The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements

Comparative structural and functional analysis of the glycine-rich regions of Class A and B J-domain protein cochaperones of Hsp70

J-domain proteins are critical Hsp70 co-chaperones. A and B types have a poorly understood glycine-rich region (Grich) adjacent to their N-terminal J-domain (Jdom). We analyzed the ability of Jdom/Grich segments of yeast Class B Sis1 and a suppressor variant of Class A, Ydj1, to rescue the inviability of sis1-∆. In each, we identified a cluster of Grich residues required for rescue. Both contain conserved hydrophobic and acidic residues and are predicted to form helices. While, as expected, the Sis1 segment docks on its J-domain, that of Ydj1 does not. However, data suggest both interact with Hsp70. We speculate that the Grich-Hsp70 interaction of Classes A and B J-domain proteins can fine tune the activity of Hsp70, thus being particularly important for the function of Class B.

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.

Inference of phylogenetic trees directly from raw sequencing reads using Read2Tree

Current methods for inference of phylogenetic trees require running complex pipelines at substantial computational and labor costs, with additional constraints in sequencing coverage, assembly and annotation quality, especially for large datasets. To overcome these challenges, we present Read2Tree, which directly processes raw sequencing reads into groups of corresponding genes and bypasses traditional steps in phylogeny inference, such as genome assembly, annotation and all-versus-all sequence comparisons, while retaining accuracy. In a benchmark encompassing a broad variety of datasets, Read2Tree is 10-100 times faster than assembly-based approaches and in most cases more accurate-the exception being when sequencing coverage is high and reference species very distant. Here, to illustrate the broad applicability of the tool, we reconstruct a yeast tree of life of 435 species spanning 590 million years of evolution. We also apply Read2Tree to >10,000 Coronaviridae samples, accurately classifying highly diverse animal samples and near-identical severe acute respiratory syndrome coronavirus 2 sequences on a single tree. The speed, accuracy and versatility of Read2Tree enable comparative genomics at scale.

Chromosome-level genome assembly of Babesia caballi reveals diversity of multigene families among Babesia species

BACKGROUND

Babesia caballi is an intraerythrocytic parasite from the phylum Apicomplexa, capable of infecting equids and causing equine piroplasmosis. However, since there is limited genome information available on B. caballi, molecular mechanisms involved in host specificity and pathogenicity of this species have not been fully elucidated yet.

RESULTS

Genomic DNA from a B. caballi subclone was purified and sequenced using both Illumina and Nanopore technologies. The resulting assembled sequence consisted of nine contigs with a size of 12.9 Mbp, rendering a total of 5,910 protein-coding genes. The phylogenetic tree of Apicomplexan species was reconstructed using 263 orthologous genes. We identified 481 ves1-like genes and named "ves1c". In contrast, expansion of the major facilitator superfamily (mfs) observed in closely related B. bigemina and B. ovata species was not found in B. caballi. A set of repetitive units containing an open reading frame with a size of 297 bp was also identified.

CONCLUSIONS

We present a chromosome-level genome assembly of B. caballi. Our genomic data may contribute to estimating gene expansion events involving multigene families and exploring the evolution of species from this genus.

Whole genome sequence and diversity in multigene families of Babesia ovis

Ovine babesiosis, caused by Babesia ovis, is an acute, lethal, and endemic disease worldwide and causes a huge economic loss to animal industry. Pathogen genome sequences can be utilized for selecting diagnostic markers, drug targets, and antigens for vaccine development; however, those for B. ovis have not been available so far. In this study, we obtained a draft genome sequence for B. ovis isolated from an infected sheep in Turkey. The genome size was 7.81 Mbp with 3,419 protein-coding genes. It consisted of 41 contigs, and the N50 was 526 Kbp. There were 259 orthologs identified among eight Babesia spp., Plasmodium falciparum, and Toxoplasma gondii. A phylogeny was estimated on the basis of the orthologs, which showed B. ovis to be closest to B. bovis. There were 43 ves genes identified using hmm model as well. They formed a discriminating cluster to other ves multigene family of Babesia spp. but showed certain similarities to those of B. bovis, B. caballi, and Babesia sp. Xinjiang, which is consistent with the phylogeny. Comparative genomics among B. ovis and B. bovis elucidated uniquely evolved genes in these species, which may account for the adaptation.

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.

Sizing Up the Onychophoran Genome: Repeats, Introns, and Gene Family Expansion Contribute to Genome Gigantism in Epiperipatus broadwayi

Genome assemblies are growing at an exponential rate and have proved indispensable for studying evolution but the effort has been biased toward vertebrates and arthropods with a particular focus on insects. Onychophora or velvet worms are an ancient group of cryptic, soil dwelling worms noted for their unique mode of prey capture, biogeographic patterns, and diversity of reproductive strategies. They constitute a poorly understood phylum of exclusively terrestrial animals that is sister group to arthropods. Due to this phylogenetic position, they are crucial in understanding the origin of the largest phylum of animals. Despite their significance, there is a paucity of genomic resources for the phylum with only one highly fragmented and incomplete genome publicly available. Initial attempts at sequencing an onychophoran genome proved difficult due to its large genome size and high repeat content. However, leveraging recent advances in long-read sequencing technology, we present here the first annotated draft genome for the phylum. With a total size of 5.6Gb, the gigantism of the Epiperipatus broadwayi genome arises from having high repeat content, intron size inflation, and extensive gene family expansion. Additionally, we report a previously unknown diversity of onychophoran hemocyanins that suggests the diversification of copper-mediated oxygen carriers occurred independently in Onychophora after its split from Arthropoda, parallel to the independent diversification of hemocyanins in each of the main arthropod lineages.

Heritability and gene functions associated with sclerotia formation of Rhizoctonia solani AG-7 using whole genome sequencing and genome-wide association study

Sclerotia are specialized fungal structures formed by pigmented and aggregated hyphae, which can survive under unfavourable environmental conditions and serve as the primary inocula for several phytopathogenic fungi including Rhizoctonia solani. Among 154 R. solani anastomosis group 7 (AG-7) isolates collected in fields, the sclerotia-forming capability regarding sclerotia number and sclerotia size varied in the fungal population, but the genetic makeup of these phenotypes remained unclear. As limited studies have focused on the genomics of R. solani AG-7 and the population genetics of sclerotia formation, this study completed the whole genome sequencing and gene prediction of R. solani AG-7 using the Oxford NanoPore and Illumina RNA sequencing. Meanwhile, a high-throughput image-based method was established to quantify the sclerotia-forming capability, and the phenotypic correlation between sclerotia number and sclerotia size was low. A genome-wide association study identified three and five significant SNPs associated with sclerotia number and size in distinct genomic regions, respectively. Of these significant SNPs, two and four showed significant differences in the phenotypic mean separation for sclerotia number and sclerotia size, respectively. Gene ontology enrichment analysis focusing on the linkage disequilibrium blocks of significant SNPs identified more categories related to oxidative stress for sclerotia number, and more categories related to cell development, signalling and metabolism for sclerotia size. These results indicated that different genetic mechanisms may underlie these two phenotypes. Moreover, the heritability of sclerotia number and sclerotia size were estimated for the first time to be 0.92 and 0.31, respectively. This study provides new insights into the heritability and gene functions related to the development of sclerotia number and sclerotia size, which could provide additional knowledge to reduce fungal residues in fields and achieve sustainable disease management.

Analysis of Pneumocystis Transcription Factor Evolution and Implications for Biology and Lifestyle

Pneumocystis jirovecii kills hundreds of thousands of immunocompromised patients each year. Yet many aspects of the biology of this obligate pathogen remain obscure because it is not possible to culture the fungus in vitro independently of its host. Consequently, our understanding of Pneumocystis pathobiology is heavily reliant upon bioinformatic inferences. We have exploited a powerful combination of genomic and phylogenetic approaches to examine the evolution of transcription factors in Pneumocystis species. We selected protein families (Pfam families) that correspond to transcriptional regulators and used bioinformatic approaches to compare these families in the seven Pneumocystis species that have been sequenced to date with those from other yeasts, other human and plant pathogens, and other obligate parasites. Some Pfam families of transcription factors have undergone significant reduction during their evolution in the Pneumocystis genus, and other Pfam families have been lost or appear to be in the process of being lost. Meanwhile, other transcription factor families have been retained in Pneumocystis species, and some even appear to have undergone expansion. On this basis, Pneumocystis species seem to have retained transcriptional regulators that control chromosome maintenance, ribosomal gene regulation, RNA processing and modification, and respiration. Meanwhile, regulators that promote the assimilation of alternative carbon sources, amino acid, lipid, and sterol biosynthesis, and iron sensing and homeostasis appear to have been lost. Our analyses of transcription factor retention, loss, and gain provide important insights into the biology and lifestyle of Pneumocystis. IMPORTANCE Pneumocystis jirovecii is a major fungal pathogen of humans that infects healthy individuals, colonizing the lungs of infants. In immunocompromised and transplant patients, this fungus causes life-threatening pneumonia, and these Pneumocystis infections remain among the most common and serious infections in HIV/AIDS patients. Yet we remain remarkably ignorant about the biology and epidemiology of Pneumocystis due to the inability to culture this fungus in vitro. Our analyses of transcription factor retentions, losses, and gains in sequenced Pneumocystis species provide valuable new views of their specialized biology, suggesting the retention of many metabolic and stress regulators and the loss of others that are essential in free-living fungi. Given the lack of in vitro culture methods for Pneumocystis, this powerful bioinformatic approach has advanced our understanding of the lifestyle of P. jirovecii and the nature of its dependence on the host for survival.

Plant-Pathogenic Ralstonia Phylotypes Evolved Divergent Respiratory Strategies and Behaviors To Thrive in Xylem

Bacterial pathogens in the Ralstonia solanacearum species complex (RSSC) infect the water-transporting xylem vessels of plants, causing bacterial wilt disease. Strains in RSSC phylotypes I and III can reduce nitrate to dinitrogen via complete denitrification. The four-step denitrification pathway enables bacteria to use inorganic nitrogen species as terminal electron acceptors, supporting their growth in oxygen-limited environments such as biofilms or plant xylem. Reduction of nitrate, nitrite, and nitric oxide all contribute to the virulence of a model phylotype I strain. However, little is known about the physiological role of the last denitrification step, the reduction of nitrous oxide to dinitrogen by NosZ. We found that phylotypes I and III need NosZ for full virulence. However, strains in phylotypes II and IV are highly virulent despite lacking NosZ. The ability to respire by reducing nitrate to nitrous oxide does not greatly enhance the growth of phylotype II and IV strains. These partial denitrifying strains reach high cell densities during plant infection and cause typical wilt disease. However, unlike phylotype I and III strains, partial denitrifiers cannot grow well under anaerobic conditions or form thick biofilms in culture or in tomato xylem vessels. Furthermore, aerotaxis assays show that strains from different phylotypes have different oxygen and nitrate preferences. Together, these results indicate that the RSSC contains two subgroups that occupy the same habitat but have evolved divergent energy metabolism strategies to exploit distinct metabolic niches in the xylem. IMPORTANCE Plant-pathogenic Ralstonia spp. are a heterogeneous globally distributed group of bacteria that colonize plant xylem vessels. Ralstonia cells multiply rapidly in plants and obstruct water transport, causing fatal wilting and serious economic losses of many key food security crops. The virulence of these pathogens depends on their ability to grow to high cell densities in the low-oxygen xylem environment. Plant-pathogenic Ralstonia can use denitrifying respiration to generate ATP. The last denitrification step, nitrous oxide reduction by NosZ, contributes to energy production and virulence for only one of the three phytopathogenic Ralstonia species. These complete denitrifiers form thicker biofilms in culture and in tomato xylem, suggesting they are better adapted to hypoxic niches. Strains with partial denitrification physiology form less biofilm and are more often planktonic. They are nonetheless highly virulent. Thus, these closely related bacteria have adapted their core metabolic functions to exploit distinct microniches in the same habitat.

Mutant structure of metabolic switch protein in complex with monomeric c-di-GMP reveals a potential mechanism of protein-mediated ligand dimerization

Bacterial second messengers c-di-GMP and (p)ppGpp have broad functional repertoires ranging from growth and cell cycle control to the regulation of biofilm formation and virulence. The recent identification of SmbA, an effector protein from Caulobacter crescentus that is jointly targeted by both signaling molecules, has opened up studies on how these global bacterial networks interact. C-di-GMP and (p)ppGpp compete for the same SmbA binding site, with a dimer of c-di-GMP inducing a conformational change that involves loop 7 of the protein that leads to downstream signaling. Here, we report a crystal structure of a partial loop 7 deletion mutant, SmbA_∆loop in complex with c-di-GMP determined at 1.4 Å resolution. SmbA_∆loop binds monomeric c-di-GMP indicating that loop 7 is required for c-di-GMP dimerization. Thus the complex probably represents the first step of consecutive c-di-GMP binding to form an intercalated dimer as has been observed in wild-type SmbA. Considering the prevalence of intercalated c-di-GMP molecules observed bound to proteins, the proposed mechanism may be generally applicable to protein-mediated c-di-GMP dimerization. Notably, in the crystal, SmbA_∆loop forms a 2-fold symmetric dimer via isologous interactions with the two symmetric halves of c-di-GMP. Structural comparisons of SmbA_∆loop with wild-type SmbA in complex with dimeric c-di-GMP or ppGpp support the idea that loop 7 is critical for SmbA function by interacting with downstream partners. Our results also underscore the flexibility of c-di-GMP, to allow binding to the symmetric SmbA_∆loop dimer interface. It is envisaged that such isologous interactions of c-di-GMP could be observed in hitherto unrecognized targets.

Defining the extent of gene function using ROC curvature

MOTIVATION

Interactions between proteins help us understand how genes are functionally related and how they contribute to phenotypes. Experiments provide imperfect 'ground truth' information about a small subset of potential interactions in a specific biological context, which can then be extended to the whole genome across different contexts, such as conditions, tissues or species, through machine learning methods. However, evaluating the performance of these methods remains a critical challenge. Here, we propose to evaluate the generalizability of gene characterizations through the shape of performance curves.

RESULTS

We identify Functional Equivalence Classes (FECs), subsets of annotated and unannotated genes that jointly drive performance, by assessing the presence of straight lines in ROC curves built from gene-centric prediction tasks, such as function or interaction predictions. FECs are widespread across data types and methods, they can be used to evaluate the extent and context-specificity of functional annotations in a data-driven manner. For example, FECs suggest that B cell markers can be decomposed into shared primary markers (10-50 genes), and tissue-specific secondary markers (100-500 genes). In addition, FECs suggest the existence of functional modules that span a wide range of the genome, with marker sets spanning at most 5% of the genome and data-driven extensions of Gene Ontology sets spanning up to 40% of the genome. Simple to assess visually and statistically, the identification of FECs in performance curves paves the way for novel functional characterization and increased robustness in the definition of functional gene sets.

AVAILABILITY AND IMPLEMENTATION

Code for analyses and figures is available at https://github.com/yexilein/pyroc.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Read2Tree: scalable and accurate phylogenetic trees from raw reads

The inference of phylogenetic trees is foundational to biology. However, state-of-the-art phylogenomics requires running complex pipelines, at significant computational and labour costs, with additional constraints in sequencing coverage, assembly and annotation quality. To overcome these challenges, we present Read2Tree, which directly processes raw sequencing reads into groups of corresponding genes. In a benchmark encompassing a broad variety of datasets, our assembly-free approach was 10-100x faster than conventional approaches, and in most cases more accurate-the exception being when sequencing coverage was high and reference species very distant. To illustrate the broad applicability of the tool, we reconstructed a yeast tree of life of 435 species spanning 590 million years of evolution. Applied to Coronaviridae samples, Read2Tree accurately classified highly diverse animal samples and near-identical SARS-CoV-2 sequences on a single tree-thereby exhibiting remarkable breadth and depth. The speed, accuracy, and versatility of Read2Tree enables comparative genomics at scale.

ConVarT: Search Engine for Missense Variants Between Humans and Other Organisms

ConVarT (https://convart.org/) is a search engine for searching for conjugate variants between humans and other species. The search engine is based on matching conjugate variants called MatchVars between species. Matching equivalent variants requires correct alignment of orthologous proteins with the use of multiple sequence alignments (MSA). Indeed, the ConVarT pipeline has performed over a million MSAs and integrated variants and variant-specific annotations (pathogenicity, phenotypic variants; etc.) into the corresponding positions on MSAs. When a clinically relevant variant is discovered whose functional relevance is unknown, ConVarT offers clinician scientists the possibility to search for a MatchVar in other species and to look for functional data on that variant. Fortunately, ConVarT enables users to paste a protein sequence in FASTA format to search for human orthologous proteins. A pairwise sequence alignment (PSA) is then performed between the provided protein sequence and the human orthologous protein, allowing users to visualize human variants on the PSA. Here, we describe the step-by-step usage of ConVarT. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Searching matching variants (MatchVar) with gene/protein identifiers. Basic Protocol 2: Searching with a FASTA sequence. Alternate Protocol: Search with gene name in multiple species. Basic Protocol 3: Search genes associated with a disease.

Genome-Wide Classification and Phylogenetic Analyses of the GDSL-Type Esterase/Lipase (GELP) Family in Flowering Plants

GDSL-type esterase/lipase (GELP) enzymes have key functions in plants, such as developmental processes, anther and pollen development, and responses to biotic and abiotic stresses. Genes that encode GELP belong to a complex and large gene family, ranging from tens to more than hundreds of members per plant species. To facilitate functional transfer between them, we conducted a genome-wide classification of GELP in 46 plant species. First, we applied an iterative phylogenetic method using a selected set of representative angiosperm genomes (three monocots and five dicots) and identified 10 main clusters, subdivided into 44 orthogroups (OGs). An expert curation for gene structures, orthogroup composition, and functional annotation was made based on a literature review. Then, using the HMM profiles as seeds, we expanded the classification to 46 plant species. Our results revealed the variable evolutionary dynamics between OGs in which some expanded, mostly through tandem duplications, while others were maintained as single copies. Among these, dicot-specific clusters and specific amplifications in monocots and wheat were characterized. This approach, by combining manual curation and automatic identification, was effective in characterizing a large gene family, allowing the establishment of a classification framework for gene function transfer and a better understanding of the evolutionary history of GELP.

Local Adaptation and the Evolution of Genome Architecture in Threespine Stickleback

Theory predicts that local adaptation should favor the evolution of a concentrated genetic architecture, where the alleles driving adaptive divergence are tightly clustered on chromosomes. Adaptation to marine versus freshwater environments in threespine stickleback has resulted in an architecture that seems consistent with this prediction: divergence among populations is mainly driven by a few genomic regions harboring multiple quantitative trait loci for environmentally adapted traits, as well as candidate genes with well-established phenotypic effects. One theory for the evolution of these "genomic islands" is that rearrangements remodel the genome to bring causal loci into tight proximity, but this has not been studied explicitly. We tested this theory using synteny analysis to identify micro- and macro-rearrangements in the stickleback genome and assess their potential involvement in the evolution of genomic islands. To identify rearrangements, we conducted a de novo assembly of the closely related tubesnout (Aulorhyncus flavidus) genome and compared this to the genomes of threespine stickleback and two other closely related species. We found that small rearrangements, within-chromosome duplications, and lineage-specific genes (LSGs) were enriched around genomic islands, and that all three chromosomes harboring large genomic islands have experienced macro-rearrangements. We also found that duplicates and micro-rearrangements are 9.9× and 2.9× more likely to involve genes differentially expressed between marine and freshwater genotypes. While not conclusive, these results are consistent with the explanation that strong divergent selection on candidate genes drove the recruitment of rearrangements to yield clusters of locally adaptive loci.

Superoxide Initiates the Hyphal Differentiation to Microsclerotia Formation of Macrophomina phaseolina

The infection of Macrophomina phaseolina often results in a grayish appearance with numerous survival structures, microsclerotia, on the plant surface. Past works have studied the development of fungal survival structures, sclerotia and microsclerotia, in the Leotiomycetes and Sordariomycetes. However, M. phaseolina belongs to the Dothideomycetes, and it remains unclear whether the mechanism of microsclerotia formation remains conserved among these phylogenetic clades. This study applied RNA-sequencing (RNA-Seq) to profile gene expressions at four stages of microsclerotia formation, and the results suggested that reactive oxygen species (ROS)-related functions were significantly different between the microsclerotia stages and the hyphal stage. Microsclerotia formation was reduced in the plates amended with antioxidants such as ascorbic acid, dithiothreitol (DTT), and glutathione. Surprisingly, DTT drastically scavenged H₂O₂, but the microsclerotia amount remained similar to the treatment of ascorbic acid and glutathione that both did not completely eliminate H₂O₂. This observation suggested the importance of O2− over H₂O₂ in initiating microsclerotia formation. To further validate this hypothesis, the superoxide dismutase 1 (SOD1) inhibitor diethyldithiocarbamate trihydrate (DETC) and H₂O₂ were tested. The addition of DETC resulted in the accumulation of endogenous O2− and more microsclerotia formation, but the treatment of H₂O₂ did not. The expression of SOD1 genes were also found to be upregulated in the hyphae to the microsclerotia stage, which suggested a higher endogenous O2− stress presented in these stages. In summary, this study not only showed that the ROS stimulation remained conserved for initiating microsclerotia formation of M. phaseolina but also highlighted the importance of O2− in initiating the hyphal differentiation to microsclerotia formation.

IMPORTANCE Reactive oxygen species (ROS) have been proposed as the key stimulus for sclerotia development by studying fungal systems such as Sclerotinia sclerotiorum, and the theory has been adapted for microsclerotia development in Verticillium dahliae and Nomuraea rileyi. While many studies agreed on the association between (micro)sclerotia development and the ROS pathway, which ROS type, superoxide (O2−) or hydrogen peroxide (H₂O₂), plays a major role in initiating hyphal differentiation to the (micro)sclerotia formation remains controversial, and literature supporting either O2− or H₂O₂ can be found. This study confirmed the association between ROS and microsclerotia formation for the charcoal rot fungus Macrophomina phaseolina. Moreover, the accumulation of O2− but not H₂O₂ was found to induce higher density of microsclerotia. By integrating transcriptomic and phenotypic assays, this study presented the first conclusive case for M. phaseolina that O2− is the main ROS stimulus in determining the amount of microsclerotia formation.

ConVarT: a search engine for matching human genetic variants with variants from non-human species

The availability of genetic variants, together with phenotypic annotations from model organisms, facilitates comparing these variants with equivalent variants in humans. However, existing databases and search tools do not make it easy to scan for equivalent variants, namely 'matching variants' (MatchVars) between humans and other organisms. Therefore, we developed an integrated search engine called ConVarT (http://www.convart.org/) for matching variants between humans, mice, and Caenorhabditis elegans. ConVarT incorporates annotations (including phenotypic and pathogenic) into variants, and these previously unexploited phenotypic MatchVars from mice and C. elegans can give clues about the functional consequence of human genetic variants. Our analysis shows that many phenotypic variants in different genes from mice and C. elegans, so far, have no counterparts in humans, and thus, can be useful resources when evaluating a relationship between a new human mutation and a disease.

Colorful orthology clustering in bounded-degree similarity graphs

Clustering genes in similarity graphs is a popular approach for orthology prediction. Most algorithms group genes without considering their species, which results in clusters that contain several paralogous genes. Moreover, clustering is known to be problematic when in-paralogs arise from ancient duplications. Recently, we proposed a two-step process that avoids these problems. First, we infer clusters of only orthologs (i.e. with only genes from distinct species), and second, we infer the missing inter-cluster orthologs. In this paper, we focus on the first step, which leads to a problem we call Colorful Clustering. In general, this is as hard as classical clustering. However, in similarity graphs, the number of species is usually small, as well as the neighborhood size of genes in other species. We therefore study the problem of clustering in which the number of colors is bounded by [Formula: see text], and each gene has at most [Formula: see text] neighbors in another species. We show that the well-known cluster editing formulation remains NP-hard even when [Formula: see text] and [Formula: see text]. We then propose a fixed-parameter algorithm in [Formula: see text] to find the single best cluster in the graph. We implemented this algorithm and included it in the aforementioned two-step approach. Experiments on simulated data show that this approach performs favorably to applying only an unconstrained clustering step.

Taxallnomy: an extension of NCBI Taxonomy that produces a hierarchically complete taxonomic tree

BACKGROUND

NCBI Taxonomy is the main taxonomic source for several bioinformatics tools and databases since all organisms with sequence accessions deposited on INSDC are organized in its hierarchical structure. Despite the extensive use and application of this data source, an alternative representation of data as a table would facilitate the use of information for processing bioinformatics data. To do so, since some taxonomic-ranks are missing in some lineages, an algorithm might propose provisional names for all taxonomic-ranks.

RESULTS

To address this issue, we developed an algorithm that takes the tree structure from NCBI Taxonomy and generates a hierarchically complete taxonomic table, maintaining its compatibility with the original tree. The procedures performed by the algorithm consist of attempting to assign a taxonomic-rank to an existing clade or "no rank" node when possible, using its name as part of the created taxonomic-rank name (e.g. Ord_Ornithischia) or interpolating parent nodes when needed (e.g. Cla_of_Ornithischia), both examples given for the dinosaur Brachylophosaurus lineage. The new hierarchical structure was named Taxallnomy because it contains names for all taxonomic-ranks, and it contains 41 hierarchical levels corresponding to the 41 taxonomic-ranks currently found in the NCBI Taxonomy database. From Taxallnomy, users can obtain the complete taxonomic lineage with 41 nodes of all taxa available in the NCBI Taxonomy database, without any hazard to the original tree information. In this work, we demonstrate its applicability by embedding taxonomic information of a specified rank into a phylogenetic tree and by producing metagenomics profiles.

CONCLUSION

Taxallnomy applies to any bioinformatics analyses that depend on the information from NCBI Taxonomy. Taxallnomy is updated periodically but with a distributed PERL script users can generate it locally using NCBI Taxonomy as input. All Taxallnomy resources are available at http://bioinfo.icb.ufmg.br/taxallnomy .

Gene Erosion Can Lead to Gain-of-Function Alleles That Contribute to Bacterial Fitness

Despite our extensive knowledge of the genetic regulation of heat shock proteins (HSPs), the evolutionary routes that allow bacteria to adaptively tune their HSP levels and corresponding proteostatic robustness have been explored less. In this report, directed evolution experiments using the Escherichia coli model system unexpectedly revealed that seemingly random single mutations in its tnaA gene can confer significant heat resistance. Closer examination, however, indicated that these mutations create folding-deficient and aggregation-prone TnaA variants that in turn can endogenously and preemptively trigger HSP expression to cause heat resistance. These findings, importantly, demonstrate that even erosive mutations with disruptive effects on protein structure and functionality can still yield true gain-of-function alleles with a selective advantage in adaptive evolution.

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.

PRMT3 interacts with ALDH1A1 and regulates gene-expression by inhibiting retinoic acid signaling

Protein arginine methyltransferase 3 (PRMT3) regulates protein functions by introducing asymmetric dimethylation marks at the arginine residues in proteins. However, very little is known about the interaction partners of PRMT3 and their functional outcomes. Using yeast-two hybrid screening, we identified Retinal dehydrogenase 1 (ALDH1A1) as a potential interaction partner of PRMT3 and confirmed this interaction using different methods. ALDH1A1 regulates variety of cellular processes by catalyzing the conversion of retinaldehyde to retinoic acid. By molecular docking and site-directed mutagenesis, we identified the specific residues in the catalytic domain of PRMT3 that facilitate interaction with the C-terminal region of ALDH1A1. PRMT3 inhibits the enzymatic activity of ALDH1A1 and negatively regulates the expression of retinoic acid responsive genes in a methyltransferase activity independent manner. Our findings show that in addition to regulating protein functions by introducing methylation modifications, PRMT3 could also regulate global gene expression through protein-protein interactions.

Here, the authors demonstrate that protein arginine methyltransferase 3 (PRMT3) interacts with and inhibits the retinal dehydrogenase ALDH1A1, negatively regulating the expression of retinoic acid responsive genes. This study shows that PRMT3 affects diverse biological processes not only by globally regulating protein function through methylation but also by regulating gene expression.

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.

Genomic signatures of convergent adaptation to Alpine environments in three Brassicaceae species

It has long been discussed to what extent related species develop similar genetic mechanisms to adapt to similar environments. Most studies documenting such convergence have either used different lineages within species or surveyed only a limited portion of the genome. Here, we investigated whether similar or different sets of orthologous genes were involved in genetic adaptation of natural populations of three related plant species to similar environmental gradients in the Alps. We used whole-genome pooled population sequencing to study genome-wide SNP variation in 18 natural populations of three Brassicaceae (Arabis alpina, Arabidopsis halleri, and Cardamine resedifolia) from the Swiss Alps. We first de novo assembled draft reference genomes for all three species. We then ran population and landscape genomic analyses with ~3 million SNPs per species to look for shared genomic signatures of selection and adaptation in response to similar environmental gradients acting on these species. Genes with a signature of convergent adaptation were found at significantly higher numbers than expected by chance. The most closely related species pair showed the highest relative over-representation of shared adaptation signatures. Moreover, the identified genes of convergent adaptation were enriched for nonsynonymous mutations, suggesting functional relevance of these genes, even though many of the identified candidate genes have hitherto unknown or poorly described functions based on comparison with Arabidopsis thaliana. We conclude that adaptation to heterogeneous Alpine environments in related species is partly driven by convergent evolution, but that most of the genomic signatures of adaptation remain species-specific.

Convergent molecular evolution among ash species resistant to the emerald ash borer

Recent studies show that molecular convergence plays an unexpectedly common role in the evolution of convergent phenotypes. We exploited this phenomenon to find candidate loci underlying resistance to the emerald ash borer (EAB, Agrilus planipennis), the United States' most costly invasive forest insect to date, within the pan-genome of ash trees (the genus Fraxinus). We show that EAB-resistant taxa occur within three independent phylogenetic lineages. In genomes from these resistant lineages, we detect 53 genes with evidence of convergent amino acid evolution. Gene-tree reconstruction indicates that, for 48 of these candidates, the convergent amino acids are more likely to have arisen via independent evolution than by another process such as hybridization or incomplete lineage sorting. Seven of the candidate genes have putative roles connected to the phenylpropanoid biosynthesis pathway and 17 relate to herbivore recognition, defence signalling or programmed cell death. Evidence for loss-of-function mutations among these candidates is more frequent in susceptible species than in resistant ones. Our results on evolutionary relationships, variability in resistance, and candidate genes for defence response within the ash genus could inform breeding for EAB resistance, facilitating ecological restoration in areas invaded by this beetle.

Discovery of Human Signaling Systems: Pairing Peptides to G Protein-Coupled Receptors

The peptidergic system is the most abundant network of ligand-receptor-mediated signaling in humans. However, the physiological roles remain elusive for numerous peptides and more than 100 G protein-coupled receptors (GPCRs). Here we report the pairing of cognate peptides and receptors. Integrating comparative genomics across 313 species and bioinformatics on all protein sequences and structures of human class A GPCRs, we identify universal characteristics that uncover additional potential peptidergic signaling systems. Using three orthogonal biochemical assays, we pair 17 proposed endogenous ligands with five orphan GPCRs that are associated with diseases, including genetic, neoplastic, nervous and reproductive system disorders. We also identify additional peptides for nine receptors with recognized ligands and pathophysiological roles. This integrated computational and multifaceted experimental approach expands the peptide-GPCR network and opens the way for studies to elucidate the roles of these signaling systems in human physiology and disease.

Video Abstract

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Universal characteristics enabled prediction of peptide ligands and receptors

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Multifaceted screening enabled detection of pathway- and assay-dependent responses

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Peptide ligands discovered for BB₃, GPR1, GPR15, GPR55, and GPR68

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Each signaling system is a link to human physiology and is associated with disease

Microbial genome analysis: the COG approach

For the past 20 years, the Clusters of Orthologous Genes (COG) database had been a popular tool for microbial genome annotation and comparative genomics. Initially created for the purpose of evolutionary classification of protein families, the COG have been used, apart from straightforward functional annotation of sequenced genomes, for such tasks as (i) unification of genome annotation in groups of related organisms; (ii) identification of missing and/or undetected genes in complete microbial genomes; (iii) analysis of genomic neighborhoods, in many cases allowing prediction of novel functional systems; (iv) analysis of metabolic pathways and prediction of alternative forms of enzymes; (v) comparison of organisms by COG functional categories; and (vi) prioritization of targets for structural and functional characterization. Here we review the principles of the COG approach and discuss its key advantages and drawbacks in microbial genome analysis.

Phylogenetic profiling, an untapped resource for the prediction of secreted proteins and its complementation with sequence-based classifiers in bacterial type III, IV and VI secretion systems

In the establishment and maintenance of the interaction between pathogenic or symbiotic bacteria with a eukaryotic organism, protein substrates of specialized bacterial secretion systems called effectors play a critical role once translocated into the host cell. Proteins are also secreted to the extracellular medium by free-living bacteria or directly injected into other competing organisms to hinder or kill. In this work, we explore an approach based on the evolutionary dependence that most of the effectors maintain with their specific secretion system that analyzes the co-occurrence of any orthologous protein group and their corresponding secretion system across multiple genomes. We compared and complemented our methodology with sequence-based machine learning prediction tools for the type III, IV and VI secretion systems. Finally, we provide the predictive results for the three secretion systems in 1606 complete genomes at http://www.iib.unsam.edu.ar/orgsissec/.

A multidimensional systems biology analysis of cellular senescence in aging and disease

BACKGROUND

Cellular senescence, a permanent state of replicative arrest in otherwise proliferating cells, is a hallmark of aging and has been linked to aging-related diseases. Many genes play a role in cellular senescence, yet a comprehensive understanding of its pathways is still lacking.

RESULTS

We develop CellAge (http://genomics.senescence.info/cells), a manually curated database of 279 human genes driving cellular senescence, and perform various integrative analyses. Genes inducing cellular senescence tend to be overexpressed with age in human tissues and are significantly overrepresented in anti-longevity and tumor-suppressor genes, while genes inhibiting cellular senescence overlap with pro-longevity and oncogenes. Furthermore, cellular senescence genes are strongly conserved in mammals but not in invertebrates. We also build cellular senescence protein-protein interaction and co-expression networks. Clusters in the networks are enriched for cell cycle and immunological processes. Network topological parameters also reveal novel potential cellular senescence regulators. Using siRNAs, we observe that all 26 candidates tested induce at least one marker of senescence with 13 genes (C9orf40, CDC25A, CDCA4, CKAP2, GTF3C4, HAUS4, IMMT, MCM7, MTHFD2, MYBL2, NEK2, NIPA2, and TCEB3) decreasing cell number, activating p16/p21, and undergoing morphological changes that resemble cellular senescence.

CONCLUSIONS

Overall, our work provides a benchmark resource for researchers to study cellular senescence, and our systems biology analyses reveal new insights and gene regulators of cellular senescence.

A systematic pipeline for classifying bacterial operons reveals the evolutionary landscape of biofilm machineries

In bacteria functionally related genes comprising metabolic pathways and protein complexes are frequently encoded in operons and are widely conserved across phylogenetically diverse species. The evolution of these operon-encoded processes is affected by diverse mechanisms such as gene duplication, loss, rearrangement, and horizontal transfer. These mechanisms can result in functional diversification, increasing the potential evolution of novel biological pathways, and enabling pre-existing pathways to adapt to the requirements of particular environments. Despite the fundamental importance that these mechanisms play in bacterial environmental adaptation, a systematic approach for studying the evolution of operon organization is lacking. Herein, we present a novel method to study the evolution of operons based on phylogenetic clustering of operon-encoded protein families and genomic-proximity network visualizations of operon architectures. We applied this approach to study the evolution of the synthase dependent exopolysaccharide (EPS) biosynthetic systems: cellulose, acetylated cellulose, poly-β-1,6-N-acetyl-D-glucosamine (PNAG), Pel, and alginate. These polymers have important roles in biofilm formation, antibiotic tolerance, and as virulence factors in opportunistic pathogens. Our approach revealed the complex evolutionary landscape of EPS machineries, and enabled operons to be classified into evolutionarily distinct lineages. Cellulose operons show phyla-specific operon lineages resulting from gene loss, rearrangement, and the acquisition of accessory loci, and the occurrence of whole-operon duplications arising through horizonal gene transfer. Our evolution-based classification also distinguishes between PNAG production from Gram-negative and Gram-positive bacteria on the basis of structural and functional evolution of the acetylation modification domains shared by PgaB and IcaB loci, respectively. We also predict several pel-like operon lineages in Gram-positive bacteria and demonstrate in our companion paper (Whitfield et al PLoS Pathogens, in press) that Bacillus cereus produces a Pel-dependent biofilm that is regulated by cyclic-3',5'-dimeric guanosine monophosphate (c-di-GMP).

BioHackathon 2015: Semantics of data for life sciences and reproducible research

We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.

Semantic Integration and Enrichment of Heterogeneous Biological Databases

Biological databases are growing at an exponential rate, currently being among the major producers of Big Data, almost on par with commercial generators, such as YouTube or Twitter. While traditionally biological databases evolved as independent silos, each purposely built by a different research group in order to answer specific research questions; more recently significant efforts have been made toward integrating these heterogeneous sources into unified data access systems or interoperable systems using the FAIR principles of data sharing. Semantic Web technologies have been key enablers in this process, opening the path for new insights into the unified data, which were not visible at the level of each independent database. In this chapter, we first provide an introduction into two of the most used database models for biological data: relational databases and RDF stores. Next, we discuss ontology-based data integration, which serves to unify and enrich heterogeneous data sources. We present an extensive timeline of milestones in data integration based on Semantic Web technologies in the field of life sciences. Finally, we discuss some of the remaining challenges in making ontology-based data access (OBDA) systems easily accessible to a larger audience. In particular, we introduce natural language search interfaces, which alleviate the need for database users to be familiar with technical query languages. We illustrate the main theoretical concepts of data integration through concrete examples, using two well-known biological databases: a gene expression database, Bgee, and an orthology database, OMA.

JustOrthologs: a fast, accurate and user-friendly ortholog identification algorithm

Motivation

Orthologous gene identification is fundamental to all aspects of biology. For example, ortholog identification between species can provide functional insights for genes of unknown function and is a necessary step in phylogenetic inference. Currently, most ortholog identification algorithms require all-versus-all BLAST comparisons, which are time-consuming and memory intensive.

Results

In contrast to existing approaches, JustOrthologs exploits the conservation of gene structure by using the lengths of coding sequence regions and dinucleotide percentages to identify orthologs. In comparison to OrthoMCL, OMA and OrthoFinder, JustOrthologs decreases ortholog identification runtime by more than 96% and achieves comparable precision and recall scores. The computational speedup allowed us to conduct pairwise comparisons of 1197 complete genomes (780 eukaryotes and 417 archaea). We confirmed gene annotations for 384 120 genes, grouped 1 675 415 genes in previously unreported ortholog groups, and identified 51 429 potentially mislabeled genes across 622 843 ortholog groups.

Availability and implementation

JustOrthologs is an open source collaborative software package available in the GitHub repository: https://github.com/ridgelab/JustOrthologs/. All test FASTA files used for comparisons are freely available at https://github.com/ridgelab/JustOrthologs/comparisonFastaFiles/. Reference genomes used in this work are available for download from the NCBI repository: ftp://ftp.ncbi.nih.gov/genomes/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Domainoid: domain-oriented orthology inference

Background

Orthology inference is normally based on full-length protein sequences. However, most proteins contain independently folding and recurring regions, domains. The domain architecture of a protein is vital for its function, and recombination events mean individual domains can have different evolutionary histories. It has previously been shown that orthologous proteins may differ in domain architecture, creating challenges for orthology inference methods operating on full-length sequences. We have developed Domainoid, a new tool aiming to overcome these challenges faced by full-length orthology methods by inferring orthology on the domain level. It employs the InParanoid algorithm on single domains separately, to infer groups of orthologous domains.

Results

This domain-oriented approach allows detection of discordant domain orthologs, cases where different domains on the same protein have different evolutionary histories. In addition to domain level analysis, protein level orthology based on the fraction of domains that are orthologous can be inferred. Domainoid orthology assignments were compared to those yielded by the conventional full-length approach InParanoid, and were validated in a standard benchmark.

Conclusions

Our results show that domain-based orthology inference can reveal many orthologous relationships that are not found by full-length sequence approaches.

Availability

https://bitbucket.org/sonnhammergroup/domainoid/

Duplicate divergence of two bacterial small heat shock proteins reduces the demand for Hsp70 in refolding of substrates

Small heat shock proteins (sHsps) are a conserved class of ATP-independent chaperones that bind to aggregation-prone polypeptides at stress conditions. sHsps encage these polypeptides in assemblies, shielding them from further aggregation. To facilitate their subsequent solubilization and refolding by Hsp70 (DnaK) and Hsp100 (ClpB) chaperones, first, sHsps need to dissociate from the assemblies. In most γ-proteobacteria, these functions are fulfilled by a single sHsp (IbpA), but in a subset of Enterobacterales, a two-protein sHsp (IbpA and IbpB) system has evolved. To gain insight into the emergence of complexity within this chaperone system, we reconstructed the phylogeny of γ-proteobacteria and their sHsps. We selected proteins representative of systems comprising either one or two sHsps and analysed their ability to form sHsps-substrate assemblies. All the tested IbpA proteins, but not IbpBs, stably interact with an aggregating substrate. Moreover, in Escherichia coli cells, ibpA but not ibpB suppress the growth defect associated with low DnaK level, which points to the major protective role of IbpA during the breakdown of protein quality control. We also examined how sHsps affect the association of Hsp70 with the assemblies at the initial phase of disaggregation and how they affect protein recovery after stress. Our results suggest that a single gene duplication event has given rise to the sHsp system consisting of a strong canonical binder, IbpA, and its non-canonical paralog IbpB that enhances sHsps dissociation from the assemblies. The cooperation between the sHsps reduces the demand for Hsp70 needed to outcompete them from the assemblies by promoting sHsps dissociation without compromising assembly formation at heat shock. This potentially increases the robustness and elasticity of sHsps protection against irreversible aggregation.

Small heat shock proteins (sHsps) are a class of molecular chaperones playing an important role in maintaining cell proteostasis. Their most widespread and evolutionarily conserved function is binding to denaturing polypeptides. Small Hsps shield their substrates from further aggregation until conditions are favourable for their refolding by chaperones from the Hsp70 and Hsp100 families. To exert this function, at stress conditions, oligomeric sHsps dissociate into dimers and scavenge partially unfolded substrates, forming assemblies containing both substrate proteins and sHsps. Substrate proteins in such assemblies are refolding-competent. Later, when a cell recovers from stress, sHsps need to dissociate from the assemblies to make the substrates available for the disaggregating and refolding chaperones. Most bacteria possess one sHsp-encoding gene. However, their single sHsp is burdened with a trade-off: on one hand, it has to rapidly associate with the misfolding proteins, on the other, it needs to dissociate from them to allow effective disaggregation. With phylogenetic and biochemical approaches, we analysed a two-sHsp system distinctive of the Enterobacterales order, unravelling a potential evolutionary advantage granted by functional cooperation between the two sHsps. Our results indicate that after a gene duplication event, one sHsp specialized in tight substrate binding, whereas another sHsp became important for efficient dissociation of both sHsps to enable recovery of proteins trapped in the assemblies.

Evolution of Termite Symbiosis Informed by Transcriptome-Based Phylogenies

Termitidae comprises ∼80% of all termite species [1] that play dominant decomposer roles in tropical ecosystems [2, 3]. Two major events during termite evolution were the loss of cellulolytic gut protozoans in the ancestor of Termitidae and the subsequent gain in the termitid subfamily Macrotermitinae of fungal symbionts cultivated externally in "combs" constructed within the nest [4, 5]. How these symbiotic transitions occurred remains unresolved. Phylogenetic analyses of mitochondrial data previously suggested that Macrotermitinae is the earliest branching termitid lineage, followed soon after by Sphaerotermitinae [6], which cultivates bacterial symbionts on combs inside its nests [7]. This has led to the hypothesis that comb building was an important evolutionary step in the loss of gut protozoa in ancestral termitids [8]. We sequenced genomes and transcriptomes of 55 termite species and reconstructed phylogenetic trees from up to 4,065 orthologous genes of 68 species. We found strong support for a novel sister-group relationship between the bacterial comb-building Sphaerotermitinae and fungus comb-building Macrotermitinae. This key finding indicates that comb building is a derived trait within Termitidae and that the creation of a comb-like "external rumen" involving bacteria or fungi may not have driven the loss of protozoa from ancestral termitids, as previously hypothesized. Instead, associations with gut prokaryotic symbionts, combined with dietary shifts from wood to other plant-based substrates, may have played a more important role in this symbiotic transition. Our phylogenetic tree provides a platform for future studies of comparative termite evolution and the evolution of symbiosis in this taxon.

PhyloProfile: dynamic visualization and exploration of multi-layered phylogenetic profiles

Summary

Phylogenetic profiles form the basis for tracing proteins and their functions across species and through time. Novel genome sequences nowadays often represent species from the remotest corner of the tree of life. Thus, phylogenetic profiling becomes increasingly important for functionally annotating this data and to integrate it into a comprehensive view on organismal evolution. To strengthen the link between the sharing of a gene across species and of the corresponding function, it is meanwhile common to complement phylogenetic profiles with additional information, such as domain architecture similarities between orthologs, or pairwise similarities of other protein features. However, there are few visualization tools that facilitate an intuitive integration of these various information layers. Here, we present PhyloProfile, an R-based tool to visualize, explore and analyze multi-layered phylogenetic profiles.

Availability and implementation

PhyloProfile is available as open source code under the MIT license at https://github.com/BIONF/phyloprofile. An online version for testing PhyloProfile and for small to medium-scale analyses is available at http://applbio.biologie.uni-frankfurt.de/phyloprofile.

Data for positive selection test and co-evolutionary analysis on mammalian cereblon

Cereblon (CRBN) is a substrate recognition subunit of the CRL4 E3 ubiquitin ligase complex, directly binding to specific substrates for poly-ubiquitination followed by proteasome-dependent degradation of proteins. Cellular CRBN is responsible for energy metabolism, ion-channel activation, and cellular stress response through binding to proteins related to the respective pathways. As CRBN binds to various proteins, the selective pressure at the interacting surface is expected to result in functional divergence. Here, we present two mammalian CRBN datasets of molecular evolutionary analyses. (1) The multiple sequence alignment data shows that positive selection occurred, determined with a dN/dS calculation. (2) Data on co-evolutionary analysis between vertebrate CRBN and related proteins are represented by calculating the correlation coefficient based on the comparison of phylogenetic trees. Co-evolutionary analysis shows the similarity of evolutionary traits of two proteins. Further molecular, functional interpretation of these analyses is explained in ‘Positive selection of Cereblon modified function including its E3 Ubiquitin Ligase activity and binding efficiency with AMPK’ (W. Onodera, T. Asahi, N. Sawamura, Positive selection of cereblon modified function including its E3 ubiquitin ligase activity and binding efficiency with AMPK. Mol Phylogenet Evol. (2019) 135:78-85. [1]).

Social genes are selection hotspots in kin groups of a soil microbe

The composition of cooperative systems, including animal societies, organismal bodies, and microbial groups, reflects their past and shapes their future evolution. However, genomic diversity within many multiunit systems remains uncharacterized, limiting our ability to understand and compare their evolutionary character. We have analyzed genomic and social-phenotype variation among 120 natural isolates of the cooperative bacterium Myxococcus xanthus derived from six multicellular fruiting bodies. Each fruiting body was composed of multiple lineages radiating from a unique recent ancestor. Genomic evolution was concentrated in selection hotspots associated with evolutionary change in social phenotypes. Synonymous mutations indicated that kin lineages within the same fruiting body often first diverged from a common ancestor more than 100 generations ago. Thus, selection appears to promote endemic diversification of kin lineages that remain together over long histories of local interaction, thereby potentiating social coevolution.

Reconciling event-labeled gene trees with MUL-trees and species networks

Phylogenomics commonly aims to construct evolutionary trees from genomic sequence information. One way to approach this problem is to first estimate event-labeled gene trees (i.e., rooted trees whose non-leaf vertices are labeled by speciation or gene duplication events), and to then look for a species tree which can be reconciled with this tree through a reconciliation map between the trees. In practice, however, it can happen that there is no such map from a given event-labeled tree to any species tree. An important situation where this might arise is where the species evolution is better represented by a network instead of a tree. In this paper, we therefore consider the problem of reconciling event-labeled trees with species networks. In particular, we prove that any event-labeled gene tree can be reconciled with some network and that, under certain mild assumptions on the gene tree, the network can even be assumed to be multi-arc free. To prove this result, we show that we can always reconcile the gene tree with some multi-labeled (MUL-)tree, which can then be "folded up" to produce the desired reconciliation and network. In addition, we study the interplay between reconciliation maps from event-labeled gene trees to MUL-trees and networks. Our results could be useful for understanding how genomes have evolved after undergoing complex evolutionary events such as polyploidy.

The OMA orthology database in 2018: retrieving evolutionary relationships among all domains of life through richer web and programmatic interfaces

The Orthologous Matrix (OMA) is a leading resource to relate genes across many species from all of life. In this update paper, we review the recent algorithmic improvements in the OMA pipeline, describe increases in species coverage (particularly in plants and early-branching eukaryotes) and introduce several new features in the OMA web browser. Notable improvements include: (i) a scalable, interactive viewer for hierarchical orthologous groups; (ii) protein domain annotations and domain-based links between orthologous groups; (iii) functionality to retrieve phylogenetic marker genes for a subset of species of interest; (iv) a new synteny dot plot viewer; and (v) an overhaul of the programmatic access (REST API and semantic web), which will facilitate incorporation of OMA analyses in computational pipelines and integration with other bioinformatic resources. OMA can be freely accessed at https://omabrowser.org.

AYbRAH: a curated ortholog database for yeasts and fungi spanning 600 million years of evolution

Budding yeasts inhabit a range of environments by exploiting various metabolic traits. The genetic bases for these traits are mostly unknown, preventing their addition or removal in a chassis organism for metabolic engineering. Insight into the evolution of orthologs, paralogs and xenologs in the yeast pan-genome can help bridge these genotypes; however, existing phylogenomic databases do not span diverse yeasts, and sometimes cannot distinguish between these homologs. To help understand the molecular evolution of these traits in yeasts, we created Analyzing Yeasts by Reconstructing Ancestry of Homologs (AYbRAH), an open-source database of predicted and manually curated ortholog groups for 33 diverse fungi and yeasts in Dikarya, spanning 600 million years of evolution. OrthoMCL and OrthoDB were used to cluster protein sequence into ortholog and homolog groups, respectively; MAFFT and PhyML reconstructed the phylogeny of all homolog groups. Ortholog assignments for enzymes and small metabolite transporters were compared to their phylogenetic reconstruction, and curated to resolve any discrepancies. Information on homolog and ortholog groups can be viewed in the AYbRAH web portal (https://lmse.github.io/aybrah/), including functional annotations, predictions for mitochondrial localization and transmembrane domains, literature references and phylogenetic reconstructions. Ortholog assignments in AYbRAH were compared to HOGENOM, KEGG Orthology, OMA, eggNOG and PANTHER. PANTHER and OMA had the most congruent ortholog groups with AYbRAH, while the other phylogenomic databases had greater amounts of under-clustering, over-clustering or no ortholog annotations for proteins. Future plans are discussed for AYbRAH, and recommendations are made for other research communities seeking to create curated ortholog databases.

Cross-species functional modules link proteostasis to human normal aging

The evolutionarily conserved nature of the few well-known anti-aging interventions that affect lifespan, such as caloric restriction, suggests that aging-related research in model organisms is directly relevant to human aging. Since human lifespan is a complex trait, a systems-level approach will contribute to a more comprehensive understanding of the underlying aging landscape. Here, we integrate evolutionary and functional information of normal aging across human and model organisms at three levels: gene-level, process-level, and network-level. We identify evolutionarily conserved modules of normal aging across diverse taxa, and notably show proteostasis to be conserved in normal aging. Additionally, we find that mechanisms related to protein quality control network are enriched for genes harboring genetic variants associated with 22 age-related human traits and associated to caloric restriction. These results demonstrate that a systems-level approach, combined with evolutionary conservation, allows the detection of candidate aging genes and pathways relevant to human normal aging.

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.

Comparing time series transcriptome data between plants using a network module finding algorithm

BACKGROUND

Comparative transcriptome analysis is the comparison of expression patterns between homologous genes in different species. Since most molecular mechanistic studies in plants have been performed in model species, including Arabidopsis and rice, comparative transcriptome analysis is particularly important for functional annotation of genes in diverse plant species. Many biological processes, such as embryo development, are highly conserved between different plant species. The challenge is to establish one-to-one mapping of the developmental stages between two species.

RESULTS

In this manuscript, we solve this problem by converting the gene expression patterns into co-expression networks and then apply network module finding algorithms to the cross-species co-expression network. We describe how such analyses are carried out using bash scripts for preliminary data processing followed by using the R programming language for module finding with a simulated annealing method. We also provide instructions on how to visualize the resulting co-expression networks across species.

CONCLUSIONS

We provide a comprehensive pipeline from installing software and downloading raw transcriptome data to predicting homologous genes and finding orthologous co-expression networks. From the example provided, we demonstrate the application of our method to reveal functional conservation and divergence of genes in two plant species.

Salmonella Typhi, Paratyphi A, Enteritidis and Typhimurium core proteomes reveal differentially expressed proteins linked to the cell surface and pathogenicity

Background

Salmonella enterica subsp. enterica contains more than 2,600 serovars of which four are of major medical relevance for humans. While the typhoidal serovars (Typhi and Paratyphi A) are human-restricted and cause enteric fever, non-typhoidal Salmonella serovars (Typhimurium and Enteritidis) have a broad host range and predominantly cause gastroenteritis.

Methodology/Principle findings

We compared the core proteomes of Salmonella Typhi, Paratyphi A, Typhimurium and Enteritidis using contemporary proteomics. For each serovar, five clinical isolates (covering different geographical origins) and one reference strain were grown in vitro to the exponential phase. Levels of orthologous proteins quantified in all four serovars and within the typhoidal and non-typhoidal groups were compared and subjected to gene ontology term enrichment and inferred regulatory interactions. Differential expression of the core proteomes of the typhoidal serovars appears mainly related to cell surface components and, for the non-typhoidal serovars, to pathogenicity.

Conclusions/Significance

Our comparative proteome analysis indicated differences in the expression of surface proteins between Salmonella Typhi and Paratyphi A, and in pathogenesis-related proteins between Salmonella Typhimurium and Enteritidis. Our findings may guide future development of novel diagnostics and vaccines, as well as understanding of disease progression.

With an estimated 20 million typhoid cases and an even higher number of non-typhoid cases the health burden caused by salmonellosis is huge. Salmonellosis is caused by the bacterial species Salmonella enterica and over 2500 different serovars exist, of which four are of major medical relevance for humans: Typhi and Paratyphi A cause typhoid fever while Typhimurium and Enteritidis are the dominant cause of non-typhoidal Salmonella infections. The proteome is the entire set of proteins that is expressed by a genome and the core proteome are all orthologous proteins detected in a given sample set. In this study we have investigated differential expression of the core proteomes of the Salmonella serovars Typhi, Paratyphi A, Typhimurium and Enteritidis, as well as the regulating molecules. Our comparative proteome analysis indicated differences in the expression of surface proteins between the serovars Typhi and Paratyphi A, and in pathogenesis-related proteins between Typhimurium and Enteritidis. Our findings in proteome-wide expression may guide the development of novel diagnostics and vaccines for Salmonella, as well as understanding of disease.

Tree reconciliation combined with subsampling improves large scale inference of orthologous group hierarchies

BACKGROUND

An orthologous group (OG) comprises a set of orthologous and paralogous genes that share a last common ancestor (LCA). OGs are defined with respect to a chosen taxonomic level, which delimits the position of the LCA in time to a specified speciation event. A hierarchy of OGs expands on this notion, connecting more general OGs, distant in time, to more recent, fine-grained OGs, thereby spanning multiple levels of the tree of life. Large scale inference of OG hierarchies with independently computed taxonomic levels can suffer from inconsistencies between successive levels, such as the position in time of a duplication event. This can be due to confounding genetic signal or algorithmic limitations. Importantly, inconsistencies limit the potential use of OGs for functional annotation and third-party applications.

RESULTS

Here we present a new methodology to ensure hierarchical consistency of OGs across taxonomic levels. To resolve an inconsistency, we subsample the protein space of the OG members and perform gene tree-species tree reconciliation for each sampling. Differently from previous approaches, by subsampling the protein space, we avoid the notoriously difficult task of accurately building and reconciling very large phylogenies. We implement the method into a high-throughput pipeline and apply it to the eggNOG database. We use independent protein domain definitions to validate its performance.

CONCLUSION

The presented consistency pipeline shows that, contrary to previous limitations, tree reconciliation can be a useful instrument for the construction of OG hierarchies. The key lies in the combination of sampling smaller trees and aggregating their reconciliations for robustness. Results show comparable or greater performance to previous pipelines. The code is available on Github at: https://github.com/meringlab/og_consistency_pipeline .