InParanoid 6: eukaryotic ortholog clusters with inparalogs

Genome-wide identification, phylogenetic, structural and functional evolution of the core components of ABA signaling in plant species: a focus on rice

MAIN CONCLUSION

A genome-wide analysis had identified 642 ABA core component genes from 20 plant species, which were further categorized into three distinct subfamilies. The gene structures and evolutionary relationships of these genes had been characterized. PP2C_1, PP2C_2, and SnRK2_1 had emerged as key players in mediating the ABA signaling transduction pathway, specifically in rice, in response to abiotic stresses. The plant hormone abscisic acid (ABA) is essential for growth, development, and stress response, relying on its core components, pyrabactin resistance, pyrabactin resistance-like, and the regulatory component of ABA receptor (PYR/PYL/RCAR), 2C protein phosphatase (PP2C), sucrose non-fermenting-1-related protein kinase 2 (SnRK2). However, there's a lack of research on their structural evolution and functional differentiation across plants. Our study analyzed the phylogenetic, gene structure, homology, and duplication evolution of this complex in 20 plant species. We found conserved patterns in copy number and homology across subfamilies. Segmental and tandem duplications drove the evolution of these genes, while whole-genome duplication (WGD) expanded PYR/PYL/RCAR and PP2C subfamilies, enhancing environmental adaptation. In rice and Arabidopsis, the PYR/PYL/RCAR, PP2C, and SnRK2 genes showed distinct tissue-specific expression and responded to various stresses. Notably, PP2C_1 and PP2C_2 interacted with SnRK2_1 and were crucial for ABA signaling in rice. These findings offered new insights into ABA signaling evolution, interactions, and integration in green plants, benefiting future research in agriculture, evolutionary biology, ecology, and environmental science.

Genomic variants disrupt miRNA-mRNA regulation

Micro RNA (miRNA) and its regulatory effect on messenger RNA (mRNA) gene expression are a major focus in cancer research. Disruption in the normal miRNA-mRNA regulation network can result in serious cascading biological repercussions. In this study, we curated miRNA-related variants from major genomic consortiums and thoroughly evaluated how these variants could exert their effects by cross-validating with independent functional knowledge bases. Nearly all known variants (more than 664 million) categorized by type (germline, somatic, epigenetic) were mapped to the genomic regions involved in miRNA-mRNA binding (miRNA seeds and miRNA-mRNA 3'-UTR binding sequence). Subsets of miRNA-related variants supported by additional functional evidence, such as expression Quantitative Trait Loci (eQTL) and Genome-Wide Association Study (GWAS), were identified and scrutinized. Our results show that variants in miRNA seeds can substantially alter the composition of an miRNA's target mRNA set. Various functional analyses converged to reveal a post-transcriptional complex regulatory network where miRNA, eQTL, and RNA-binding protein intertwined to disseminate the impact of genomic variants. These results may potentially explain how certain variants affect disease/trait risks in genome wide association studies.

A Pan-Cancer Analysis of the Oncogenic Role of WD Repeat Domain 74 in Multiple Tumors

Although emerging patient-derived samples and cellular-based evidence support the relationship between WDR74 (WD Repeat Domain 74) and carcinogenesis in multiple cancers, no systematic pan-cancer analysis is available. Our preliminary research demonstrated that WDR74 is over-expressed in lung squamous cell carcinoma (LUSC) and related with worse survival. We thus investigated the potential oncogenic roles of WDR74 across 33 tumors based on the database of TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus). WDR74 is highly expressed in most cancers and correlated with poor prognosis in several cancers (all p < 0.05). Mutation analysis demonstrated that WDR74 is frequently mutated in promoter regions of lung cancer. Moreover, we found that CD8⁺ T-cells and the fibroblast infiltration level increased in WDR74 over-expressed cancer cells. The GO (Gene Ontology) enrichment analysis of the WDR74 pathway revealed its participation in cellular biogenesis of the RNA metabolism and its critical role in cancer initiation and progression through the tumor cell energy metabolism. Our first pan-cancer study inferred a relatively comprehensive understanding of the oncogenic roles of WDR74 across various cancers.

Comprehensive Analysis of Co-Mutations Identifies Cooperating Mechanisms of Tumorigenesis

Somatic mutations are one of the most important factors in tumorigenesis and are the focus of most cancer-sequencing efforts. The co-occurrence of multiple mutations in one tumor has gained increasing attention as a means of identifying cooperating mutations or pathways that contribute to cancer. Using multi-omics, phenotypical, and clinical data from 29,559 cancer subjects and 1747 cancer cell lines covering 78 distinct cancer types, we show that co-mutations are associated with prognosis, drug sensitivity, and disparities in sex, age, and race. Some co-mutation combinations displayed stronger effects than their corresponding single mutations. For example, co-mutation TP53:KRAS in pancreatic adenocarcinoma is significantly associated with disease specific survival (hazard ratio = 2.87, adjusted p-value = 0.0003) and its prognostic predictive power is greater than either TP53 or KRAS as individually mutated genes. Functional analyses revealed that co-mutations with higher prognostic values have higher potential impact and cause greater dysregulation of gene expression. Furthermore, many of the prognostically significant co-mutations caused gains or losses of binding sequences of RNA binding proteins or micro RNAs with known cancer associations. Thus, detailed analyses of co-mutations can identify mechanisms that cooperate in tumorigenesis.

SBSA: an online service for somatic binding sequence annotation

Efficient annotation of alterations in binding sequences of molecular regulators can help identify novel candidates for mechanisms study and offer original therapeutic hypotheses. In this work, we developed Somatic Binding Sequence Annotator (SBSA) as a full-capacity online tool to annotate altered binding motifs/sequences, addressing diverse types of genomic variants and molecular regulators. The genomic variants can be somatic mutation, single nucleotide polymorphism, RNA editing, etc. The binding motifs/sequences involve transcription factors (TFs), RNA-binding proteins, miRNA seeds, miRNA-mRNA 3′-UTR binding target, or can be any custom motifs/sequences. Compared to similar tools, SBSA is the first to support miRNA seeds and miRNA-mRNA 3′-UTR binding target, and it unprecedentedly implements a personalized genome approach that accommodates joint adjacent variants. SBSA is empowered to support an indefinite species, including preloaded reference genomes for SARS-Cov-2 and 25 other common organisms. We demonstrated SBSA by annotating multi-omics data from over 30,890 human subjects. Of the millions of somatic binding sequences identified, many are with known severe biological repercussions, such as the somatic mutation in TERT promoter region which causes a gained binding sequence for E26 transformation-specific factor (ETS1). We further validated the function of this TERT mutation using experimental data in cancer cells. Availability:http://innovebioinfo.com/Annotation/SBSA/SBSA.php.

RNA editing affects cis-regulatory elements and predicts adverse cancer survival

BACKGROUND

RNA editing exerts critical impacts on numerous biological processes and thus are implicated in crucial human phenotypes, including tumorigenesis and prognosis. While previous studies have analyzed aggregate RNA editing activity at the sample level and associated it with overall cancer survival, there is not yet a large-scale disease-specific survival study to examine genome-wide RNA editing sites' prognostic value taking into account the host gene expression and clinical variables.

METHODS

In this study, we solved comprehensive Cox proportional models of disease-specific survival on individual RNA-editing sites plus host gene expression and critical demographic covariates. This allowed us to interrogate the prognostic value of a large number of RNA-editing sites at single-nucleotide resolution.

RESULTS

As a result, we identified 402 gene-proximal RNA-editing sites that generally predict adverse cancer survival. For example, an RNA-editing site residing in ZNF264 indicates poor survival of uterine corpus endometrial carcinoma, with a hazard ratio of 2.13 and an adjusted p-value of 4.07 × 10-7 . Some of these prognostic RNA-editing sites mediate the binding of RNA binding proteins and microRNAs, thus propagating their impacts to extensive regulatory targets.

CONCLUSIONS

In conclusion, RNA editing affects cis-regulatory elements and predicts adverse cancer survival.

Interplay of RNA-Binding Proteins and microRNAs in Neurodegenerative Diseases

The number of patients with neurodegenerative diseases (NDs) is increasing, along with the growing number of older adults. This escalation threatens to create a medical and social crisis. NDs include a large spectrum of heterogeneous and multifactorial pathologies, such as amyotrophic lateral sclerosis, frontotemporal dementia, Alzheimer’s disease, Parkinson’s disease, Huntington’s disease and multiple system atrophy, and the formation of inclusion bodies resulting from protein misfolding and aggregation is a hallmark of these disorders. The proteinaceous components of the pathological inclusions include several RNA-binding proteins (RBPs), which play important roles in splicing, stability, transcription and translation. In addition, RBPs were shown to play a critical role in regulating miRNA biogenesis and metabolism. The dysfunction of both RBPs and miRNAs is often observed in several NDs. Thus, the data about the interplay among RBPs and miRNAs and their cooperation in brain functions would be important to know for better understanding NDs and the development of effective therapeutics. In this review, we focused on the connection between miRNAs, RBPs and neurodegenerative diseases.

Integrative omics analysis reveals relationships of genes with synthetic lethal interactions through a pan-cancer analysis

Synthetic lethality is thought to play an important role in anticancer therapies. Herein, to understand the potential distributions and relationships between synthetic lethal interactions between genes, especially for pairs deriving from different sources, we performed an integrative analysis of genes at multiple molecular levels. Based on inter-species phylogenetic conservation of synthetic lethal interactions, gene pairs from yeast and humans were analyzed; a total of 37,588 candidate gene pairs containing 7,816 genes were collected. Of these, 49.74% of genes had 2–10 interactions, 22.93% were involved in hallmarks of cancer, and 21.61% were identified as core essential genes. Many genes were shown to have important biological roles via functional enrichment analysis, and 65 were identified as potentially crucial in the pathophysiology of cancer. Gene pairs with dysregulated expression patterns had higher prognostic values. Further screening based on mutation and expression levels showed that remaining gene pairs were mainly derived from human predicted or validated pairs, while most predicted pairs from yeast were filtered from analysis. Genes with synthetic lethality were further analyzed with their interactive microRNAs (miRNAs) at the isomiR level which have been widely studied as negatively regulatory molecules. The miRNA–mRNA interaction network revealed that many synthetic lethal genes contributed to the cell cycle (seven of 12 genes), cancer pathways (five of 12 genes), oocyte meiosis, the p53 signaling pathway, and hallmarks of cancer. Our study contributes to the understanding of synthetic lethal interactions and promotes the application of genetic interactions in further cancer precision medicine.

SMDB: pivotal somatic sequence alterations reprogramming regulatory cascades

Binding motifs for transcription factors, RNA-binding proteins, microRNAs (miRNAs), etc. are vital for proper gene transcription and translation regulation. Sequence alteration mechanisms including single nucleotide mutations, insertion, deletion, RNA editing and single nucleotide polymorphism can lead to gains and losses of binding motifs; such consequentially emerged or vanished binding motifs are termed ‘somatic motifs’ by us. Somatic motifs have been studied sporadically but have never been curated into a comprehensive resource. By analyzing various types of sequence altering data from large consortiums, we successfully identified millions of somatic motifs, including those for important transcription factors, RNA-binding proteins, miRNA seeds and miRNA–mRNA 3′-UTR target motifs. While a few of these somatic motifs have been well studied, our results contain many novel somatic motifs that occur at high frequency and are thus likely to cause important biological repercussions. Genes targeted by these altered motifs are excellent candidates for further mechanism studies. Here, we present the first database that hosts millions of somatic motifs ascribed to a variety of sequence alteration mechanisms.

Challenges in gene-oriented approaches for pangenome content discovery

Given a group of genomes, represented as the sets of genes that belong to them, the discovery of the pangenomic content is based on the search of genetic homology among the genes for clustering them into families. Thus, pangenomic analyses investigate the membership of the families to the given genomes. This approach is referred to as the gene-oriented approach in contrast to other definitions of the problem that takes into account different genomic features. In the past years, several tools have been developed to discover and analyse pangenomic contents. Because of the hardness of the problem, each tool applies a different strategy for discovering the pangenomic content. This results in a differentiation of the performance of each tool that depends on the composition of the input genomes. This review reports the main analysis instruments provided by the current state of the art tools for the discovery of pangenomic contents. Moreover, unlike previous works, the presented study compares pangenomic tools from a methodological perspective, analysing the causes that lead a given methodology to outperform other tools. The analysis is performed by taking into account different bacterial populations, which are synthetically generated by changing evolutionary parameters. The benchmarks used to compare the pangenomic tools, in addition to the computational pipeline developed for this purpose, are available at https://github.com/InfOmics/pangenes-review. Contact: V. Bonnici, R. Giugno Supplementary information: Supplementary data are available at Briefings in Bioinformatics online.

Integrated identification of key genes and pathways in Alzheimer's disease via comprehensive bioinformatical analyses

Background

Alzheimer's disease (AD) is known to be caused by multiple factors, meanwhile the pathogenic mechanism and development of AD associate closely with genetic factors. Existing understanding of the molecular mechanisms underlying AD remains incomplete.

Methods

Gene expression data (GSE48350) derived from post-modern brain was extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were derived from hippocampus and entorhinal cortex regions between AD patients and healthy controls and detected via Morpheus. Functional enrichment analyses, including Gene Ontology (GO) and pathway analyses of DEGs, were performed via Cytoscape and followed by the construction of protein-protein interaction (PPI) network. Hub proteins were screened using the criteria: nodes degree≥10 (for hippocampus tissues) and ≥ 8 (for entorhinal cortex tissues). Molecular Complex Detection (MCODE) was used to filtrate the important clusters. University of California Santa Cruz (UCSC) and the database of RNA-binding protein specificities (RBPDB) were employed to identify the RNA-binding proteins of the long non-coding RNA (lncRNA).

Results

251 & 74 genes were identified as DEGs, which consisted of 56 & 16 up-regulated genes and 195 & 58 down-regulated genes in hippocampus and entorhinal cortex, respectively. Biological analyses demonstrated that the biological processes and pathways related to memory, transmembrane transport, synaptic transmission, neuron survival, drug metabolism, ion homeostasis and signal transduction were enriched in these genes. 11 genes were identified as hub genes in hippocampus and entorhinal cortex, and 3 hub genes were identified as the novel candidates involved in the pathology of AD. Furthermore, 3 lncRNAs were filtrated, whose binding proteins were closely associated with AD.

Conclusions

Through GO enrichment analyses, pathway analyses and PPI analyses, we showed a comprehensive interpretation of the pathogenesis of AD at a systematic biology level, and 3 novel candidate genes and 3 lncRNAs were identified as novel and potential candidates participating in the pathology of AD. The results of this study could supply integrated insights for understanding the pathogenic mechanism underlying AD and potential novel therapeutic targets.

RRMdb-an evolutionary-oriented database of RNA recognition motif sequences

RNA-recognition motif (RRM) is an RNA-interacting protein domain that plays an important role in the processes of RNA metabolism such as the splicing, editing, export, degradation, and regulation of translation. Here, we present the RNA-recognition motif database (RRMdb), which affords rapid identification and annotation of RRM domains in a given protein sequence. The RRMdb database is compiled from ~57 000 collected representative RRM domain sequences, classified into 415 families. Whenever possible, the families are associated with the available literature and structural data. Moreover, the RRM families are organized into a network of sequence similarities that allows for the assessment of the evolutionary relationships between them.

RNA⁻Protein Interactions Prevent Long RNA Duplex Formation: Implications for the Design of RNA-Based Therapeutics

Cells frequently simultaneously express RNAs and cognate antisense transcripts without necessarily leading to the formation of RNA duplexes. Here, we present a novel transcriptome-wide experimental approach to ascertain the presence of accessible double-stranded RNA structures based on sequencing of RNA fragments longer than 18 nucleotides that were not degraded by single-strand cutting nucleases. We applied this approach to four different cell lines with respect to three different treatments (native cell lysate, removal of proteins, and removal of ribosomal RNA and proteins). We found that long accessible RNA duplexes were largely absent in native cell lysates, while the number of RNA duplexes was dramatically higher when proteins were removed. The majority of RNA duplexes involved ribosomal transcripts. The duplex formation between different non-ribosomal transcripts appears to be largely of a stochastic nature. These results suggest that cells are—via RNA-binding proteins—mostly devoid of long RNA duplexes, leading to low “noise” in the molecular patterns that are utilized by the innate immune system. These findings have implications for the design of RNA interference (RNAi)-based therapeutics by imposing structural constraints on designed RNA complexes that are intended to have specific properties with respect to Dicer cleavage and target gene downregulation.

Gene Tree Construction and Correction Using SuperTree and Reconciliation

The supertree problem asking for a tree displaying a set of consistent input trees has been largely considered for the reconstruction of species trees. Here, we rather explore this framework for the sake of reconstructing a gene tree from a set of input gene trees on partial data. In this perspective, the phylogenetic tree for the species containing the genes of interest can be used to choose among the many possible compatible "supergenetrees", the most natural criteria being to minimize a reconciliation cost. We develop a variety of algorithmic solutions for the construction and correction of gene trees using the supertree framework. A dynamic programming supertree algorithm for constructing or correcting gene trees, exponential in the number of input trees, is first developed for the less constrained version of the problem. It is then adapted to gene trees with nodes labeled as duplication or speciation, the additional constraint being to preserve the orthology and paralogy relations between genes. Then, a quadratic time algorithm is developed for efficiently correcting an initial gene tree while preserving a set of "trusted" subtrees, as well as the relative phylogenetic distance between them, in both cases of labeled or unlabeled input trees. By applying these algorithms to the set of Ensembl gene trees, we show that this new correction framework is particularly useful to correct weakly-supported duplication nodes. The C++ source code for the algorithms and simulations described in the paper are available at https://github.com/UdeM-LBIT/SuGeT.

Whole Genome Sequencing, de Novo Assembly and Phenotypic Profiling for the New Budding Yeast Species Saccharomyces jurei

Saccharomyces sensu stricto complex consist of yeast species, which are not only important in the fermentation industry but are also model systems for genomic and ecological analysis. Here, we present the complete genome assemblies of Saccharomyces jurei, a newly discovered Saccharomyces sensu stricto species from high altitude oaks. Phylogenetic and phenotypic analysis revealed that S. jurei is more closely related to S. mikatae, than S. cerevisiae, and S. paradoxus. The karyotype of S. jurei presents two reciprocal chromosomal translocations between chromosome VI/VII and I/XIII when compared to the S. cerevisiae genome. Interestingly, while the rearrangement I/XIII is unique to S. jurei, the other is in common with S. mikatae strain IFO1815, suggesting shared evolutionary history of this species after the split between S. cerevisiae and S. mikatae. The number of Ty elements differed in the new species, with a higher number of Ty elements present in S. jurei than in S. cerevisiae. Phenotypically, the S. jurei strain NCYC 3962 has relatively higher fitness than the other strain NCYC 3947^T under most of the environmental stress conditions tested and showed remarkably increased fitness in higher concentration of acetic acid compared to the other sensu stricto species. Both strains were found to be better adapted to lower temperatures compared to S. cerevisiae.

Integration of Comparative Genomics with Genome-Scale Metabolic Modeling to Investigate Strain-Specific Phenotypical Differences

Genome-scale metabolic reconstructions are powerful resources that allow translation biological knowledge and genomic information to phenotypical predictions using a number of constraint-based methods. This approach has been applied in recent years to gain deep insights into the cellular phenotype role of the genes at a systems-level, driving the design of targeted experiments and paving the way for knowledge-based synthetic biology.The identification of genetic determinants underlying the variability at the phenotypical level is crucial to understand the evolutionary trajectories of a bacterial species. Recently, genome-scale metabolic models of different strains have been assembled to highlight the intra-species diversity at the metabolic level. The strain-specific metabolic capabilities and auxotrophies can be used to identify factors related to the lifestyle diversity of a bacterial species.In this chapter, we present the computational steps to perform genome-scale metabolic modeling in the context of comparative genomics, and the different challenges related to this task.

Adaptation of Arabidopsis thaliana to the Yangtze River basin

Background

Organisms need to adapt to keep pace with a changing environment. Examining recent range expansion aids our understanding of how organisms evolve to overcome environmental constraints. However, how organisms adapt to climate changes is a crucial biological question that is still largely unanswered. The plant Arabidopsis thaliana is an excellent system to study this fundamental question. Its origin is in the Iberian Peninsula and North Africa, but it has spread to the Far East, including the most south-eastern edge of its native habitats, the Yangtze River basin, where the climate is very different.

Results

We sequenced 118 A. thaliana strains from the region surrounding the Yangtze River basin. We found that the Yangtze River basin population is a unique population and diverged about 61,409 years ago, with gene flows occurring at two different time points, followed by a population dispersion into the Yangtze River basin in the last few thousands of years. Positive selection analyses revealed that biological regulation processes, such as flowering time, immune and defense response processes could be correlated with the adaptation event. In particular, we found that the flowering time gene SVP has contributed to A. thaliana adaptation to the Yangtze River basin based on genetic mapping.

Conclusions

A. thaliana adapted to the Yangtze River basin habitat by promoting the onset of flowering, a finding that sheds light on how a species can adapt to locales with very different climates.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1378-9) contains supplementary material, which is available to authorized users.

Long-term balancing selection contributes to adaptation in Arabidopsis and its relatives

BACKGROUND

In contrast to positive selection, which reduces genetic variation by fixing beneficial alleles, balancing selection maintains genetic variation within a population or species and plays crucial roles in adaptation in diverse organisms. However, which genes, genome-wide, are under balancing selection and the extent to which these genes are involved in adaptation are largely unknown.

RESULTS

We performed a genome-wide scan for genes under balancing selection across two plant species, Arabidopsis thaliana and its relative Capsella rubella, which diverged about 8 million generations ago. Among hundreds of genes with shared coding-region polymorphisms, we find evidence for long-term balancing selection in five genes: AT1G35220, AT2G16570, AT4G29360, AT5G38460, and AT5G44000. These genes are involved in the response to biotic and abiotic stress and other fundamental biochemical processes. More intriguingly, for these genes, we detected significant ecological diversification between the two haplotype groups, suggesting that balancing selection has been very important for adaptation.

CONCLUSIONS

Our results indicate that beyond the well-known S-locus genes and resistance genes, many loci are under balancing selection. These genes are mostly correlated with resistance to stress or other fundamental functions and likely play a more important role in adaptation to diverse habitats than previously thought.

Genome sequencing of the staple food crop white Guinea yam enables the development of a molecular marker for sex determination

Background

Root and tuber crops are a major food source in tropical Africa. Among these crops are several species in the monocotyledonous genus Dioscorea collectively known as yam, a staple tuber crop that contributes enormously to the subsistence and socio-cultural lives of millions of people, principally in West and Central Africa. Yam cultivation is constrained by several factors, and yam can be considered a neglected “orphan” crop that would benefit from crop improvement efforts. However, the lack of genetic and genomic tools has impeded the improvement of this staple crop.

Results

To accelerate marker-assisted breeding of yam, we performed genome analysis of white Guinea yam (Dioscorea rotundata) and assembled a 594-Mb genome, 76.4% of which was distributed among 21 linkage groups. In total, we predicted 26,198 genes. Phylogenetic analyses with 2381 conserved genes revealed that Dioscorea is a unique lineage of monocotyledons distinct from the Poales (rice), Arecales (palm), and Zingiberales (banana). The entire Dioscorea genus is characterized by the occurrence of separate male and female plants (dioecy), a feature that has limited efficient yam breeding. To infer the genetics of sex determination, we performed whole-genome resequencing of bulked segregants (quantitative trait locus sequencing [QTL-seq]) in F1 progeny segregating for male and female plants and identified a genomic region associated with female heterogametic (male = ZZ, female = ZW) sex determination. We further delineated the W locus and used it to develop a molecular marker for sex identification of Guinea yam plants at the seedling stage.

Conclusions

Guinea yam belongs to a unique and highly differentiated clade of monocotyledons. The genome analyses and sex-linked marker development performed in this study should greatly accelerate marker-assisted breeding of Guinea yam. In addition, our QTL-seq approach can be utilized in genetic studies of other outcrossing crops and organisms with highly heterozygous genomes. Genomic analysis of orphan crops such as yam promotes efforts to improve food security and the sustainability of tropical agriculture.

Electronic supplementary material

The online version of this article (doi:10.1186/s12915-017-0419-x) contains supplementary material, which is available to authorized users.

DRNApred, fast sequence-based method that accurately predicts and discriminates DNA- and RNA-binding residues

Protein-DNA and protein-RNA interactions are part of many diverse and essential cellular functions and yet most of them remain to be discovered and characterized. Recent research shows that sequence-based predictors of DNA-binding residues accurately find these residues but also cross-predict many RNA-binding residues as DNA-binding, and vice versa. Most of these methods are also relatively slow, prohibiting applications on the whole-genome scale. We describe a novel sequence-based method, DRNApred, which accurately and in high-throughput predicts and discriminates between DNA- and RNA-binding residues. DRNApred was designed using a new dataset with both DNA- and RNA-binding proteins, regression that penalizes cross-predictions, and a novel two-layered architecture. DRNApred outperforms state-of-the-art predictors of DNA- or RNA-binding residues on a benchmark test dataset by substantially reducing the cross predictions and predicting arguably higher quality false positives that are located nearby the native binding residues. Moreover, it also more accurately predicts the DNA- and RNA-binding proteins. Application on the human proteome confirms that DRNApred reduces the cross predictions among the native nucleic acid binders. Also, novel putative DNA/RNA-binding proteins that it predicts share similar subcellular locations and residue charge profiles with the known native binding proteins. Webserver of DRNApred is freely available at http://biomine.cs.vcu.edu/servers/DRNApred/.

Approximating the correction of weighted and unweighted orthology and paralogy relations

Background

Given a gene family, the relations between genes (orthology/paralogy), are represented by a relation graph, where edges connect pairs of orthologous genes and “missing” edges represent paralogs. While a gene tree directly induces a relation graph, the converse is not always true. Indeed, a relation graph is not necessarily “satisfiable”, i.e. does not necessarily correspond to a gene tree. And even if that holds, it may not be “consistent”, i.e. the tree may not represent a true history in agreement with a species tree. Previous studies have addressed the problem of correcting a relation graph for satisfiability and consistency. Here we consider the weighted version of the problem, where a degree of confidence is assigned to each orthology or paralogy relation. We also consider a maximization variant of the unweighted version of the problem.

Results

We provide complexity and algorithmic results for the approximation of the considered problems. We show that minimizing the correction of a weighted graph does not admit a constant factor approximation algorithm assuming the unique game conjecture, and we give an n-approximation algorithm, n being the number of vertices in the graph. We also provide polynomial time approximation schemes for the maximization variant for unweighted graphs.

Conclusions

We provided complexity and algorithmic results for variants of the problem of correcting a relation graph for satisfiability and consistency. For the maximization variants we were able to design polynomial time approximation schemes, while for the weighted minimization variants we were able to provide the first inapproximability results.

The link between orthology relations and gene trees: a correction perspective

Background

While tree-oriented methods for inferring orthology and paralogy relations between genes are based on reconciling a gene tree with a species tree, many tree-free methods are also available (usually based on sequence similarity). Recently, the link between orthology relations and gene trees has been formally considered from the perspective of reconstructing phylogenies from orthology relations. In this paper, we consider this link from a correction point of view. Indeed, a gene tree induces a set of relations, but the converse is not always true: a set of relations is not necessarily in agreement with any gene tree. A natural question is thus how to minimally correct an infeasible set of relations. Another natural question, given a gene tree and a set of relations, is how to minimally correct a gene tree so that the resulting gene tree fits the set of relations.

Results

We consider four variants of relation and gene tree correction problems, and provide hardness results for all of them. More specifically, we show that it is NP-Hard to edit a minimum of set of relations to make them consistent with a given species tree. We also show that the problem of finding a maximum subset of genes that share consistent relations is hard to approximate. We then demonstrate that editing a gene tree to satisfy a given set of relations in a minimum way is NP-Hard, where “minimum” refers either to the number of modified relations depicted by the gene tree or the number of clades that are lost. We also discuss some of the algorithmic perspectives given these hardness results.

Towards plant pangenomics

As an increasing number of genome sequences become available for a wide range of species, there is a growing understanding that the genome of a single individual is insufficient to represent the gene diversity within a whole species. Many studies examine the sequence diversity within genes, and this allelic variation is an important source of phenotypic variation which can be selected for by man or nature. However, the significant gene presence/absence variation that has been observed within species and the impact of this variation on traits is only now being studied in detail. The sum of the genes for a species is termed the pangenome, and the determination and characterization of the pangenome is a requirement to understand variation within a species. In this review, we explore the current progress in pangenomics as well as methods and approaches for the characterization of pangenomes for a wide range of plant species.

Evolutionary Conservation and Diversification of Puf RNA Binding Proteins and Their mRNA Targets

Reprogramming of a gene’s expression pattern by acquisition and loss of sequences recognized by specific regulatory RNA binding proteins may be a major mechanism in the evolution of biological regulatory programs. We identified that RNA targets of Puf3 orthologs have been conserved over 100–500 million years of evolution in five eukaryotic lineages. Focusing on Puf proteins and their targets across 80 fungi, we constructed a parsimonious model for their evolutionary history. This model entails extensive and coordinated changes in the Puf targets as well as changes in the number of Puf genes and alterations of RNA binding specificity including that: 1) Binding of Puf3 to more than 200 RNAs whose protein products are predominantly involved in the production and organization of mitochondrial complexes predates the origin of budding yeasts and filamentous fungi and was maintained for 500 million years, throughout the evolution of budding yeast. 2) In filamentous fungi, remarkably, more than 150 of the ancestral Puf3 targets were gained by Puf4, with one lineage maintaining both Puf3 and Puf4 as regulators and a sister lineage losing Puf3 as a regulator of these RNAs. The decrease in gene expression of these mRNAs upon deletion of Puf4 in filamentous fungi (N. crassa) in contrast to the increase upon Puf3 deletion in budding yeast (S. cerevisiae) suggests that the output of the RNA regulatory network is different with Puf4 in filamentous fungi than with Puf3 in budding yeast. 3) The coregulated Puf4 target set in filamentous fungi expanded to include mitochondrial genes involved in the tricarboxylic acid (TCA) cycle and other nuclear-encoded RNAs with mitochondrial function not bound by Puf3 in budding yeast, observations that provide additional evidence for substantial rewiring of post-transcriptional regulation. 4) Puf3 also expanded and diversified its targets in filamentous fungi, gaining interactions with the mRNAs encoding the mitochondrial electron transport chain (ETC) complex I as well as hundreds of other mRNAs with nonmitochondrial functions. The many concerted and conserved changes in the RNA targets of Puf proteins strongly support an extensive role of RNA binding proteins in coordinating gene expression, as originally proposed by Keene. Rewiring of Puf-coordinated mRNA targets and transcriptional control of the same genes occurred at different points in evolution, suggesting that there have been distinct adaptations via RNA binding proteins and transcription factors. The changes in Puf targets and in the Puf proteins indicate an integral involvement of RNA binding proteins and their RNA targets in the adaptation, reprogramming, and function of gene expression.

A map of the evolutionary history of Puf proteins and their RNA targets shows that reprogramming of global gene expression programs via adaptive mutations that affect protein-RNA interactions is an important source of biological diversity.

We set out to trace the evolutionary history of an RNA binding protein and how its interactions with targets change over evolution. Identifying this natural history is a step toward understanding the critical differences between organisms and how gene expression programs are rewired during evolution. Using bioinformatics and experimental approaches, we broadly surveyed the evolution of binding targets of a particular family of RNA binding proteins—the Puf proteins, whose protein sequences and target RNA sequences are relatively well-characterized—across 99 eukaryotic species. We found five groups of species in which targets have been conserved for at least 100 million years and then took advantage of genome sequences from a large number of fungal species to deeply investigate the conservation and changes in Puf proteins and their RNA targets. Our analyses identified multiple and extensive reconfigurations during the natural history of fungi and suggest that RNA binding proteins and their RNA targets are profoundly involved in evolutionary reprogramming of gene expression and help define distinct programs unique to each organism. Continuing to uncover the natural history of RNA binding proteins and their interactions will provide a unique window into the gene expression programs of present day species and point to new ways to engineer gene expression programs.

Genome-wide identification and evolutionary analyses of bZIP transcription factors in wheat and its relatives and expression profiles of anther development related TabZIP genes

BACKGROUND

Among the largest and most diverse transcription factor families in plants, basic leucine zipper (bZIP) family participate in regulating various processes, including floral induction and development, stress and hormone signaling, photomorphogenesis, seed maturation and germination, and pathogen defense. Although common wheat (Triticum aestivum L.) is one of the most widely cultivated and consumed food crops in the world, there is no comprehensive analysis of bZIPs in wheat, especially those involved in anther development. Previous studies have demonstrated wheat, T. urartu, Ae. tauschii, barley and Brachypodium are evolutionarily close in Gramineae family, however, the real evolutionary relationship still remains mysterious.

RESULTS

In this study, 187 bZIP family genes were comprehensively identified from current wheat genome. 98, 96 and 107 members of bZIP family were also identified from the genomes of T.urartu, Ae.tauschii and barley, respectively. Orthology analyses suggested 69.4 % of TubZIPs were orthologous to 68.8 % of AetbZIPs and wheat had many more in-paralogs in the bZIP family than its relatives. It was deduced wheat had a closer phylogenetic relationship with barley and Brachypodium than T.urartu and Ae.tauschii. bZIP proteins in wheat, T.urartu and Ae.tauschii were divided into 14 subgroups based on phylogenetic analyses. Using Affymetrix microarray data, 48 differentially expressed TabZIP genes were identified to be related to anther development from comparison between the male sterility line and the restorer line. Genes with close evolutionary relationship tended to share similar gene structures. 15 of 23 selected TabZIP genes contained LTR elements in their promoter regions. Expression of 21 among these 23 TabZIP genes were obviously responsive to low temperature. These 23 TabZIP genes all exhibited distinct tissue-specific expression pattern. Among them, 11 TabZIP genes were predominantly expressed in anther and most of them showed over-dominance expression mode in the cross combination TY806 × BS366.

CONCLUSIONS

The genome-wide identification provided an overall insight of bZIP gene family in wheat and its relatives. The evolutionary relationship of wheat and its relatives was proposed based on orthology analyses. Microarray and expression analyses suggested the potential involvement of bZIP genes in anther development and facilitated selection of anther development related gene for further functional characterization.

Systematic discovery of linear binding motifs targeting an ancient protein interaction surface on MAP kinases

Mitogen‐activated protein kinases (MAPK) are broadly used regulators of cellular signaling. However, how these enzymes can be involved in such a broad spectrum of physiological functions is not understood. Systematic discovery of MAPK networks both experimentally and in silico has been hindered because MAPKs bind to other proteins with low affinity and mostly in less‐characterized disordered regions. We used a structurally consistent model on kinase‐docking motif interactions to facilitate the discovery of short functional sites in the structurally flexible and functionally under‐explored part of the human proteome and applied experimental tools specifically tailored to detect low‐affinity protein–protein interactions for their validation in vitro and in cell‐based assays. The combined computational and experimental approach enabled the identification of many novel MAPK‐docking motifs that were elusive for other large‐scale protein–protein interaction screens. The analysis produced an extensive list of independently evolved linear binding motifs from a functionally diverse set of proteins. These all target, with characteristic binding specificity, an ancient protein interaction surface on evolutionarily related but physiologically clearly distinct three MAPKs (JNK, ERK, and p38). This inventory of human protein kinase binding sites was compared with that of other organisms to examine how kinase‐mediated partnerships evolved over time. The analysis suggests that most human MAPK‐binding motifs are surprisingly new evolutionarily inventions and newly found links highlight (previously hidden) roles of MAPKs. We propose that short MAPK‐binding stretches are created in disordered protein segments through a variety of ways and they represent a major resource for ancient signaling enzymes to acquire new regulatory roles.

Reconstructing a SuperGeneTree minimizing reconciliation

Combining a set of trees on partial datasets into a single tree is a classical method for inferring large phylogenetic trees. Ideally, the combined tree should display each input partial tree, which is only possible if input trees do not contain contradictory phylogenetic information. The simplest version of the supertree problem is thus to state whether a set of trees is compatible, and if so, construct a tree displaying them all. Classically, supertree methods have been applied to the reconstruction of species trees. Here we rather consider reconstructing a super gene tree in light of a known species tree S. We define the supergenetree problem as finding, among all supertrees displaying a set of input gene trees, one supertree minimizing a reconciliation distance with S. We first show how classical exact methods to the supertree problem can be extended to the supergenetree problem. As all these methods are highly exponential, we also exhibit a natural greedy heuristic for the duplication cost, based on minimizing the set of duplications preceding the first speciation event. We then show that both the supergenetree problem and its restriction to minimizing duplications preceding the first speciation are NP-hard to approximate within a n^1-ϵ factor, for any 0 < ϵ < 1. Finally, we show that a restriction of this problem to uniquely labeled speciation gene trees, which is relevant to many biological applications, is also NP-hard. Therefore, we introduce new avenues in the field of supertrees, and set the theoretical basis for the exploration of various algorithmic aspects of the problems.

Molecular dynamics study of naturally existing cavity couplings in proteins

Couplings between protein sub-structures are a common property of protein dynamics. Some of these couplings are especially interesting since they relate to function and its regulation. In this article we have studied the case of cavity couplings because cavities can host functional sites, allosteric sites, and are the locus of interactions with the cell milieu. We have divided this problem into two parts. In the first part, we have explored the presence of cavity couplings in the natural dynamics of 75 proteins, using 20 ns molecular dynamics simulations. For each of these proteins, we have obtained two trajectories around their native state. After applying a stringent filtering procedure, we found significant cavity correlations in 60% of the proteins. We analyze and discuss the structure origins of these correlations, including neighbourhood, cavity distance, etc. In the second part of our study, we have used longer simulations (≥100 ns) from the MoDEL project, to obtain a broader view of cavity couplings, particularly about their dependence on time. Using moving window computations we explored the fluctuations of cavity couplings along time, finding that these couplings could fluctuate substantially during the trajectory, reaching in several cases correlations above 0.25/0.5. In summary, we describe the structural origin and the variations with time of cavity couplings. We complete our work with a brief discussion of the biological implications of these results.

Systems-based analysis of the Sarcocystis neurona genome identifies pathways that contribute to a heteroxenous life cycle

Sarcocystis neurona is a member of the coccidia, a clade of single-celled parasites of medical and veterinary importance including Eimeria, Sarcocystis, Neospora, and Toxoplasma. Unlike Eimeria, a single-host enteric pathogen, Sarcocystis, Neospora, and Toxoplasma are two-host parasites that infect and produce infectious tissue cysts in a wide range of intermediate hosts. As a genus, Sarcocystis is one of the most successful protozoan parasites; all vertebrates, including birds, reptiles, fish, and mammals are hosts to at least one Sarcocystis species. Here we sequenced Sarcocystis neurona, the causal agent of fatal equine protozoal myeloencephalitis. The S. neurona genome is 127 Mbp, more than twice the size of other sequenced coccidian genomes. Comparative analyses identified conservation of the invasion machinery among the coccidia. However, many dense-granule and rhoptry kinase genes, responsible for altering host effector pathways in Toxoplasma and Neospora, are absent from S. neurona. Further, S. neurona has a divergent repertoire of SRS proteins, previously implicated in tissue cyst formation in Toxoplasma. Systems-based analyses identified a series of metabolic innovations, including the ability to exploit alternative sources of energy. Finally, we present an S. neurona model detailing conserved molecular innovations that promote the transition from a purely enteric lifestyle (Eimeria) to a heteroxenous parasite capable of infecting a wide range of intermediate hosts.

Sarcocystis neurona is a member of the coccidia, a clade of single-celled apicomplexan parasites responsible for major economic and health care burdens worldwide. A cousin of Plasmodium, Cryptosporidium, Theileria, and Eimeria, Sarcocystis is one of the most successful parasite genera; it is capable of infecting all vertebrates (fish, reptiles, birds, and mammals—including humans). The past decade has witnessed an increasing number of human outbreaks of clinical significance associated with acute sarcocystosis. Among Sarcocystis species, S. neurona has a wide host range and causes fatal encephalitis in horses, marine mammals, and several other mammals. To provide insights into the transition from a purely enteric parasite (e.g., Eimeria) to one that forms tissue cysts (Toxoplasma), we present the first genome sequence of S. neurona. Comparisons with other coccidian genomes highlight the molecular innovations that drive its distinct life cycle strategies.

Robustness analysis on interspecies interaction network for iron and glucose competition between Candida albicans and zebrafish during infection

Candida albicans has emerged as an important model organism for the study of infectious disease. Using high-throughput simultaneously quantified time-course transcriptomics, this study constructed host-pathogen interspecies interaction networks between C. albicans and zebrafish during the adhesion, invasion, and damage stages. Given that iron and glucose have been identified as crucial resources required during the infection process between C. albicans and zebrafish, we focused on the construction of the interspecies networks associated with them. Furthermore, a randomization technique was proposed to identify differentially regulated proteins that are statistically eminent for the three infection stages. The behaviors of the highly connected or differentially regulated proteins identified from the resulting networks were further investigated.

"Robustness" is an important system property that measures the ability of the system tolerating the intrinsic perturbations in a dynamic network. This characteristic provides a systematic and quantitative view to elucidate the dynamics of iron and glucose competition in terms of the interspecies interaction networks. Here, we further estimated the robustness of our constructed interspecies interaction networks for the three infection stages.

The constructed networks and robustness analysis provided significant insight into dynamic interactions related to iron and glucose competition during infection and enabled us to quantify the system's intrinsic perturbation tolerance ability during iron and glucose competition throughout the three infection stages. Moreover, the networks also assist in elucidating the offensive and defensive mechanisms of C. albicans and zebrafish during their competition for iron and glucose. Our proposed method can be easily extended to identify other such networks involved in the competition for essential resources during infection.

InParanoid 8: orthology analysis between 273 proteomes, mostly eukaryotic

The InParanoid database (http://InParanoid.sbc.su.se) provides a user interface to orthologs inferred by the InParanoid algorithm. As there are now international efforts to curate and standardize complete proteomes, we have switched to using these resources rather than gathering and curating the proteomes ourselves. InParanoid release 8 is based on the 66 reference proteomes that the ‘Quest for Orthologs’ community has agreed on using, plus 207 additional proteomes from the UniProt complete proteomes—in total 273 species. These represent 246 eukaryotes, 20 bacteria and seven archaea. Compared to the previous release, this increases the number of species by 173% and the number of pairwise species comparisons by 650%. In turn, the number of ortholog groups has increased by 423%. We present the contents and usages of InParanoid 8, and a detailed analysis of how the proteome content has changed since the previous release.

Orthology and paralogy constraints: satisfiability and consistency

Background

A variety of methods based on sequence similarity, reconciliation, synteny or functional characteristics, can be used to infer orthology and paralogy relations between genes of a given gene family  G. But is a given set  C of orthology/paralogy constraints possible, i.e., can they simultaneously co-exist in an evolutionary history for  G? While previous studies have focused on full sets of constraints, here we consider the general case where  C does not necessarily involve a constraint for each pair of genes. The problem is subdivided in two parts: (1) Is  C satisfiable, i.e. can we find an event-labeled gene tree G inducing  C? (2) Is there such a G which is consistent, i.e., such that all displayed triplet phylogenies are included in a species tree?

Results

Previous results on the Graph sandwich problem can be used to answer to (1), and we provide polynomial-time algorithms for satisfiability and consistency with a given species tree. We also describe a new polynomial-time algorithm for the case of consistency with an unknown species tree and full knowledge of pairwise orthology/paralogy relationships, as well as a branch-and-bound algorithm in the case when unknown relations are present. We show that our algorithms can be used in combination with ProteinOrtho, a sequence similarity-based orthology detection tool, to extract a set of robust orthology/paralogy relationships.

New tricks for "old" domains: how novel architectures and promiscuous hubs contributed to the organization and evolution of the ECM

The extracellular matrix (ECM) is a defining characteristic of metazoans and consists of a meshwork of self-assembling, fibrous proteins, and their functionally related neighbours. Previous studies, focusing on a limited number of gene families, suggest that vertebrate complexity predominantly arose through the duplication and subsequent modification of retained, preexisting ECM genes. These genes provided the structural underpinnings to support a variety of specialized tissues, as well as a platform for the organization of spatio-temporal signaling and cell migration. However, the relative contributions of ancient versus novel domains to ECM evolution have not been quantified across the full range of ECM proteins. Here, utilizing a high quality list comprising 324 ECM genes, we reveal general and clade-specific domain combinations, identifying domains of eukaryotic and metazoan origin recruited into new roles in approximately two-third of the ECM proteins in humans representing novel vertebrate proteins. We show that, rather than acquiring new domains, sampling of new domain combinations has been key to the innovation of paralogous ECM genes during vertebrate evolution. Applying a novel framework for identifying potentially important, noncontiguous, conserved arrangements of domains, we find that the distinct biological characteristics of the ECM have arisen through unique evolutionary processes. These include the preferential recruitment of novel domains to existing architectures and the utilization of high promiscuity domains in organizing the ECM network around a connected array of structural hubs. Our focus on ECM proteins reveals that distinct types of proteins and/or the biological systems in which they operate have influenced the types of evolutionary forces that drive protein innovation. This emphasizes the need for rigorously defined systems to address questions of evolution that focus on specific systems of interacting proteins.

The genome-scale metabolic network of Ectocarpus siliculosus (EctoGEM): a resource to study brown algal physiology and beyond

Brown algae (stramenopiles) are key players in intertidal ecosystems, and represent a source of biomass with several industrial applications. Ectocarpus siliculosus is a model to study the biology of these organisms. Its genome has been sequenced and a number of post-genomic tools have been implemented. Based on this knowledge, we report the reconstruction and analysis of a genome-scale metabolic network for E. siliculosus, EctoGEM (http://ectogem.irisa.fr). This atlas of metabolic pathways consists of 1866 reactions and 2020 metabolites, and its construction was performed by means of an integrative computational approach for identifying metabolic pathways, gap filling and manual refinement. The capability of the network to produce biomass was validated by flux balance analysis. EctoGEM enabled the reannotation of 56 genes within the E. siliculosus genome, and shed light on the evolution of metabolic processes. For example, E. siliculosus has the potential to produce phenylalanine and tyrosine from prephenate and arogenate, but does not possess a phenylalanine hydroxylase, as is found in other stramenopiles. It also possesses the complete eukaryote molybdenum co-factor biosynthesis pathway, as well as a second molybdopterin synthase that was most likely acquired via horizontal gene transfer from cyanobacteria by a common ancestor of stramenopiles. EctoGEM represents an evolving community resource to gain deeper understanding of the biology of brown algae and the diversification of physiological processes. The integrative computational method applied for its reconstruction will be valuable to set up similar approaches for other organisms distant from biological benchmark models.

Volatile evolution of long noncoding RNA repertoires: mechanisms and biological implications

Thousands of genes encoding long noncoding RNAs (lncRNAs) have been identified in all vertebrate genomes thus far examined. The list of lncRNAs partaking in arguably important biochemical, cellular, and developmental activities is steadily growing. However, it is increasingly clear that lncRNA repertoires are subject to weak functional constraint and rapid turnover during vertebrate evolution. We discuss here some of the factors that may explain this apparent paradox, including relaxed constraint on sequence to maintain lncRNA structure/function, extensive redundancy in the regulatory circuits in which lncRNAs act, as well as adaptive and non-adaptive forces such as genetic drift. We explore the molecular mechanisms promoting the birth and rapid evolution of lncRNA genes, with an emphasis on the influence of bidirectional transcription and transposable elements, two pervasive features of vertebrate genomes. Together these properties reveal a remarkably dynamic and malleable noncoding transcriptome which may represent an important source of robustness and evolvability.

Orthology detection combining clustering and synteny for very large datasets

The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the course of this work, FFAdj-MCS, a heuristic that assesses pairwise gene order using adjacencies (a similarity measure related to the breakpoint distance) was adapted to support multiple linear chromosomes and extended to detect duplicated regions. PoFF largely reduces the number of false positives and enables more fine-grained predictions than purely similarity-based approaches. The extension maintains the low memory requirements and the efficient concurrency options of its basis Proteinortho, making the software applicable to very large datasets.

The Index-based Subgraph Matching Algorithm with General Symmetries (ISMAGS): exploiting symmetry for faster subgraph enumeration

Subgraph matching algorithms are used to find and enumerate specific interconnection structures in networks. By enumerating these specific structures/subgraphs, the fundamental properties of the network can be derived. More specifically in biological networks, subgraph matching algorithms are used to discover network motifs, specific patterns occurring more often than expected by chance. Finding these network motifs yields information on the underlying biological relations modelled by the network. In this work, we present the Index-based Subgraph Matching Algorithm with General Symmetries (ISMAGS), an improved version of the Index-based Subgraph Matching Algorithm (ISMA). ISMA quickly finds all instances of a predefined motif in a network by intelligently exploring the search space and taking into account easily identifiable symmetric structures. However, more complex symmetries (possibly involving switching multiple nodes) are not taken into account, resulting in superfluous output. ISMAGS overcomes this problem by using a customised symmetry analysis phase to detect all symmetric structures in the network motif subgraphs. These structures are then converted to symmetry-breaking constraints used to prune the search space and speed up calculations. The performance of the algorithm was tested on several types of networks (biological, social and computer networks) for various subgraphs with a varying degree of symmetry. For subgraphs with complex (multi-node) symmetric structures, high speed-up factors are obtained as the search space is pruned by the symmetry-breaking constraints. For subgraphs with no or simple symmetric structures, ISMAGS still reduces computation times by optimising set operations. Moreover, the calculated list of subgraph instances is minimal as it contains no instances that differ by only a subgraph symmetry. An implementation of the algorithm is freely available at https://github.com/mhoubraken/ISMAGS.

Beyond genomic variation--comparison and functional annotation of three Brassica rapa genomes: a turnip, a rapid cycling and a Chinese cabbage

Background

Brassica rapa is an economically important crop species. During its long breeding history, a large number of morphotypes have been generated, including leafy vegetables such as Chinese cabbage and pakchoi, turnip tuber crops and oil crops.

Results

To investigate the genetic variation underlying this morphological variation, we re-sequenced, assembled and annotated the genomes of two B. rapa subspecies, turnip crops (turnip) and a rapid cycling. We then analysed the two resulting genomes together with the Chinese cabbage Chiifu reference genome to obtain an impression of the B. rapa pan-genome. The number of genes with protein-coding changes between the three genotypes was lower than that among different accessions of Arabidopsis thaliana, which can be explained by the smaller effective population size of B. rapa due to its domestication. Based on orthology to a number of non-brassica species, we estimated the date of divergence among the three B. rapa morphotypes at approximately 250,000 YA, far predating Brassica domestication (5,000-10,000 YA).

Conclusions

By analysing genes unique to turnip we found evidence for copy number differences in peroxidases, pointing to a role for the phenylpropanoid biosynthesis pathway in the generation of morphological variation. The estimated date of divergence among three B. rapa morphotypes implies that prior to domestication there was already considerably divergence among B. rapa genotypes. Our study thus provides two new B. rapa reference genomes, delivers a set of computer tools to analyse the resulting pan-genome and uses these to shed light on genetic drivers behind the rich morphological variation found in B. rapa.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-250) contains supplementary material, which is available to authorized users.

NADH binds and stabilizes the 26S proteasomes independent of ATP

The 26S proteasome is the end point of the ubiquitin- and ATP-dependent degradation pathway. The 26S proteasome complex (26S PC) integrity and function has been shown to be highly dependent on ATP and its homolog nucleotides. We report here that the redox molecule NADH binds the 26S PC and is sufficient in maintaining 26S PC integrity even in the absence of ATP. Five of the 19S proteasome complex subunits contain a putative NADH binding motif (GxGxxG) including the AAA-ATPase subunit, Psmc1 (Rpt2). We demonstrate that recombinant Psmc1 binds NADH via the GxGxxG motif. Introducing the ΔGxGxxG Psmc1 mutant into cells results in reduced NADH-stabilized 26S proteasomes and decreased viability following redox stress induced by the mitochondrial inhibitor rotenone. The newly identified NADH binding of 26S proteasomes advances our understanding of the molecular mechanisms of protein degradation and highlights a new link between protein homeostasis and the cellular metabolic/redox state.

Comparative RNAi screens in C. elegans and C. briggsae reveal the impact of developmental system drift on gene function

Although two related species may have extremely similar phenotypes, the genetic networks underpinning this conserved biology may have diverged substantially since they last shared a common ancestor. This is termed Developmental System Drift (DSD) and reflects the plasticity of genetic networks. One consequence of DSD is that some orthologous genes will have evolved different in vivo functions in two such phenotypically similar, related species and will therefore have different loss of function phenotypes. Here we report an RNAi screen in C. elegans and C. briggsae to identify such cases. We screened 1333 genes in both species and identified 91 orthologues that have different RNAi phenotypes. Intriguingly, we find that recently evolved genes of unknown function have the fastest evolving in vivo functions and, in several cases, we identify the molecular events driving these changes. We thus find that DSD has a major impact on the evolution of gene function and we anticipate that the C. briggsae RNAi library reported here will drive future studies on comparative functional genomics screens in these nematodes.

De novo genome assembly of the fungal plant pathogen Pyrenophora semeniperda

Pyrenophora semeniperda (anamorph Drechslera campulata) is a necrotrophic fungal seed pathogen that has a wide host range within the Poaceae. One of its hosts is cheatgrass (Bromus tectorum), a species exotic to the United States that has invaded natural ecosystems of the Intermountain West. As a natural pathogen of cheatgrass, P. semeniperda has potential as a biocontrol agent due to its effectiveness at killing seeds within the seed bank; however, few genetic resources exist for the fungus. Here, the genome of P. semeniperda isolate assembled from sequence reads of 454 pyrosequencing is presented. The total assembly is 32.5 Mb and includes 11,453 gene models encoding putative proteins larger than 24 amino acids. The models represent a variety of putative genes that are involved in pathogenic pathways typically found in necrotrophic fungi. In addition, extensive rearrangements, including inter- and intrachromosomal rearrangements, were found when the P. semeniperda genome was compared to P. tritici-repentis, a related fungal species.

Mating type gene homologues and putative sex pheromone-sensing pathway in arbuscular mycorrhizal fungi, a presumably asexual plant root symbiont

The fungal kingdom displays a fascinating diversity of sex-determination systems. Recent advances in genomics provide insights into the molecular mechanisms of sex, mating type determination, and evolution of sexual reproduction in many fungal species in both ancient and modern phylogenetic lineages. All major fungal groups have evolved sexual differentiation and recombination pathways. However, sexuality is unknown in arbuscular mycorrhizal fungi (AMF) of the phylum Glomeromycota, an ecologically vital group of obligate plant root symbionts. AMF are commonly considered an ancient asexual lineage dating back to the Ordovician, approximately 460 M years ago. In this study, we used genomic and transcriptomic surveys of several AMF species to demonstrate the presence of conserved putative sex pheromone-sensing mitogen-activated protein (MAP) kinases, comparable to those described in Ascomycota and Basidiomycota. We also find genes for high mobility group (HMG) transcription factors, homologous to SexM and SexP genes in the Mucorales. The SexM genes show a remarkable sequence diversity among multiple copies in the genome, while only a single SexP sequence was detected in some isolates of Rhizophagus irregularis. In the Mucorales and Microsporidia, the sexM gene is flanked by genes for a triosephosphate transporter (TPT) and a RNA helicase, but we find no evidence for synteny in the vicinity of the Sex locus in AMF. Nonetheless, our results, together with previous observations on meiotic machinery, suggest that AMF could undergo a complete sexual reproduction cycle.

The vertebrate ancestral repertoire of visual opsins, transducin alpha subunits and oxytocin/vasopressin receptors was established by duplication of their shared genomic region in the two rounds of early vertebrate genome duplications

BACKGROUND

Vertebrate color vision is dependent on four major color opsin subtypes: RH2 (green opsin), SWS1 (ultraviolet opsin), SWS2 (blue opsin), and LWS (red opsin). Together with the dim-light receptor rhodopsin (RH1), these form the family of vertebrate visual opsins. Vertebrate genomes contain many multi-membered gene families that can largely be explained by the two rounds of whole genome duplication (WGD) in the vertebrate ancestor (2R) followed by a third round in the teleost ancestor (3R). Related chromosome regions resulting from WGD or block duplications are said to form a paralogon. We describe here a paralogon containing the genes for visual opsins, the G-protein alpha subunit families for transducin (GNAT) and adenylyl cyclase inhibition (GNAI), the oxytocin and vasopressin receptors (OT/VP-R), and the L-type voltage-gated calcium channels (CACNA1-L).

RESULTS

Sequence-based phylogenies and analyses of conserved synteny show that the above-mentioned gene families, and many neighboring gene families, expanded in the early vertebrate WGDs. This allows us to deduce the following evolutionary scenario: The vertebrate ancestor had a chromosome containing the genes for two visual opsins, one GNAT, one GNAI, two OT/VP-Rs and one CACNA1-L gene. This chromosome was quadrupled in 2R. Subsequent gene losses resulted in a set of five visual opsin genes, three GNAT and GNAI genes, six OT/VP-R genes and four CACNA1-L genes. These regions were duplicated again in 3R resulting in additional teleost genes for some of the families. Major chromosomal rearrangements have taken place in the teleost genomes. By comparison with the corresponding chromosomal regions in the spotted gar, which diverged prior to 3R, we could time these rearrangements to post-3R.

CONCLUSIONS

We present an extensive analysis of the paralogon housing the visual opsin, GNAT and GNAI, OT/VP-R, and CACNA1-L gene families. The combined data imply that the early vertebrate WGD events contributed to the evolution of vision and the other neuronal and neuroendocrine functions exerted by the proteins encoded by these gene families. In pouched lamprey all five visual opsin genes have previously been identified, suggesting that lampreys diverged from the jawed vertebrates after 2R.

FunCoup 3.0: database of genome-wide functional coupling networks

We present an update of the FunCoup database (http://FunCoup.sbc.su.se) of functional couplings, or functional associations, between genes and gene products. Identifying these functional couplings is an important step in the understanding of higher level mechanisms performed by complex cellular processes. FunCoup distinguishes between four classes of couplings: participation in the same signaling cascade, participation in the same metabolic process, co-membership in a protein complex and physical interaction. For each of these four classes, several types of experimental and statistical evidence are combined by Bayesian integration to predict genome-wide functional coupling networks. The FunCoup framework has been completely re-implemented to allow for more frequent future updates. It contains many improvements, such as a regularization procedure to automatically downweight redundant evidences and a novel method to incorporate phylogenetic profile similarity. Several datasets have been updated and new data have been added in FunCoup 3.0. Furthermore, we have developed a new Web site, which provides powerful tools to explore the predicted networks and to retrieve detailed information about the data underlying each prediction.

Intronic non-CG DNA hydroxymethylation and alternative mRNA splicing in honey bees

Background

Previous whole-genome shotgun bisulfite sequencing experiments showed that DNA cytosine methylation in the honey bee (Apis mellifera) is almost exclusively at CG dinucleotides in exons. However, the most commonly used method, bisulfite sequencing, cannot distinguish 5-methylcytosine from 5-hydroxymethylcytosine, an oxidized form of 5-methylcytosine that is catalyzed by the TET family of dioxygenases. Furthermore, some analysis software programs under-represent non-CG DNA methylation and hydryoxymethylation for a variety of reasons. Therefore, we used an unbiased analysis of bisulfite sequencing data combined with molecular and bioinformatics approaches to distinguish 5-methylcytosine from 5-hydroxymethylcytosine. By doing this, we have performed the first whole genome analyses of DNA modifications at non-CG sites in honey bees and correlated the effects of these DNA modifications on gene expression and alternative mRNA splicing.

Results

We confirmed, using unbiased analyses of whole-genome shotgun bisulfite sequencing (BS-seq) data, with both new data and published data, the previous finding that CG DNA methylation is enriched in exons in honey bees. However, we also found evidence that cytosine methylation and hydroxymethylation at non-CG sites is enriched in introns. Using antibodies against 5-hydroxmethylcytosine, we confirmed that DNA hydroxymethylation at non-CG sites is enriched in introns. Additionally, using a new technique, Pvu-seq (which employs the enzyme PvuRts1l to digest DNA at 5-hydroxymethylcytosine sites followed by next-generation DNA sequencing), we further confirmed that hydroxymethylation is enriched in introns at non-CG sites.

Conclusions

Cytosine hydroxymethylation at non-CG sites might have more functional significance than previously appreciated, and in honey bees these modifications might be related to the regulation of alternative mRNA splicing by defining the locations of the introns.

Ultrasonic incisions produce less inflammatory mediator response during early healing than electrosurgical incisions

As the use of laparoscopic surgery has become more widespread in recent years, the need has increased for minimally-invasive surgical devices that effectively cut and coagulate tissue with reduced tissue trauma. Although electrosurgery (ES) has been used for many generations, newly-developed ultrasonic devices (HARMONIC® Blade, HB) have been shown at a macroscopic level to offer better coagulation with less thermally-induced tissue damage. We sought to understand the differences between ES and HB at a microscopic level by comparing mRNA transcript and protein responses at the 3-day timepoint to incisions made by the devices in subcutaneous fat tissue in a porcine model. Samples were also assessed via histological examination. ES-incised tissue had more than twice as many differentially-expressed genes as HB (2,548 vs 1,264 respectively), and more differentially-expressed proteins (508 vs 432) compared to control (untreated) tissue. Evaluation of molecular functions using Gene Ontology showed that gene expression changes for the energized devices reflected the start of wound healing, including immune response and inflammation, while protein expression showed a slightly earlier stage, with some remnants of hemostasis. For both transcripts and proteins, ES exhibited a greater response than HB, especially in inflammatory mediators. These findings were in qualitative agreement with histological results. This study has shown that transcriptomics and proteomics can monitor the wound healing response following surgery and can differentiate between surgical devices. In agreement with clinical observations, electrosurgery was shown to incur a greater inflammatory immune response than an ultrasonic device during initial iatrogenic wound healing.

Spatial and functional organization of mitochondrial protein network

Characterizing the spatial organization of the human mitochondrial proteome will enhance our understanding of mitochondrial functions at the molecular level and provide key insight into protein-disease associations. However, the sub-organellar location and possible association with mitochondrial diseases are not annotated for most mitochondrial proteins. Here, we characterized the functional and spatial organization of mitochondrial proteins by assessing their position in the Mitochondrial Protein Functional (MPF) network. Network position was assigned to the MPF network and facilitated the determination of sub-organellar location and functional organization of mitochondrial proteins. Moreover, network position successfully identified candidate disease genes of several mitochondrial disorders. Thus, our data support the use of network position as a novel method to explore the molecular function and pathogenesis of mitochondrial proteins.

Circadian rhythms of sense and antisense transcription in sugarcane, a highly polyploid crop

Commercial sugarcane (Saccharum hybrid) is a highly polyploid and aneuploid grass that stores large amounts of sucrose in its stem. We have measured circadian rhythms of sense and antisense transcription in a commercial cultivar (RB855453) using a custom oligoarray with 14,521 probes that hybridize to sense transcripts (SS) and 7,380 probes that hybridize to antisense transcripts (AS).We estimated that 32% of SS probes and 22% AS probes were rhythmic. This is a higher proportion of rhythmic probes than the usually found in similar experiments in other plant species. Orthologs and inparalogs of Arabidopsis thaliana, sugarcane, rice, maize and sorghum were grouped in ortholog clusters. When ortholog clusters were used to compare probes among different datasets, sugarcane also showed a higher proportion of rhythmic elements than the other species. Thus, it is possible that a higher proportion of transcripts are regulated by the sugarcane circadian clock. Thirty-six percent of the identified AS/SS pairs had significant correlated time courses and 64% had uncorrelated expression patterns. The clustering of transcripts with similar function, the anticipation of daily environmental changes and the temporal compartmentation of metabolic processes were some properties identified in the circadian sugarcane transcriptome. During the day, there was a dominance of transcripts associated with photosynthesis and carbohydrate metabolism, including sucrose and starch synthesis. During the night, there was dominance of transcripts associated with genetic processing, such as histone regulation and RNA polymerase, ribosome and protein synthesis. Finally, the circadian clock also regulated hormone signalling pathways: a large proportion of auxin and ABA signalling components were regulated by the circadian clock in an unusual biphasic distribution.

The genome of tolypocladium inflatum: evolution, organization, and expression of the cyclosporin biosynthetic gene cluster

The ascomycete fungus Tolypocladium inflatum, a pathogen of beetle larvae, is best known as the producer of the immunosuppressant drug cyclosporin. The draft genome of T. inflatum strain NRRL 8044 (ATCC 34921), the isolate from which cyclosporin was first isolated, is presented along with comparative analyses of the biosynthesis of cyclosporin and other secondary metabolites in T. inflatum and related taxa. Phylogenomic analyses reveal previously undetected and complex patterns of homology between the nonribosomal peptide synthetase (NRPS) that encodes for cyclosporin synthetase (simA) and those of other secondary metabolites with activities against insects (e.g., beauvericin, destruxins, etc.), and demonstrate the roles of module duplication and gene fusion in diversification of NRPSs. The secondary metabolite gene cluster responsible for cyclosporin biosynthesis is described. In addition to genes necessary for cyclosporin biosynthesis, it harbors a gene for a cyclophilin, which is a member of a family of immunophilins known to bind cyclosporin. Comparative analyses support a lineage specific origin of the cyclosporin gene cluster rather than horizontal gene transfer from bacteria or other fungi. RNA-Seq transcriptome analyses in a cyclosporin-inducing medium delineate the boundaries of the cyclosporin cluster and reveal high levels of expression of the gene cluster cyclophilin. In medium containing insect hemolymph, weaker but significant upregulation of several genes within the cyclosporin cluster, including the highly expressed cyclophilin gene, was observed. T. inflatum also represents the first reference draft genome of Ophiocordycipitaceae, a third family of insect pathogenic fungi within the fungal order Hypocreales, and supports parallel and qualitatively distinct radiations of insect pathogens. The T. inflatum genome provides additional insight into the evolution and biosynthesis of cyclosporin and lays a foundation for further investigations of the role of secondary metabolite gene clusters and their metabolites in fungal biology.