The Gene Ontology Resource: 20 years and still GOing strong

Evolution of placental invasion and cancer metastasis are causally linked

Among mammals, placental invasion is correlated with vulnerability to malignancy. Animals with more invasive placentation (e.g. humans) are more vulnerable to malignancy. To explain this correlation, we propose the hypothesis of Evolved Levels of Invasibility: the evolution of invasibility of stromal tissue affects both, placental and cancer invasion. We provide evidence for this hypothesis using an in vitro model. We find that bovine endometrial and skin fibroblasts are more resistant to invasion than their human counterparts. Gene expression profiling identified genes with high expression in human but not in bovine fibroblasts. Knocking down a subset of them in human fibroblasts leads to stronger resistance to cancer cell invasion. Identifying the evolutionary determinants of stromal invasibility can provide significant insights to develop rational anti-metastatic therapeutics.

Using INTERSPIA to Explore the Dynamics of Protein-Protein Interactions Among Multiple Species

INTER-Species Protein Interaction Analysis (INTERSPIA) is a web application for identifying diverse patterns of protein-protein interactions (PPIs) in different species. Given a set of proteins of interest to the user, INTERSPIA first discovers additional proteins that are functionally associated with the input proteins as well as different or common patterns of PPIs among the proteins in multiple species through a server-side pipeline. Second, it visualizes the dynamics of PPIs in multiple species via an easy-to-use web interface. This article contains a basic protocol describing how to visualize diverse patterns of PPIs of input proteins in multiple species, and how to use them for functional analysis in the web interface. INTERSPIA is freely available at http://bioinfo.konkuk.ac.kr/INTERSPIA/. © 2019 by John Wiley & Sons, Inc. Basic Protocol: Running INTERSPIA using a list of input proteins.

The Cyclic AMP Receptor Protein Regulates Quorum Sensing and Global Gene Expression in Yersinia pestis during Planktonic Growth and Growth in Biofilms

Cyclic AMP (cAMP) receptor protein (Crp) is an important transcriptional regulator of Yersinia pestis Expression of crp increases during pneumonic plague as the pathogen depletes glucose and forms large biofilms within lungs. To better understand control of Y. pestis Crp, we determined a 1.8-Å crystal structure of the protein-cAMP complex. We found that compared to Escherichia coli Crp, C helix amino acid substitutions in Y. pestis Crp did not impact the cAMP dependency of Crp to bind DNA promoters. To investigate Y. pestis Crp-regulated genes during plague pneumonia, we performed RNA sequencing on both wild-type and Δcrp mutant bacteria growing in planktonic and biofilm states in minimal media with glucose or glycerol. Y. pestis Crp was found to dramatically alter expression of hundreds of genes in a manner dependent upon carbon source and growth state. Gel shift assays confirmed direct regulation of the malT and ptsG promoters, and Crp was then linked to Y. pestis growth on maltose as a sole carbon source. Iron regulation genes ybtA and fyuA were found to be indirectly regulated by Crp. A new connection between carbon source and quorum sensing was revealed as Crp was found to regulate production of acyl-homoserine lactones (AHLs) through direct and indirect regulation of genes for AHL synthetases and receptors. AHLs were subsequently identified in the lungs of Y. pestis-infected mice when crp expression was highest in Y. pestis biofilms. Thus, in addition to the well-studied pla gene, other Crp-regulated genes likely have important functions during plague infection.IMPORTANCE Bacterial pathogens have evolved extensive signaling pathways to translate environmental signals into changes in gene expression. While Crp has long been appreciated for its role in regulating metabolism of carbon sources in many bacterial species, transcriptional profiling has revealed that this protein regulates many other aspects of bacterial physiology. The plague pathogen Y. pestis requires this global regulator to survive in blood, skin, and lungs. During disease progression, this organism adapts to changes within these niches. In addition to regulating genes for metabolism of nonglucose sugars, we found that Crp regulates genes for virulence, metal acquisition, and quorum sensing by direct or indirect mechanisms. Thus, this single transcriptional regulator, which responds to changes in available carbon sources, can regulate multiple critical behaviors for causing disease.

Is MYND Domain-Mediated Assembly of SMYD3 Complexes Involved in Calcium Dependent Signaling?

Macromolecular complexes are essential to intracellular signal transduction by creating signaling niches and enabling a chain of reactions that transmit external signals into various cellular responses. Analysis of SMYD3 interactome indicates this protein lysine methyltransferase might be involved in calcium dependent signaling pathways through forming complexes with the phospholipase PLCB3, calcium/calmodulin dependent kinase CAMK2B, or calcineurin inhibitor RCAN3. SMYD3 is well-known as a histone H3K4 methyltransferase involved in epigenetic transcriptional regulation; however, any roles SMYD3 may play in signaling transduction remain unknown. KEGG pathway enrichment analysis reveals the SMYD3 interacting proteins are overrepresented in several signaling pathways such as estrogen signaling pathway, NOD-like receptor signaling pathway, and WNT signaling pathway. Sequence motif scanning reveals a significant enrichment of PXLXP motif in SMYD3 interacting proteins. The MYND domain of SMYD3 is known to bind to the PXLXP motif. The enrichment of the PXLXP motif suggests that the MYND domain is likely to be a key interaction module that mediates formation of some SMYD3 complexes. The presence of the PXLXP motifs in PLCB3 and CAMK2B indicates the potential role of the MYND domain in mediating complex formation in signaling. The structural basis of SMYD3 MYND domain-mediated interactions is unknown. The only available MYND-peptide complex structure suggests the MYND domain-mediated interaction is likely transient and dynamic. The transient nature will make this domain well-suited to mediate signaling transduction processes where it may allow rapid responses to cellular perturbations and changes in environment.

Genome-Scale Metabolic Networks Shed Light on the Carotenoid Biosynthesis Pathway in the Brown Algae Saccharina japonica and Cladosiphon okamuranus

Understanding growth mechanisms in brown algae is a current scientific and economic challenge that can benefit from the modeling of their metabolic networks. The sequencing of the genomes of Saccharina japonica and Cladosiphon okamuranus has provided the necessary data for the reconstruction of Genome-Scale Metabolic Networks (GSMNs). The same in silico method deployed for the GSMN reconstruction of Ectocarpus siliculosus to investigate the metabolic capabilities of these two algae, was used. Integrating metabolic profiling data from the literature, we provided functional GSMNs composed of an average of 2230 metabolites and 3370 reactions. Based on these GSMNs and previously published work, we propose a model for the biosynthetic pathways of the main carotenoids in these two algae. We highlight, on the one hand, the reactions and enzymes that have been preserved through evolution and, on the other hand, the specificities related to brown algae. Our data further indicate that, if abscisic acid is produced by Saccharina japonica, its biosynthesis pathway seems to be different in its final steps from that described in land plants. Thus, our work illustrates the potential of GSMNs reconstructions for formalizing hypotheses that can be further tested using targeted biochemical approaches.

Mapping the perturbome network of cellular perturbations

Drug combinations provide effective treatments for diverse diseases, but also represent a major cause of adverse reactions. Currently there is no systematic understanding of how the complex cellular perturbations induced by different drugs influence each other. Here, we introduce a mathematical framework for classifying any interaction between perturbations with high-dimensional effects into 12 interaction types. We apply our framework to a large-scale imaging screen of cell morphology changes induced by diverse drugs and their combination, resulting in a perturbome network of 242 drugs and 1832 interactions. Our analysis of the chemical and biological features of the drugs reveals distinct molecular fingerprints for each interaction type. We find a direct link between drug similarities on the cell morphology level and the distance of their respective protein targets within the cellular interactome of molecular interactions. The interactome distance is also predictive for different types of drug interactions.

High content phenotypic screening identifies serotonin receptor modulators with selective activity upon breast cancer cell cycle and cytokine signaling pathways

Heterogeneity in disease mechanisms between genetically distinct patients contributes to high attrition rates in late stage clinical drug development. New personalized medicine strategies aim to identify predictive biomarkers which stratify patients most likely to respond to a particular therapy. However, for complex multifactorial diseases not characterized by a single genetic driver, empirical approaches to identifying predictive biomarkers and the most promising therapies for personalized medicine are required. In vitro pharmacogenomics seeks to correlate in vitro drug sensitivity testing across panels of genetically distinct cell models with genomic, gene expression or proteomic data to identify predictive biomarkers of drug response. However, the vast majority of in vitro pharmacogenomic studies performed to date are limited to dose-response screening upon a single viability assay endpoint. In this article we describe the application of multiparametric high content phenotypic screening and the theta comparative cell scoring method to quantify and rank compound hits, screened at a single concentration, which induce a broad variety of divergent phenotypic responses between distinct breast cancer cell lines. High content screening followed by transcriptomic pathway analysis identified serotonin receptor modulators which display selective activity upon breast cancer cell cycle and cytokine signaling pathways correlating with inhibition of cell growth and survival. These methods describe a new evidence-led approach to rapidly identify compounds which display distinct response between different cell types. The results presented also warrant further investigation of the selective activity of serotonin receptor modulators upon breast cancer cell growth and survival as a potential drug repurposing opportunity.

The Cytoscape BioGateway App: explorative network building from the BioGateway triple store

SUMMARY

The BioGateway App is a Cytoscape (version 3) plugin designed to provide easy query access to the BioGateway RDF triple store, which contains functional and interaction information for proteins from several curated resources. For explorative network building, we have added a comprehensive dataset with regulatory relationships of mammalian DNA binding transcription factors and their target genes, compiled both from curated resources and from a text mining effort. Query results are visualised using the inherent flexibility of the Cytoscape framework, and network links can be checked against curated database records or against the original publication.

AVAILABILITY

Install through the Cytoscape application manager or visit www.biogateway.eu for download and tutorial documents.

SUPPLEMENTARY INFORMATION

Supplementary information is available at Bioinformatics online.

LFQ-Analyst: An Easy-To-Use Interactive Web Platform To Analyze and Visualize Label-Free Proteomics Data Preprocessed with MaxQuant

Relative label-free quantification (LFQ) of shotgun proteomics data using precursor (MS1) signal intensities is one of the most commonly used applications to comprehensively and globally quantify proteins across biological samples and conditions. Due to the popularity of this technique, several software packages, such as the popular software suite MaxQuant, have been developed to extract, analyze, and compare spectral features and to report quantitative information of peptides, proteins, and even post-translationally modified sites. However, there is still a lack of accessible tools for the interpretation and downstream statistical analysis of these complex data sets, in particular for researchers and biologists with no or only limited experience in proteomics, bioinformatics, and statistics. We have therefore created LFQ-Analyst, which is an easy-to-use, interactive web application developed to perform differential expression analysis with "one click" and to visualize label-free quantitative proteomic data sets preprocessed with MaxQuant. LFQ-Analyst provides a wealth of user-analytic features and offers numerous publication-quality result graphics to facilitate statistical and exploratory analysis of label-free quantitative data sets. LFQ-Analyst, including an in-depth user manual, is freely available at https://bioinformatics.erc.monash.edu/apps/LFQ-Analyst .

Molecular Profiling of the Drosophila Antenna Reveals Conserved Genes Underlying Olfaction in Insects

Repellent odors are widely used to prevent insect-borne diseases, making it imperative to identify the conserved molecular underpinnings of their olfactory systems. Currently, little is known about the molecules supporting odor signaling beyond the odor receptors themselves. Most known molecules function in one of two classes of olfactory sensilla, single-walled or double-walled, which have differing morphology and odor response profiles. Here, we took two approaches to discover novel genes that contribute to insect olfaction in the periphery. We transcriptionally profiled Drosophila melanogasteramos mutants that lack trichoid and basiconic sensilla, the single-walled sensilla in this species. This revealed 187 genes whose expression is enriched in these sensilla, including pickpocket ion channels and neuromodulator GPCRs that could mediate signaling pathways unique to single-walled sensilla. For our second approach, we computationally identified 141 antennal-enriched (AE) genes that are more than ten times as abundant in D. melanogaster antennae as in other tissues or whole-body extracts, and are thus likely to play a role in olfaction. We identified unambiguous orthologs of AE genes in the genomes of four distantly related insect species, and most identified orthologs were expressed in the antenna of these species. Further analysis revealed that nearly half of the 141 AE genes are localized specifically to either single or double-walled sensilla. Functional annotation suggests the AE genes include signaling molecules and enzymes that could be involved in odorant degradation. Together, these two resources provide a foundation for future studies investigating conserved mechanisms of odor signaling.

LncRNA ROR1‑AS1 high expression and its prognostic significance in liver cancer

Hepatocellular carcinoma (HCC) is a common disease of the digestive system with no curative treatments. Long noncoding RNA tyrosine protein kinase transmembrane receptor 1 antisense RNA 1 (lncRNA ROR1-AS1) is an lncRNA whose functions have been predicted in human diseases; however, its important role in cancer has been probed only in mantle cell lymphoma, not in HCC. Therefore, the present study aimed to elucidate the prognostic significance of lncRNA ROR1-AS1 in HCC. The Cancer Genome Atlas Liver Hepatocellular Carcinoma was used to analyze the expression of ROR1-AS1 in liver cancer. χ² tests were performed to evaluate associations between clinical characteristics and ROR1-AS1 expression. The role of ROR1-AS1 in HCC prognosis was assessed using Kaplan-Meier curves and proportional hazards model (Cox) analysis. Gene set enrichment analysis was performed by using a Gene Expression Omnibus dataset. At the same time, Multi Experiment Matrix was used to predict genes that may be co-expressed with ROR1-AS1. The Database for Annotation, Visualization and Integrated Discovery and KO-Based Annotation System were used to analyze the most closely associated cytological behaviors and pathways in HCC. Then, the genes in the three databases were integrated to screen mRNAs, microRNAs and lncRNAs that had co-expression relationships with ROR1-AS1. Cytoscape, Search Tool for the Retrieval of Interacting Genes/Proteins and Molecular Evolutionary Genetics Analysis were used to map potential regulatory networks and developmental relationships associated with ROR1-AS1. Finally, 12 genes most closely associated with ROR1-AS1 were identified, and their relationship was described using a Circos plot. The results showed that ROR1-AS1 was upregulated in HCC, and its expression was related to clinical stage, T stage and N stage. Furthermore, Kaplan-Meier curves and Cox analysis indicated that high expression of ROR1-AS1 was associated with poor prognosis, and that ROR1-AS1 was an independent risk factor for HCC. Co-expression data suggested that there may be a large regulatory network of 45 genes with indirect associations with ROR1-AS1, a small regulatory network of 15 genes with direct or indirect regulatory relationships, and a special regulatory network containing 12 genes directly associated with ROR1-AS1. The present findings indicated that high expression of ROR1-AS1 suggests poor prognosis in patients with HCC.

Challenges in the annotation of pseudoenzymes in databases: the UniProtKB approach

The universal protein knowledgebase (UniProtKB) collects and centralises functional information on proteins across a wide range of species. In addition to the functional information added to all protein entries, for enzymes, which represent 20-40% of most proteomes, UniProtKB provides additional information about Enzyme Commission classification, catalytic activity, cofactors, enzyme regulation, kinetics and pathways, all based on critical assessment of published experimental data. Computer-based analysis and structural data are used to enrich the annotation of the sequence through the identification of active sites and binding sites. While the annotation of enzymes is well-defined, the curation of pseudoenzymes in UniProtKB has highlighted some challenges: how to identify them, how to assess their lack of catalytic activity, how to annotate their lack of catalytic activity in a consistent way and how much can be inferred and propagated from experimental data obtained from other species. Through various examples, we illustrate some of these issues and discuss some of the changes we propose to enhance the annotation and discovery of pseudoenzymes. Ultimately, improving the curation of pseudoenzymes will provide the scientific community with a comprehensive resource for pseudoenzymes, which in turn will lead to a better understanding of the evolution of these molecules, the aetiology of related diseases and the development of drugs.

Sequence and Structure Properties Uncover the Natural Classification of Protein Complexes Formed by Intrinsically Disordered Proteins via Mutual Synergistic Folding

Intrinsically disordered proteins mediate crucial biological functions through their interactions with other proteins. Mutual synergistic folding (MSF) occurs when all interacting proteins are disordered, folding into a stable structure in the course of the complex formation. In these cases, the folding and binding processes occur in parallel, lending the resulting structures uniquely heterogeneous features. Currently there are no dedicated classification approaches that take into account the particular biological and biophysical properties of MSF complexes. Here, we present a scalable clustering-based classification scheme, built on redundancy-filtered features that describe the sequence and structure properties of the complexes and the role of the interaction, which is directly responsible for structure formation. Using this approach, we define six major types of MSF complexes, corresponding to biologically meaningful groups. Hence, the presented method also shows that differences in binding strength, subcellular localization, and regulation are encoded in the sequence and structural properties of proteins. While current protein structure classification methods can also handle complex structures, we show that the developed scheme is fundamentally different, and since it takes into account defining features of MSF complexes, it serves as a better representation of structures arising through this specific interaction mode.

Synergistic Genetic Interactions between Pkhd1 and Pkd1 Result in an ARPKD-Like Phenotype in Murine Models

BACKGROUND

Autosomal recessive polycystic kidney disease (ARPKD) and autosomal dominant polycystic kidney disease (ADPKD) are genetically distinct, with ADPKD usually caused by the genes PKD1 or PKD2 (encoding polycystin-1 and polycystin-2, respectively) and ARPKD caused by PKHD1 (encoding fibrocystin/polyductin [FPC]). Primary cilia have been considered central to PKD pathogenesis due to protein localization and common cystic phenotypes in syndromic ciliopathies, but their relevance is questioned in the simple PKDs. ARPKD's mild phenotype in murine models versus in humans has hampered investigating its pathogenesis.

METHODS

To study the interaction between Pkhd1 and Pkd1, including dosage effects on the phenotype, we generated digenic mouse and rat models and characterized and compared digenic, monogenic, and wild-type phenotypes.

RESULTS

The genetic interaction was synergistic in both species, with digenic animals exhibiting phenotypes of rapidly progressive PKD and early lethality resembling classic ARPKD. Genetic interaction between Pkhd1 and Pkd1 depended on dosage in the digenic murine models, with no significant enhancement of the monogenic phenotype until a threshold of reduced expression at the second locus was breached. Pkhd1 loss did not alter expression, maturation, or localization of the ADPKD polycystin proteins, with no interaction detected between the ARPKD FPC protein and polycystins. RNA-seq analysis in the digenic and monogenic mouse models highlighted the ciliary compartment as a common dysregulated target, with enhanced ciliary expression and length changes in the digenic models.

CONCLUSIONS

These data indicate that FPC and the polycystins work independently, with separate disease-causing thresholds; however, a combined protein threshold triggers the synergistic, cystogenic response because of enhanced dysregulation of primary cilia. These insights into pathogenesis highlight possible common therapeutic targets.

P38-Mediated Cellular Senescence in Conjunctivochalasis Fibroblasts

Purpose

Conjunctivochalasis (CCH) is a common ocular disease and has received extensive attention recently. However, its exact pathogenesis remains largely unknown. Owing to the high morbidity of CCH in older people, this study aimed to investigate whether cellular senescence contributes to CCH progression and the underlying mechanism.

Methods

Loose conjunctival tissues from CCH patients (n = 13) and normal conjunctival tissues from age-matched persons (n = 12) were obtained and the fibroblasts were separately induced and obtained. Cellular senescence, and the expression of senescence-associated genes (p53 and p21) and p38 in CCH conjunctival tissues and normal controls, were determined by senescence-associated β-galactosidase (SA-β-Gal) staining and quantitative (q)RT-PCR, respectively. To explore the effects of p38 on cellular senescence in CCH fibroblasts, small interfering RNA (siRNA) targeting p38 (siP38) and p38-specific inhibitor SB203580 was performed in CCH fibroblasts. Then, cellular senescence, cell viability, reactive oxygen species (ROS) production, and gene expression were detected according to the corresponding methods.

Results

CCH conjunctival tissues had significantly more senescent cells, evidenced by more SA-β-Gal-positive cells, and higher expression of senescence-associated genes (p53 and p21) and p38. CCH fibroblasts transfected with siP38 or treated with SB203580 had obviously reduced numbers of senescent cells, decreased ROS production, and increased cell viability, as well as reduced expression of senescence-associated genes. Meanwhile, blocking p38 signaling decreased the expression of p53 and p21.

Conclusions

Therefore, these findings indicate that cellular senescence might be a causative factor for CCH. P38 signaling might play an important role in the progress of cellular senescence in CCH fibroblasts via manipulation of p53/p21 signaling.

Association between breast cancer cell migration and radiosensitivity in vitro

The aim of the present study was to examine the association between the migration of breast cancer cells in vitro and radiosensitivity by establishing a breast cancer cell model with different migratory capacities. Transwell chambers in a 24-well plate were used to separate MDA-MB-231 and ZR-7530 cells and to establish cell models with different migratory capacities. Subsequently, the radiosensitivity of the cell models was measured using a radiation clone formation assay. Furthermore, differential gene expression was determined using gene microarray analysis. The protein expression levels of the differentially expressed genes (DEGs) were assessed using western blot analysis. From each parental cell line, a pair of daughter cell lines were established in with differing migratory abilities. These daughter cell lines were named MDA-MB-231 UP-10 (231 UP-10), MDA-MB-231 Down-10 (231 Down-10), ZR-75-30 UP-10 (7530 UP-10) and ZR-75-30 Down-10 (7530 Down-10). Radiation clone formation assays revealed that the cell lines with increased migratory abilities (231 Down-10 and 7530 Down-10) demonstrated higher radio-resistance compared with the cell lines with decreased migratory abilities (231 UP-10 and 7530 UP-10). Gene microarrays identified numerous DEGs between the pairs of UP and Down cell lines. A focus was placed on genes associated with cell adhesion and it was identified that phosphorylated Fak and phosphorylated EGFR expression levels were increased in 231 Down-10 and 7530 Down-10 cells, compared with the 231 UP-10 and 7530 UP-10 cells. Other genes including ZO-1, FN1 and SOX9 expression were also increased in the 231 Down-10 and 7530 Down-10 cells compared with 231 UP-10 and 7530 UP-10 cells. Cell lines with increased migratory capacities may be more radio-resistant compared with cell lines with a decreased migratory capabilities. The mechanism may be associated with changes in the expression of cell adhesion molecules and epithelial-mesenchymal transition (EMT). Therapeutic strategies targeting cell adhesion or EMT may increase the radiation sensitivity of breast cancer cells, in addition to improving the effect of radiation therapy.

A Genome-Wide Screen for Wortmannin-Resistant Mutants in Schizosaccharomyces pombe: The Phosphorylation-Impaired Mutants Are Resistant to Signaling Defect

Complex human diseases such as metabolic disorders, cancer, neurodegenerative diseases, and mitochondrial dysfunctions arise from the biochemical or genetic defects in various cellular processes. Therefore, it is important to understand which metabolic processes are affected by which cellular impairment. Because genome-wide screening of mutant collections (haploid/diploid deletion library) provides important clues for the understanding of conserved biological processes and for finding potential target genes, we screened the haploid mutant collection of Schizosaccharomyces pombe with wortmannin that inhibits phosphatidylinositol-3-kinase signaling. Using genome-wide screening, we determined that 52 mutants were resistant to this chemical. When 52 genes that are deleted in these mutants were grouped in 41 different biological processes, we found that 37 of them have human orthologues and 4 genes were associated with human metabolic disorders. In addition, when we examined the pathways in which these 52 genes function, we determined that 9 genes were related to phosphorylation process. These results might provide new insights for better understanding of certain human diseases.

PSMD: An extensive database for pan-species microsatellite investigation and marker development

Microsatellites are widely distributed throughout nearly all genomes which have been extensively exploited as powerful genetic markers for diverse applications due to their high polymorphisms. Their length variations are involved in gene regulation and implicated in numerous genetic diseases even in cancers. Although much effort has been devoted in microsatellite database construction, the existing microsatellite databases still had some drawbacks, such as limited number of species, unfriendly export format, missing marker development, lack of compound microsatellites and absence of gene annotation, which seriously restricted researchers to perform downstream analysis. In order to overcome the above limitations, we developed PSMD (Pan-Species Microsatellite Database, http://big.cdu.edu.cn/psmd/) as a web-based database to facilitate researchers to easily identify microsatellites, exploit reliable molecular markers and compare microsatellite distribution pattern on genome-wide scale. In current release, PSMD comprises 678,106,741 perfect microsatellites and 43,848,943 compound microsatellites from 18,408 organisms, which covered almost all species with available genomic data. In addition to interactive browse interface, PSMD also offers a flexible filter function for users to quickly gain desired microsatellites from large data sets. PSMD allows users to export GFF3 formatted file and CSV formatted statistical file for downstream analysis. We also implemented an online tool for analysing occurrence of microsatellites with user-defined parameters. Furthermore, Primer3 was embedded to help users to design high-quality primers with customizable settings. To our knowledge, PSMD is the most extensive resource which is likely to be adopted by scientists engaged in biological, medical, environmental and agricultural research.

Multi-tissue network analysis for drug prioritization in knee osteoarthritis

Knee osteoarthritis (OA) is a joint disease that affects several tissues: cartilage, synovium, meniscus and subchondral bone. The pathophysiology of this complex disease is still not completely understood and existing pharmaceutical strategies are limited to pain relief treatments. Therefore, a computational method was developed considering the diverse mechanisms and the multi-tissue nature of OA in order to suggest pharmaceutical compounds. Specifically, weighted gene co-expression network analysis (WGCNA) was utilized to identify gene modules that were preserved across four joint tissues. The driver genes of these modules were selected as an input for a network-based drug discovery approach. WGCNA identified two preserved modules that described functions related to extracellular matrix physiology and immune system responses. Compounds that affected various anti-inflammatory pathways and drugs targeted at coagulation pathways were suggested. 9 out of the top 10 compounds had a proven association with OA and significantly outperformed randomized approaches not including WGCNA. The method presented herein is a viable strategy to identify overlapping molecular mechanisms in multi-tissue diseases such as OA and employ this information for drug discovery and compound prioritization.

Screening and Identification of Key Biomarkers in Pancreatic Cancer: Evidence from Bioinformatic Analysis

Pancreatic cancer (PC) whose mortality is comparable to morbidity is a highly fatal disease. Early approaches of diagnosis and treatment for PC are quite limited, so it is of great urgency to figure out the exact tumorigenesis and development mechanism of PC. To identify the related molecular markers of pancreatic oncogenesis, we downloaded three microarray datasets (GSE63111, GSE101448, and GSE107610) from Gene Expression Omnibus (GEO) database. The common differentially expressed genes (DEGs) among them were identified, and the corresponding function enrichment analyses were accomplished. The protein-protein interaction network was conducted by Search Tool for the Retrieval of Interacting Genes (STRING), and the corresponding module analysis was accomplished by Cytoscape. There were 55 DEGs found in total. The molecular function and biological processes (BP) of these DEGs mainly include cytokinesis, mitotic nuclear division, cell division, cell proliferation, microtubule-based movement, and mineral absorption. Among the 55 DEGs, 14 hub genes were further confirmed and it was concluded that they mainly function in mitotic cytokinesis, microtubule-based movement, mitotic chromosome condensation, and mitotic spindle assembly from the BP analysis. The survival analysis showed that all the 14 hub genes, especially nucleolar and spindle associated protein 1 and abnormal spindle microtubule assembly, may involve in the tumorigenesis and development of PC. And they might be used as new biomarkers for auxiliary diagnosis and potential targets for immunotherapy of PC.

Fermentation innovation through complex hybridization of wild and domesticated yeasts

The most common fermented beverage, lager beer, is produced by interspecies hybrids of the brewing yeast Saccharomyces cerevisiae and its wild relative S. eubayanus. Lager-brewing yeasts are not the only example of hybrid vigour or heterosis in yeasts, but the full breadth of interspecies hybrids associated with human fermentations has received less attention. Here we present a comprehensive genomic analysis of 122 Saccharomyces hybrids and introgressed strains. These strains arose from hybridization events between two to four species. Hybrids with S. cerevisiae contributions originated from three lineages of domesticated S. cerevisiae, including the major wine-making lineage and two distinct brewing lineages. In contrast, the undomesticated parents of these interspecies hybrids were all from wild Holarctic or European lineages. Most hybrids have inherited a mitochondrial genome from a parent other than S. cerevisiae, which recent functional studies suggest could confer adaptation to colder temperatures. A subset of hybrids associated with crisp flavour profiles, including both lineages of lager-brewing yeasts, have inherited inactivated S. cerevisiae alleles of critical phenolic off-flavour genes and/or lost functional copies from the wild parent through multiple genetic mechanisms. These complex hybrids shed light on the convergent and divergent evolutionary trajectories of interspecies hybrids and their impact on innovation in lager brewing and other diverse fermentation industries.

Regulation of interferon stimulated gene expression levels at homeostasis

Interferon stimulated genes (ISGs), a collection of genes important in the early innate immune response, are upregulated in response to stimulation by extracellular type I interferons. The regulation of ISGs has been extensively studied in cells exposed to significant interferon stimulation, but less is known about ISG regulation in homeostatic regimes in which extracellular interferon levels are low. Using a collection of pre-existing, publicly available microarray datasets, we investigated ISG regulation at homeostasis in CD4, pulmonary epithelial, fibroblast and macrophage cells. We used a linear regression model to predict ISG expression levels from regulator expression levels. Our results suggest significant regulation of ISG expression at homeostasis, both through the ISGF3 molecule and through IRF7 and IRF8 associated pathways. We find that roughly 50% of ISGs have expression levels significantly correlated with ISGF3 expression levels at homeostasis, supporting previous results suggesting that homeostatic IFN levels have broad functional consequences. We find that ISG expression levels varied in their correlation with ISGF3, with epithelial and macrophage cells showing more correlation than CD4 and fibroblast cells. Our analysis provides a novel approach for decomposing and quantifying ISG regulation.

Identification of hub genes and key pathways associated with the progression of gynecological cancer

Gynecological cancer is the leading cause of cancer mortality in women. However, the mechanisms underlying gynecological cancer progression have remained largely unclear. In the present study, 799 dysregulated genes were identified in ovarian serous cystadenocarcinoma (OV), 488 dysregulated genes in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), and 621 dysregulated genes in uterine corpus endometrial carcinoma (UCEC). Bioinformatics analysis revealed that mRNA splicing and cell proliferation-associated biological processes served important roles in OV progression. Metabolism-associated biological processes played important roles in CESC progression, and protein phosphorylation and small GTPase-mediated signal transduction served important roles in UCEC progression. The present study also constructed OV, CESC and UCEC progression-associated protein-protein interaction networks to reveal the associations among these genes. Furthermore, Kaplan-Meier curve analysis showed that progression-related genes were associated with the duration of overall survival. Finally, NARS2 and TPT1 in OV, SMYD2, EGLN1, TNFRSF10D, FUT11, SYTL3, MMP8 and EREG in CESC, and SLC5A1, TXN, KDM4B, TXNDC11, HSDL2, COX16, MGAT4A, DAGLA, ELOVL7, THRB and PCOLCE2 in UCEC were identified as hub genes in cancer progression. Therefore, this study may assist in the identification of novel mechanisms underlying cancer progression and new biomarkers for gynecological cancer prognosis and therapy.

Expression of Protein-Coding Gene Orthologs in Zebrafish and Mouse Inner Ear Non-sensory Supporting Cells

Non-mammalian vertebrates, including zebrafish, retain the ability to regenerate hair cells (HCs) due to unknown molecular mechanisms that regulate proliferation and conversion of non-sensory supporting cells (nsSCs) to HCs. This regenerative capacity is not conserved in mammals. Identification of uniquely expressed orthologous genes in zebrafish nsSCs may reveal gene candidates involved in the proliferation and transdifferentiation of zebrafish nsSCs to HCs in the inner ear. A list of orthologous protein-coding genes was generated based on an Ensembl Biomart comparison of the zebrafish and mouse genomes. Our previously published RNA-seq-based transcriptome datasets of isolated inner ear zebrafish nsSCs and HCs, and mouse non-sensory supporting pillar and Deiters’ cells, and HCs, were merged to analyze gene expression patterns between the two species. Out of 17,498 total orthologs, 11,752 were expressed in zebrafish nsSCs and over 10,000 orthologs were expressed in mouse pillar and Deiters’ cells. Differentially expressed genes common among the zebrafish nsSCs and mouse pillar and Deiters’ cells, compared to species-specific HCs, included 306 downregulated and 314 upregulated genes; however, over 1,500 genes were uniquely upregulated in zebrafish nsSCs. Functional analysis of genes uniquely expressed in nsSCs identified several transcription factors associated with cell fate determination, cell differentiation and nervous system development, indicating inherent molecular properties of nsSCs that promote self-renewal and transdifferentiation into new HCs. Our study provides a means of characterizing these orthologous genes, involved in proliferation and transdifferentiation of nsSCs to HCs in zebrafish, which may lead to identification of potential targets for HC regeneration in mammals.

GENAVi: a shiny web application for gene expression normalization, analysis and visualization

BACKGROUND

The development of next generation sequencing (NGS) methods led to a rapid rise in the generation of large genomic datasets, but the development of user-friendly tools to analyze and visualize these datasets has not developed at the same pace. This presents a two-fold challenge to biologists; the expertise to select an appropriate data analysis pipeline, and the need for bioinformatics or programming skills to apply this pipeline. The development of graphical user interface (GUI) applications hosted on web-based servers such as Shiny can make complex workflows accessible across operating systems and internet browsers to those without programming knowledge.

RESULTS

We have developed GENAVi (Gene Expression Normalization Analysis and Visualization) to provide a user-friendly interface for normalization and differential expression analysis (DEA) of human or mouse feature count level RNA-Seq data. GENAVi is a GUI based tool that combines Bioconductor packages in a format for scientists without bioinformatics expertise. We provide a panel of 20 cell lines commonly used for the study of breast and ovarian cancer within GENAVi as a foundation for users to bring their own data to the application. Users can visualize expression across samples, cluster samples based on gene expression or correlation, calculate and plot the results of principal components analysis, perform DEA and gene set enrichment and produce plots for each of these analyses. To allow scalability for large datasets we have provided local install via three methods. We improve on available tools by offering a range of normalization methods and a simple to use interface that provides clear and complete session reporting and for reproducible analysis.

CONCLUSION

The development of tools using a GUI makes them practical and accessible to scientists without bioinformatics expertise, or access to a data analyst with relevant skills. While several GUI based tools are currently available for RNA-Seq analysis we improve on these existing tools. This user-friendly application provides a convenient platform for the normalization, analysis and visualization of gene expression data for scientists without bioinformatics expertise.

Exosome complex genes mediate RNA degradation and predict survival in mantle cell lymphoma

Exosome complex (EXOSC) genes, which encode a multi-protein intracellular complex, mediate the degradation of various types of RNA molecules. EXOSCs, also known as polymyositis/scleroderma complexes, exist in eukaryotic cells and archaea, and primarily mediate 3′ to 5′mRNA degradation. However, how EXOSC genes are implicated in processes of B-cell immune-associated pathways and B-cell tumorigenesis remains unclear. The present bioinformatics study indicated that 6 of 10 EXOSC genes, particularly the EXO.index, were able to predict the survival of patients with mantle cell lymphoma (MCL), by analyzing gene expression profiles of 123 patients with MCL from the Gene Expression Omnibus database. The results suggested that EXOSC gene expression may be a molecular marker for MCL. Compared with the whole transcript profile, patients with MCL with a high EXO.index exhibited poorer survival and decreased RNA levels, which was also verified in a second dataset. The EXOSC genes may be associated with DNA repair and B-cell activation pathways, which may be the cause of poorer survival of patients with MCL.

Biological Network Approaches and Applications in Rare Disease Studies

Network biology has the capability to integrate, represent, interpret, and model complex biological systems by collectively accommodating biological omics data, biological interactions and associations, graph theory, statistical measures, and visualizations. Biological networks have recently been shown to be very useful for studies that decipher biological mechanisms and disease etiologies and for studies that predict therapeutic responses, at both the molecular and system levels. In this review, we briefly summarize the general framework of biological network studies, including data resources, network construction methods, statistical measures, network topological properties, and visualization tools. We also introduce several recent biological network applications and methods for the studies of rare diseases.

Stereotyped transcriptomic transformation of somatosensory neurons in response to injury

In mice, spared nerve injury replicates symptoms of human neuropathic pain and induces upregulation of many genes in somatosensory neurons. Here we used single cell transcriptomics to probe the effects of partial infraorbital transection of the trigeminal nerve at the cellular level. Uninjured neurons were unaffected by transection of major nerve branches, segregating into many different classes. In marked contrast, axotomy rapidly transformed damaged neurons into just two new and closely-related classes where almost all original identity was lost. Remarkably, sensory neurons also adopted this transcriptomic state following various minor peripheral injuries. By genetically marking injured neurons, we showed that the injury-induced transformation was reversible, with damaged cells slowly reacquiring normal gene expression profiles. Thus, our data expose transcriptomic plasticity, previously thought of as a driver of chronic pain, as a programed response to many types of injury and a potential mechanism for regulating sensation during wound healing.

The application of omics-based human liver platforms for investigating the mechanism of drug-induced hepatotoxicity in vitro

Drug-induced liver injury (DILI) complicates safety assessment for new drugs and poses major threats to both patient health and drug development in the pharmaceutical industry. A number of human liver cell-based in vitro models combined with toxicogenomics methods have been developed as an alternative to animal testing for studying human DILI mechanisms. In this review, we discuss the in vitro human liver systems and their applications in omics-based drug-induced hepatotoxicity studies. We furthermore present bioinformatic approaches that are useful for analyzing toxicogenomic data generated from these models and discuss their current and potential contributions to the understanding of mechanisms of DILI. Human pluripotent stem cells, carrying donor-specific genetic information, hold great potential for advancing the study of individual-specific toxicological responses. When co-cultured with other liver-derived non-parenchymal cells in a microfluidic device, the resulting dynamic platform enables us to study immune-mediated drug hypersensitivity and accelerates personalized drug toxicology studies. A flexible microfluidic platform would also support the assembly of a more advanced organs-on-a-chip device, further bridging gap between in vitro and in vivo conditions. The standard transcriptomic analysis of these cell systems can be complemented with causality-inferring approaches to improve the understanding of DILI mechanisms. These approaches involve statistical techniques capable of elucidating regulatory interactions in parts of these mechanisms. The use of more elaborated human liver models, in harmony with causality-inferring bioinformatic approaches will pave the way for establishing a powerful methodology to systematically assess DILI mechanisms across a wide range of conditions.

CAGEfightR: analysis of 5'-end data using R/Bioconductor

BACKGROUND

5'-end sequencing assays, and Cap Analysis of Gene Expression (CAGE) in particular, have been instrumental in studying transcriptional regulation. 5'-end methods provide genome-wide maps of transcription start sites (TSSs) with base pair resolution. Because active enhancers often feature bidirectional TSSs, such data can also be used to predict enhancer candidates. The current availability of mature and comprehensive computational tools for the analysis of 5'-end data is limited, preventing efficient analysis of new and existing 5'-end data.

RESULTS

We present CAGEfightR, a framework for analysis of CAGE and other 5'-end data implemented as an R/Bioconductor-package. CAGEfightR can import data from BigWig files and allows for fast and memory efficient prediction and analysis of TSSs and enhancers. Downstream analyses include quantification, normalization, annotation with transcript and gene models, TSS shape statistics, linking TSSs to enhancers via co-expression, identification of enhancer clusters, and genome-browser style visualization. While built to analyze CAGE data, we demonstrate the utility of CAGEfightR in analyzing nascent RNA 5'-data (PRO-Cap). CAGEfightR is implemented using standard Bioconductor classes, making it easy to learn, use and combine with other Bioconductor packages, for example popular differential expression tools such as limma, DESeq2 and edgeR.

CONCLUSIONS

CAGEfightR provides a single, scalable and easy-to-use framework for comprehensive downstream analysis of 5'-end data. CAGEfightR is designed to be interoperable with other Bioconductor packages, thereby unlocking hundreds of mature transcriptomic analysis tools for 5'-end data. CAGEfightR is freely available via Bioconductor: bioconductor.org/packages/CAGEfightR .

Binding to medium and long chain fatty acyls is a common property of HEAT and ARM repeat modules

Covalent post-translational modification (PTM) of proteins with acyl groups of various carbon chain-lengths regulates diverse biological processes ranging from chromatin dynamics to subcellular localization. While the YEATS domain has been found to be a prominent reader of acetylation and other short acyl modifications, whether additional acyl-lysine reader domains exist, particularly for longer carbon chains, is unclear. Here, we employed a quantitative proteomic approach using various modified peptide baits to identify reader proteins of various acyl modifications. We discovered that proteins harboring HEAT and ARM repeats bind to lysine myristoylated peptides. Recombinant HEAT and ARM repeats bind to myristoylated peptides independent of the peptide sequence or the position of the myristoyl group. Indeed, HEAT and ARM repeats bind directly to medium- and long-chain free fatty acids (MCFA and LCFA). Lipidomic experiments suggest that MCFAs and LCFAs interact with HEAT and ARM repeat proteins in mammalian cells. Finally, treatment of cells with exogenous MCFAs and inhibitors of MCFA-CoA synthases increase the transactivation activity of the ARM repeat protein β-catenin. Taken together, our results suggest an unappreciated role for fatty acids in the regulation of proteins harboring HEAT or ARM repeats.

Druggable Transcriptional Networks in the Human Neurogenic Epigenome

Chromosome conformation capture methods have revealed the dynamics of genome architecture which is spatially organized into topologically associated domains, with gene regulation mediated by enhancer-promoter pairs in chromatin space. New evidence shows that endogenous hormones and several xenobiotics act within circumscribed topological domains of the spatial genome, impacting subsets of the chromatin contacts of enhancer-gene promoter pairs in cis and trans Results from the National Institutes of Health-funded PsychENCODE project and the study of chromatin remodeling complexes have converged to provide a clearer understanding of the organization of the neurogenic epigenome in humans. Neuropsychiatric diseases, including schizophrenia, bipolar spectrum disorder, autism spectrum disorder, attention deficit hyperactivity disorder, and other neuropsychiatric disorders are significantly associated with mutations in neurogenic transcriptional networks. In this review, we have reanalyzed the results from publications of the PsychENCODE Consortium using pharmacoinformatics network analysis to better understand druggable targets that control neurogenic transcriptional networks. We found that valproic acid and other psychotropic drugs directly alter these networks, including chromatin remodeling complexes, transcription factors, and other epigenetic modifiers. We envision a new generation of CNS therapeutics targeted at neurogenic transcriptional control networks, including druggable parts of chromatin remodeling complexes and master transcription factor-controlled pharmacogenomic networks. This may provide a route to the modification of interconnected gene pathways impacted by disease in patients with neuropsychiatric and neurodegenerative disorders. Direct and indirect therapeutic strategies to modify the master regulators of neurogenic transcriptional control networks may ultimately help extend the life span of CNS neurons impacted by disease.

Comprehensive in vivo identification of the c-Myc mRNA protein interactome using HyPR-MS

Proteins bind mRNA through their entire life cycle from transcription to degradation. We analyzed c-Myc mRNA protein interactors in vivo using the HyPR-MS method to capture the crosslinked mRNA by hybridization and then analyzed the bound proteins using mass spectrometry proteomics. Using HyPR-MS, 229 c-Myc mRNA-binding proteins were identified, confirming previously proposed interactors, suggesting new interactors, and providing information related to the roles and pathways known to involve c-Myc. We performed structural and functional analysis of these proteins and validated our findings with a combination of RIP-qPCR experiments, in vitro results released in past studies, publicly available RIP- and eCLIP-seq data, and results from software tools for predicting RNA-protein interactions.

Dysregulated immunological and metabolic functions discovered by a polygenic integrative analysis for PCOS

RESEARCH QUESTION

Polycystic ovary syndrome (PCOS) is a complex disease and its pathophysiology is still unclear. This polygenic study may provide some clues.

DESIGN

A polygenic, functionome-based study with the ovarian gene expression profiles downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database, including 48 PCOS and 181 normal control samples. These profiles were converted to the gene set regularity (GSR) indices, which were computed by the modified differential rank conversion algorithm and were defined by the gene ontology terms.

RESULTS

Machine learning could accurately recognize the patterns of functional regularities between PCOS and normal controls. The significantly aberrant functions in PCOS included transporter activity, catalytic activity, the receptor signalling pathway via signal transducer and activator of transcription (STAT), the cellular metabolic process, and immune response.

CONCLUSION

This study provided a comprehensive view of the dysregulated functions and information for further studies on the management of PCOS.

Diesel exhaust particles dysregulate multiple immunological pathways in murine macrophages: Lessons from microarray and scRNA-seq technologies

Exposure to ambient particulate matter has been shown to promote a variety of disorders, including cardiovascular diseases predominantly of ischemic etiology. However, the mechanisms linking inhaled particulates with systemic vascular effects, resulting in worsened atherosclerosis, are not well defined. We assessed the potential role of macrophages in translating these effects by analyzing gene expression patterns in response to diesel exhaust particles (DEP) at the average cell level, using Affymetrix microarrays in peritoneal macrophages in culture (in vitro), and at the individual cell level, using single-cell RNA sequencing (scRNA-seq) in alveolar macrophages collected from exposed mice (in vivo). Peritoneal macrophages were harvested from C57BL/6J mice and treated with 25 μg/mL of a DEP methanol extract (DEPe). These cells exhibited significant (FDR < 0.05) differential expression of a large number of genes and enrichment in pathways, especially engaged in immune responses and antioxidant defense. DEPe led to marked upregulation of heme oxygenase 1 (Hmox1), the most significantly upregulated gene (FDR = 1.75E-06), and several other antioxidant genes. For the in vivo work, C57BL/6J mice were subjected to oropharyngeal aspiration of 200 μg of whole DEP. The gene expression profiles of the alveolar macrophages harvested from these mice were analyzed at the single-cell level using scRNA-seq, which showed significant dysregulation of a broad number of genes enriched in immune system pathways as well, but with a large heterogeneity in how individual alveolar macrophages responded to DEP exposures. Altogether, DEP pollutants dysregulated immunological pathways in macrophages that may mediate the development of pulmonary and systemic vascular effects.

Myo-REG: A Portal for Signaling Interactions in Muscle Regeneration

Muscle regeneration is a complex process governed by the interplay between several muscle-resident mononuclear cell populations. Following acute or chronic damage these cell populations are activated, communicate via cell-cell interactions and/or paracrine signals, influencing fate decisions via the activation or repression of internal signaling cascades. These are highly dynamic processes, occurring with distinct temporal and spatial kinetics. The main challenge toward a system level description of the muscle regeneration process is the integration of this plethora of inter- and intra-cellular interactions. We integrated the information on muscle regeneration in a web portal. The scientific content annotated in this portal is organized into two information layers representing relationships between different cell types and intracellular signaling-interactions, respectively. The annotation of the pathways governing the response of each cell type to a variety of stimuli/perturbations occurring during muscle regeneration takes advantage of the information stored in the SIGNOR database. Additional curation efforts have been carried out to increase the coverage of molecular interactions underlying muscle regeneration and to annotate cell-cell interactions. To facilitate the access to information on cell and molecular interactions in the context of muscle regeneration, we have developed Myo-REG, a web portal that captures and integrates published information on skeletal muscle regeneration. The muscle-centered resource we provide is one of a kind in the myology field. A friendly interface allows users to explore, approximately 100 cell interactions or to analyze intracellular pathways related to muscle regeneration. Finally, we discuss how data can be extracted from this portal to support in silico modeling experiments.

S‑allyl‑cysteine sulfoxide (alliin) alleviates myocardial infarction by modulating cardiomyocyte necroptosis and autophagy

S-allyl-cysteine sulfoxide (alliin) is the main organosulfur component of garlic and its preparations. The present study aimed to examine the protective effect of alliin on cardiac function and the underlying mechanism in a mouse model of myocardial infarction (MI). Notably, alliin treatment preserved heart function, attenuated the area of infarction in the myocardium of mice and reduced lesions in the myocardium, including cardiomyocyte fibrosis and death. Further mechanistic experiments revealed that alliin inhibited necroptosis but promoted autophagy in vitro and in vivo. Cell viability assays showed that alliin dose-dependently reduced the necroptotic index and inhibited the expression of necroptosis-related receptor-interacting protein 1, receptor-interacting protein 3 and tumor necrosis factor receptor-associated factor 2, whereas the levels of Beclin 1 and microtubule-associated protein 1 light chain 3, which are associated with autophagy, exhibited an opposite trend upon treatment with alliin. In addition, the level of peroxisome proliferator-activated receptor γ was increased by alliin. Collectively, these findings demonstrate that alliin has the potential to protect cardiomyocytes from necroptosis following MI and that this protective effect occurs via the enhancement of autophagy.

The sugarcane mitochondrial genome: assembly, phylogenetics and transcriptomics

BACKGROUND

Chloroplast genomes provide insufficient phylogenetic information to distinguish between closely related sugarcane cultivars, due to the recent origin of many cultivars and the conserved sequence of the chloroplast. In comparison, the mitochondrial genome of plants is much larger and more plastic and could contain increased phylogenetic signals. We assembled a consensus reference mitochondrion with Illumina TruSeq synthetic long reads and Oxford Nanopore Technologies MinION long reads. Based on this assembly we also analyzed the mitochondrial transcriptomes of sugarcane and sorghum and improved the annotation of the sugarcane mitochondrion as compared with other species.

METHODS

Mitochondrial genomes were assembled from genomic read pools using a bait and assemble methodology. The mitogenome was exhaustively annotated using BLAST and transcript datasets were mapped with HISAT2 prior to analysis with the Integrated Genome Viewer.

RESULTS

The sugarcane mitochondrion is comprised of two independent chromosomes, for which there is no evidence of recombination. Based on the reference assembly from the sugarcane cultivar SP80-3280 the mitogenomes of four additional cultivars (R570, LCP85-384, RB72343 and SP70-1143) were assembled (with the SP70-1143 assembly utilizing both genomic and transcriptomic data). We demonstrate that the sugarcane plastome is completely transcribed and we assembled the chloroplast genome of SP80-3280 using transcriptomic data only. Phylogenomic analysis using mitogenomes allow closely related sugarcane cultivars to be distinguished and supports the discrimination between Saccharum officinarum and Saccharum cultum as modern sugarcane's female parent. From whole chloroplast comparisons, we demonstrate that modern sugarcane arose from a limited number of Saccharum cultum female founders. Transcriptomic and spliceosomal analyses reveal that the two chromosomes of the sugarcane mitochondrion are combined at the transcript level and that splice sites occur more frequently within gene coding regions than without. We reveal one confirmed and one potential cytoplasmic male sterility (CMS) factor in the sugarcane mitochondrion, both of which are transcribed.

CONCLUSION

Transcript processing in the sugarcane mitochondrion is highly complex with diverse splice events, the majority of which span the two chromosomes. PolyA baited transcripts are consistent with the use of polyadenylation for transcript degradation. For the first time we annotate two CMS factors within the sugarcane mitochondrion and demonstrate that sugarcane possesses all the molecular machinery required for CMS and rescue. A mechanism of cross-chromosomal splicing based on guide RNAs is proposed. We also demonstrate that mitogenomes can be used to perform phylogenomic studies on sugarcane cultivars.

Phosphoproteomic profiling of oxycodone‑treated spinal cord of rats with cancer‑induced bone pain

Treatment of cancer‑induced bone pain (CIBP) is challenging in clinical settings. Oxycodone (OXY) is used to treat CIBP; however, a lack of understanding of the mechanisms underlying CIBP limits the application of OXY. In the present study, all rats were randomly divided into three groups: The sham group, the CIBP group, and the OXY group. Then, a rat model of CIBP was established by inoculation of Walker 256 tumor cells from rat tibia. Phosphoproteomic profiling of the OXY‑treated spinal dorsal cords of rats with CIBP was performed, and 1,679 phosphorylated proteins were identified, of which 160 proteins were significantly different between the CIBP and sham groups, and 113 proteins were significantly different between the CIBP and OXY groups. Gene Ontology analysis revealed that these proteins mainly clustered as synaptic‑associated cellular components; among these, disks large homolog 3 expression was markedly increased in rats with CIBP and was reversed by OXY treatment. Subsequent domain analysis of the differential proteins revealed several significant synaptic‑associated domains. In conclusion, synaptic‑associated cellular components may be critical in OXY‑induced analgesia in rats with CIBP.

Multifaced regulator: RNA binding proteins and their roles in hematopoiesis

Despite the conventional definition of RNA binding proteins (RBPs) as controlling the metabolism of their bound RNAs, more and more RBPs are found to function via distinct ways in complex biological processes. With the recent discovery of transcriptional regulation activity of some RBPs, a hypothesis that RBPs could be multilayered regulators orchestrating gene expression has emerged. Hematopoiesis is a stepwise process that needs to be fine-tuned to keep the subtle balance between hematopoietic stem cell (HSC) stemness maintenance and downstream lineage commitment. Although the classic RBPs account for the posttranscriptional regulation in hematopoiesis, the importance and multiple regulatory capacities of RBPs have not been well-characterized. In this review, we summarize the recent findings of large-scale screening of novel RBPs and their novel transcriptional regulation potentials. In hematopoietic system, this kind of multifaced regulators account for nearly a half of functional RBPs. Therefore, further studies on identifying this new kind of multifaced RBPs and clarifying their regulatory mechanisms would help us better understand the precise and complex regulatory networks of gene expression in hematopoiesis.

Four targeted genes for predicting the prognosis of colorectal cancer: A bioinformatics analysis case

The molecular mechanisms underlying the development and progression of colorectal cancer (CRC) have not been clarified. The purpose of the present study was to identify key genes that may serve as novel therapeutic targets or prognostic predictors in patients with CRC using bioinformatics analysis. Four gene expression datasets were downloaded from the Gene Expression Omnibus database, which revealed 19 upregulated and 34 downregulated differentially expressed genes (DEGs). The downregulated DEGs were significantly enriched in eight pathways according to Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. A protein-protein interaction network was constructed with 52 DEGs and 458 edges. Ten key genes were identified according to the degree value, betweenness centrality and closeness centrality. Survival analysis revealed that low expression of four of the ten genes, carcinoembryonic antigen related cell adhesion molecule 7 (CEACAM7), solute carrier family 4 member 4 (SLC4A4), glucagon (GCG) and chloride channel accessory 1 (CLCA1) genes, were associated with unfavorable prognosis in CRC. Furthermore, gene set enrichment analysis revealed that two pathways were significantly enriched in the CEACAM7 low-expression group. Thus, CEACAM7, SLC4A4, GCG and CLCA1 may be prognostic markers or therapeutic targets of CRC. Low CEACAM7 expression may be associated with the activation of glycosaminoglycan biosynthesis-chondroitin sulfate and extracellular matrix receptor interaction pathways and may affect the prognosis of CRC.

Reconstruction and analysis of competitive endogenous RNA network reveals regulatory role of long non‑coding RNAs in hepatic fibrosis

Hepatic fibrosis (HF), one of the leading global health problems, is defined as aberrant and excess production of extracellular matrix components. The pathogenesis of HF is complex and poorly understood. Long non‑coding RNAs (LncRNAs) can interact with microRNAs (miRNAs) as competing endogenous RNAs (ceRNAs) to regulate the expression of target genes, which play a significant role in the initiation and progression of HF. In the present study, the LncRNA‑associated ceRNA network was reconstructed based on LncRNA, miRNA and mRNA expression profiles that were downloaded from National Center for Biotechnology Information Gene Expression Omnibus. Bioinformatics assessments including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed with Database for Annotation, Visualization and Integration Discovery. The ceRNA network was composed of 220 LncRNA nodes, 24 miRNA nodes, 164 mRNA nodes and 1,149 edges. Functional assays identified that a total of 338 GO terms and 25 pathways, including regulation of cytokine and collagen, and the transforming growth factor‑β and Toll‑like receptor signaling pathways, were significantly enriched. In addition, 4 LncRNAs (NONMMUT036242, XR_877072, XR_378619 and XR_378418) were highly related to HF and thereby chosen as key LncRNAs. The present study uncovered a ceRNA network that could further the understanding of the mechanisms underlying HF development and provide potential novel markers for clinical diagnosis and targets for treatment.

Comprehensive expression profiles and bioinformatics analysis reveal special circular RNA expression and potential predictability in the peripheral blood of humans with idiopathic membranous nephropathy

The etiology of idiopathic membranous nephropathy (IMN) is considered to be closely associated with immunoregulation and genetic factors. Circular RNAs (circRNAs) have been found to regulate gene expression in various organisms, and to play an important role in multiple physiological and pathological processes, which may be involved in the pathogenesis of IMN. The purpose of the present study was to investigate the potential relationship between circRNAs in peripheral blood and disease. The diagnoses of IMN were confirmed using electron microscopy and immunofluorescence. Total RNA was isolated and microarray analysis was used to detect the expression levels of circRNAs in the peripheral blood of patients with IMN and in normal subjects. Selected genes from the microarray were selected and verified by reverse transcription‑quantitative (RT‑q)PCR. Bioinformatics tools were applied for further functional evaluation, and the potential disease predictability of circRNAs was determined using receiver‑operating characteristic (ROC) curves. The results showed that a total of 955 differentially expressed circRNAs were found in blood samples, 645 of which were upregulated and 310 which were downregulated. In total, five candidate circRNAs were validated using RT‑qPCR analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses identified numerous types of target genes and their corresponding microRNAs (miRNAs). The miRNAs identified were involved in biological processes and enriched in multiple important pathways, including the mitogen‑activated protein kinase, transforming growth factor‑β and Ras signaling pathways. The levels of circ_101319 were significantly higher (P<0.001) and exhibited promising diagnostic value in patients with IMN (area under ROC =0.89). The co‑expression network constructed for circ_101319 indicated that it may be associated with membranous nephropathy‑related pathways by mediating miRNAs. In conclusion, the present study revealed the expression and functional profile of differentially expressed circRNAs in the peripheral blood of patients with IMN, and provided new perspectives to predict and elucidate the development of IMN.

Ligand Binding Site Structure Shapes Folding, Assembly and Degradation of Homomeric Protein Complexes

Ligand binding site structure has profound consequences for the evolution of function of protein complexes, particularly in homomers—complexes comprising multiple copies of the same protein. Previously, we have shown that homomers with multichain binding sites (MBSs) are characterized by more conserved binding sites and quaternary structure, and qualitatively different allosteric pathways than homomers with single-chain binding sites (SBSs) or monomers. Here, using computational methods, we show that the folds of single-domain MBS and SBS homomers are different, and SBS homomers are likely to be folded cotranslationally, while MBS homomers are more likely to form post-translationally and rely on more advanced folding-assistance and quality control mechanisms, which include chaperonins. In addition, our findings demonstrate that MBS homomers are qualitatively different from monomers, while SBS homomers are much less distinct, supporting the hypothesis that the evolution of quaternary structure in SBS homomers is significantly influenced by stochastic processes.

Randomized trial of weight loss in primary breast cancer: Impact on body composition, circulating biomarkers and tumor characteristics

Obesity adversely impacts overall and cancer‐specific survival among breast cancer patients. Preclinical studies demonstrate negative energy balance inhibits cancer progression; however, feasibility and effects in patients are unknown. A two‐arm, single‐blinded, randomized controlled weight‐loss trial was undertaken presurgery among 32 overweight/obese, Stage 0–II breast cancer patients. The attention control arm (AC) received basic nutritional counseling and upper‐body progressive resistance training whereas the weight loss intervention (WLI) arm received identical guidance, plus counseling on caloric restriction and aerobic exercise to promote 0.68–0.92 kg/week weight loss. Anthropometrics, body composition, blood and survey data were collected at baseline and presurgery ∼30 days later. Tumor markers (e.g., Ki67) and gene expression were assessed on biopsy and surgical specimens; sera were analyzed for cytokines, growth and metabolic factors. Significant WLI vs. AC differences were seen in baseline‐to‐follow‐up changes in weight (−3.62 vs. −0.52 kg), %body fat (−1.3 vs. 0%), moderate‐to‐vigorous physical activity (+224 vs. +115 min/week), caloric density (−0.3 vs. 0 kcal/g), serum leptin (−12.3 vs. −4.0 ng/dl) and upregulation of tumor PI3Kinase signaling and cell cycle‐apoptosis related genes (CC‐ARG; all p‐values <0.05). Cytolytic CD56^dimNK cell expression was positively associated with weight loss; CC‐ARG increased with physical activity. Increased tumor (nuclear) TNFα and IL‐1β, CX3CL1 and CXCL1 gene expression was observed in the WLI. Tumor Ki67 did not differ between arms. Feasibility benchmarks included 80% accrual, 100% retention, no adverse effects and excellent adherence. Short‐term weight loss interventions are feasible; however, mixed effects on tumor biology suggest unclear benefit to presurgical caloric restriction, but possible benefits of physical activity.

What's new?

Obesity adversely impacts survival among breast cancer patients. Preclinical studies demonstrate negative energy balance inhibits cancer progression; however, effects in patients are unknown. This is the first randomized controlled trial to assess the impact of a pre‐surgical weight loss intervention among early‐stage breast cancer patients. Results show the effects of acute negative energy balance on tumor biology, circulating biomarkers, and quality‐of‐life. Short‐term weight loss interventions are feasible; however, mixed effects on tumor biology suggest unclear benefit to pre‐surgical caloric restriction. Such interventions may be better timed after surgical resection, though cell cycle‐apoptosis and DNA damage‐repair scores support increasing physical activity.

Migratory Neural Crest Cells Phagocytose Dead Cells in the Developing Nervous System

During neural tube closure and spinal cord development, many cells die in both the central and peripheral nervous systems (CNS and PNS, respectively). However, myeloid-derived professional phagocytes have not yet colonized the trunk region during early neurogenesis. How apoptotic cells are removed from this region during these stages remains largely unknown. Using live imaging in zebrafish, we demonstrate that neural crest cells (NCCs) respond rapidly to dying cells and phagocytose cellular debris around the neural tube. Additionally, NCCs have the ability to enter the CNS through motor exit point transition zones and clear debris in the spinal cord. Surprisingly, NCCs phagocytosis mechanistically resembles macrophage phagocytosis and their recruitment toward cellular debris is mediated by interleukin-1β. Taken together, our results reveal a role for NCCs in phagocytosis of debris in the developing nervous system before the presence of professional phagocytes.