Inparanoid: a comprehensive database of eukaryotic orthologs

Construction of protein-protein interaction network in sulfate-reducing bacteria: Unveiling of global response to Hg

Sulfate-reducing bacteria (SRB) play pivotal roles in the biotransformation of mercury (Hg). However, unrevealed global responses of SRB to Hg have restricted our understanding of details of Hg biotransformation processes. The absence of protein-protein interaction (PPI) network under Hg stimuli has been a bottleneck of proteomic analysis for molecular mechanisms of Hg transformation. This study constructed the first comprehensive PPI network of SRB in response to Hg, encompassing 67 connected nodes, 26 independent nodes, and 121 edges, covering 93% of differentially expressed proteins from both previous studies and this study. The network suggested that proteomic changes of SRB in response to Hg occurred globally, including microbial metabolism in diverse environments, carbon metabolism, nucleic acid metabolism and translation, nucleic acid repair, transport systems, nitrogen metabolism, and methyltransferase activity, partial of which could cover the known knowledge. Antibiotic resistance was the original response revealed by this network, providing insights into of Hg biotransformation mechanisms. This study firstly provided the foundational network for a comprehensive understanding of SRB's responses to Hg, convenient for exploration of potential targets for Hg biotransformation. Furthermore, the network indicated that Hg enhances the metabolic activities and modification pathways of SRB to maintain cellular activities, shedding light on the influences of Hg on the carbon, nitrogen, and sulfur cycles at the cellular level.

Seagrass genomes reveal ancient polyploidy and adaptations to the marine environment

We present chromosome-level genome assemblies from representative species of three independently evolved seagrass lineages: Posidonia oceanica, Cymodocea nodosa, Thalassia testudinum and Zostera marina. We also include a draft genome of Potamogeton acutifolius, belonging to a freshwater sister lineage to Zosteraceae. All seagrass species share an ancient whole-genome triplication, while additional whole-genome duplications were uncovered for C. nodosa, Z. marina and P. acutifolius. Comparative analysis of selected gene families suggests that the transition from submerged-freshwater to submerged-marine environments mainly involved fine-tuning of multiple processes (such as osmoregulation, salinity, light capture, carbon acquisition and temperature) that all had to happen in parallel, probably explaining why adaptation to a marine lifestyle has been exceedingly rare. Major gene losses related to stomata, volatiles, defence and lignification are probably a consequence of the return to the sea rather than the cause of it. These new genomes will accelerate functional studies and solutions, as continuing losses of the 'savannahs of the sea' are of major concern in times of climate change and loss of biodiversity.

Improved integration of single-cell transcriptome data demonstrates common and unique signatures of heart failure in mice and humans

BACKGROUND

Cardiovascular research heavily relies on mouse (Mus musculus) models to study disease mechanisms and to test novel biomarkers and medications. Yet, applying these results to patients remains a major challenge and often results in noneffective drugs. Therefore, it is an open challenge of translational science to develop models with high similarities and predictive value. This requires a comparison of disease models in mice with diseased tissue derived from humans.

RESULTS

To compare the transcriptional signatures at single-cell resolution, we implemented an integration pipeline called OrthoIntegrate, which uniquely assigns orthologs and therewith merges single-cell RNA sequencing (scRNA-seq) RNA of different species. The pipeline has been designed to be as easy to use and is fully integrable in the standard Seurat workflow.We applied OrthoIntegrate on scRNA-seq from cardiac tissue of heart failure patients with reduced ejection fraction (HFrEF) and scRNA-seq from the mice after chronic infarction, which is a commonly used mouse model to mimic HFrEF. We discovered shared and distinct regulatory pathways between human HFrEF patients and the corresponding mouse model. Overall, 54% of genes were commonly regulated, including major changes in cardiomyocyte energy metabolism. However, several regulatory pathways (e.g., angiogenesis) were specifically regulated in humans.

CONCLUSIONS

The demonstration of unique pathways occurring in humans indicates limitations on the comparability between mice models and human HFrEF and shows that results from the mice model should be validated carefully. OrthoIntegrate is publicly accessible (https://github.com/MarianoRuzJurado/OrthoIntegrate) and can be used to integrate other large datasets to provide a general comparison of models with patient data.

John N, Zaidi F, Doyle F, Fasullo M. High-throughput screening of the Saccharomyces cerevisiae genome for 2-amino-3-methylimidazo [4,5-f] quinoline resistance identifies colon cancer-associated genes

Heterocyclic aromatic amines (HAAs) are potent carcinogenic agents found in charred meats and cigarette smoke. However, few eukaryotic resistance genes have been identified. We used Saccharomyces cerevisiae (budding yeast) to identify genes that confer resistance to 2-amino-3-methylimidazo[4,5-f] quinoline (IQ). CYP1A2 and NAT2 activate IQ to become a mutagenic nitrenium compound. Deletion libraries expressing human CYP1A2 and NAT2 or no human genes were exposed to either 400 or 800 µM IQ for 5 or 10 generations. DNA barcodes were sequenced using the Illumina HiSeq 2500 platform and statistical significance was determined for exactly matched barcodes. We identified 424 ORFs, including 337 genes of known function, in duplicate screens of the "humanized" collection for IQ resistance; resistance was further validated for a select group of 51 genes by growth curves, competitive growth, or trypan blue assays. Screens of the library not expressing human genes identified 143 ORFs conferring resistance to IQ per se. Ribosomal protein and protein modification genes were identified as IQ resistance genes in both the original and "humanized" libraries, while nitrogen metabolism, DNA repair, and growth control genes were also prominent in the "humanized" library. Protein complexes identified included the casein kinase 2 (CK2) and histone chaperone (HIR) complex. Among DNA Repair and checkpoint genes, we identified those that function in postreplication repair (RAD18, UBC13, REV7), base excision repair (NTG1), and checkpoint signaling (CHK1, PSY2). These studies underscore the role of ribosomal protein genes in conferring IQ resistance, and illuminate DNA repair pathways for conferring resistance to activated IQ.

Resistance gene-guided genome mining reveals the roseopurpurins as inhibitors of cyclin-dependent kinases

With the significant increase in the availability of microbial genome sequences in recent years, resistance gene-guided genome mining has emerged as a powerful approach for identifying natural products with specific bioactivities. Here, we present the use of this approach to reveal the roseopurpurins as potent inhibitors of cyclin-dependent kinases (CDKs), a class of cell cycle regulators implicated in multiple cancers. We identified a biosynthetic gene cluster (BGC) with a putative resistance gene with homology to human CDK2. Using targeted gene disruption and transcription factor overexpression in Aspergillus uvarum, and heterologous expression of the BGC in Aspergillus nidulans, we demonstrated that roseopurpurin C (1) is produced by this cluster and characterized its biosynthesis. We determined the potency, specificity, and mechanism of action of 1 as well as multiple intermediates and shunt products produced from the BGC. We show that 1 inhibits human CDK2 with a Kiapp of 44 nM, demonstrates selectivity for clinically relevant members of the CDK family, and induces G1 cell cycle arrest in HCT116 cells. Structural analysis of 1 complexed with CDK2 revealed the molecular basis of ATP-competitive inhibition.

Early urinary candidate biomarkers and clinical outcomes of intervention in a rat model of experimental autoimmune encephalomyelitis

Multiple sclerosis is a chronic autoimmune demyelinating disease of the central nervous system and is difficult to diagnose in early stages. Without homeostatic control, urine was reported to have the ability to accumulate early changes in the body. We expect that urinary proteome can reflect early changes in the nervous system. The early urinary proteome changes in a most employed multiple sclerosis rat model (experimental autoimmune encephalomyelitis) were analysed to explore early urinary candidate biomarkers, and early treatment of methylprednisolone was used to evaluate the therapeutic effect. Twenty-five urinary proteins were altered at day 7 when there were no clinical symptoms and obvious histological changes. Fourteen were reported to be differently expressed in the serum/cerebrospinal fluid/brain tissues of multiple sclerosis patients or animals such as angiotensinogen and matrix metallopeptidase 8. Functional analysis showed that the dysregulated proteins were associated with asparagine degradation, neuroinflammation and lipid metabolism. After the early treatment of methylprednisolone, the incidence of encephalomyelitis in the intervention group was only 1/13. This study demonstrates that urine may be a good source of biomarkers for the early detection of multiple sclerosis. These findings may provide important information for early diagnosis and intervention of multiple sclerosis in the future.

Transgressive and parental dominant gene expression and cytosine methylation during seed development in Brassica napus hybrids

KEY MESSAGE

Transcriptomic and epigenomic profiling of gene expression and small RNAs during seed and seedling development reveals expression and methylation dominance levels with implications on early stage heterosis in oilseed rape. The enhanced performance of hybrids through heterosis remains a key aspect in plant breeding; however, the underlying mechanisms are still not fully elucidated. To investigate the potential role of transcriptomic and epigenomic patterns in early expression of hybrid vigor, we investigated gene expression, small RNA abundance and genome-wide methylation in hybrids from two distant Brassica napus ecotypes during seed and seedling developmental stages using next-generation sequencing. A total of 31117, 344, 36229 and 7399 differentially expressed genes, microRNAs, small interfering RNAs and differentially methylated regions were identified, respectively. Approximately 70% of the differentially expressed or methylated features displayed parental dominance levels where the hybrid followed the same patterns as the parents. Via gene ontology enrichment and microRNA-target association analyses during seed development, we found copies of reproductive, developmental and meiotic genes with transgressive and paternal dominance patterns. Interestingly, maternal dominance was more prominent in hypermethylated and downregulated features during seed formation, contrasting to the general maternal gamete demethylation reported during gametogenesis in angiosperms. Associations between methylation and gene expression allowed identification of putative epialleles with diverse pivotal biological functions during seed formation. Furthermore, most differentially methylated regions, differentially expressed siRNAs and transposable elements were in regions that flanked genes without differential expression. This suggests that differential expression and methylation of epigenomic features may help maintain expression of pivotal genes in a hybrid context. Differential expression and methylation patterns during seed formation in an F₁ hybrid provide novel insights into genes and mechanisms with potential roles in early heterosis.

High resolution genomes of multiple Xiphophorus species provide new insights into microevolution, hybrid incompatibility, and epistasis

Because of diverged adaptative phenotypes, fish species of the genus Xiphophorus have contributed to a wide range of research for a century. Existing Xiphophorus genome assemblies are not at the chromosomal level and are prone to sequence gaps, thus hindering advancement of the intra- and inter-species differences for evolutionary, comparative, and translational biomedical studies. Herein, we assembled high-quality chromosome-level genome assemblies for three distantly related Xiphophorus species, namely, X. maculatus, X. couchianus, and X. hellerii Our overall goal is to precisely assess microevolutionary processes in the clade to ascertain molecular events that led to the divergence of the Xiphophorus species and to progress understanding of genetic incompatibility to disease. In particular, we measured intra- and inter-species divergence and assessed gene expression dysregulation in reciprocal interspecies hybrids among the three species. We found expanded gene families and positively selected genes associated with live bearing, a special mode of reproduction. We also found positively selected gene families are significantly enriched in nonpolymorphic transposable elements, suggesting the dispersal of these nonpolymorphic transposable elements has accompanied the evolution of the genes, possibly by incorporating new regulatory elements in support of the Britten-Davidson hypothesis. We characterized inter-specific polymorphisms, structural variants, and polymorphic transposable element insertions and assessed their association to interspecies hybridization-induced gene expression dysregulation related to specific disease states in humans.

lron-11 guides axons in the ventral nerve cord of Caenorhabditis elegans

For the nervous system to develop properly, neurons must connect in a precise way to form functional networks. This requires that outgrowing neuronal processes (axons) navigate to their target areas, where they establish proper synaptic connections. The molecular basis of this navigation process is not firmly understood. A candidate family containing putative receptors acting in various aspects of neuronal development including axon navigation are transmembrane proteins of the extracellular Leucine-Rich Repeat family (eLRRs). We systematically tested members of this family in C. elegans for a role in axon navigation in the ventral nerve cord (VNC). We found that lron-11 mutants showed VNC navigation defects in several classes of neurons, including a pioneer neuron and various classes of interneurons and motoneurons. This suggests that while most members of the lron-family do not seem to have a role in axon navigation in the VNC, lron-11 is likely to be a receptor required for correct navigation of axons in the VNC of C. elegans.

Frequent spontaneous structural rearrangements promote rapid genome diversification in a Brassica napus F1 generation

In a cross between two homozygous Brassica napus plants of synthetic and natural origin, we demonstrate that novel structural genome variants from the synthetic parent cause immediate genome diversification among F1 offspring. Long read sequencing in twelve F1 sister plants revealed five large-scale structural rearrangements where both parents carried different homozygous alleles but the heterozygous F1 genomes were not identical heterozygotes as expected. Such spontaneous rearrangements were part of homoeologous exchanges or segmental deletions and were identified in different, individual F1 plants. The variants caused deletions, gene copy-number variations, diverging methylation patterns and other structural changes in large numbers of genes and may have been causal for unexpected phenotypic variation between individual F1 sister plants, for example strong divergence of plant height and leaf area. This example supports the hypothesis that spontaneous de novo structural rearrangements after de novo polyploidization can rapidly overcome intense allopolyploidization bottlenecks to re-expand crops genetic diversity for ecogeographical expansion and human selection. The findings imply that natural genome restructuring in allopolyploid plants from interspecific hybridization, a common approach in plant breeding, can have a considerably more drastic impact on genetic diversity in agricultural ecosystems than extremely precise, biotechnological genome modifications.

Behavioral innovation and genomic novelty are associated with the exploitation of a challenging dietary opportunity by an avivorous bat

Foraging on nocturnally migrating birds is one of the most challenging foraging tasks in the animal kingdom. Only three bat species (e.g., Ia io) known to date can prey on migratory birds. However, how these bats have exploited this challenging dietary niche remains unknown. Here, we demonstrate that I. io hunts at the altitude of migrating birds during the bird migration season. The foraging I. io exhibited high flight altitudes (up to 4945 m above sea level) and high flight speeds (up to 143.7 km h⁻¹). I. io in flight can actively prey on birds in the night sky via echolocation cues. Genes associated with DNA damage repair, hypoxia adaptation, biting and mastication, and digestion and metabolism have evolved to adapt to this species’ avivorous habits. Our results suggest that the evolution of behavioral innovation and genomic novelty are associated with the exploitation of challenging dietary opportunities.

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Predation on nocturnally migrating birds is rare and challenging in nature

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Bats exhibit high flight altitude and speed associated with foraging on migrating birds

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Bats can actively prey on birds in the night sky via echolocation cues

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The adaptive evolution of genes enables bats to adapt to the avivorous habits

Multilayered Networks of SalmoNet2 Enable Strain Comparisons of the Salmonella Genus on a Molecular Level

Serovars of the genus Salmonella primarily evolved as gastrointestinal pathogens in a wide range of hosts. Some serotypes later evolved further, adopting a more invasive lifestyle in a narrower host range associated with systemic infections. A system-level knowledge of these pathogens could identify the complex adaptations associated with the evolution of serovars with distinct pathogenicity, host range, and risk to human health. This promises to aid the design of interventions and serve as a knowledge base in the Salmonella research community. Here, we present SalmoNet2, a major update to SalmoNet1, the first multilayered interaction resource for Salmonella strains, containing protein-protein, transcriptional regulatory, and enzyme-enzyme interactions. The new version extends the number of Salmonella networks from 11 to 20. We now include a strain from the second species in the Salmonella genus, a strain from the Salmonella enterica subspecies arizonae and additional strains of importance from the subspecies enterica, including S. Typhimurium strain D23580, an epidemic multidrug-resistant strain associated with invasive nontyphoidal salmonellosis (iNTS). The database now uses strain specific metabolic models instead of a generalized model to highlight differences between strains. The update has increased the coverage of high-quality protein-protein interactions, and enhanced interoperability with other computational resources by adopting standardized formats. The resource website has been updated with tutorials to help researchers analyze their Salmonella data using molecular interaction networks from SalmoNet2. SalmoNet2 is accessible at http://salmonet.org/. IMPORTANCE Multilayered network databases collate interaction information from multiple sources, and are powerful both as a knowledge base and subject of analysis. Here, we present SalmoNet2, an integrated network resource containing protein-protein, transcriptional regulatory, and metabolic interactions for 20 Salmonella strains. Key improvements to the update include expanding the number of strains, strain-specific metabolic networks, an increase in high-quality protein-protein interactions, community standard computational formats to help interoperability, and online tutorials to help users analyze their data using SalmoNet2.

System analysis of Lipomyces starkeyi during growth on various plant-based sugars

Oleaginous yeasts have received significant attention due to their substantial lipid storage capability. The accumulated lipids can be utilized directly or processed into various bioproducts and biofuels. Lipomyces starkeyi is an oleaginous yeast capable of using multiple plant-based sugars, such as glucose, xylose, and cellobiose. It is, however, a relatively unexplored yeast due to limited knowledge about its physiology. In this study, we have evaluated the growth of L. starkeyi on different sugars and performed transcriptomic and metabolomic analyses to understand the underlying mechanisms of sugar metabolism. Principal component analysis showed clear differences resulting from growth on different sugars. We have further reported various metabolic pathways activated during growth on these sugars. We also observed non-specific regulation in L. starkeyi and have updated the gene annotations for the NRRL Y-11557 strain. This analysis provides a foundation for understanding the metabolism of these plant-based sugars and potentially valuable information to guide the metabolic engineering of L. starkeyi to produce bioproducts and biofuels. KEY POINTS: • L. starkeyi metabolism reprograms for consumption of different plant-based sugars. • Non-specific regulation was observed during growth on cellobiose. • L. starkeyi secretes β-glucosidases for extracellular hydrolysis of cellobiose.

Melanoma RBPome identification reveals PDIA6 as an unconventional RNA-binding protein involved in metastasis

RNA-binding proteins (RBPs) have been relatively overlooked in cancer research despite their contribution to virtually every cancer hallmark. Here, we use RNA interactome capture (RIC) to characterize the melanoma RBPome and uncover novel RBPs involved in melanoma progression. Comparison of RIC profiles of a non-tumoral versus a metastatic cell line revealed prevalent changes in RNA-binding capacities that were not associated with changes in RBP levels. Extensive functional validation of a selected group of 24 RBPs using five different in vitro assays unveiled unanticipated roles of RBPs in melanoma malignancy. As proof-of-principle we focused on PDIA6, an ER-lumen chaperone that displayed a novel RNA-binding activity. We show that PDIA6 is involved in metastatic progression, map its RNA-binding domain, and find that RNA binding is required for PDIA6 tumorigenic properties. These results exemplify how RIC technologies can be harnessed to uncover novel vulnerabilities of cancer cells.

How much do model organism phenotypes contribute to the computational identification of human disease genes?

Computing phenotypic similarity helps identify new disease genes and diagnose rare diseases. Genotype–phenotype data from orthologous genes in model organisms can compensate for lack of human data and increase genome coverage. In the past decade, cross-species phenotype comparisons have proven valuble, and several ontologies have been developed for this purpose. The relative contribution of different model organisms to computational identification of disease-associated genes is not fully explored. We used phenotype ontologies to semantically relate phenotypes resulting from loss-of-function mutations in model organisms to disease-associated phenotypes in humans. Semantic machine learning methods were used to measure the contribution of different model organisms to the identification of known human gene–disease associations. We found that mouse genotype–phenotype data provided the most important dataset in the identification of human disease genes by semantic similarity and machine learning over phenotype ontologies. Other model organisms' data did not improve identification over that obtained using the mouse alone, and therefore did not contribute significantly to this task. Our work impacts on the development of integrated phenotype ontologies, as well as for the use of model organism phenotypes in human genetic variant interpretation.

This article has an associated First Person interview with the first author of the paper.

Editor's choice: We investigated the use of model organism phenotypes in the computational identification of disease genes, identifying several data biases and concluding that mouse model phenotypes contribute most to computational disease gene identification.

Comprehensive molecular evaluation of the histone methyltransferase gene family and their important roles in two-line hybrid wheat

BACKGROUND

Histone methylation usually plays important roles in plant development through post-translational regulation and may provide a new visual field for heterosis. The histone methyltransferase gene family has been identified in various plants, but its members and functions in hybrid wheat related in heterosis is poorly studied.

RESULTS

In this study, 175 histone methyltransferase (HMT) genes were identified in wheat, including 152 histone lysine methyltransferase (HKMT) genes and 23 protein arginine methyltransferase (PRMT) genes. Gene structure analysis, physicochemical properties and subcellular localization predictions of the proteins, exhibited the adequate complexity of this gene family. As an allohexaploid species, the number of the genes (seven HKMTs orthologous groups and four PRMTs orthologous groups) in wheat were about three times than those in diploids and showed certain degrees of conservation, while only a small number of subfamilies such as ASH-like and Su-(var) subfamilies have expanded their members. Transcriptome analysis showed that HMT genes were mainly expressed in the reproductive organs. Expression analysis showed that some TaHMT genes with different trends in various hybrid combinations may be regulated by lncRNAs with similar expression trends. Pearson correlation analysis of the expression of TaHMT genes and two yield traits indicated that four DEGs may participate in the yield heterosis of two-line hybrid wheat. ChIP-qPCR results showed that the histone modifications (H3K4me3, H3K36me3 and H3K9ac) enriched in promoter regions of three TaCCA1 genes which are homologous to Arabidopsis heterosis-related CCA1/LHY genes. The higher expression levels of TaCCA1 in F₁ than its parents are positive with these histone modifications. These results showed that histone modifications may play important roles in wheat heterosis.

CONCLUSIONS

Our study identified characteristics of the histone methyltransferase gene family and enhances the understanding of the evolution and function of these members in allohexaploid wheat. The causes of heterosis of two-line hybrid wheat were partially explained from the perspective of histone modifications.

FertilityOnline: A Straightforward Pipeline for Functional Gene Annotation and Disease Mutation Discovery

Exploring the genetic basis of human infertility is currently under intensive investigation. However, only a handful of genes have been validated in animal models as disease-causing genes in infertile men. Thus, to better understand the genetic basis of human spermatogenesis and bridge the knowledge gap between humans and other animal species, we construct the FertilityOnline, a database integrating the literature-curated functional genes during spermatogenesis into an existing spermatogenic database, SpermatogenesisOnline 1.0. Additional features, including the functional annotation and genetic variants of human genes, are also incorporated into FertilityOnline. By searching this database, users can browse the functional genes involved in spermatogenesis and instantly narrow down the number of candidates of genetic mutations underlying male infertility in a user-friendly web interface. Clinical application of this database was exampled by the identification of novel causative mutations in synaptonemal complex central element protein 1 (SYCE1) and stromal antigen 3 (STAG3) in azoospermic men. In conclusion, FertilityOnline is not only an integrated resource for spermatogenic genes but also a useful tool facilitating the exploration of the genetic basis of male infertility. FertilityOnline can be freely accessed at http://mcg.ustc.edu.cn/bsc/spermgenes2.0/index.html.

Conservation and architecture of housekeeping genes in the model marine diatom Thalassiosira pseudonana

Housekeeping genes (HKGs) are constitutively expressed with low variation across tissues/conditions. They are thought to be highly conserved and fundamental to cellular maintenance, with distinctive genomic features. Here, we identify 1505 HKGs in the unicellular marine diatom Thalassiosira pseudonana based on an RNA-seq analysis of 232 samples taken under 12 experimental conditions over 0-72 h. We identify promising internal reference genes (IRGs) for T. pseudonana from the most stably expressed HKGs. A comparative analysis indicates < 18% of HKGs in T. pseudonana have orthologs in other eukaryotes, including other diatom species. Contrary to work on human tissues, T. pseudonana HKGs are longer than non-HKGs, due to elongated introns. More ancient HKGs tend to be shorter than more recent HKGs, and expression levels of HKGs decrease more rapidly with gene length relative to non-HKGs. Our results indicate that HKGs are highly variable across the tree of life and thus unlikely to be universally fundamental for cellular maintenance. We hypothesize that the distinct genomic features of HKGs of T. pseudonana may be a consequence of selection pressures associated with high expression and low variance across conditions.

Predicted mouse interactome and network-based interpretation of differentially expressed genes

The house mouse or Mus musculus has become a premier mammalian model for genetic research due to its genetic and physiological similarities to humans. It brought mechanistic insights into numerous human diseases and has been routinely used to assess drug efficiency and toxicity, as well as to predict patient responses. To facilitate molecular mechanism studies in mouse, we present the Mouse Interactome Database (MID, Version 1), which includes 155,887 putative functional associations between mouse protein-coding genes inferred from functional association evidence integrated from 9 public databases. These putative functional associations are expected to cover 19.32% of all mouse protein interactions, and 26.02% of these function associations may represent protein interactions. On top of MID, we developed a gene set linkage analysis (GSLA) web tool to annotate potential functional impacts from observed differentially expressed genes. Two case studies show that the MID/GSLA system provided precise and informative annotations that other widely used gene set annotation tools, such as PANTHER and DAVID, did not. Both MID and GSLA are accessible through the website http://mouse.biomedtzc.cn.

New data and collaborations at the Saccharomyces Genome Database: updated reference genome, alleles, and the Alliance of Genome Resources

Saccharomyces cerevisiae is used to provide fundamental understanding of eukaryotic genetics, gene product function, and cellular biological processes. Saccharomyces Genome Database (SGD) has been supporting the yeast research community since 1993, serving as its de facto hub. Over the years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation, and developed various tools and methods for analysis and curation of a variety of emerging data types. More recently, SGD and six other model organism focused knowledgebases have come together to create the Alliance of Genome Resources to develop sustainable genome information resources that promote and support the use of various model organisms to understand the genetic and genomic bases of human biology and disease. Here we describe recent activities at SGD, including the latest reference genome annotation update, the development of a curation system for mutant alleles, and new pages addressing homology across model organisms as well as the use of yeast to study human disease.

Computational methods, databases and tools for synthetic lethality prediction

Synthetic lethality (SL) occurs between two genes when the inactivation of either gene alone has no effect on cell survival but the inactivation of both genes results in cell death. SL-based therapy has become one of the most promising targeted cancer therapies in the last decade as PARP inhibitors achieve great success in the clinic. The key point to exploiting SL-based cancer therapy is the identification of robust SL pairs. Although many wet-lab-based methods have been developed to screen SL pairs, known SL pairs are less than 0.1% of all potential pairs due to large number of human gene combinations. Computational prediction methods complement wet-lab-based methods to effectively reduce the search space of SL pairs. In this paper, we review the recent applications of computational methods and commonly used databases for SL prediction. First, we introduce the concept of SL and its screening methods. Second, various SL-related data resources are summarized. Then, computational methods including statistical-based methods, network-based methods, classical machine learning methods and deep learning methods for SL prediction are summarized. In particular, we elaborate on the negative sampling methods applied in these models. Next, representative tools for SL prediction are introduced. Finally, the challenges and future work for SL prediction are discussed.

Pollution induces epigenetic effects that are stably transmitted across multiple generations

It has been hypothesized that the effects of pollutants on phenotypes can be passed to subsequent generations through epigenetic inheritance, affecting populations long after the removal of a pollutant. But there is still little evidence that pollutants can induce persistent epigenetic effects in animals. Here, we show that low doses of commonly used pollutants induce genome‐wide differences in cytosine methylation in the freshwater crustacean Daphnia pulex. Uniclonal populations were either continually exposed to pollutants or switched to clean water, and methylation was compared to control populations that did not experience pollutant exposure. Although some direct changes to methylation were only present in the continually exposed populations, others were present in both the continually exposed and switched to clean water treatments, suggesting that these modifications had persisted for 7 months (>15 generations). We also identified modifications that were only present in the populations that had switched to clean water, indicating a long‐term legacy of pollutant exposure distinct from the persistent effects. Pollutant‐induced differential methylation tended to occur at sites that were highly methylated in controls. Modifications that were observed in both continually and switched treatments were highly methylated in controls and showed reduced methylation in the treatments. On the other hand, modifications found just in the switched treatment tended to have lower levels of methylation in the controls and showed increase methylation in the switched treatment. In a second experiment, we confirmed that sublethal doses of the same pollutants generate effects on life histories for at least three generations following the removal of the pollutant. Our results demonstrate that even low doses of pollutants can induce transgenerational epigenetic effects that are stably transmitted over many generations. Persistent effects are likely to influence phenotypic development, which could contribute to the rapid adaptation, or extinction, of populations confronted by anthropogenic stressors.

Comparative transcriptomics reveal tissue level specialization towards diet in prickleback fishes

Beyond a few obvious examples (e.g., gut length, amylase activity), digestive and metabolic specializations towards diet remain elusive in fishes. Thus, we compared gut length, δ¹³C and δ¹⁵N signatures of the liver, and expressed genes in the intestine and liver of wild-caught individuals of four closely-related, sympatric prickleback species (family Stichaeidae) with different diets: Xiphister mucosus (herbivore), its sister taxon X. atropurpureus (omnivore), Phytichthys chirus (omnivore) and the carnivorous Anoplarchus purpurescens. We also measured the same parameters after feeding them carnivore or omnivore diets in the laboratory for 4 weeks. Growth and isotopic signatures showed assimilation of the laboratory diets, and gut length was significantly longer in X. mucosus in comparison to the other fishes, whether in the wild, or in the lab consuming the different diets. Dozens of genes relating to digestion and metabolism were observed to be under selection in the various species, but P. chirus stood out with some genes in the liver showing strong positive selection, and these genes correlating with differing isotopic incorporation of the laboratory carnivore diet in this species. Although the intestine showed variation in the expression of hundreds of genes in response to the laboratory diets, the liver exhibited species-specific gene expression patterns that changed very little (generally <40 genes changing expression, with P. chirus providing an exception). Overall, our results suggest that the intestine is plastic in function, but the liver may be where specialization manifests since this tissue shows species-specific gene expression patterns that match with natural diet.

GRAND: An Integrated Genome, Transcriptome Resources, and Gene Network Database for Gossypium

With the increasing amount of cotton omics data, breeding scientists are confronted with the question of how to use massive cotton data to mine effective breeding information. Here, we construct a Gossypium Resource And Network Database (GRAND), which integrates 18 cotton genome sequences, genome annotations, two cotton genome variations information, and also four transcriptomes for Gossypium species. GRAND allows to explore and mine this data with the help of a toolbox that comprises a flexible search system, BLAST and BLAT suite, orthologous gene ID, networks of co-expressed genes, primer design, Gbrowse and Jbrowse, and drawing instruments. GRAND provides important information regarding Gossypium resources and hopefully can accelerate the progress of cultivating cotton varieties.

Enabling Studies of Genome-Scale Regulatory Network Evolution in Large Phylogenies with MRTLE

Transcriptional regulatory networks specify context-specific patterns of genes and play a central role in how species evolve and adapt. Inferring genome-scale regulatory networks in non-model species is the first step for examining patterns of conservation and divergence of regulatory networks. Transcriptomic data obtained under varying environmental stimuli in multiple species are becoming increasingly available, which can be used to infer regulatory networks. However, inference and analysis of multiple gene regulatory networks in a phylogenetic setting remains challenging. We developed an algorithm, Multi-species Regulatory neTwork LEarning (MRTLE), to facilitate such studies of regulatory network evolution. MRTLE is a probabilistic graphical model-based algorithm that uses phylogenetic structure, transcriptomic data for multiple species, and sequence-specific motifs in each species to simultaneously infer genome-scale regulatory networks across multiple species. We applied MRTLE to study regulatory network evolution across six ascomycete yeasts using transcriptomic measurements collected across different stress conditions. MRTLE networks recapitulated experimentally derived interactions in the model organism S. cerevisiae as well as non-model species, and it was more beneficial for network inference than methods that do not use phylogenetic information. We examined the regulatory networks across species and found that regulators associated with significant expression and network changes are involved in stress-related processes. MTRLE and its associated downstream analysis provide a scalable and principled framework to examine evolutionary dynamics of transcriptional regulatory networks across multiple species in a large phylogeny.

An integrated network analysis approach to identify potential key genes, transcription factors, and microRNAs regulating human hematopoietic stem cell aging

Hematopoietic stem cells (HSCs) undergo functional deterioration with increasing age that causes loss of their self-renewal and regenerative potential. Despite various efforts, significant success in identifying molecular regulators of HSC aging has not been achieved, one prime reason being the non-availability of appropriate human HSC samples. To demonstrate the scope of integrating and re-analyzing the HSC transcriptomics data available, we used existing tools and databases to structure a sequential data analysis pipeline to predict potential candidate genes, transcription factors, and microRNAs simultaneously. This sequential approach comprises (i) collecting matched young and aged mice HSC sample datasets, (ii) identifying differentially expressed genes, (iii) identifying human homologs of differentially expressed genes, (iv) inferring gene co-expression network modules, and (v) inferring the microRNA-transcription factor-gene regulatory network. Systems-level analyses of HSC interaction networks provided various insights based on which several candidates were predicted. For example, 16 HSC aging-related candidate genes were predicted (e.g., CD38, BRCA1, AGTR1, GSTM1, etc.) from GCN analysis. Following this, the shortest path distance-based analyses of the regulatory network predicted several novel candidate miRNAs and TFs. Among these, miR-124-3p was a common regulator in candidate gene modules, while TFs MYC and SP1 were identified to regulate various candidate genes. Based on the regulatory interactions among candidate genes, TFs, and miRNAs, a potential regulation model of biological processes in each of the candidate modules was predicted, which provided systems-level insights into the molecular complexity of each module to regulate HSC aging.

KinOrtho: a method for mapping human kinase orthologs across the tree of life and illuminating understudied kinases

BACKGROUND

Protein kinases are among the largest druggable family of signaling proteins, involved in various human diseases, including cancers and neurodegenerative disorders. Despite their clinical relevance, nearly 30% of the 545 human protein kinases remain highly understudied. Comparative genomics is a powerful approach for predicting and investigating the functions of understudied kinases. However, an incomplete knowledge of kinase orthologs across fully sequenced kinomes severely limits the application of comparative genomics approaches for illuminating understudied kinases. Here, we introduce KinOrtho, a query- and graph-based orthology inference method that combines full-length and domain-based approaches to map one-to-one kinase orthologs across 17 thousand species.

RESULTS

Using multiple metrics, we show that KinOrtho performed better than existing methods in identifying kinase orthologs across evolutionarily divergent species and eliminated potential false positives by flagging sequences without a proper kinase domain for further evaluation. We demonstrate the advantage of using domain-based approaches for identifying domain fusion events, highlighting a case between an understudied serine/threonine kinase TAOK1 and a metabolic kinase PIK3C2A with high co-expression in human cells. We also identify evolutionary fission events involving the understudied OBSCN kinase domains, further highlighting the value of domain-based orthology inference approaches. Using KinOrtho-defined orthologs, Gene Ontology annotations, and machine learning, we propose putative biological functions of several understudied kinases, including the role of TP53RK in cell cycle checkpoint(s), the involvement of TSSK3 and TSSK6 in acrosomal vesicle localization, and potential functions for the ULK4 pseudokinase in neuronal development.

CONCLUSIONS

In sum, KinOrtho presents a novel query-based tool to identify one-to-one orthologous relationships across thousands of proteomes that can be applied to any protein family of interest. We exploit KinOrtho here to identify kinase orthologs and show that its well-curated kinome ortholog set can serve as a valuable resource for illuminating understudied kinases, and the KinOrtho framework can be extended to any protein-family of interest.

Mutation of the nuclear pore complex component, aladin1, disrupts asymmetric cell division in Zea mays (maize)

The nuclear pore complex (NPC) regulates the movement of macromolecules between the nucleus and cytoplasm. Dysfunction of many components of the NPC results in human genetic diseases, including triple A syndrome (AAAS) as a result of mutations in ALADIN. Here, we report a nonsense mutation in the maize ortholog, aladin1 (ali1-1), at the orthologous amino acid residue of an AAAS allele from humans, alters plant stature, tassel architecture, and asymmetric divisions of subsidiary mother cells (SMCs). Crosses with the stronger nonsense allele ali1-2 identified complex allele interactions for plant height and aberrant SMC division. RNA-seq analysis of the ali1-1 mutant identified compensatory transcript accumulation for other NPC components as well as gene expression consequences consistent with conservation of ALADIN1 functions between humans and maize. These findings demonstrate that ALADIN1 is necessary for normal plant development, shoot architecture, and asymmetric cell division in maize.

Echolocation in soft-furred tree mice

Echolocation is the use of reflected sound to sense features of the environment. Here, we show that soft-furred tree mice (Typhlomys) echolocate based on multiple independent lines of evidence. Behavioral experiments show that these mice can locate and avoid obstacles in darkness using hearing and ultrasonic pulses. The proximal portion of their stylohyal bone fuses with the tympanic bone, a form previously only seen in laryngeally echolocating bats. Further, we found convergence of hearing-related genes across the genome and of the echolocation-related gene prestin between soft-furred tree mice and echolocating mammals. Together, our findings suggest that soft-furred tree mice are capable of echolocation, and thus are a new lineage of echolocating mammals.

Degradation of ester linkages in rice straw components by Sphingobium species recovered from the sea bottom using a non-secretory tannase-family α/β hydrolase

Microbial decomposition of allochthonous plant components imported into the aquatic environment is one of the vital steps of the carbon cycle on earth. To expand the knowledge of the biodegradation of complex plant materials in aquatic environments, we recovered a sunken wood from the bottom of Otsuchi Bay, situated in northeastern Japan in 2012. We isolated Sphingobium with high ferulic acid esterase activity. The strain, designated as OW59, grew on various aromatic compounds and sugars, occurring naturally in terrestrial plants. A genomic study of the strain suggested its role in degrading hemicelluloses. We identified a gene encoding a non-secretory tannase-family α/β hydrolase, which exhibited ferulic acid esterase activity. This enzyme shares the consensus catalytic triad (Ser-His-Asp) within the tannase family block X in the ESTHER database. The molecules, which had the same calculated elemental compositions, were produced consistently in both the enzymatic and microbial degradation of rice straw crude extracts. The non-secretory tannase-family α/β hydrolase activity may confer an important phenotypic feature on the strain to accelerate plant biomass degradation. Our study provides insights into the underlying biodegradation process of terrestrial plant polymers in aquatic environments.

pSONIC: Ploidy-aware Syntenic Orthologous Networks Identified via Collinearity

With the rapid rise in availability of high-quality genomes for closely related species, methods for orthology inference that incorporate synteny are increasingly useful. Polyploidy perturbs the 1:1 expected frequencies of orthologs between two species, complicating the identification of orthologs. Here we present a method of ortholog inference, Ploidy-aware Syntenic Orthologous Networks Identified via Collinearity (pSONIC). We demonstrate the utility of pSONIC using four species in the cotton tribe (Gossypieae), including one allopolyploid, and place between 75% and 90% of genes from each species into nearly 32,000 orthologous groups, 97% of which consist of at most singletons or tandemly duplicated genes—58.8% more than comparable methods that do not incorporate synteny. We show that 99% of singleton gene groups follow the expected tree topology and that our ploidy-aware algorithm recovers 97.5% identical groups when compared to splitting the allopolyploid into its two respective subgenomes, treating each as separate “species.”

Is Phylotranscriptomics as Reliable as Phylogenomics?

Phylogenomics, the study of phylogenetic relationships among taxa based on their genome sequences, has emerged as the preferred phylogenetic method because of the wealth of phylogenetic information contained in genome sequences. Genome sequencing, however, can be prohibitively expensive, especially for taxa with huge genomes and when many taxa need sequencing. Consequently, the less costly phylotranscriptomics has seen an increased use in recent years. Phylotranscriptomics reconstructs phylogenies using DNA sequences derived from transcriptomes, which are often orders of magnitude smaller than genomes. However, in the absence of corresponding genome sequences, comparative analyses of transcriptomes can be challenging and it is unclear whether phylotranscriptomics is as reliable as phylogenomics. Here, we respectively compare the phylogenomic and phylotranscriptomic trees of 22 mammals and 15 plants that have both sequenced nuclear genomes and publicly available RNA sequencing data from multiple tissues. We found that phylotranscriptomic analysis can be sensitive to orthologous gene identification. When a rigorous method for identifying orthologs is employed, phylogenomic and phylotranscriptomic trees are virtually identical to each other, regardless of the tissue of origin of the transcriptomes and whether the same tissue is used across species. These findings validate phylotranscriptomics, brighten its prospect, and illustrate the criticality of reliable ortholog detection in such practices.

Ongoing repair of migration-coupled DNA damage allows planarian adult stem cells to reach wound sites

Mechanical stress during cell migration may be a previously unappreciated source of genome instability, but the extent to which this happens in any animal in vivo remains unknown. We consider an in vivo system where the adult stem cells of planarian flatworms are required to migrate to a distal wound site. We observe a relationship between adult stem cell migration and ongoing DNA damage and repair during tissue regeneration. Migrating planarian stem cells undergo changes in nuclear shape and exhibit increased levels of DNA damage. Increased DNA damage levels reduce once stem cells reach the wound site. Stem cells in which DNA damage is induced prior to wounding take longer to initiate migration and migrating stem cell populations are more sensitive to further DNA damage than stationary stem cells. RNAi-mediated knockdown of DNA repair pathway components blocks normal stem cell migration, confirming that active DNA repair pathways are required to allow successful migration to a distal wound site. Together these findings provide evidence that levels of migration-coupled-DNA-damage are significant in adult stem cells and that ongoing migration requires DNA repair mechanisms. Our findings reveal that migration of normal stem cells in vivo represents an unappreciated source of damage, which could be a significant source of mutations in animals during development or during long-term tissue homeostasis.

Sex-Biased Gene Expression and Evolution in the Cerebrum and Syrinx of Chinese Hwamei (Garrulax canorus)

It is common that males and females display sexual dimorphisms, which usually result from sex-biased gene expression. Chinese hwamei (Garrulax canorus) is a good model for studying sex-biased gene expression because the song between the sexes is quite different. In this study, we analyze cerebrum and syrinx sex-biased gene expression and evolution using the de novo assembled Chinese hwamei transcriptome. In both the cerebrum and syrinx, our study revealed that most female-biased genes were actively expressed in females only, while most male-biased genes were actively expressed in both sexes. In addition, both male- and female-biased genes were enriched on the putative Z chromosome, suggesting the existence of sexually antagonistic genes and the insufficient dosage compensation of the Z-linked genes. We also identified a 9 Mb sex linkage region on the putative 4A chromosome which enriched more than 20% of female-biased genes. Resultantly, male-biased genes in both tissues had significantly higher Ka/Ks and effective number of codons (ENCs) than unbiased genes, and this suggested that male-biased genes which exhibit accelerated divergence may have resulted from positive selection. Taken together, our results initially revealed the reasons for the differences in singing behavior between males and females of Chinese hwamei.

Identification of Genetic Modifiers of TDP-43: Inflammatory Activation of Astrocytes for Neuroinflammation

Transactive response DNA-binding protein 43 (TDP-43) is a ubiquitously expressed DNA/RNA-binding protein linked to amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). TDP-43 has been implicated in numerous aspects of the mRNA life cycle, as well as in cell toxicity and neuroinflammation. In this study, we used the toxicity of the TDP-43 expression in Saccharomyces cerevisiae as an assay to identify TDP-43 genetic interactions. Specifically, we transformed human TDP-43 cDNAs of wild-type or disease-associated mutants (M337V and Q331K) en masse into 4653 homozygous diploid yeast deletion mutants and then used next-generation sequencing readouts of growth to identify yeast toxicity modifiers. Genetic interaction analysis provided a global view of TDP-43 pathways, some of which are known to be involved in cellular metabolic processes. Selected putative loci with the potential of genetic interactions with TDP-43 were assessed for associations with neurotoxicity and inflammatory activation of astrocytes. The pharmacological inhibition of succinate dehydrogenase flavoprotein subunit A (SDHA) and voltage-dependent anion-selective channel 3 (VDAC3) suppressed TDP-43-induced expression of proinflammatory cytokines in astrocytes, indicating the critical roles played by SDHA and VDAC3 in TDP-43 pathways during inflammatory activation of astrocytes and neuroinflammation. Thus, the findings of our TDP-43 genetic interaction screen provide a global landscape of TDP-43 pathways and may help improve our understanding of the roles of glia and neuroinflammation in ALS and FTD pathogenesis.

Comparative Genomic and Transcriptomic Analysis Reveals Specific Features of Gene Regulation in Kluyveromyces marxianus

Kluyveromyces marxianus is a promising host for producing bioethanol and heterologous proteins. It displays many superior traits to a conventional industrial yeast species, Saccharomyces cerevisiae, including fast growth, thermotolerance and the capacity to assimilate a wider variety of sugars. However, little is known about the mechanisms underlying the fast-growing feature of K. marxianus. In this study, we performed a comparative genomic analysis between K. marxianus and other Saccharomycetaceae species. Genes involved in flocculation, iron transport, and biotin biosynthesis have particularly high copies in K. marxianus. In addition, 60 K. marxianus specific genes were identified, 45% of which were upregulated during cultivation in rich medium and these genes may participate in glucose transport and mitochondrion related functions. Furthermore, the transcriptomic analysis revealed that under aerobic condition, normalized levels of genes participating in TCA cycles, respiration chain and ATP biosynthesis in the lag phase were higher in K. marxianus than those in S. cerevisiae. Levels of highly copied genes, genes involved in the respiratory chain and mitochondrion assembly, were upregulated in K. marxianus, but not in S. cerevisiae, in later time points during cultivation compared with those in the lag phase. Notably, during the fast-growing phase, genes involved in the respiratory chain, ATP synthesis and glucose transport were co-upregulated in K. marxianus. A few shared motifs in upstream sequences of relevant genes might result in the co-upregulation. Specific features in the co-regulations of gene expressions might contribute to the fast-growing phenotype of K. marxianus. Our study underscores the importance of genome-wide rewiring of the transcriptional network during evolution.

HIR V2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis

To facilitate biomedical studies of disease mechanisms, a high-quality interactome that connects functionally related genes is needed to help investigators formulate pathway hypotheses and to interpret the biological logic of a phenotype at the biological process level. Interactions in the updated version of the human interactome resource (HIR V2) were inferred from 36 mathematical characterizations of six types of data that suggest functional associations between genes. This update of the HIR consists of 88 069 pairs of genes (23.2% functional interactions of HIR V2 are in common with the previous version of HIR), representing functional associations that are of strengths similar to those between well-studied protein interactions. Among these functional interactions, 57% may represent protein interactions, which are expected to cover 32% of the true human protein interactome. The gene set linkage analysis (GSLA) tool is developed based on the high-quality HIR V2 to identify the potential functional impacts of the observed transcriptomic changes, helping to elucidate their biological significance and complementing the currently widely used enrichment-based gene set interpretation tools. A case study shows that the annotations reported by the HIR V2/GSLA system are more comprehensive and concise compared to those obtained by the widely used gene set annotation tools such as PANTHER and DAVID. The HIR V2 and GSLA are available at http://human.biomedtzc.cn.

Predicted Drosophila Interactome Resource and web tool for functional interpretation of differentially expressed genes

Drosophila melanogaster is a well-established model organism that is widely used in genetic studies. This species enjoys the availability of a wide range of research tools, well-annotated reference databases and highly similar gene circuitry to other insects. To facilitate molecular mechanism studies in Drosophila, we present the Predicted Drosophila Interactome Resource (PDIR), a database of high-quality predicted functional gene interactions. These interactions were inferred from evidence in 10 public databases providing information for functional gene interactions from diverse perspectives. The current version of PDIR includes 102 835 putative functional associations with balanced sensitivity and specificity, which are expected to cover 22.56% of all Drosophila protein interactions. This set of functional interactions is a good reference for hypothesis formulation in molecular mechanism studies. At the same time, these interactions also serve as a high-quality reference interactome for gene set linkage analysis (GSLA), which is a web tool for the interpretation of the potential functional impacts of a set of changed genes observed in transcriptomics analyses. In a case study, we show that the PDIR/GSLA system was able to produce a more comprehensive and concise interpretation of the collective functional impact of multiple simultaneously changed genes compared with the widely used gene set annotation tools, including PANTHER and David. PDIR and its associated GSLA service can be accessed at http://drosophila.biomedtzc.cn.

Giant lungfish genome elucidates the conquest of land by vertebrates

Lungfishes belong to lobe-fined fish (Sarcopterygii) that, in the Devonian period, 'conquered' the land and ultimately gave rise to all land vertebrates, including humans1-3. Here we determine the chromosome-quality genome of the Australian lungfish (Neoceratodus forsteri), which is known to have the largest genome of any animal. The vast size of this genome, which is about 14× larger than that of humans, is attributable mostly to huge intergenic regions and introns with high repeat content (around 90%), the components of which resemble those of tetrapods (comprising mainly long interspersed nuclear elements) more than they do those of ray-finned fish. The lungfish genome continues to expand independently (its transposable elements are still active), through mechanisms different to those of the enormous genomes of salamanders. The 17 fully assembled lungfish macrochromosomes maintain synteny to other vertebrate chromosomes, and all microchromosomes maintain conserved ancient homology with the ancestral vertebrate karyotype. Our phylogenomic analyses confirm previous reports that lungfish occupy a key evolutionary position as the closest living relatives to tetrapods4,5, underscoring the importance of lungfish for understanding innovations associated with terrestrialization. Lungfish preadaptations to living on land include the gain of limb-like expression in developmental genes such as hoxc13 and sall1 in their lobed fins. Increased rates of evolution and the duplication of genes associated with obligate air-breathing, such as lung surfactants and the expansion of odorant receptor gene families (which encode proteins involved in detecting airborne odours), contribute to the tetrapod-like biology of lungfishes. These findings advance our understanding of this major transition during vertebrate evolution.

Regulatory network analysis of Paneth cell and goblet cell enriched gut organoids using transcriptomics approaches

The epithelial lining of the small intestine consists of multiple cell types, including Paneth cells and goblet cells, that work in cohort to maintain gut health. 3D in vitro cultures of human primary epithelial cells, called organoids, have become a key model to study the functions of Paneth cells and goblet cells in normal and diseased conditions. Advances in these models include the ability to skew differentiation to particular lineages, providing a useful tool to study cell type specific function/dysfunction in the context of the epithelium. Here, we use comprehensive profiling of mRNA, microRNA and long non-coding RNA expression to confirm that Paneth cell and goblet cell enrichment of murine small intestinal organoids (enteroids) establishes a physiologically accurate model. We employ network analysis to infer the regulatory landscape altered by skewing differentiation, and using knowledge of cell type specific markers, we predict key regulators of cell type specific functions: Cebpa, Jun, Nr1d1 and Rxra specific to Paneth cells, Gfi1b and Myc specific for goblet cells and Ets1, Nr3c1 and Vdr shared between them. Links identified between these regulators and cellular phenotypes of inflammatory bowel disease (IBD) suggest that global regulatory rewiring during or after differentiation of Paneth cells and goblet cells could contribute to IBD aetiology. Future application of cell type enriched enteroids combined with the presented computational workflow can be used to disentangle multifactorial mechanisms of these cell types and propose regulators whose pharmacological targeting could be advantageous in treating IBD patients with Crohn's disease or ulcerative colitis.

Padhoc: a computational pipeline for pathway reconstruction on the fly

MOTIVATION

Molecular pathway databases represent cellular processes in a structured and standardized way. These databases support the community-wide utilization of pathway information in biological research and the computational analysis of high-throughput biochemical data. Although pathway databases are critical in genomics research, the fast progress of biomedical sciences prevents databases from staying up-to-date. Moreover, the compartmentalization of cellular reactions into defined pathways reflects arbitrary choices that might not always be aligned with the needs of the researcher. Today, no tool exists that allow the easy creation of user-defined pathway representations.

RESULTS

Here we present Padhoc, a pipeline for pathway ad hoc reconstruction. Based on a set of user-provided keywords, Padhoc combines natural language processing, database knowledge extraction, orthology search and powerful graph algorithms to create navigable pathways tailored to the user's needs. We validate Padhoc with a set of well-established Escherichia coli pathways and demonstrate usability to create not-yet-available pathways in model (human) and non-model (sweet orange) organisms.

AVAILABILITY AND IMPLEMENTATION

Padhoc is freely available at https://github.com/ConesaLab/padhoc.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Interrogation of kinase genetic interactions provides a global view of PAK1-mediated signal transduction pathways

Kinases are critical components of intracellular signaling pathways and have been extensively investigated with regard to their roles in cancer. p21-activated kinase-1 (PAK1) is a serine/threonine kinase that has been previously implicated in numerous biological processes, such as cell migration, cell cycle progression, cell motility, invasion, and angiogenesis, in glioma and other cancers. However, the signaling network linked to PAK1 is not fully defined. We previously reported a large-scale yeast genetic interaction screen using toxicity as a readout to identify candidate PAK1 genetic interactions. En masse transformation of the PAK1 gene into 4,653 homozygous diploid Saccharomyces cerevisiae yeast deletion mutants identified ∼400 candidates that suppressed yeast toxicity. Here we selected 19 candidate PAK1 genetic interactions that had human orthologs and were expressed in glioma for further examination in mammalian cells, brain slice cultures, and orthotopic glioma models. RNAi and pharmacological inhibition of potential PAK1 interactors confirmed that DPP4, KIF11, mTOR, PKM2, SGPP1, TTK, and YWHAE regulate PAK1-induced cell migration and revealed the importance of genes related to the mitotic spindle, proteolysis, autophagy, and metabolism in PAK1-mediated glioma cell migration, drug resistance, and proliferation. AKT1 was further identified as a downstream mediator of the PAK1-TTK genetic interaction. Taken together, these data provide a global view of PAK1-mediated signal transduction pathways and point to potential new drug targets for glioma therapy.

High-quality genome sequence assembly of R.A73 Enterococcus faecium isolated from freshwater fish mucus

BACKGROUND

Whole-genome sequencing using high throughput technologies has revolutionized and speeded up the scientific investigation of bacterial genetics, biochemistry, and molecular biology. Lactic acid bacteria (LABs) have been extensively used in fermentation and more recently as probiotics in food products that promote health. Genome sequencing and functional genomics investigations of LABs varieties provide rapid and important information about their diversity and their evolution, revealing a significant molecular basis. This study investigated the whole genome sequences of the Enterococcus faecium strain (HG937697), isolated from the mucus of freshwater fish in Tunisian dams. Genomic DNA was extracted using the Quick-GDNA kit and sequenced using the Illumina HiSeq2500 system. Sequences quality assessment was performed using FastQC software. The complete genome annotation was carried out with the Rapid Annotation using Subsystem Technology (RAST) web server then NCBI PGAAP.

RESULTS

The Enterococcus faecium R.A73 assembled in 28 contigs consisting of 2,935,283 bps. The genome annotation revealed 2884 genes in total including 2834 coding sequences and 50 RNAs containing 3 rRNAs (one rRNA 16 s, one rRNA 23 s and one rRNA 5 s) and 47 tRNAs. Twenty-two genes implicated in bacteriocin production are identified within the Enterococcus faecium R.A73 strain.

CONCLUSION

Data obtained provide insights to further investigate the effective strategy for testing this Enterococcus faecium R.A73 strain in the industrial manufacturing process. Studying their metabolism with bioinformatics tools represents the future challenge and contribution to improving the utilization of the multi-purpose bacteria in food.

Predicted functional interactome of Caenorhabditis elegans and a web tool for the functional interpretation of differentially expressed genes

BACKGROUND

The nematode worm, Caenorhabditis elegans, is a saprophytic species that has been emerging as a standard model organism since the early 1960s. This species is useful in numerous fields, including developmental biology, neurobiology, and ageing. A high-quality comprehensive molecular interaction network is needed to facilitate molecular mechanism studies in C. elegans.

RESULTS

We present the predicted functional interactome of Caenorhabditis elegans (FIC), which integrates functional association data from 10 public databases to infer functional gene interactions on diverse functional perspectives. In this work, FIC includes 108,550 putative functional associations with balanced sensitivity and specificity, which are expected to cover 21.42% of all C. elegans protein interactions, and 29.25% of these associations may represent protein interactions. Based on FIC, we developed a gene set linkage analysis (GSLA) web tool to interpret potential functional impacts from a set of differentially expressed genes observed in transcriptome analyses.

CONCLUSION

We present the predicted C. elegans interactome database FIC, which is a high-quality database of predicted functional interactions among genes. The functional interactions in FIC serve as a good reference interactome for GSLA to annotate differentially expressed genes for their potential functional impacts. In a case study, the FIC/GSLA system shows more comprehensive and concise annotations compared to other widely used gene set annotation tools, including PANTHER and DAVID. FIC and its associated GSLA are available at the website http://worm.biomedtzc.cn .

Congruence Amidst Discordance between Sequence and Protein-Content Based Phylogenies of Fungi

Amid the genomic data explosion, phylogenomic analysis has resolved the tree of life of different organisms, including fungi. Genome-wide clustering has also been conducted based on gene content data that can lighten the issue of the unequal evolutionary rate of genes. In this study, using different fungal species as models, we performed phylogenomic and protein-content (PC)-based clustering analysis. The obtained sequence tree reflects the phylogenetic trajectory of examined fungal species. However, 15 PC-based trees constructed from the Pfam matrices of the whole genomes, four protein families, and ten subcellular locations largely failed to resolve the speciation relationship of cross-phylum fungal species. However, lifestyle and taxonomic associations were more or less evident between closely related fungal species from PC-based trees. Pairwise congruence tests indicated that a varied level of congruent or discordant relationships were observed between sequence- and PC-based trees, and among PC-based trees. It was intriguing to find that a few protein family and subcellular PC-based trees were more topologically similar to the phylogenomic tree than was the whole genome PC-based phylogeny. In particular, a most significant level of congruence was observed between sequence- and cell wall PC-based trees. Cophylogenetic analysis conducted in this study may benefit the prediction of the magnitude of evolutionary conservation, interactive associations, or networking between different family or subcellular proteins.

Predicted yeast interactome and network-based interpretation of transcriptionally changed genes

Saccharomyces cerevisiae, budding yeast, is a widely used model organism and research tool in genetics studies. Many efforts have been directed at constructing a high-quality comprehensive molecular interaction network to elucidate the design logic of the gene circuitries in this classic model organism. In this work, we present the yeast interactome resource (YIR), which includes 22,238 putative functional gene interactions inferred from functional gene association data integrated from 10 databases focusing on diverse functional perspectives. These putative functional gene interactions are expected to cover 18.84% of yeast protein interactions, and 38.49% may represent protein interactions. Based on the YIR, a gene set linkage analysis (GSLA) web tool was developed to annotate the potential functional impacts of a set of transcriptionally changed genes. In a case study, we show that the YIR/GSLA system produced more extensive and concise annotations compared with widely used gene set annotation tools, including PANTHER and DAVID. Both YIR and GSLA are accessible through the website http://yeast.biomedtzc.cn.

Phylogenomic Analysis of R2R3 MYB Transcription Factors in Sorghum and their Role in Conditioning Biofuel Syndrome

Background

Large scale cultivation of sorghum for food, feed, and biofuel requires concerted efforts for engineering multipurpose cultivars with optimised agronomic traits. Due to their vital role in regulating the biosynthesis of phenylpropanoid-derived compounds, biomass composition, biotic, and abiotic stress response, R2R3-MYB family transcription factors are ideal targets for improving environmental resilience and economic value of sorghum.

Methods

We used diverse computational biology tools to survey the sorghum genome to identify R2R3-MYB transcription factors followed by their structural and phylogenomic analysis. We used in-house generated as well as publicly available high throughput expression data to analyse the R2R3 expression patterns in various sorghum tissue types.

Results

We have identified a total of 134 R2R3-MYB genes from sorghum and developed a framework to predict gene functions. Collating information from the physical location, duplication, structural analysis, orthologous sequences, phylogeny, and expression patterns revealed the role of duplications in clade-wise expansion of the R2R3-MYB family as well as intra-clade functional diversification. Using publicly available and in-house generated RNA sequencing data, we provide MYB candidates for conditioning biofuel syndrome by engineering phenylpropanoid biosynthesis and sugar signalling pathways in sorghum.

Conclusion

The results presented here are pivotal to prioritize MYB genes for functional validation and optimize agronomic traits in sorghum.

Comparative Transcriptomics Reveals Patterns of Adaptive Evolution Associated with Depth and Age Within Marine Rockfishes (Sebastes)

The genetic underpinnings that contribute to ecological adaptation and speciation are not completely understood, especially within marine ecosystems. These evolutionary processes can be elucidated by studying adaptive radiations, because they provide replicates of divergence within a given environment or time-frame. Marine rockfishes (genus Sebastes) are an adaptive radiation and unique model system for studying adaptive evolution in the marine realm. We investigated molecular evolution associated with ecological (depth) and life history (lifespan) divergence in 2 closely related clades of Sebastes. Brain transcriptomes were sequenced via RNA-Seq from 3 species within the subgenus Pteropodus and a pair of related congeners from the subgenus Sebastosomus in order to identify patterns of adaptive evolution. De novo assemblies from these transcriptomes were used to identify 3867 orthologous clusters, and genes subject to positive selection were identified based on all 5 species, depth, and lifespan. Within all our analyses, we identified hemoglobin subunit α to be under strong positive selection and is associated with the depth of occurrence. In our lifespan analysis we identified immune function genes under positive selection in association with maximum lifespan. This study provides insight on the molecular evolution of rockfishes and these candidate genes may provide a better understanding of how these subgenera radiated within the Northeast Pacific.