in long-standing associations with particular hosts are expected to evolve host-specific adaptations that limit their capacity to thrive in other environments. Consistent with this, many gut symbionts seem to have a limited host range, based on community profiling and phylogenomics. However, few studies have experimentally investigated host specialization of gut symbionts and the underlying mechanisms have largely remained elusive. Here, we studied host specialization of a dominant gut symbiont of social bees, Lactobacillus Firm5. We show that Firm5 strains isolated from honey bees and bumble bees separate into deep-branching host-specific phylogenetic lineages. Despite their divergent evolution, colonization experiments show that bumble bee strains are capable of colonizing the honey bee gut. However, they were less successful than honey bee strains, and competition with honey bee strains completely abolished their colonization. In contrast, honey bee strains of divergent phylogenetic lineages were able to coexist within individual bees. This suggests that both host selection and interbacterial competition play important roles in host specialization. Using comparative genomics of 27 Firm5 isolates, we found that the genomes of honey bee strains harbour more carbohydrate-related functions than bumble bee strains, possibly providing a competitive advantage in the honey bee gut. Remarkably, most of the genes encoding carbohydrate-related functions were not conserved among the honey bee strains, which suggests that honey bees can support a metabolically more diverse community of Firm5 strains than bumble bees. These findings advance our understanding of the genomic changes underlying host specialization.