Ensembl Genomes: extending Ensembl across the taxonomic space

Profiling conserved transcription factor binding motifs in Phaseolus vulgaris through comparative genomics

Common bean (Phaseolus vulgaris), a staple food in Latin America and Africa, serves as a vital source of energy, protein, and essential minerals for millions of people. However, genomics knowledge that breeders could leverage for improvement of this crop is scarce. We have developed and validated a comparative genomics approach to predict conserved transcription factor binding sites (TFBS) in common bean and studied gene regulatory networks. We analyzed promoter regions and identified TFBS for 12,631 bean genes with an average of 6 conserved motifs per gene. Moreover, we discovered a statistically significant relationship between the number of conserved motifs and amount of available experimental evidence of gene regulation. Notably, ERF, MYB, and bHLH transcription factor families dominated conserved motifs, with implications for starch biosynthesis regulation. Furthermore, we provide gene regulatory data as a resource that can be interrogated for the regulatory landscape of any set of genes. Our results underscore the significance of TFBS conservation in legumes and aligns with the notion that core genes often exhibit a more conserved regulatory makeup. The study demonstrates the effectiveness of a comparative genomics approach for addressing genome information gaps in non-model organisms and provides valuable insights into the regulatory networks governing starch biosynthesis genes that can support crop improvement programs.

The dynamics of fungal genome organization and its impact on host adaptation and antifungal resistance

Fungi are a diverse kingdom characterized by remarkable genomic plasticity that facilitates pathogenicity and adaptation to adverse environmental conditions. In this review, we delve into the dynamic organization of fungal genomes and its implications for host adaptation and antifungal resistance. We examine key features and the heterogeneity of genomes across different fungal species, including but not limited to their chromosome content, DNA composition, distribution and arrangement of their content across chromosomes, and other major traits. We further highlight how this variability in genomic traits influences their virulence and adaptation to adverse conditions. Fungal genomes exhibit large variations in size, gene content, and structural features, such as abundance of transposable elements (TEs), compartmentalization into gene-rich and TE-rich regions, and the presence or absence of dispensable chromosomes. Genomic structural variations are equally diverse in fungi, ranging from whole-chromosome duplications that may enhance tolerance to antifungal compounds, to targeted deletion of effector encoding genes that may promote virulence. Finally, the often-overlooked fungal mitochondrial genomes can also affect virulence and resistance to fungicides. Such and other features of fungal genome organization are reviewed and discussed in the context of host-microbe interactions and antifungal resistance.

FEAtl: a comprehensive web-based expression atlas for functional genomics in tropical and subtropical fruit crops

BACKGROUND

Fruit crops, including tropical and subtropical fruits like Avocado (Persea americana), Fig (Ficus carica), Date Palm (Phoenix dactylifera), Mango (Mangifera indica), Guava (Psidium guajava), Papaya (Carica papaya), Pineapple (Ananas comosus), and Banana (Musa acuminata) are economically vital, contributing significantly to global agricultural output, as classified by the FAO's World Programme for the Census of Agriculture. Advancements in next-generation sequencing, have transformed fruit crop breeding by providing in-depth genomic and transcriptomic data. RNA sequencing enables high-throughput analysis of gene expression, and functional genomics, crucial for addressing horticultural challenges and enhancing fruit production. The genomic and expression data for key tropical and sub-tropical fruit crops is currently lacking a comprehensive expression atlas, revealing a significant gap in resources for horticulturists who require a unified platform with diverse datasets across various conditions and cultivars.

RESULTS

The Fruit Expression Atlas (FEAtl), available at http://backlin.cabgrid.res.in/FEAtl/ , is a first-ever extensive and unified expression atlas for tropical and subtropical fruit crops developed using 3-tier architecture. The expressivity of coding and non-coding genes, encompassing 2,060 RNA-Seq samples across 91 tissue types and 177 BioProjects, it provides a comprehensive view of gene expression patterns for different tissues under various conditions. FEAtl features multiple tabs that cater to different aspects of the dataset, namely, Home, About, Analyze, Statistics, and Team and contains seven central functional modules: Transcript Information,Sample Information, Expression Profiles in FPKM and TPM, Functional Analysis, Genes Based on Tau Score, and Search for Specific Gene. The expression of a transcript of interest can be easily queried by searching by tissue ID and transcript type. Expression data can be displayed as a heat map, along with functional descriptions as well as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes.

CONCLUSIONS

This atlas represents a groundbreaking compilation of a wide array of information pertaining to eight distinct fruit crops and serves as a fundamental resource for comparative analysis among different fruit species and is a catalyst for functional genomic studies. Database availability: http://backlin.cabgrid.res.in/FEAtl/ .

Biodegradation of PVCs through in-vitro identification of Bacillus albus and computational pathway analysis of ABH enzyme

Microplastics pose significant challenges to ecosystems and organisms. They can be ingested by marine and terrestrial species, leading to potential health risks and ecological disruptions. This study aims to address the urgent need for effective remediation strategies by focusing on the biodegradation of microplastics, specifically polyvinyl chloride (PVC) derivatives, using the bacterial strain Bacillus albus. The study provides a comprehensive background on the accumulation of noxious substances in the environment and the importance of harnessing biodegradation as an eco-friendly method for pollutant elimination. The specific objective is to investigate the enzymatic capabilities of Bacillus albus, particularly the alpha/beta hydrolases (ABH), in degrading microplastics. To achieve this, in-silico studies were conducted, including analysis of the ABH protein sequence and its interaction with potential inhibitors targeting PVC derivatives. Docking scores of - 7.2 kcal/mol were obtained to evaluate the efficacy of the interactions. The study demonstrates the promising bioremediation prospects of Bacillus albus for microplastics, highlighting its potential as a key player in addressing microplastic pollution. The findings underscore the urgent need for further experimental validation and practical implementation of Bacillus albus in environmental remediation strategies.

Revealing Hidden Genes in Botrytis cinerea: New Insights into Genes Involved in the Biosynthesis of Secondary Metabolites

Utilizing bioinformatics tools, this study expands our understanding of secondary metabolism in Botrytis cinerea, identifying novel genes within polyketide synthase (PKS), non-ribosomal peptide synthetase (NRPS), sesquiterpene cyclase (STC), diterpene cyclase (DTC), and dimethylallyltryptophan synthase (DMATS) families. These findings enrich the genetic framework associated with B. cinerea's pathogenicity and ecological adaptation, offering insights into uncharted metabolic pathways. Significantly, the discovery of previously unannotated genes provides new molecular targets for developing targeted antifungal strategies, promising to enhance crop protection and advance our understanding of fungal biochemistry. This research not only broadens the scope of known secondary metabolites but also opens avenues for future exploration into B. cinerea's biosynthetic capabilities, potentially leading to novel antifungal compounds. Our work underscores the importance of integrating bioinformatics and genomics for fungal research, paving the way for sustainable agricultural practices by pinpointing precise molecular interventions against B. cinerea. This study sets a foundation for further investigations into the fungus's secondary metabolism, with implications for biotechnology and crop disease management.

Plant genomic resources at National Genomics Data Center: assisting in data-driven breeding applications

Genomic data serve as an invaluable resource for unraveling the intricacies of the higher plant systems, including the constituent elements within and among species. Through various efforts in genomic data archiving, integrative analysis and value-added curation, the National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), has successfully established and currently maintains a vast amount of database resources. This dedicated initiative of the NGDC facilitates a data-rich ecosystem that greatly strengthens and supports genomic research efforts. Here, we present a comprehensive overview of central repositories dedicated to archiving, presenting, and sharing plant omics data, introduce knowledgebases focused on variants or gene-based functional insights, highlight species-specific multiple omics database resources, and briefly review the online application tools. We intend that this review can be used as a guide map for plant researchers wishing to select effective data resources from the NGDC for their specific areas of study.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42994-023-00134-4.

The Transcription Factor StuA Regulates the Glyoxylate Cycle in the Dermatophyte Trichophyton rubrum under Carbon Starvation

Trichophyton rubrum is the primary causative agent of dermatophytosis worldwide. This fungus colonizes keratinized tissues and uses keratin as a nutritional source during infection. In T. rubrum-host interactions, sensing a hostile environment triggers the adaptation of its metabolic machinery to ensure its survival. The glyoxylate cycle has emerged as an alternative metabolic pathway when glucose availability is limited; this enables the conversion of simple carbon compounds into glucose via gluconeogenesis. In this study, we investigated the impact of stuA deletion on the response of glyoxylate cycle enzymes during fungal growth under varying culture conditions in conjunction with post-transcriptional regulation through alternative splicing of the genes encoding these enzymes. We revealed that the ΔstuA mutant downregulated the malate synthase and isocitrate lyase genes in a keratin-containing medium or when co-cultured with human keratinocytes. Alternative splicing of an isocitrate lyase gene yielded a new isoform. Enzymatic activity assays showed specific instances where isocitrate lyase and malate synthase activities were affected in the mutant strain compared to the wild type strain. Taken together, our results indicate a relevant balance in transcriptional regulation that has distinct effects on the enzymatic activities of malate synthase and isocitrate lyase.

Unusual Evolution of Cephalopod Tryptophan Indole-Lyases

Tryptophan indole-lyase (TIL), a pyridoxal-5-phosphate-dependent enzyme, catalyzes the hydrolysis of L-tryptophan (L-Trp) to indole and ammonium pyruvate. TIL is widely distributed among bacteria and bacterial TILs consist of a D2-symmetric homotetramer. On the other hand, TIL genes are also present in several metazoans. Cephalopods have two TILs, TILα and TILβ, which are believed to be derived from a gene duplication that occurred before octopus and squid diverged. However, both TILα and TILβ individually contain disruptive amino acid substitutions for TIL activity, and neither was active when expressed alone. When TILα and TILβ were coexpressed, however, they formed a heterotetramer that exhibited low TIL activity. The loss of TIL activity of the heterotetramer following site-directed mutagenesis strongly suggests that the active heterotetramer contains the TILα/TILβ heterodimer. Metazoan TILs generally have lower kcat values for L-Trp than those of bacterial TILs, but such low TIL activity may be rather suitable for metazoan physiology, where L-Trp is in high demand. Therefore, reduced activity may have been a less likely target for purifying selection in the evolution of cephalopod TILs. Meanwhile, the unusual evolution of cephalopod TILs may indicate the difficulty of post-gene duplication evolution of enzymes with catalytic sites contributed by multiple subunits, such as TIL.

The Two-Track Investigation of Fibronectin Binding Protein A of Staphylococcus aureus from Bovine Mastitis as a Potential Candidate for Immunodiagnosis: A Pilot Study

Bovine mastitis is the most common disease affecting dairy cattle worldwide and it generates substantial losses for cattle breeders. One of the most common pathogens identified in infected milk samples is Staphylococcus aureus. Currently, there is no fast test for recognizing bacteria species on the market. The aim of this study was to bioinformatically and laboratory detect and characterize the fibronectin binding protein A (FnBPA) of S. aureus (SA) in milk samples obtained from cows diagnosed with mastitis. More than 90,000,000 amino acid sequences were subjected to bioinformatic detection in the search for a potential biomarker for bovine SA. The analysis of FnBPA included the detection of signal peptides and nonclassical proteins, antigenicity, and the prediction of epitopes. To confirm the presence of the fnbA gene in four SA isolates, amplification with specific primers was performed. FnBPA was detected by immunoblotting. The immunoreactivity and selectivity were performed with monoclonal anti-FnBPA antibodies and SA-negative serum. The bioinformatic analysis showed that FnBPA is a surface, conservative, immunoreactive, and species-specific protein with antigenic potential. Its presence was confirmed in all of the SA isolates we studied. Immunoblotting proved its immunoreactivity and specificity. Thus, it can be considered a potential biomarker in mastitis immunodiagnostics.

Identification of conserved slow codons that are important for protein expression and function

ABSTRASTDue to the redundancy of the genetic code most amino acids are encoded by several 'synonymous' codons. These codons are used unevenly, and each organism demonstrates its own unique codon usage bias, where the 'preferred' codons are associated with tRNAs that are found in high concentrations. Therefore, for decades, the prevailing view had been that preferred and non-preferred codons are linked to high or slow translation rates, respectively.However, this simplified view is contrasted by the frequent failures of codon-optimization efforts and by evidence of non-preferred (i.e. 'slow') codons having specific roles important for efficient production of functional proteins. One such specific role of slower codons is the regulation of co-translational protein folding, a complex biophysical process that is very challenging to model or to measure.Here, we combined a genome-wide approach with experiments to investigate the role of slow codons in protein production and co-translational folding. We analysed homologous gene groups from divergent bacteria and identified positions of inter-species conservation of bias towards slow codons. We then generated mutants where the conserved slow codons are substituted with 'fast' ones, and experimentally studied the effects of these codon substitutions. Using cellular and biochemical approaches we find that at certain locations, slow-to-fast codon substitutions reduce protein expression, increase protein aggregation, and impair protein function.This report provides an approach for identifying functionally relevant regions with slower codons and demonstrates that such codons are important for protein expression and function.

Long non-coding RNAs and their targets as potential biomarkers in breast cancer

Breast cancer is among the lethal types of cancer with a high mortality rate, globally. Its high prevalence can be controlled through improved analysis and identification of disease-specific biomarkers. Recently, long non-coding RNAs (lncRNAs) have been reported as key contributors of carcinogenesis and regulate various cellular pathways through post-transcriptional regulatory mechanisms. The specific aim of this study was to identify the novel interactions of aberrantly expressed genetic components in breast cancer by applying integrative analysis of publicly available expression profiles of both lncRNAs and mRNAs. Differential expression patterns were identified by comparing the breast cancer expression profiles of samples with controls. Significant co-expression networks were identified through WGCNA analysis. WGCNA is a systems biology approach used to elucidate the pattern of correlation between genes across microarray samples. It is also used to identify the highly correlated modules. The results obtained from this study revealed significantly differentially expressed and co-expressed lncRNAs and their cis- and trans-regulating mRNA targets which include RP11-108F13.2 targeting TAF5L, RPL23AP2 targeting CYP4F3, CYP4F8 and AL022324.2 targeting LRP5L, AL022324.3, and Z99916.3, respectively. Moreover, pathway analysis revealed the involvement of identified mRNAs and lncRNAs in major cell signalling pathways, and target mRNAs expression is also validated through cohort data. Thus, the identified lncRNAs and their target mRNAs represent novel biomarkers that could serve as potential therapeutics for breast cancer and their roles could also be further validated through wet labs to employ them as potential therapeutic targets in future.

Pseudomonas aeruginosa antitoxin HigA functions as a diverse regulatory factor by recognizing specific pseudopalindromic DNA motifs

Type II toxin-antitoxin (TA) systems modulate many essential cellular processes in prokaryotic organisms. Recent studies indicate certain type II antitoxins also transcriptionally regulate other genes, besides neutralizing toxin activity. Herein, we investigated the diverse transcriptional repression properties of type II TA antitoxin PaHigA from Pseudomonas aeruginosa. Biochemical and functional analyses showed that PaHigA recognized variable pseudopalindromic DNA sequences and repressed expression of multiple genes. Furthermore, we presented high resolution structures of apo-PaHigA, PaHigA-P_higBA and PaHigA-P_pa2440 complex, describing how the rearrangements of the HTH domain accounted for the different DNA-binding patterns among HigA homologues. Moreover, we demonstrated that the N-terminal loop motion of PaHigA was associated with its apo and DNA-bound states, reflecting a switch mechanism regulating HigA antitoxin function. Collectively, this work extends our understanding of how the PaHigB/HigA system regulates multiple metabolic pathways to balance the growth and stress response in P. aeruginosa and could guide further development of anti-TA oriented strategies for pathogen treatment.

Pathogenomics and Management of Fusarium Diseases in Plants

There is an urgency to supplant the heavy reliance on chemical control of Fusarium diseases in different economically important, staple food crops due to development of resistance in the pathogen population, the high cost of production to the risk-averse grower, and the concomitant environmental impacts. Pathogenomics has enabled (i) the creation of genetic inventories which identify those putative genes, regulators, and effectors that are associated with virulence, pathogenicity, and primary and secondary metabolism; (ii) comparison of such genes among related pathogens; (iii) identification of potential genetic targets for chemical control; and (iv) better characterization of the complex dynamics of host–microbe interactions that lead to disease. This type of genomic data serves to inform host-induced gene silencing (HIGS) technology for targeted disruption of transcription of select genes for the control of Fusarium diseases. This review discusses the various repositories and browser access points for comparison of genomic data, the strategies for identification and selection of pathogenicity- and virulence-associated genes and effectors in different Fusarium species, HIGS and successful Fusarium disease control trials with a consideration of loss of RNAi, off-target effects, and future challenges in applying HIGS for management of Fusarium diseases.

Identification of the Regulatory Role of lncRNA SNHG16 in Myasthenia Gravis by Constructing a Competing Endogenous RNA Network

Myasthenia gravis (MG) is an autoimmune disorder resulting from antibodies against the proteins at the neuromuscular junction. Emerging evidence indicates that long non-coding RNAs (lncRNAs), acting as competing endogenous RNAs (ceRNAs), are involved in various diseases. However, the regulatory mechanisms of ceRNAs underlying MG remain largely unknown. In this study, we constructed a lncRNA-mediated ceRNA network involved in MG using a multi-step computational strategy. Functional annotation analysis suggests that these lncRNAs may play crucial roles in the immunological mechanism underlying MG. Importantly, through manual literature mining, we found that lncRNA SNHG16 (small nucleolar RNA host gene 16), acting as a ceRNA, plays important roles in the immune processes. Further experiments showed that SNHG16 expression was upregulated in peripheral blood mononuclear cells (PBMCs) from MG patients compared to healthy controls. Luciferase reporter assays confirmed that SNHG16 is a target of the microRNA (miRNA) let-7c-5p. Subsequent experiments indicated that SNHG16 regulates the expression of the key MG gene interleukin (IL)-10 by sponging let-7c-5p in a ceRNA manner. Furthermore, functional assays showed that SNHG16 inhibits Jurkat cell apoptosis and promotes cell proliferation by sponging let-7c-5p. Our study will contribute to a deeper understanding of the regulatory mechanism of MG and will potentially provide new therapeutic targets for MG patients.

Prioritization of novel ADPKD drug candidates from disease-stage specific gene expression profiles

Background

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is one of the most common causes of end-stage renal failure, caused by mutations in PKD1 or PKD2 genes. Tolvaptan, the only drug approved for ADPKD treatment, results in serious side-effects, warranting the need for novel drugs.

Methods

In this study, we applied RNA-sequencing of Pkd1cko mice at different disease stages, and with/without drug treatment to identify genes involved in ADPKD progression that were further used to identify novel drug candidates for ADPKD. We followed an integrative computational approach using a combination of gene expression profiling, bioinformatics and cheminformatics data.

Findings

We identified 1162 genes that had a normalized expression after treating the mice with drugs proven effective in preclinical models. Intersecting these genes with target affinity profiles for clinically-approved drugs in ChEMBL, resulted in the identification of 116 drugs targeting 29 proteins, of which several are previously linked to Polycystic Kidney Disease such as Rosiglitazone. Further testing the efficacy of six candidate drugs for inhibition of cyst swelling using a human 3D-cyst assay, revealed that three of the six had cyst-growth reducing effects with limited toxicity.

Interpretation

Our data further establishes drug repurposing as a robust drug discovery method, with three promising drug candidates identified for ADPKD treatment (Meclofenamic Acid, Gamolenic Acid and Birinapant). Our strategy that combines multiple-omics data, can be extended for ADPKD and other diseases in the future.

Funding

European Union's Seventh Framework Program, Dutch Technology Foundation Stichting Technische Wetenschappen and the Dutch Kidney Foundation.

Mapping and Identifying a Candidate Gene Plr4, a Recessive Gene Regulating Purple Leaf in Rice, by Using Bulked Segregant and Transcriptome Analysis with Next-Generation Sequencing

The anthocyanin biosynthesis of rice is a major concern due to the potential nutritional value. Purple appears in various organs and tissues of rice such as pericarp, flower organs, leaves, leaf sheaths, internodes, ligules, apex, and stigma. At present, there are many studies on the color of rice pericarp, but the gene and mechanism of other organs such as leaves are still unclear, and the gene regulatory network of specific organ coloring has not been systematically understood. In this study, genetic analysis demonstrated that the purple leaf traits of rice were regulated by a recessive gene. The green leaf cultivar Y58S and purple leaf cultivar XianHongB were used to construct the mapping population. A set of near isogenicline (NIL) (BC₃F₁) was bred via crossing and back-crossing. The generations of BC₃F₂ appeared to separate four phenotypes, pl1, pl2, pl3, and pl4, due to the occurrence of a purple color in different organs. We constructed three bulked segregant analysis (BSA) pools (pl1-pl2, pl1-pl3, and pl1-pl4) by using the separated generations of BC₃F₅ and mapped the purple leaf gene plr4 to the vicinity of 27.9-31.1 Mb on chromosome 4. Subsequently, transcriptome sequencing (RNA-Seq) for pl3 and pl2 was used to analyze the differentially expressed genes in the localization interval, where 12 unigenes exhibited differential expression in which two genes (Os04g0577800, Os04g0616400) were downregulated. The two downregulated genes (Os04g0577800 and Os04g0616400) are possible candidate genes because of the recessive genetic characteristics of the purple leaf genes. These results will facilitate the cloning of plr4 and illustrate the molecular mechanisms of the anthocyanin synthesis pathway.

Comprehensive Characterization of Somatic Mutations Impacting lncRNA Expression for Pan-Cancer

Somatic mutations have long been recognized as an important feature of cancer. However, analysis of somatic mutations, to date, has focused almost entirely on the protein coding regions of the genome. The potential roles of somatic mutations in human long noncoding RNAs (lncRNAs) are therefore largely unknown, particularly their functional significance across different cancer types. In this study, we characterized some lncRNAs whose expression was affected by somatic mutations (defined as MutLncs) and constructed global MutLnc landscapes across 17 cancer types by systematically integrating multiple levels of data. MutLncs were commonly downregulated and carried low mutation frequencies and non-silent mutations in most cancer types. Co-occurrence analysis in pan-cancer highlighted combined patterns of specific MutLncs, suggesting that a number of MutLncs influence diverse cancer types through combination effects. Several conserved and cancer-specific functions of MutLncs were determined. We further explored the somatic mutations affecting lncRNA expression via mixed and unmixed effects, which led to specific functions in pan-cancer. Survival analysis indicated that MutLncs and co-occurrence pairs can potentially serve as cancer biomarkers. Clarification of the specific roles of MutLncs in human cancers could be beneficial for understanding the molecular pathogenesis of different cancer types and developing the appropriate treatments.

ECOdrug: a database connecting drugs and conservation of their targets across species

Pharmaceuticals are designed to interact with specific molecular targets in humans and these targets generally have orthologs in other species. This provides opportunities for the drug discovery community to use alternative model species for drug development. It also means, however, there is potential for mode of action related effects in non-target wildlife species as many pharmaceuticals reach the environment through patient use and manufacturing wastes. Acquiring insight in drug target ortholog predictions across species and taxonomic groups has proven difficult because of the lack of an optimal strategy and because necessary information is spread across multiple and diverse sources and platforms. We introduce a new research platform tool, ECOdrug, that reliably connects drugs to their protein targets across divergent species. It harmonizes ortholog predictions from multiple sources via a simple user interface underpinning critical applications for a wide range of studies in pharmacology, ecotoxicology and comparative evolutionary biology. ECOdrug can be used to identify species with drug targets and identify drugs that interact with those targets. As such, it can be applied to support intelligent targeted drug safety testing by ensuring appropriate and relevant species are selected in ecological risk assessments. ECOdrug is freely accessible and available at: http://www.ecodrug.org.

Plant and fungus transcriptomic data from grapevine berries undergoing artificially-induced noble rot caused by Botrytis cinerea

Noble rot is a latent infection of grape berries caused by the necrotrophic fungus Botrytis cinerea, which develops under specific climatic conditions. The infected berries undergo biochemical and metabolic changes, associated with a rapid withering, which altogether offer interesting organoleptic features to sweet white wines. In this paper, we provide RNAseq datasets (raw and normalized counts as well as differentially expressed genes lists) of the transcriptome profiles of both grapevine berries (Vitis vinifera cv. Garganega) and B. cinerea during the establishment of noble rot, artificially induced in controlled conditions. The sequencing data are available in the NCBI GEO database under accession number GSE116741. These data were exploited in a comprehensive meta-analysis of gene expression during noble rot infection, gray mold and post-harvest withering. This highlighted an important common transcriptional reprogramming in different botrytized grape berry varieties and led to the identification of key genes specifically modulated during noble rot infection, which are described in the article entitled “Specific molecular interactions between Vitis vinifera and Botrytis cinerea are required for noble rot development in grape berries” Lovato et al., 2019.

Biological and chemical diversity go hand in hand: Basidiomycota as source of new pharmaceuticals and agrochemicals

The Basidiomycota constitutes the second largest higher taxonomic group of the Fungi after the Ascomycota and comprises over 30.000 species. Mycelial cultures of Basidiomycota have already been studied since the 1950s for production of antibiotics and other beneficial secondary metabolites. Despite the fact that unique and selective compounds like pleuromutilin were obtained early on, it took several decades more until they were subjected to a systematic screening for antimicrobial and anticancer activities. These efforts led to the discovery of the strobilurins and several hundreds of further compounds that mainly constitute terpenoids. In parallel the traditional medicinal mushrooms of Asia were also studied intensively for metabolite production, aimed at finding new therapeutic agents for treatment of various diseases including metabolic disorders and the central nervous system. While the evaluation of this organism group has in general been more tedious as compared to the Ascomycota, the chances to discover new metabolites and to develop them further to candidates for drugs, agrochemicals and other products for the Life Science industry have substantially increased over the past decade. This is owing to the revolutionary developments in -OMICS techniques, bioinformatics, analytical chemistry and biotechnological process technology, which are steadily being developed further. On the other hand, the new developments in polythetic fungal taxonomy now also allow a more concise selection of previously untapped organisms. The current review is dedicated to summarize the state of the art and to give an outlook to further developments.

Construction of a transcription factor‑long non‑coding RNA‑microRNA network for the identification of key regulators in lung adenocarcinoma and lung squamous cell carcinoma

The interactions of microRNAs (miRNAs), transcription factors (TFs) and their common target long non-coding RNAs (lncRNAs) can lead to the production of TF-miRNA-lncRNA (TML) network motifs. These motifs are functional regulators that perform a wide range of biological processes, such as carcinogenesis. However, TML network motifs have not been systematically identified, and their roles in lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) are largely unknown. In the present study, a computational integration approach was performed using multiple sources in order to construct a global TML network for LUAD and LUSC. The analysis revealed several dysregulated TML network motifs, which were common between the two lung cancer subtypes or specific to a single cancer subtype. In addition, functional analysis further indicated that the TML network motifs may potentially serve as putative biomarkers in LUAD and LUSC. The associations between drug treatments and dysregulated TML network motifs were also examined. Collectively, the present study elucidated the roles of TML network motifs in LUAD and LUSC, which may be beneficial for understanding the pathogenesis of lung cancer and its potential treatment.

Comparative genomic analysis of fungal TPP-riboswitches

Riboswitches are conserved RNA structures located in non-coding regions of mRNA and able to bind small molecules (e.g. metabolites) changing conformation upon binding. This feature enables them to function as regulators of gene expression. The thiamin pyrophosphate (TPP) riboswitch is the only type of riboswitches found not only in bacteria, but also in eukaryotes - in plants, green algae, protists, and fungi. Two main mechanisms of fungal TPP riboswitch action, involving alternative splicing, have been established so far. Here, we report a large-scale bioinformatic study of riboswitch structural features, action mechanisms, and distribution along the fungal taxonomy groups. For each putatively regulated gene, we reconstruct the riboswitch structure, identify other components of the regulation machinery, and establish mechanisms of riboswitch-mediated regulation. In addition to three genes known to be regulated by TPP riboswitches, thiazole synthase THI4, hydroxymethilpyrimidine-syntase NMT1, and putative transporter NCU01977, we identify two new genes, a putative thiamin transporter THI9 and a transporter of unknown specificity. While the riboswitch sequence and structure remain highly conserved in all species and genes, the mode of riboswitch-mediated regulation varies between regulated genes. The riboswitch usage varies strongly between fungal taxa, with the largest number of riboswitch-regulated genes found in Pezizomycotina and no riboswitch-mediated regulation established in Saccaromycotina.

Identification of prognostic biomarkers in glioblastoma using a long non-coding RNA-mediated, competitive endogenous RNA network

Glioblastoma multiforme (GBM) is a highly malignant brain tumor associated with a poor prognosis. Cross-talk between competitive endogenous RNAs (ceRNAs) plays a critical role in tumor development and physiology. In this study, we present a multi-step computational approach to construct a functional GBM long non-coding RNA (lncRNA)-mediated ceRNA network (LMCN) by integrating genome-wide lncRNA and mRNA expression profiles, miRNA-target interactions, functional analyses, and clinical survival analyses. LncRNAs in the LMCN exhibited specific topological features consistent with a regulatory association with coding mRNAs across GBM pathology. We determined that the lncRNA MCM3AP-AS was involved in RNA processing and cell cycle-related functions, and was correlated with patient survival. MCM3AP-AS and MIR17HG acted synergistically to regulate mRNAs in a network module of the competitive LMCN. By integrating the expression profile of this module into a risk model, we stratified GBM patients in both the The Cancer Genome Atlas and an independent GBM dataset into distinct risk groups. Finally, survival analyses demonstrated that the lncRNAs and network module are potential prognostic biomarkers for GBM. Thus, ceRNAs could accelerate biomarker discovery and therapeutic development in GBM.

Construction of a lncRNA-mediated feed-forward loop network reveals global topological features and prognostic motifs in human cancers

Long non-coding RNAs (lncRNAs), transcription factors and microRNAs can form lncRNA-mediated feed-forward loops (L-FFLs), which are functional network motifs that regulate a wide range of biological processes, such as development and carcinogenesis. However, L-FFL network motifs have not been systematically identified, and their roles in human cancers are largely unknown. In this study, we computationally integrated data from multiple sources to construct a global L-FFL network for six types of human cancer and characterized the topological features of the network. Our approach revealed several dysregulated L-FFL motifs common across different cancers or specific to particular cancers. We also found that L-FFL motifs can take part in other types of regulatory networks, such as mRNA-mediated FFLs and ceRNA networks, and form the more complex networks in human cancers. In addition, survival analyses further indicated that L-FFL motifs could potentially serve as prognostic biomarkers. Collectively, this study elucidated the roles of L-FFL motifs in human cancers, which could be beneficial for understanding cancer pathogenesis and treatment.

Genome of Russian wheat aphid an economically important cereal aphid

Although the hemipterans (Aphididae) are comprised of roughly 50,000 extant insect species, only four have sequenced genomes that are publically available, namely Acyrthosiphon pisum (pea aphid), Rhodnius prolixus (Kissing bug), Myzus persicae (Green peach aphid) and Diuraphis noxia (Russian wheat aphid). As a significant proportion of agricultural pests are phloem feeding aphids, it is crucial for sustained global food security that a greater understanding of the genomic and molecular functioning of this family be elucidated. Recently, the genome of US D. noxia biotype US2 was sequenced but its assembly only incorporated ~ 32% of produced reads and contained a surprisingly low gene count when compared to that of the model/first sequenced aphid, A. pisum. To this end, we present here the genomes of two South African Diuraphis noxia (Kurdjumov, Hemiptera: Aphididae) biotypes (SA1 and SAM), obtained after sequencing the genomes of the only two D. noxia biotypes with documented linked genealogy. To better understand overall targets and patterns of heterozygosity, we also sequenced a pooled sample of 9 geographically separated D. noxia populations (MixIX). We assembled a 399 Mb reference genome (PRJNA297165, representing 64% of the projected genome size 623 Mb) using ± 28 Gb of 101 bp paired-end HiSeq2000 reads from the D. noxia biotype SAM, whilst ± 13 Gb 101 bp paired-end HiSeq2000 reads from the D. noxia biotype SA1 were generated to facilitate genomic comparisons between the two biotypes. Sequencing the MixIX sample yielded ±26 Gb 50 bp paired-end SOLiD reads which facilitated SNP detection when compared to the D. noxia biotype SAM assembly. Ab initio gene calling produced a total of 31,885 protein coding genes from the assembled contigs spanning ~ 399 Mb (GCA_001465515.1).

The mutational landscape of MYCN, Lin28b and ALKF1174L driven murine neuroblastoma mimics human disease

Genetically engineered mouse models have proven to be essential tools for unraveling fundamental aspects of cancer biology and for testing novel therapeutic strategies. To optimally serve these goals, it is essential that the mouse model faithfully recapitulates the human disease. Recently, novel mouse models for neuroblastoma have been developed. Here, we report on the further genomic characterization through exome sequencing and DNA copy number analysis of four of the currently available murine neuroblastoma model systems (ALK, Th-MYCN, Dbh-MYCN and Lin28b). The murine tumors revealed a low number of genomic alterations – in keeping with human neuroblastoma - and a positive correlation of the number of genetic lesions with the time to onset of tumor formation was observed. Gene copy number alterations are the hallmark of both murine and human disease and frequently affect syntenic genomic regions. Despite low mutational load, the genes mutated in murine disease were found to be enriched for genes mutated in human disease. Taken together, our study further supports the validity of the tested mouse models for mechanistic and preclinical studies of human neuroblastoma.

Dihydroartemisinin-regulated mRNAs and lncRNAs in chronic myeloid leukemia

Chronic myelocytic leukemia (CML) is characterized by increased and unregulated growth of predominantly myeloid cells in the bone marrow, and accumulation of these cells in blood. We investigated the effects of an anti-malarial drug, dihydroartemisinin (DHA), on K562 CML cells. We identified 34 mRNAs and eight lncRNAs dysregulated following DHA treatment in pure and hemin-induced K562 cells. Up- or downregulation of these potential DHA targets increased with increasing DHA concentration. We also constructed and analyzed a DHA-related mRNA-lncRNA regulation network in K562 cells, and found that four DHA-modulated mRNAs regulated by four lncRNAs participated in the steroid biosynthesis pathway. Some estrogen-related drugs, such as tamoxifen, shared common targets with DHA. We inferred that DHA exerted anti-cancer effects on K562 cells by influencing estrogen levels. Our findings indicate that DHA has potential not only as an anti-malarial drug, but also as an anti-CML chemotherapeutic.

DaMold: A data-mining platform for variant annotation and visualization in molecular diagnostics research

Next-generation sequencing (NGS) has become a powerful and efficient tool for routine mutation screening in clinical research. As each NGS test yields hundreds of variants, the current challenge is to meaningfully interpret the data and select potential candidates. Analyzing each variant while manually investigating several relevant databases to collect specific information is a cumbersome and time-consuming process, and it requires expertise and familiarity with these databases. Thus, a tool that can seamlessly annotate variants with clinically relevant databases under one common interface would be of great help for variant annotation, cross-referencing, and visualization. This tool would allow variants to be processed in an automated and high-throughput manner and facilitate the investigation of variants in several genome browsers. Several analysis tools are available for raw sequencing-read processing and variant identification, but an automated variant filtering, annotation, cross-referencing, and visualization tool is still lacking. To fulfill these requirements, we developed DaMold, a Web-based, user-friendly tool that can filter and annotate variants and can access and compile information from 37 resources. It is easy to use, provides flexible input options, and accepts variants from NGS and Sanger sequencing as well as hotspots in VCF and BED formats. DaMold is available as an online application at http://damold.platomics.com/index.html, and as a Docker container and virtual machine at https://sourceforge.net/projects/damold/.

Improved method for prioritization of disease associated lncRNAs based on ceRNA theory and functional genomics data

Although several computational models that predict disease-associated lncRNAs (long non-coding RNAs) exist, only a limited number of disease-associated lncRNAs are known. In this study, we mapped lncRNAs to their functional genomics context using competing endogenous RNAs (ceRNAs) theory. Based on the criteria that similar lncRNAs are likely involved in similar diseases, we proposed a disease lncRNA prioritization method, DisLncPri, to identify novel disease-lncRNA associations. Using a leave-one-out cross validation (LOOCV) strategy, DisLncPri achieved reliable area under curve (AUC) values of 0.89 and 0.87 for the LncRNADisease and Lnc2Cancer datasets that further improved to 0.90 and 0.89 by integrating a multiple rank fusion strategy. We found that DisLncPri had the highest rank enrichment score and AUC value in comparison to several other methods for case studies of alzheimer's disease, ovarian cancer, pancreatic cancer and gastric cancer. Several novel lncRNAs in the top ranks of these diseases were found to be newly verified by relevant databases or reported in recent studies. Prioritization of lncRNAs from a microarray (GSE53622) of oesophageal cancer patients highlighted ENSG00000226029 (top 2), a previously unidentified lncRNA as a potential prognostic biomarker. Our analysis thus indicates that DisLncPri is an excellent tool for identifying lncRNAs that could be novel biomarkers and therapeutic targets in a variety of human diseases.

Infectious Disease Genomics

The history and development of infectious disease genomics have been closely associated with the Human Genome Project (HGP) during the past 20 years. It has been emphasized since the beginning of the HGP that such effort must not be restricted to the human genome and should include other organisms including mouse, bacteria, yeast, fruit fly, and worm for comparative sequence analyses. A brief history is reviewed in this chapter. As of 2016, more than 7000 completed genome sequencing projects have been reported. One of the important motivations for these efforts is to develop preventative, diagnostic, and therapeutic strategies through the analysis of sequenced microorganisms, parasites, and vectors related to human health. A number of examples are discussed in this chapter.

Protein Bioinformatics Databases and Resources

Many publicly available data repositories and resources have been developed to support protein-related information management, data-driven hypothesis generation, and biological knowledge discovery. To help researchers quickly find the appropriate protein-related informatics resources, we present a comprehensive review (with categorization and description) of major protein bioinformatics databases in this chapter. We also discuss the challenges and opportunities for developing next-generation protein bioinformatics databases and resources to support data integration and data analytics in the Big Data era.

RAG Recombinase as a Selective Pressure for Genome Evolution

The RAG recombinase is a domesticated transposable element co-opted in jawed vertebrates to drive the process of the so-called V(D)J recombination, which is the hallmark of the adaptive immune system to produce antigen receptors. RAG targets, namely, the Recombination Signal Sequences (RSS), are rather long and degenerated sequences, which highlights the ability of the recombinase to interact with a wide range of target sequences, including outside of antigen receptor loci. The recognition of such cryptic targets by the recombinase threatens genome integrity by promoting aberrant DNA recombination, as observed in lymphoid malignancies. Genomes evolution resulting from RAG acquisition is an ongoing discussion, in particular regarding the counter-selection of sequences resembling the RSS and the modifications of epigenetic regulation at these potential cryptic sites. Here, we describe a new bioinformatics tool to map potential RAG targets in all jawed vertebrates. We show that our REcombination Classifier (REC) outperforms the currently available tool and is suitable for full genomes scans from species other than human and mouse. Using the REC, we document a reduction in density of potential RAG targets at the transcription start sites of genes co-expressed with the rag genes and marked with high levels of the trimethylation of the lysine 4 of the histone 3 (H3K4me3), which correlates with the retention of functional RAG activity after the horizontal transfer.

Fine mapping of the stem rust resistance gene SrTA10187

SrTA10187 was fine-mapped to a 1.1 cM interval, candidate genes were identified in the region of interest, and molecular markers were developed for marker-assisted selection and Sr gene pyramiding. Stem rust (Puccinia graminis f. sp. tritici, Pgt) races belonging to the Ug99 (TTKSK) race group pose a serious threat to global wheat (Triticum aestivum L.) production. To improve Pgt host resistance, the Ug99-effective resistance gene SrTA10187 previously identified in Aegilops tauschii Coss. was introgressed into wheat, and mapped to the short arm of wheat chromosome 6D. In this study, high-resolution mapping of SrTA10187 was done using a population of 1,060 plants. Pgt resistance was screened using race QFCSC. PCR-based SNP and STS markers were developed from genotyping-by-sequencing tags and SNP sequences available in online databases. SrTA10187 segregated as expected in a 3:1 ratio of resistant to susceptible individuals in three out of six BC₃F₂ families, and was fine-mapped to a 1.1 cM region on wheat chromosome 6DS. Marker context sequence was aligned to the reference Ae. tauschii genome to identify the physical region encompassing SrTA10187. Due to the size of the corresponding region, candidate disease resistance genes could not be identified with confidence. Comparisons with the Ae. tauschii genetic map developed by Luo et al. (PNAS 110(19):7940-7945, 2013) enabled identification of a discrete genetic locus and a BAC minimum tiling path of the region spanning SrTA10187. Annotation of pooled BAC library sequences led to the identification of candidate genes in the region of interest-including a single NB-ARC-LRR gene. The shorter genetic interval and flanking KASP™ and STS markers developed in this study will facilitate marker-assisted selection, gene pyramiding, and positional cloning of SrTA10187.

Identifying survival-associated ceRNA clusters in cholangiocarcinoma

Competing endogenous RNAs (ceRNAs) represent a novel layer regulations of long non-coding RNAs (lncRNAs) and genes that play important roles in cancer pathogenesis by binding microRNAs (miRNAs). However, the competition mechanism of ceRNAs in cholangiocarcinoma (CHOL) is not fully understood. In this study, we constructed a dysregulated ceRNA competitive network (CCEN) to globally characterize the competing difference between CHOL and normal tissues. Then, we integrated affinity propagation and Kaplan‑Meier (K-M) methods to identify functional clusters associated with survival. A total of 7 key ceRNA clusters were identified. Further functional annotation analyses found that Cluster23 and Cluster32 involved cell based functions, and the loss of ceRNA competitive relations in clusters may contribute to CHOL, by disturbing important biological processes, such as 'Pathway in cancer', MAPK and Neurotrophin signaling pathway. This study provides further insights into understanding the competitive mechanism of ceRNAs in CHOL.

An inducible tool for random mutagenesis in Aspergillus niger based on the transposon Vader

The ascomycete Aspergillus niger is widely used in the biotechnology, for instance in producing most of the world's citric acid. It is also known as a major food and feed contaminant. While generation of gene knockouts for functional genomics has become feasible in ku70 mutants, analyzing gene functions or metabolic pathways remains a laborious task. An unbiased transposon-based mutagenesis approach may aid this process of analyzing gene functions by providing mutant libraries in a short time. The Vader transposon is a non-autonomous DNA-transposon, which is activated by the homologous tan1-transposase. However, in the most commonly used lab strain of A. niger (N400 strain and derivatives), we found that the transposase, encoded by the tan1 gene, is mutated and inactive. To establish a Vader transposon-based mutagenesis system in the N400 background, we expressed the functional transposase of A. niger strain CBS 513.88 under the control of an inducible promoter based on the Tet-on system, which is activated in the presence of the antibiotic doxycycline (DOX). Increasing amounts of doxycycline lead to higher Vader excision frequencies, whereas little to none activity of Vader was observed without addition of doxycycline. Hence, this system appears to be suitable for producing stable mutants in the A. niger N400 background.

MutAid: Sanger and NGS Based Integrated Pipeline for Mutation Identification, Validation and Annotation in Human Molecular Genetics

Traditional Sanger sequencing as well as Next-Generation Sequencing have been used for the identification of disease causing mutations in human molecular research. The majority of currently available tools are developed for research and explorative purposes and often do not provide a complete, efficient, one-stop solution. As the focus of currently developed tools is mainly on NGS data analysis, no integrative solution for the analysis of Sanger data is provided and consequently a one-stop solution to analyze reads from both sequencing platforms is not available. We have therefore developed a new pipeline called MutAid to analyze and interpret raw sequencing data produced by Sanger or several NGS sequencing platforms. It performs format conversion, base calling, quality trimming, filtering, read mapping, variant calling, variant annotation and analysis of Sanger and NGS data under a single platform. It is capable of analyzing reads from multiple patients in a single run to create a list of potential disease causing base substitutions as well as insertions and deletions. MutAid has been developed for expert and non-expert users and supports four sequencing platforms including Sanger, Illumina, 454 and Ion Torrent. Furthermore, for NGS data analysis, five read mappers including BWA, TMAP, Bowtie, Bowtie2 and GSNAP and four variant callers including GATK-HaplotypeCaller, SAMTOOLS, Freebayes and VarScan2 pipelines are supported. MutAid is freely available at https://sourceforge.net/projects/mutaid.

Draft genome sequences of Phytophthora kernoviae and Phytophthora ramorum lineage EU2 from Scotland

Newly discovered Phytophthora species include invasive pathogens that threaten trees and shrubs. We present draft genome assemblies for three isolates of Phytophthora kernoviae and one isolate of the EU2 lineage of Phytophthora ramorum, collected from outbreak sites in Scotland.

AnGeLi: A Tool for the Analysis of Gene Lists from Fission Yeast

Genome-wide assays and screens typically result in large lists of genes or proteins. Enrichments of functional or other biological properties within such lists can provide valuable insights and testable hypotheses. To systematically detect these enrichments can be challenging and time-consuming, because relevant data to compare against query gene lists are spread over many different sources. We have developed AnGeLi (Analysis of Gene Lists), an intuitive, integrated web-tool for comprehensive and customized interrogation of gene lists from the fission yeast, Schizosaccharomyces pombe. AnGeLi searches for significant enrichments among multiple qualitative and quantitative information sources, including gene and phenotype ontologies, genetic and protein interactions, numerous features of genes, transcripts, translation, and proteins such as copy numbers, chromosomal positions, genetic diversity, RNA polymerase II and ribosome occupancy, localization, conservation, half-lives, domains, and molecular weight among others, as well as diverse sets of genes that are co-regulated or lead to the same phenotypes when mutated. AnGeLi uses robust statistics which can be tailored to specific needs. It also provides the option to upload user-defined gene sets to compare against the query list. Through an integrated data submission form, AnGeLi encourages the community to contribute additional curated gene lists to further increase the usefulness of this resource and to get the most from the ever increasing large-scale experiments. AnGeLi offers a rigorous yet flexible statistical analysis platform for rich insights into functional enrichments and biological context for query gene lists, thus providing a powerful exploratory tool through which S. pombe researchers can uncover fresh perspectives and unexpected connections from genomic data. AnGeLi is freely available at: www.bahlerlab.info/AnGeLi.

Pathogen-regulated genes in wheat isogenic lines differing in resistance to brown rust Puccinia triticina

BACKGROUND

Inoculation of wheat plants with Puccinia triticina (Pt) spores activates a wide range of host responses. Compatible Pt interaction with susceptible Thatcher plants supports all stages of the pathogen life cycle. Incompatible interaction with TcLr9 activates defense responses including oxidative burst and micronecrotic reactions associated with the pathogen's infection structures and leads to complete termination of pathogen development. These two contrasting host-pathogen interactions were a foundation for transcriptome analysis of incompatible wheat-Pt interaction.

METHODS

A suppression subtractive hybridization (SSH) library was constructed using cDNA from pathogen-inoculated susceptible Thatcher and resistant TcLr9 isogenic lines. cDNA represented steps of wheat-brown rust interactions: spore germination, haustorium mother cell (HMC) formation and micronecrotic reactions. All ESTs were clustered and validated by similarity search to wheat genome using BLASTn and sim4db tools. qRT-PCR was used to determine transcript levels of selected ESTs after inoculation in both lines.

RESULTS AND DISCUSSION

Out of 793 isolated cDNA clones, 183 were classified into 152 contigs. 89 cDNA clones and encoded proteins were functionally annotated and assigned to 5 Gene Ontology categories: catalytic activity 48 clones (54 %), binding 32 clones (36 %), transporter activity 6 clones (7 %), structural molecule activity 2 clones (2 %) and molecular transducer activity 1 clone (1 %). Detailed expression profiles of 8 selected clones were analyzed using the same plant-pathogen system. The strongest induction after pathogen infection and the biggest differences between resistant and susceptible interactions were detected for clones encoding wall-associated kinase (GenBank accession number JG969003), receptor with leucine-rich repeat domain (JG968955), putative serine/threonine protein kinase (JG968944), calcium-mediated signaling protein (JG968925) and 14-3-3 protein (JG968969).

CONCLUSIONS

The SSH library represents transcripts regulated by pathogen infection during compatible and incompatible interactions of wheat with P. triticina. Annotation of selected clones confirms their putative roles in successive steps of plant-pathogen interactions. The transcripts can be categorized as defense-related due to their involvement in either basal defense or resistance through an R-gene mediated reaction. The possible involvement of selected clones in pathogen recognition and pathogen-induced signaling as well as resistance mechanisms such as cell wall enforcement, oxidative burst and micronecrotic reactions is discussed.

Transcriptome sequencing of three Pseudo-nitzschia species reveals comparable gene sets and the presence of Nitric Oxide Synthase genes in diatoms

Diatoms are among the most diverse eukaryotic microorganisms on Earth, they are responsible for a large fraction of primary production in the oceans and can be found in different habitats. Pseudo-nitzschia are marine planktonic diatoms responsible for blooms in coastal and oceanic waters. We analyzed the transcriptome of three species, Pseudo-nitzschia arenysensis, Pseudo-nitzschia delicatissima and Pseudo-nitzschia multistriata, with different levels of genetic relatedness. These species have a worldwide distribution and the last one produces the neurotoxin domoic acid. We were able to annotate about 80% of the sequences in each transcriptome and the analysis of the relative functional annotations allowed comparison of the main metabolic pathways, pathways involved in the biosynthesis of isoprenoids (MAV and MEP pathways), and pathways putatively involved in domoic acid synthesis. The search for homologous transcripts among the target species and other congeneric species resulted in the discovery of a sequence annotated as Nitric Oxide Synthase (NOS), found uniquely in Pseudo-nitzschia multistriata. The predicted protein product contained all the domains of the canonical metazoan sequence. Putative NOS sequences were found in other available diatom datasets, supporting a role for nitric oxide as signaling molecule in this group of microalgae.

Young Genes out of the Male: An Insight from Evolutionary Age Analysis of the Pollen Transcriptome

The birth of new genes in genomes is an important evolutionary event. Several studies reveal that new genes in animals tend to be preferentially expressed in male reproductive tissues such as testis (Betrán et al., 2002; Begun et al., 2007; Dubruille et al., 2012), and thus an "out of testis" hypothesis for the emergence of new genes has been proposed (Vinckenbosch et al., 2006; Kaessmann, 2010). However, such phenomena have not been examined in plant species. Here, by employing a phylostratigraphic method, we dated the origin of protein-coding genes in rice and Arabidopsis thaliana and observed a number of young genes in both species. These young genes tend to encode short extracellular proteins, which may be involved in rapid evolving processes, such as reproductive barriers, species specification, and anti-microbial processes. Further analysis of transcriptome age indexes across different tissues revealed that male reproductive cells express a phylogenetically younger transcriptome than other plant tissues. Compared with sporophytic tissues, the young transcriptomes of the male gametophyte displayed greater complexity and diversity, which included a higher ratio of anti-sense and inter-genic transcripts, reflecting a pervasive transcription state that facilitated the emergence of new genes. Here, we propose that pollen may act as an "innovation incubator" for the birth of de novo genes. With cases of male-biased expression of young genes reported in animals, the "new genes out of the male" model revealed a common evolutionary force that drives reproductive barriers, species specification, and the upgrading of defensive mechanisms against pathogens.

ProCARs: Progressive Reconstruction of Ancestral Gene Orders

Background

In the context of ancestral gene order reconstruction from extant genomes, there exist two main computational approaches: rearrangement-based, and homology-based methods. The rearrangement-based methods consist in minimizing a total rearrangement distance on the branches of a species tree. The homology-based methods consist in the detection of a set of potential ancestral contiguity features, followed by the assembling of these features into Contiguous Ancestral Regions (CARs).

Results

In this paper, we present a new homology-based method that uses a progressive approach for both the detection and the assembling of ancestral contiguity features into CARs. The method is based on detecting a set of potential ancestral adjacencies iteratively using the current set of CARs at each step, and constructing CARs progressively using a 2-phase assembling method.

Conclusion

We show the usefulness of the method through a reconstruction of the boreoeutherian ancestral gene order, and a comparison with three other homology-based methods: AnGeS, InferCARs and GapAdj. The program, written in Python, and the dataset used in this paper are available at http://bioinfo.lifl.fr/procars/.

Identification of lncRNA-associated competing triplets reveals global patterns and prognostic markers for cancer

Recent studies have suggested that long non-coding RNAs (lncRNAs) can interact with microRNAs (miRNAs) and indirectly regulate miRNA targets though competing interactions. However, the molecular mechanisms underlying these interactions are still largely unknown. In this study, these lncRNA–miRNA–gene interactions were defined as lncRNA-associated competing triplets (LncACTs), and an integrated pipeline was developed to identify lncACTs that are active in cancer. Competing lncRNAs had sponge features distinct from non-competing lncRNAs. In the lncACT cross-talk network, disease-associated lncRNAs, miRNAs and coding-genes showed specific topological patterns indicative of their competence and control of communication within the network. The construction of global competing activity profiles revealed that lncACTs had high activity specific to cancers. Analyses of clustered lncACTs revealed that they were enriched in various cancer-related biological processes. Based on the global cross-talk network and cluster analyses, nine cancer-specific sub-networks were constructed. H19- and BRCA1/2-associated lncACTs were able to discriminate between two groups of patients with different clinical outcomes. Disease-associated lncACTs also showed variable competing patterns across normal and cancer patient samples. In summary, this study uncovered and systematically characterized global properties of human lncACTs that may have prognostic value for predicting clinical outcome in cancer patients.

Unlimited Thirst for Genome Sequencing, Data Interpretation, and Database Usage in Genomic Era: The Road towards Fast-Track Crop Plant Improvement

The number of sequenced crop genomes and associated genomic resources is growing rapidly with the advent of inexpensive next generation sequencing methods. Databases have become an integral part of all aspects of science research, including basic and applied plant and animal sciences. The importance of databases keeps increasing as the volume of datasets from direct and indirect genomics, as well as other omics approaches, keeps expanding in recent years. The databases and associated web portals provide at a minimum a uniform set of tools and automated analysis across a wide range of crop plant genomes. This paper reviews some basic terms and considerations in dealing with crop plant databases utilization in advancing genomic era. The utilization of databases for variation analysis with other comparative genomics tools, and data interpretation platforms are well described. The major focus of this review is to provide knowledge on platforms and databases for genome-based investigations of agriculturally important crop plants. The utilization of these databases in applied crop improvement program is still being achieved widely; otherwise, the end for sequencing is not far away.

MiRNAting control of DNA methylation

DNA methylation is a type of epigenetic modification where a methyl group is added to the cytosine or adenine residue of a given DNA sequence. It has been observed that DNA methylation is achieved by some collaborative agglomeration of certain proteins and non-coding RNAs. The assembly of IDN2 and its homologous proteins with siRNAs recruits the enzyme DRM2, which adds a methyl group at certain cytosine residues within the DNA sequence. In this study, it was found that de novo DNA methylation might be regulated by miRNAs through systematic targeting of the genes involved in DNA methylation. A comprehensive genome-wide and system-level study of miRNA targeting, transcription factors, DNA-methylation-causing genes and their target genes has provided a clear picture of an interconnected relationship of all these factors which regulate DNA methylation in Arabidopsis. The study has identified a DNA methylation system that is controlled by four different genes: IDN2, IDNl1, IDNl2 and DRM2. These four genes along with various critical transcription factors appear to be controlled by five different miRNAs. Altogether, DNA methylation appears to be a finely tuned process of opposite control systems of DNAmethylation- causing genes and certain miRNAs pitted against each other.

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

The Orthologous Matrix (OMA) project is a method and associated database inferring evolutionary relationships amongst currently 1706 complete proteomes (i.e. the protein sequence associated for every protein-coding gene in all genomes). In this update article, we present six major new developments in OMA: (i) a new web interface; (ii) Gene Ontology function predictions as part of the OMA pipeline; (iii) better support for plant genomes and in particular homeologs in the wheat genome; (iv) a new synteny viewer providing the genomic context of orthologs; (v) statically computed hierarchical orthologous groups subsets downloadable in OrthoXML format; and (vi) possibility to export parts of the all-against-all computations and to combine them with custom data for 'client-side' orthology prediction. OMA can be accessed through the OMA Browser and various programmatic interfaces at http://omabrowser.org.

FungiFun2: a comprehensive online resource for systematic analysis of gene lists from fungal species

Summary: Systematically extracting biological meaning from omics data is a major challenge in systems biology. Enrichment analysis is often used to identify characteristic patterns in candidate lists. FungiFun is a user-friendly Web tool for functional enrichment analysis of fungal genes and proteins. The novel tool FungiFun2 uses a completely revised data management system and thus allows enrichment analysis for 298 currently available fungal strains published in standard databases. FungiFun2 offers a modern Web interface and creates interactive tables, charts and figures, which users can directly manipulate to their needs.

Availability and implementation: FungiFun2, examples and tutorials are publicly available at https://elbe.hki-jena.de/fungifun/.

Contact: steffen.priebe@hki-jena.de or joerg.linde@hki-jena.de