Gene Expression Atlas update--a value-added database of microarray and sequencing-based functional genomics experiments

Term-BLAST-like alignment tool for concept recognition in noisy clinical texts

MOTIVATION

Methods for concept recognition (CR) in clinical texts have largely been tested on abstracts or articles from the medical literature. However, texts from electronic health records (EHRs) frequently contain spelling errors, abbreviations, and other nonstandard ways of representing clinical concepts.

RESULTS

Here, we present a method inspired by the BLAST algorithm for biosequence alignment that screens texts for potential matches on the basis of matching k-mer counts and scores candidates based on conformance to typical patterns of spelling errors derived from 2.9 million clinical notes. Our method, the Term-BLAST-like alignment tool (TBLAT) leverages a gold standard corpus for typographical errors to implement a sequence alignment-inspired method for efficient entity linkage. We present a comprehensive experimental comparison of TBLAT with five widely used tools. Experimental results show an increase of 10% in recall on scientific publications and 20% increase in recall on EHR records (when compared against the next best method), hence supporting a significant enhancement of the entity linking task. The method can be used stand-alone or as a complement to existing approaches.

AVAILABILITY AND IMPLEMENTATION

Fenominal is a Java library that implements TBLAT for named CR of Human Phenotype Ontology terms and is available at https://github.com/monarch-initiative/fenominal under the GNU General Public License v3.0.

Development and validation of a robot social presence measurement dimension scale

Robots that can exhibit human-like behaviour, build social relationships with humans, and carry out social interaction that can be considered to have a social presence. Measuring the social presence of robots can provide an important basis for optimizing the design of robots' human-like behaviour, but until now, there has been no research and discussion on the presence of robots from the perspective of social interaction. Based on related studies, such as the theory of the presence of interpersonal interaction society, the mechanism of network social presence measurement and human-computer interaction, this study constructs a theoretical model of robot social presence, and develops corresponding measurement scales with five dimensions, namely, the presence, attention distribution, interactive expression and information understanding, perceived emotional interdependence, and interaction behaviour perception. The 5-dimensional robot social presence model was finalized, and a 17-question questionnaire scale was developed. The validation of the model and the development of the scale includes one expert assessment (involving three experts), one user interview (involving five interviewees), and two questionnaire surveys (involving 172 valid questionnaires and 494 valid questionnaires respectively). The final model shows good reliability of the measurement questionnaire, high inter-factor correlation, high model fit, high internal consistency of the dimensions, high reliability of the scale, and high convergent validity of all dimensions. This study provides a theoretical basis for the study of robot social presence and human-robot collaboration and provides a reference measurement tool for social robot-related development and research.

Potential Influence of Age and Diabetes Mellitus Type 1 on MSH2 (MutS homolog 2) Expression in a Rat Kidney Tissue

Background: Homeostasis of proliferating tissues is strongly dependent on intact DNA. Both neoplastic and non-neoplastic diseases have been associated with MSH2 (MutS homolog 2, a mismatch repair protein) deficiency. In this study, we examined how age and diabetes mellitus influence the expression of MSH2 in the kidney. Methods: To study the effect of age, three groups of healthy rats were formed: 2 months, 8 months, and 14 months old. Two groups of diabetic rats were formed: 8 months old and 14 months old. Expression of MSH2 in the kidney was studied by quantifying immunofluorescent staining. Results: Age was identified as the main factor that influences MSH2 expression in kidneys. The effect of age followed parabolic dynamics, with peak expression at 8 months of age and similar levels at 2 and 14 months. Diabetes had an age-dependent effect, which manifested as the increase of MSH2 expression in 14-month-old diabetic rats in comparison to healthy animals. Conclusions: Age influences MSH2 expression in the kidney more than diabetes mellitus. Since ageing is a risk factor for kidney neoplasia, downregulation of MSH2 in older rats might represent one of the pro-oncogenic mechanisms of ageing at a molecular level.

Deubiquitylases in developmental ubiquitin signaling and congenital diseases

Metazoan development from a one-cell zygote to a fully formed organism requires complex cellular differentiation and communication pathways. To coordinate these processes, embryos frequently encode signaling information with the small protein modifier ubiquitin, which is typically attached to lysine residues within substrates. During ubiquitin signaling, a three-step enzymatic cascade modifies specific substrates with topologically unique ubiquitin modifications, which mediate changes in the substrate's stability, activity, localization, or interacting proteins. Ubiquitin signaling is critically regulated by deubiquitylases (DUBs), a class of ~100 human enzymes that oppose the conjugation of ubiquitin. DUBs control many essential cellular functions and various aspects of human physiology and development. Recent genetic studies have identified mutations in several DUBs that cause developmental disorders. Here we review principles controlling DUB activity and substrate recruitment that allow these enzymes to regulate ubiquitin signaling during development. We summarize key mechanisms of how DUBs control embryonic and postnatal differentiation processes, highlight developmental disorders that are caused by mutations in particular DUB members, and describe our current understanding of how these mutations disrupt development. Finally, we discuss how emerging tools from human disease genetics will enable the identification and study of novel congenital disease-causing DUBs.

Expression and significance of aquaporin-4 in thyroid carcinoma

OBJECTIVE

To investigate the expression of aquaporin-4 (AQP4) in thyroid carcinoma (TC) and explore its clinical significance.

MATERIALS AND METHODS

The formalin-fixed paraffin-embedded specimens including 275 TC cancer tissues, 258 corresponding paracancerous thyroid tissues and their clinicopathologic data were retrospectively analyzed. Immunohistochemical EnVision two-step method was used to detect the expression of AQP4 in the cancer tissues and adjacent thyroid tissues, and its clinical significance was analyzed.

RESULTS

AQP4 could be expressed in both TC cancer tissues and paracancerous thyroid tissues. In TC cancer tissues, the positive expression rate was 99.3% (273/275), and the positive expression rate was 86.4% (223/258) in paracancerous thyroid tissues. The expression level of AQP4 in cancer tissues was significantly higher than that in paracancerous thyroid tissues, and the difference was statistically significant (P < 0.05). The positive expression rates of AQP4 in papillary thyroid carcinoma (PTC), follicular thyroid carcinoma (FTC), medullary thyroid carcinoma (MTC) and undifferentiated thyroid carcinoma (UTC) were 99.2% (258/260), 100.0% (6/6), 100.0% (6/6) and 100.0% (3/3), respectively and there was little difference in different types of TC. Analysis of relationship between expression level of AQP4 in 275 TC cancer tissues and 260 PTC cancer tissues and clinicopathologic characteristics of patients was not significant correlation (P > 0.05). Among the 275 patients, one (0.4%, 1/275) was diagnosed as neuromyelitis optica spectrum disorder (NMOSD) associated with TC.

CONCLUSIONS

AQP4 is generally expressed in TC cancer tissues and paracancerous thyroid tissues. Expression level of AQP4 in cancer tissues was significantly higher than that in paracancerous thyroid tissue. Expression level of AQP4 in TC cancer tissues is not related to the clinicopathological characteristics of the patients. Paraneoplastic NMOSD caused by TC is rare, and whether its specific pathogenesis is related to the expression of AQP4 in TC still needs further study.

EXPath 2.0: An Updated Database for Integrating High-Throughput Gene Expression Data with Biological Pathways

Co-expressed genes tend to have regulatory relationships and participate in similar biological processes. Construction of gene correlation networks from microarray or RNA-seq expression data has been widely applied to study transcriptional regulatory mechanisms and metabolic pathways under specific conditions. Furthermore, since transcription factors (TFs) are critical regulators of gene expression, it is worth investigating TFs on the promoters of co-expressed genes. Although co-expressed genes and their related metabolic pathways can be easily identified from previous resources, such as EXPath and EXPath Tool, this information is not simultaneously available to identify their regulatory TFs. EXPath 2.0 is an updated database for the investigation of regulatory mechanisms in various plant metabolic pathways with 1,881 microarray and 978 RNA-seq samples. There are six significant improvements in EXPath 2.0: (i) the number of species has been extended from three to six to include Arabidopsis, rice, maize, Medicago, soybean and tomato; (ii) gene expression at various developmental stages have been added; (iii) construction of correlation networks according to a group of genes is available; (iv) hierarchical figures of the enriched Gene Ontology (GO) terms are accessible; (v) promoter analysis of genes in a metabolic pathway or correlation network is provided; and (vi) user's gene expression data can be uploaded and analyzed. Thus, EXPath 2.0 is an updated platform for investigating gene expression profiles and metabolic pathways under specific conditions. It facilitates users to access the regulatory mechanisms of plant biological processes. The new version is available at http://EXPath.itps.ncku.edu.tw.

The oilseed rape developmental expression resource: a resource for the investigation of gene expression dynamics during the floral transition in oilseed rape

BACKGROUND

Transcriptome time series can be used to track the expression of genes during development, allowing the timing, intensity, and dynamics of genetic programmes to be determined. Furthermore, time series analysis can reveal causal relationships between genes, leading to an understanding of how the regulatory networks are rewired during development. Due to its impact on yield, a developmental transition of agricultural interest in crops is the switch from vegetative to floral growth. We previously reported the collection of genome-wide gene expression data during the floral transition in the allopolyploid crop Brassica napus (oilseed rape, OSR). To provide the OSR research community with easy access to this dataset, we have developed the Oilseed Rape Developmental Expression Resource (ORDER; http://order.jic.ac.uk ).

RESULTS

ORDER enables users to search for genes of interest and plot expression patterns during the floral transition in both a winter and a spring variety of OSR. We illustrate the utility of ORDER using two case studies: the first investigating the interaction between transcription factors, the second comparing genes that mediate the vernalisation response between OSR and radish (Raphanus sativus L.). All the data is downloadable and the generic website platform underlying ORDER, called AionPlot, is made freely and openly available to facilitate the dissemination of other time series datasets.

CONCLUSIONS

ORDER provides the OSR research community with access to a dataset focused on a period of OSR development important for yield. AionPlot, the platform on which ORDER is built, will allow researchers from all fields to share similar time series datasets.

Machine learning: A powerful tool for gene function prediction in plants

Recent advances in sequencing and informatic technologies have led to a deluge of publicly available genomic data. While it is now relatively easy to sequence, assemble, and identify genic regions in diploid plant genomes, functional annotation of these genes is still a challenge. Over the past decade, there has been a steady increase in studies utilizing machine learning algorithms for various aspects of functional prediction, because these algorithms are able to integrate large amounts of heterogeneous data and detect patterns inconspicuous through rule-based approaches. The goal of this review is to introduce experimental plant biologists to machine learning, by describing how it is currently being used in gene function prediction to gain novel biological insights. In this review, we discuss specific applications of machine learning in identifying structural features in sequenced genomes, predicting interactions between different cellular components, and predicting gene function and organismal phenotypes. Finally, we also propose strategies for stimulating functional discovery using machine learning-based approaches in plants.

Multi-species annotation of transcriptome and chromatin structure in domesticated animals

BACKGROUND

Comparative genomics studies are central in identifying the coding and non-coding elements associated with complex traits, and the functional annotation of genomes is a critical step to decipher the genotype-to-phenotype relationships in livestock animals. As part of the Functional Annotation of Animal Genomes (FAANG) action, the FR-AgENCODE project aimed to create reference functional maps of domesticated animals by profiling the landscape of transcription (RNA-seq), chromatin accessibility (ATAC-seq) and conformation (Hi-C) in species representing ruminants (cattle, goat), monogastrics (pig) and birds (chicken), using three target samples related to metabolism (liver) and immunity (CD4+ and CD8+ T cells).

RESULTS

RNA-seq assays considerably extended the available catalog of annotated transcripts and identified differentially expressed genes with unknown function, including new syntenic lncRNAs. ATAC-seq highlighted an enrichment for transcription factor binding sites in differentially accessible regions of the chromatin. Comparative analyses revealed a core set of conserved regulatory regions across species. Topologically associating domains (TADs) and epigenetic A/B compartments annotated from Hi-C data were consistent with RNA-seq and ATAC-seq data. Multi-species comparisons showed that conserved TAD boundaries had stronger insulation properties than species-specific ones and that the genomic distribution of orthologous genes in A/B compartments was significantly conserved across species.

CONCLUSIONS

We report the first multi-species and multi-assay genome annotation results obtained by a FAANG project. Beyond the generation of reference annotations and the confirmation of previous findings on model animals, the integrative analysis of data from multiple assays and species sheds a new light on the multi-scale selective pressure shaping genome organization from birds to mammals. Overall, these results emphasize the value of FAANG for research on domesticated animals and reinforces the importance of future meta-analyses of the reference datasets being generated by this community on different species.

zfRegeneration: a database for gene expression profiling during regeneration

MOTIVATION

Zebrafish is a model organism with the ability to regenerate many different organs. Although RNA-Seq has been used extensively to study this process, there are no databases that allow easy access to data.

RESULTS

Here we develop the first regeneration database that provides easy access to a large number of RNA-Seq datasets through custom-made plots of expression levels, differential expression analyses, correlations of genes and comparisons of the different datasets. zfRegeneration has a user-friendly web interface designed to enhance regeneration studies and to overcome the barriers between different research groups that study the regeneration of distinct organs. Using several case studies, we demonstrate that zfRegeneration provides a unique platform to analyse and understand gene expression during regeneration.

AVAILABILITY AND IMPLEMENTATION

zfRegeneration is freely available at www.zfregeneration.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Novel Y-Chromosome Long Non-Coding RNAs Expressed in Human Male CNS During Early Development

Global microarray gene expression analyses previously demonstrated differences in female and male embryos during neurodevelopment. In particular, before sexual maturation of the gonads, the differences seem to concentrate on the expression of genes encoded on the X- and Y-chromosomes. To investigate genome-wide differences in expression during this early developmental window, we combined high-resolution RNA sequencing with qPCR to analyze brain samples from human embryos during the first trimester of development. Our analysis was tailored for maximum sensitivity to discover Y-chromosome gene expression, but at the same time, it was underpowered to detect X-inactivation escapees. Using this approach, we found that 5 out of 13 expressed gametolog pairs showed unbalanced gene dosage, and as a consequence, a male-biased expression. In addition, we found six novel non-annotated long non-coding RNAs on the Y-chromosome with conserved expression patterns in newborn chimpanzee. The tissue specific and time-restricted expression of these long non-coding RNAs strongly suggests important functions during central nervous system development in human males.

Genetic Variants Implicate Dual Oxidase-2 in Familial and Sporadic Nonmedullary Thyroid Cancer

Highly penetrant hereditary thyroid cancer manifests as familial nonmedullary thyroid cancer (FNMTC), whereas low-penetrance hereditary thyroid cancer manifests as sporadic disease and is associated with common polymorphisms, including rs965513[A]. Whole-exome sequencing of an FNMTC kindred identified a novel Y1203H germline dual oxidase-2 (DUOX2) mutation. DUOX2_Y1203H is enzymatically active, with increased production of reactive oxygen species. Furthermore, patients with sporadic thyroid cancer homozygous for rs965513[A] demonstrated higher DUOX2 expression than heterozygous rs965513[A/G] or homozygous rs965513[A]-negative patients. These data suggest that dysregulated hydrogen peroxide metabolism is a common mechanism by which high- and low-penetrance genetic factors increase thyroid cancer risk. SIGNIFICANCE: This study provides novel insights into the genetic and molecular mechanisms underlying familial and sporadic thyroid cancers.

Bioinformatics challenges and perspectives when studying the effect of epigenetic modifications on alternative splicing

It is widely known that epigenetic modifications are important in regulating transcription, but several have also been reported in alternative splicing. The regulation of pre-mRNA splicing is important to explain proteomic diversity and the misregulation of splicing has been implicated in many diseases. Here, we give a brief overview of the role of epigenetics in alternative splicing and disease. We then discuss the bioinformatics methods that can be used to model interactions between epigenetic marks and regulators of splicing. These models can be used to identify alternative splicing and epigenetic changes across different phenotypes.

This article is part of a discussion meeting issue ‘Frontiers in epigenetic chemical biology’.

Significant prognostic values of aquaporin mRNA expression in breast cancer

Introduction

Aquaporins (AQPs), also called water channels, have been shown to have functions in the migration, invasion, and proliferation of human breast tumor cells. Most AQP mRNA expression levels were tested by cell lines, mouse models, and even human breast tissues. However, the mRNA expression of individual AQPs in different clinicopathologic characteristics and prognostic values according to different kinds of classifications of breast cancer patients remains unclear.

Materials and methods

In the current study, we used the Oncomine database, Breast cancer Gene-Expression Miner v4.1, Kaplan–Meier Plotter, and cBioPortal to investigate the expression distribution and prognostic values of AQPs in breast cancer patients.

Results

Our study revealed that the mRNA expression levels of AQP8, AQP9, and AQP10 were upregulated, while those of AQP3, AQP4, AQP5, and AQP7 were downregulated in breast cancer. The clinical database showed that lower mRNA levels of AQP1 were associated with a high Scarff–Bloom–Richardson grade, but AQP9 showed the opposite trend. Further survival analyses indicated that high mRNA expression levels of AQP0, AQP1, AQP2, AQP4, AQP6, AQP8, AQP10, and AQP11 were significantly associated with better relapse-free survival (RFS). Conversely, AQP3 and AQP9 were associated with worse RFS in breast cancer patients, suggesting that these two genes might be potential targets in future chemotherapy.

Discussion

These significant AQP members might be further explored as new biomarkers for breast cancer prognosis, but this needs further study.

The function of miR-143, miR-145 and the MiR-143 host gene in cardiovascular development and disease

Noncoding RNAs (long noncoding RNAs and small RNAs) are emerging as critical modulators of phenotypic changes associated with physiological and pathological contexts in a variety of cardiovascular diseases (CVDs). Although it has been well established that hereditable genetic alterations and exposure to risk factors are crucial in the development of CVDs, other critical regulators of cell function impact on disease processes. Here we discuss noncoding RNAs have only recently been identified as key players involved in the progression of disease. In particular, we discuss micro RNA (miR)-143/145 since they represent one of the most characterised microRNA clusters regulating smooth muscle cell (SMC) differentiation and phenotypic switch in response to vascular injury and remodelling. MiR143HG is a well conserved long noncoding RNA (lncRNA), which is the host gene for miR-143/145 and recently implicated in cardiac specification during heart development. Although the lncRNA-miRNA interactions have not been completely characterised, their crosstalk is now beginning to emerge and likely requires further research focus. In this review we give an overview of the biology of the genomic axis that is miR-143/145 and MiR143HG, focusing on their important functional role(s) in the cardiovascular system.

Immune Responsive Release of Tacrolimus to Overcome Organ Transplant Rejection

Transplant rejection is the key problem in organ transplantation and, in clinic, immunosuppressive agents such as tacrolimus are directly administered to the recipients after surgery for T-cell inhibition. However, direct administration of tacrolimus may bring severe side effects to the recipients. Herein, by rational design of two hydrogelators NapPhePheGluTyrOH (1) and Nap d-Phe dPheGluTyrOH (2), a facile method of immune responsive release of tacrolimus is developed from their hydrogels to overcome organ transplantation rejection. Upon incubation with protein tyrosine kinase, which is activated in T cells after organ transplantation, the tacrolimus-encapsulating Gel 1 or Gel 2 is disassembled to release tacrolimus. Cell experiments show that both Gel 1 and Gel 2 have better inhibition effect on the activated T cells than free drug tacrolimus. Liver transplantation experiments indicate that, after 7 days of treatment of same dose tacrolimus, the recipient rats in the Gel 2 group show significantly extended median survival time of 22 days while the recipients treated with conventional tacrolimus medication have a median survival time of 13 days. It is expected herein that this "smart" facile method of immune responsive release of tacrolimus can be applied to overcome organ transplantation rejection in clinic in the near future.

Long Noncoding RNAs in Colorectal Adenocarcinoma; an in silico Analysis

Long noncoding RNAs (lncRNAs) are lengthy noncoding transcripts which are involved in critical signaling pathways including cell cycle and apoptosis so it is not surprising to see their altered expression in human tumors. Colorectal adenocarcinoma is one the most frequent malignancies worldwide. The role of lncRNAs in colorectal adenocarcinoma is not well understood. To study the significance of lncRNAs in colorectal adenocarcinoma, we retrieved 189 approved lncRNAs from HGNC. The genes were imported into the cBioPortal database for transcriptomic analyses. We queried all the samples from TCGA provisional colorectal adenocarcinoma with RNA-seq v2 data in our study and considered RNA dysregulation with Z-score: ±2. The lncRNA which was altered in most of the patients were considered as "significant lncRNA" for further analyses. We considered the association of candidate lncRNAs with clinicopathologic parameters of samples including tumor disease anatomic site, neoplasm histologic types, tumor stage and survival. We also compute the specificity of the significant lncRNAs expression in colorectal adenocarcinoma comparing with other human cancers in cancer portal. Our analysis showed that lncRNAs SNHG6, PVT1 and ZFAS1 allocated the maximum alteration among the colorectal cases. The expression of SNHG6 and ZFAS1 was more in rectal adenocarcinoma than the colon carcinoma while the PVT1 showed the same expression levels in both tissues. However, we found that upregulation of PVT1 has been reduced the overall survival in patients. Altogether these data showed SNHG6, PVT1 and ZFAS1, are promising candidates for experimental research on colorectal adenocarcinoma to discover novel biomarker for this prevalent cancer.

MetaSRA: normalized human sample-specific metadata for the Sequence Read Archive

Motivation

The NCBI’s Sequence Read Archive (SRA) promises great biological insight if one could analyze the data in the aggregate; however, the data remain largely underutilized, in part, due to the poor structure of the metadata associated with each sample. The rules governing submissions to the SRA do not dictate a standardized set of terms that should be used to describe the biological samples from which the sequencing data are derived. As a result, the metadata include many synonyms, spelling variants and references to outside sources of information. Furthermore, manual annotation of the data remains intractable due to the large number of samples in the archive. For these reasons, it has been difficult to perform large-scale analyses that study the relationships between biomolecular processes and phenotype across diverse diseases, tissues and cell types present in the SRA.

Results

We present MetaSRA, a database of normalized SRA human sample-specific metadata following a schema inspired by the metadata organization of the ENCODE project. This schema involves mapping samples to terms in biomedical ontologies, labeling each sample with a sample-type category, and extracting real-valued properties. We automated these tasks via a novel computational pipeline.

Availability and implementation

The MetaSRA is available at metasra.biostat.wisc.edu via both a searchable web interface and bulk downloads. Software implementing our computational pipeline is available at http://github.com/deweylab/metasra-pipeline

Supplementary information

Supplementary data are available at Bioinformatics online.

A survey of microRNA single nucleotide polymorphisms identifies novel breast cancer susceptibility loci in a case-control, population-based study of African-American women

BACKGROUND

MicroRNAs (miRNAs) regulate gene expression and influence cancer. Primary transcripts of miRNAs (pri-miRNAs) are poorly annotated and little is known about the role of germline variation in miRNA genes and breast cancer (BC). We sought to identify germline miRNA variants associated with BC risk and tumor subtype among African-American (AA) women.

METHODS

Under the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium, genotyping and imputed data from four studies on BC in AA women were combined into a final dataset containing 224,188 miRNA gene single nucleotide polymorphisms (SNPs) for 8350 women: 3663 cases and 4687 controls. The primary miRNA sequence was identified for 566 miRNA genes expressed in Encyclopedia of DNA Elements (ENCODE) Tier 1 cell types and human pancreatic islets. Association analysis was conducted using logistic regression for BC status overall and by tumor subtype.

RESULTS

A novel BC signal was localized to an 8.6-kb region of 17q25.3 by four SNPs (rs9913477, rs1428882938, rs28585511, and rs7502931) and remained statistically significant after multiple test correction (odds ratio (OR) = 1.44, 95% confidence interval (CI) = 1.26-1.65; p = 3.15 × 10-7; false discovery rate (FDR) = 0.03). These SNPs reside in a genomic location that includes both the predicted primary transcript of the noncoding miRNA gene MIR3065 and the first intron of the gene for brain-specific angiogenesis inhibitor 1-associated protein 2 (BAIAP2). Furthermore, miRNA-associated SNPs on chromosomes 1p32.3, 5q32, and 3p25.1 were the strongest signals for hormone receptor, luminal versus basal-like, and HER2 enrichment status, respectively. A second phase of genotyping (1397 BC cases, 2418 controls) that included two SNPs in the 8.6-kb region was used for validation and meta-analysis. While neither rs4969239 nor rs9913477 was validated, when meta-analyzed with the original dataset their association with BC remained directionally consistent (OR = 1.29, 95% CI = 1.16-1.44 (p = 4.18 × 10-6) and OR = 1.33, 95% CI = 1.17-1.51 (p = 1.6 × 10-5), respectively).

CONCLUSION

Germline genetic variation indicates that MIR3065 may play an important role in BC development and heterogeneity among AA women. Further investigation to determine the potential functional effects of these SNPs is warranted. This study contributes to our understanding of BC risk in AA women and highlights the complexity in evaluating variation in gene-dense regions of the human genome.

ZFR coordinates crosstalk between RNA decay and transcription in innate immunity

Control of type I interferon production is crucial to combat infection while preventing deleterious inflammatory responses, but the extent of the contribution of post-transcriptional mechanisms to innate immune regulation is unclear. Here, we show that human zinc finger RNA-binding protein (ZFR) represses the interferon response by regulating alternative pre-mRNA splicing. ZFR expression is tightly controlled during macrophage development; monocytes express truncated ZFR isoforms, while macrophages induce full-length ZFR to modulate macrophage-specific alternative splicing. Interferon-stimulated genes are constitutively activated by ZFR depletion, and immunostimulation results in hyper-induction of interferon β (IFNβ/IFNB1). Through whole-genome analyses, we show that ZFR controls interferon signaling by preventing aberrant splicing and nonsense-mediated decay of histone variant macroH2A1/H2AFY mRNAs. Together, our data suggest that regulation of ZFR in macrophage differentiation guards against aberrant interferon responses and reveal a network of mRNA processing and decay that shapes the transcriptional response to infection.

Type I interferon signaling is critical for the control of infection. Here the authors show that zinc finger RNA-binding protein (ZFR) can control type I interferon responses, and that this control is itself regulated by distinct ZFR truncation patterns that differ between monocytes and macrophages.

The fungal snoRNAome

Small nucleolar RNAs (snoRNAs) are essential players in the rRNA biogenesis due to their involvement in the nucleolytic processing of the precursor and the subsequent guidance of nucleoside modifications. Within the kingdom Fungi, merely a few species-specific surveys have explored their snoRNA repertoire. However, the wide range of the snoRNA landscape spanning all major fungal lineages has not been mapped so far, mainly because of missing tools for automatized snoRNA detection and functional analysis. For the first time, we report here a comprehensive inventory of fungal snoRNAs together with a functional analysis and an in-depth investigation of their evolutionary history including innovations, deletions, and target switches. This large-scale analysis, incorporating more than 120 snoRNA families with more than 7700 individual snoRNA sequences, catalogs and clarifies the landscape of fungal snoRNA families, assigns functions to previously orphan snoRNAs, and increases the number of sequences by 450%. We also show that the snoRNAome is subject to ongoing rearrangements and adaptations, e.g., through lineage-specific targets and redundant guiding functions.

Genomewide identification of genes involved in the potato response to drought indicates functional evolutionary conservation with Arabidopsis plants

Potato is one of the four most important food crop plants worldwide and is strongly affected by drought. The following two pairs of potato cultivars, which are related in ancestry but show different drought tolerances, were chosen for comparative gene expression studies: Gwiazda/Oberon and Tajfun/Owacja. Comparative RNA-seq analyses of gene expression differences in the transcriptomes obtained from drought-tolerant versus drought-sensitive plants during water shortage conditions were performed. The 23 top-ranking genes were selected, 22 of which are described here as novel potato drought-responsive genes. Moreover, all but one of the potato genes selected have homologues in the Arabidopsis genome. Of the seven tested A. thaliana mutants with altered expression of the selected homologous genes, compared to the wild-type Arabidopsis plants, six showed an improved tolerance to drought. These genes encode carbohydrate transporter, mitogen-activated protein kinase kinase kinase 15 (MAPKKK15), serine carboxypeptidase-like 19 protein (SCPL19), armadillo/beta-catenin-like repeat-containing protein, high-affinity nitrate transporter 2.7 and nonspecific lipid transfer protein type 2 (nsLPT). The evolutionary conservation of the functions of the selected genes in the plant response to drought confirms the importance of these identified potato genes in the ability of plants to cope with water shortage conditions. Knowledge regarding these gene functions can be used to generate potato cultivars that are resistant to unfavourable conditions. The approach used in this work and the obtained results allowed for the identification of new players in the plant response to drought.

The Kohlschütter-Tönz syndrome associated gene Rogdi encodes a novel presynaptic protein

Mutations in the human homolog of the Drosophila gene Rogdi cause Kohlschütter-Tönz syndrome. This disorder is characterised by amelogenesis imperfecta, as well as severe neurological symptoms including epilepsy and psychomotor delay. However, little is known about the protein encoded by Rogdi, and hence the pathogenic mechanisms underlying Kohlschütter-Tönz syndrome have remained elusive. Using immunofluorescence of rat cultured hippocampal neurons and brain sections we find that Rogdi is enriched at synaptic sites. In addition, recombinant GFP-Rogdi expressed in cultured neurons was efficiently targeted to presynaptic sites, where it colocalised with the presynaptic scaffolding protein Bassoon and the synaptic vesicle markers Synaptophysin, Synapsin-1, VAMP2/Synaptobrevin and Mover. Our data indicate that GFP-Rogdi harbours efficient signals for presynaptic targeting, and that Rogdi is a presynaptic protein. Thus, the neurological symptoms associated with Kohlschütter-Tönz syndrome may arise from presynaptic dysfunction.

CARMIL family proteins as multidomain regulators of actin-based motility

CARMILs are large multidomain proteins that regulate the actin-binding activity of capping protein (CP), a major capper of actin filament barbed ends in cells. CARMILs bind directly to CP and induce a conformational change that allosterically decreases but does not abolish its actin-capping activity. The CP-binding domain of CARMIL consists of the CP-interaction (CPI) and CARMIL-specific interaction (CSI) motifs, which are arranged in tandem. Many cellular functions of CARMILs require the interaction with CP; however, a more surprising result is that the cellular function of CP in cells appears to require binding to a CARMIL or another protein with a CPI motif, suggesting that CPI-motif proteins target CP and modulate its actin-capping activity. Vertebrates have three highly conserved genes and expressed isoforms of CARMIL with distinct and overlapping localizations and functions in cells. Various domains of these CARMIL isoforms interact with plasma membranes, vimentin intermediate filaments, SH3-containing class I myosins, the dual-GEF Trio, and other adaptors and signaling molecules. These biochemical properties suggest that CARMILs play a variety of membrane-associated functions related to actin assembly and signaling. CARMIL mutations and variants have been implicated in several human diseases. We focus on roles for CARMILs in signaling in addition to their function as regulators of CP and actin.

Withdrawn: Discovering Genes Essential to the Hypothalamic Regulation of Human Reproduction Using a Human Disease Model: Adjusting to Life in the "-Omics" Era

The neuroendocrine regulation of reproduction is an intricate process requiring the exquisite coordination of an assortment of cellular networks, all converging on the GnRH neurons. These neurons have a complex life history, migrating mainly from the olfactory placode into the hypothalamus, where GnRH is secreted and acts as the master regulator of the hypothalamic-pituitary-gonadal axis. Much of what we know about the biology of the GnRH neurons has been aided by discoveries made using the human disease model of isolated GnRH deficiency (IGD), a family of rare Mendelian disorders that share a common failure of secretion and/or action of GnRH causing hypogonadotropic hypogonadism. Over the last 30 years, research groups around the world have been investigating the genetic basis of IGD using different strategies based on complex cases that harbor structural abnormalities or single pleiotropic genes, endogamous pedigrees, candidate gene approaches as well as pathway gene analyses. Although such traditional approaches, based on well-validated tools, have been critical to establish the field, new strategies, such as next-generation sequencing, are now providing speed and robustness, but also revealing a surprising number of variants in known IGD genes in both patients and healthy controls. Thus, before the field moves forward with new genetic tools and continues discovery efforts, we must reassess what we know about IGD genetics and prepare to hold our work to a different standard. The purpose of this review is to: 1) look back at the strategies used to discover the "known" genes implicated in the rare forms of IGD; 2) examine the strengths and weaknesses of the methodologies used to validate genetic variation; 3)substantiate the role of known genes in the pathophysiology of the disease; and 4) project forward as we embark upon a widening use of these new and powerful technologies for gene discovery. (Endocrine Reviews 36: 603-621, 2015).

New astroglial injury-defined biomarkers for neurotrauma assessment

Traumatic brain injury (TBI) is an expanding public health epidemic with pathophysiology that is difficult to diagnose and thus treat. TBI biomarkers should assess patients across severities and reveal pathophysiology, but currently, their kinetics and specificity are unclear. No single ideal TBI biomarker exists. We identified new candidates from a TBI CSF proteome by selecting trauma-released, astrocyte-enriched proteins including aldolase C (ALDOC), its 38kD breakdown product (BDP), brain lipid binding protein (BLBP), astrocytic phosphoprotein (PEA15), glutamine synthetase (GS) and new 18-25kD-GFAP-BDPs. Their levels increased over four orders of magnitude in severe TBI CSF. First post-injury week, ALDOC levels were markedly high and stable. Short-lived BLBP and PEA15 related to injury progression. ALDOC, BLBP and PEA15 appeared hyper-acutely and were similarly robust in severe and mild TBI blood; 25kD-GFAP-BDP appeared overnight after TBI and was rarely present after mild TBI. Using a human culture trauma model, we investigated biomarker kinetics. Wounded (mechanoporated) astrocytes released ALDOC, BLBP and PEA15 acutely. Delayed cell death corresponded with GFAP release and proteolysis into small GFAP-BDPs. Associating biomarkers with cellular injury stages produced astroglial injury-defined (AID) biomarkers that facilitate TBI assessment, as neurological deficits are rooted not only in death of CNS cells, but also in their functional compromise.

Immune cell profiling in cancer: molecular approaches to cell-specific identification

The immune system has many important regulatory roles in cancer development and progression. Given the emergence of effective immune therapies against many cancers, reliable predictors of response are needed. One method of determining response is by evaluating immune cell populations from treated and untreated tumor samples. The amount of material obtained from tumor biopsies can be limited; therefore, gene-based or protein-based analyses may be attractive because they require minimal tissue. Cell-specific signatures are being analyzed with use of the latest technologies, including NanoString’s nCounter technology, intracellular staining flow cytometry, cytometry by time-of-flight, RNA-Seq, and barcoding antibody-based protein arrays. These signatures provide information about the contributions of specific types of immune cells to bulk tumor samples. To date, both tumor tissue and immune cells have been analyzed for molecular expression profiles that can assess genes and proteins that are specific to immune cells, yielding results of varying specificity. Here, we discuss the importance of profiling tumor tissue and immune cells to identify immune-cell-associated genes and proteins and specific gene profiles of immune cells. We also discuss the use of these signatures in cancer treatment and the challenges faced in molecular expression profiling of immune cell populations.

Long Non-Coding RNA SNHG6 as a Potential Biomarker for Hepatocellular Carcinoma

Long Non-coding RNAs (lncRNAs) refer to all non-protein coding transcripts longer than 200 nucleotides. Their critical roles in different biological pathways have been already well established. Altered expression of lncRNAs can be involved in the cancer initiation and/or progression. Since patients with hepatocellular carcinoma (HCC) are usually diagnosed in late stages, developing diagnostic methods seems to be essential. In this study, the expression levels of different lncRNAs were systematically analysed in different genomic and transcriptome datasets. The analyses showed that SNHG6 is among the lncRNAs with distinctive dysregulation of expression and copy number variation in HCC tumors compared with normal tissues. The results also suggest that the dysregulation of SNHG6 is highly cancer type specific. Through co-occurrence analyses, we found that SNHG6 and its related co-expressed genes on 8q are involved in the structural integrity of ribosome and translation. This comprehensive in silico analysis, provides a resource for investigating SNHG6 in hepatocellular carcinoma and lays the groundwork for design of next researches.

De Novo Coding Variants Are Strongly Associated with Tourette Disorder

Whole-exome sequencing (WES) and de novo variant detection have proven a powerful approach to gene discovery in complex neurodevelopmental disorders. We have completed WES of 325 Tourette disorder trios from the Tourette International Collaborative Genetics cohort and a replication sample of 186 trios from the Tourette Syndrome Association International Consortium on Genetics (511 total). We observe strong and consistent evidence for the contribution of de novo likely gene-disrupting (LGD) variants (rate ratio [RR] 2.32, p = 0.002). Additionally, de novo damaging variants (LGD and probably damaging missense) are overrepresented in probands (RR 1.37, p = 0.003). We identify four likely risk genes with multiple de novo damaging variants in unrelated probands: WWC1 (WW and C2 domain containing 1), CELSR3 (Cadherin EGF LAG seven-pass G-type receptor 3), NIPBL (Nipped-B-like), and FN1 (fibronectin 1). Overall, we estimate that de novo damaging variants in approximately 400 genes contribute risk in 12% of clinical cases. VIDEO ABSTRACT.

Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams

Monitoring and modeling biomedical, health care and wellness data from individuals and converging data on a population scale have tremendous potential to improve understanding of the transition to the healthy state of human physiology to disease setting. Wellness monitoring devices and companion software applications capable of generating alerts and sharing data with health care providers or social networks are now available. The accessibility and clinical utility of such data for disease or wellness research are currently limited. Designing methods for streaming data capture, real-time data aggregation, machine learning, predictive analytics and visualization solutions to integrate wellness or health monitoring data elements with the electronic medical records (EMRs) maintained by health care providers permits better utilization. Integration of population-scale biomedical, health care and wellness data would help to stratify patients for active health management and to understand clinically asymptomatic patients and underlying illness trajectories. In this article, we discuss various health-monitoring devices, their ability to capture the unique state of health represented in a patient and their application in individualized diagnostics, prognosis, clinical or wellness intervention. We also discuss examples of translational bioinformatics approaches to integrating patient-generated data with existing EMRs, personal health records, patient portals and clinical data repositories. Briefly, translational bioinformatics methods, tools and resources are at the center of these advances in implementing real-time biomedical and health care analytics in the clinical setting. Furthermore, these advances are poised to play a significant role in clinical decision-making and implementation of data-driven medicine and wellness care.

Morphological and Transcriptomic Analysis of a Beetle Chemosensory System Reveals a Gnathal Olfactory Center

BACKGROUND

The red flour beetle Tribolium castaneum is an emerging insect model organism representing the largest insect order, Coleoptera, which encompasses several serious agricultural and forest pests. Despite the ecological and economic importance of beetles, most insect olfaction studies have so far focused on dipteran, lepidopteran, or hymenopteran systems.

RESULTS

Here, we present the first detailed morphological description of a coleopteran olfactory pathway in combination with genome-wide expression analysis of the relevant gene families involved in chemoreception. Our study revealed that besides the antennae, also the mouthparts are highly involved in olfaction and that their respective contribution is processed separately. In this beetle, olfactory sensory neurons from the mouthparts project to the lobus glomerulatus, a structure so far only characterized in hemimetabolous insects, as well as to a so far non-described unpaired glomerularly organized olfactory neuropil in the gnathal ganglion, which we term the gnathal olfactory center. The high number of functional odorant receptor genes expressed in the mouthparts also supports the importance of the maxillary and labial palps in olfaction of this beetle. Moreover, gustatory perception seems equally distributed between antenna and mouthparts, since the number of expressed gustatory receptors is similar for both organs.

CONCLUSIONS

Our analysis of the T. castaneum chemosensory system confirms that olfactory and gustatory perception are not organotopically separated to the antennae and mouthparts, respectively. The identification of additional olfactory processing centers, the lobus glomerulatus and the gnathal olfactory center, is in contrast to the current picture that in holometabolous insects all olfactory inputs allegedly converge in the antennal lobe. These findings indicate that Holometabola have evolved a wider variety of solutions to chemoreception than previously assumed.

Comprehensive genomic characterization of five canine lymphoid tumor cell lines

BACKGROUND

Leukemia/lymphoma cell lines have been critical in the investigation of the pathogenesis and therapy of hematological malignancies. While human LL cell lines have generally been found to recapitulate the primary tumors from which they were derived, appropriate characterization including cytogenetic and transcriptional assessment is crucial for assessing their clinical predictive value.

RESULTS

In the following study, five canine LL cell lines, CLBL-1, Ema, TL-1 (Nody-1), UL-1, and 3132, were characterized using extensive immunophenotyping, karyotypic analysis, oligonucleotide array comparative genomic hybridization (oaCGH), and gene expression profiling. Genome-wide DNA copy number data from the cell lines were also directly compared with 299 primary canine round cell tumors to determine whether the cell lines represent primary tumors, and, if so, what subtype each most closely resembled.

CONCLUSIONS

Based on integrated analyses, CLBL-1 was classified as B-cell lymphoma, Ema and TL-1 as T-cell lymphoma, and UL-1 as T-cell acute lymphoblastic leukemia. 3132, originally classified as a B-cell lymphoma, was reclassified as a histiocytic sarcoma based on characteristic cytogenomic properties. In combination, these data begin to elucidate the clinical predictive value of these cell lines which will enhance the appropriate selection of in vitro models for future studies of canine hematological malignancies.

Gene Expression Profiling Reveals Functional Specialization along the Intestinal Tract of a Carnivorous Teleostean Fish (Dicentrarchus labrax)

High-quality sequencing reads from the intestine of European sea bass were assembled, annotated by similarity against protein reference databases and combined with nucleotide sequences from public and private databases. After redundancy filtering, 24,906 non-redundant annotated sequences encoding 15,367 different gene descriptions were obtained. These annotated sequences were used to design a custom, high-density oligo-microarray (8 × 15 K) for the transcriptomic profiling of anterior (AI), middle (MI), and posterior (PI) intestinal segments. Similar molecular signatures were found for AI and MI segments, which were combined in a single group (AI-MI) whereas the PI outstood separately, with more than 1900 differentially expressed genes with a fold-change cutoff of 2. Functional analysis revealed that molecular and cellular functions related to feed digestion and nutrient absorption and transport were over-represented in AI-MI segments. By contrast, the initiation and establishment of immune defense mechanisms became especially relevant in PI, although the microarray expression profiling validated by qPCR indicated that these functional changes are gradual from anterior to posterior intestinal segments. This functional divergence occurred in association with spatial transcriptional changes in nutrient transporters and the mucosal chemosensing system via G protein-coupled receptors. These findings contribute to identify key indicators of gut functions and to compare different fish feeding strategies and immune defense mechanisms acquired along the evolution of teleosts.

FANTOM5 transcriptome catalog of cellular states based on Semantic MediaWiki

The Functional Annotation of the Mammalian Genome project (FANTOM5) mapped transcription start sites (TSSs) and measured their activities in a diverse range of biological samples. The FANTOM5 project generated a large data set; including detailed information about the profiled samples, the uncovered TSSs at high base-pair resolution on the genome, their transcriptional initiation activities, and further information of transcriptional regulation. Data sets to explore transcriptome in individual cellular states encoded in the mammalian genomes have been enriched by a series of additional analysis, based on the raw experimental data, along with the progress of the research activities. To make the heterogeneous data set accessible and useful for investigators, we developed a web-based database called Semantic catalog of Samples, Transcription initiation And Regulators (SSTAR). SSTAR utilizes the open source wiki software MediaWiki along with the Semantic MediaWiki (SMW) extension, which provides flexibility to model, store, and display a series of data sets produced during the course of the FANTOM5 project. Our use of SMW demonstrates the utility of the framework for dissemination of large-scale analysis results. SSTAR is a case study in handling biological data generated from a large-scale research project in terms of maintenance and growth alongside research activities.

Database URL:http://fantom.gsc.riken.jp/5/sstar/

NeuroRDF: semantic integration of highly curated data to prioritize biomarker candidates in Alzheimer's disease

BACKGROUND

Neurodegenerative diseases are incurable and debilitating indications with huge social and economic impact, where much is still to be learnt about the underlying molecular events. Mechanistic disease models could offer a knowledge framework to help decipher the complex interactions that occur at molecular and cellular levels. This motivates the need for the development of an approach integrating highly curated and heterogeneous data into a disease model of different regulatory data layers. Although several disease models exist, they often do not consider the quality of underlying data. Moreover, even with the current advancements in semantic web technology, we still do not have cure for complex diseases like Alzheimer's disease. One of the key reasons accountable for this could be the increasing gap between generated data and the derived knowledge.

RESULTS

In this paper, we describe an approach, called as NeuroRDF, to develop an integrative framework for modeling curated knowledge in the area of complex neurodegenerative diseases. The core of this strategy lies in the usage of well curated and context specific data for integration into one single semantic web-based framework, RDF. This increases the probability of the derived knowledge to be novel and reliable in a specific disease context. This infrastructure integrates highly curated data from databases (Bind, IntAct, etc.), literature (PubMed), and gene expression resources (such as GEO and ArrayExpress). We illustrate the effectiveness of our approach by asking real-world biomedical questions that link these resources to prioritize the plausible biomarker candidates. Among the 13 prioritized candidate genes, we identified MIF to be a potential emerging candidate due to its role as a pro-inflammatory cytokine. We additionally report on the effort and challenges faced during generation of such an indication-specific knowledge base comprising of curated and quality-controlled data.

CONCLUSION

Although many alternative approaches have been proposed and practiced for modeling diseases, the semantic web technology is a flexible and well established solution for harmonized aggregation. The benefit of this work, to use high quality and context specific data, becomes apparent in speculating previously unattended biomarker candidates around a well-known mechanism, further leveraged for experimental investigations.

GEE: An Informatics Tool for Gene Expression Data Explore

Objectives

Major public high-throughput functional genomic data repositories, including the Gene Expression Omnibus (GEO) and ArrayExpress have rapidly expanded. As a result, a large number of diverse high-throughput functional genomic data retrieval systems have been developed. However, high-throughput functional genomic data retrieval remains challenging.

Methods

We developed Gene Expression data Explore (GEE), the first powerful, flexible web and mobile search application for searching whole-genome epigenetic data and microarray data in public databases, such as GEO and ArrayExpress.

Results

GEE provides an elaborate, convenient interface of query generation competences not available via various high-throughput functional genomic data retrieval systems, including GEO, ArrayExpress, and Atlas. In particular, GEE provides a suitable query generator using eVOC, the Experimental Factor Ontology (EFO), which is well represented with a variety of high-throughput functional genomic data experimental conditions. In addition, GEE provides an experimental design query constructor (EDQC), which provides elaborate retrieval filter conditions when the user designs real experiments.

Conclusions

The web version of GEE is available at http://www.snubi.org/software/gee, and its app version is available from the Apple App Store.

Computational Reconstruction of NFκB Pathway Interaction Mechanisms during Prostate Cancer

Molecular research in cancer is one of the largest areas of bioinformatic investigation, but it remains a challenge to understand biomolecular mechanisms in cancer-related pathways from high-throughput genomic data. This includes the Nuclear-factor-kappa-B (NFκB) pathway, which is central to the inflammatory response and cell proliferation in prostate cancer development and progression. Despite close scrutiny and a deep understanding of many of its members’ biomolecular activities, the current list of pathway members and a systems-level understanding of their interactions remains incomplete. Here, we provide the first steps toward computational reconstruction of interaction mechanisms of the NFκB pathway in prostate cancer. We identified novel roles for ATF3, CXCL2, DUSP5, JUNB, NEDD9, SELE, TRIB1, and ZFP36 in this pathway, in addition to new mechanistic interactions between these genes and 10 known NFκB pathway members. A newly predicted interaction between NEDD9 and ZFP36 in particular was validated by co-immunoprecipitation, as was NEDD9's potential biological role in prostate cancer cell growth regulation. We combined 651 gene expression datasets with 1.4M gene product interactions to predict the inclusion of 40 additional genes in the pathway. Molecular mechanisms of interaction among pathway members were inferred using recent advances in Bayesian data integration to simultaneously provide information specific to biological contexts and individual biomolecular activities, resulting in a total of 112 interactions in the fully reconstructed NFκB pathway: 13 (11%) previously known, 29 (26%) supported by existing literature, and 70 (63%) novel. This method is generalizable to other tissue types, cancers, and organisms, and this new information about the NFκB pathway will allow us to further understand prostate cancer and to develop more effective prevention and treatment strategies.

In molecular research in cancer it remains challenging to uncover biomolecular mechanisms in cancer-related pathways from high-throughput genomic data, including the Nuclear-factor-kappa-B (NFκB) pathway. Despite close scrutiny and a deep understanding of many of the NFκB pathway members’ biomolecular activities, the current list of pathway members and a systems-level understanding of their interactions remains incomplete. In this study, we provide the first steps toward computational reconstruction of interaction mechanisms of the NFκB pathway in prostate cancer. We identified novel roles for 8 genes in this pathway and new mechanistic interactions between these genes and 10 known pathway members. We combined 651 gene expression datasets with 1.4M interactions to predict the inclusion of 40 additional genes in the pathway. Molecular mechanisms of interaction were inferred using recent advances in Bayesian data integration to simultaneously provide information specific to biological contexts and individual biomolecular activities, resulting in 112 interactions in the fully reconstructed NFκB pathway. This method is generalizable, and this new information about the NFκB pathway will allow us to further understand prostate cancer.

Multifaceted enrichment analysis of RNA-RNA crosstalk reveals cooperating micro-societies in human colorectal cancer

Alterations in the balance of mRNA and microRNA (miRNA) expression profiles contribute to the onset and development of colorectal cancer. The regulatory functions of individual miRNA-gene pairs are widely acknowledged, but group effects are largely unexplored. We performed an integrative analysis of mRNA–miRNA and miRNA–miRNA interactions using high-throughput mRNA and miRNA expression profiles obtained from matched specimens of human colorectal cancer tissue and adjacent non-tumorous mucosa. This investigation resulted in a hypernetwork-based model, whose functional backbone was fulfilled by tight micro-societies of miRNAs. These proved to modulate several genes that are known to control a set of significantly enriched cancer-enhancer and cancer-protection biological processes, and that an array of upstream regulatory analyses demonstrated to be dependent on miR-145, a cell cycle and MAPK signaling cascade master regulator. In conclusion, we reveal miRNA-gene clusters and gene families with close functional relationships and highlight the role of miR-145 as potent upstream regulator of a complex RNA–RNA crosstalk, which mechanistically modulates several signaling pathways and regulatory circuits that when deranged are relevant to the changes occurring in colorectal carcinogenesis.

HNdb: an integrated database of gene and protein information on head and neck squamous cell carcinoma

The total amount of scientific literature has grown rapidly in recent years. Specifically, there are several million citations in the field of cancer. This makes it difficult, if not impossible, to manually retrieve relevant information on the mechanisms that govern tumor behavior or the neoplastic process. Furthermore, cancer is a complex disease or, more accurately, a set of diseases. The heterogeneity that permeates many tumors is particularly evident in head and neck (HN) cancer, one of the most common types of cancer worldwide. In this study, we present HNdb, a free database that aims to provide a unified and comprehensive resource of information on genes and proteins involved in HN squamous cell carcinoma, covering data on genomics, transcriptomics, proteomics, literature citations and also cross-references of external databases. Different literature searches of MEDLINE abstracts were performed using specific Medical Subject Headings (MeSH terms) for oral, oropharyngeal, hypopharyngeal and laryngeal squamous cell carcinomas. A curated gene-to-publication assignment yielded a total of 1370 genes related to HN cancer. The diversity of results allowed identifying novel and mostly unexplored gene associations, revealing,for example, that processes linked to response to steroid hormone stimulus are significantly enriched in genes related to HN carcinomas. Thus, our database expands the possibilities for gene networks investigation, providing potential hypothesis to be tested. Database URL:http://www.gencapo.famerp.br/hndb.

Spatiotemporal variation of mammalian protein complex stoichiometries

Background

Recent large-scale studies revealed cell-type specific proteomes. However, protein complexes, the basic functional modules of a cell, have been so far mostly considered as static entities with well-defined structures. The co-expression of their members has not been systematically charted at the protein level.

Results

We used measurements of protein abundance across 11 cell types and five temporal states to analyze the co-expression and the compositional variations of 182 well-characterized protein complexes. We show that although the abundance of protein complex members is generally co-regulated, a considerable fraction of all investigated protein complexes is subject to stoichiometric changes. Compositional variation is most frequently seen in complexes involved in chromatin regulation and cellular transport, and often involves paralog switching as a mechanism for the regulation of complex stoichiometry. We demonstrate that compositional signatures of variable protein complexes have discriminative power beyond individual cell states and can distinguish cancer cells from healthy ones.

Conclusions

Our work demonstrates that many protein complexes contain variable members that cause distinct stoichometries and functionally fine-tune complexes spatiotemporally. Only a fraction of these compositional variations is mediated by changes in transcription and other mechanisms regulating protein abundance contribute to determine protein complex stoichiometries. Our work highlights the superior power of proteome profiles to study protein complexes and their variants across cell states.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-016-0912-5) contains supplementary material, which is available to authorized users.

Comprehensive Map of Molecules Implicated in Obesity

Obesity is a global epidemic affecting over 1.5 billion people and is one of the risk factors for several diseases such as type 2 diabetes mellitus and hypertension. We have constructed a comprehensive map of the molecules reported to be implicated in obesity. A deep curation strategy was complemented by a novel semi-automated text mining system in order to screen 1,000 full-length research articles and over 90,000 abstracts that are relevant to obesity. We obtain a scale free network of 804 nodes and 971 edges, composed of 510 proteins, 115 genes, 62 complexes, 23 RNA molecules, 83 simple molecules, 3 phenotype and 3 drugs in "bow-tie" architecture. We classify this network into 5 modules and identify new links between the recently discovered fat mass and obesity associated FTO gene with well studied examples such as insulin and leptin. We further built an automated docking pipeline to dock orlistat as well as other drugs against the 24,000 proteins in the human structural proteome to explain the therapeutics and side effects at a network level. Based upon our experiments, we propose that therapeutic effect comes through the binding of one drug with several molecules in target network, and the binding propensity is both statistically significant and different in comparison with any other part of human structural proteome.

Withdrawn: Discovering Genes Essential to the Hypothalamic Regulation of Human Reproduction Using a Human Disease Model: Adjusting to Life in the "-Omics" Era

The neuroendocrine regulation of reproduction is an intricate process requiring the exquisite coordination of an assortment of cellular networks, all converging on the GnRH neurons. These neurons have a complex life history, migrating mainly from the olfactory placode into the hypothalamus, where GnRH is secreted and acts as the master regulator of the hypothalamic-pituitary-gonadal axis. Much of what we know about the biology of the GnRH neurons has been aided by discoveries made using the human disease model of isolated GnRH deficiency (IGD), a family of rare Mendelian disorders that share a common failure of secretion and/or action of GnRH causing hypogonadotropic hypogonadism. Over the last 30 years, research groups around the world have been investigating the genetic basis of IGD using different strategies based on complex cases that harbor structural abnormalities or single pleiotropic genes, endogamous pedigrees, candidate gene approaches as well as pathway gene analyses. Although such traditional approaches, based on well-validated tools, have been critical to establish the field, new strategies, such as next-generation sequencing, are now providing speed and robustness, but also revealing a surprising number of variants in known IGD genes in both patients and healthy controls. Thus, before the field moves forward with new genetic tools and continues discovery efforts, we must reassess what we know about IGD genetics and prepare to hold our work to a different standard. The purpose of this review is to: 1) look back at the strategies used to discover the "known" genes implicated in the rare forms of IGD; 2) examine the strengths and weaknesses of the methodologies used to validate genetic variation; 3)substantiate the role of known genes in the pathophysiology of the disease; and 4) project forward as we embark upon a widening use of these new and powerful technologies for gene discovery. (Endocrine Reviews 36: 603-621, 2015).

Global analysis of human duplicated genes reveals the relative importance of whole-genome duplicates originated in the early vertebrate evolution

Background

Gene duplication is a genetic mutation that creates functionally redundant gene copies that are initially relieved from selective pressures and may adapt themselves to new functions with time. The levels of gene duplication may vary from small-scale duplication (SSD) to whole genome duplication (WGD). Studies with yeast revealed ample differences between these duplicates: Yeast WGD pairs were functionally more similar, less divergent in subcellular localization and contained a lesser proportion of essential genes. In this study, we explored the differences in evolutionary genomic properties of human SSD and WGD genes, with the identifiable human duplicates coming from the two rounds of whole genome duplication occurred early in vertebrate evolution.

Results

We observed that these two groups of duplicates were also dissimilar in terms of their evolutionary and genomic properties. But interestingly, this is not like the same observed in yeast. The human WGDs were found to be functionally less similar, diverge more in subcellular level and contain a higher proportion of essential genes than the SSDs, all of which are opposite from yeast. Additionally, we explored that human WGDs were more divergent in their gene expression profile, have higher multifunctionality and are more often associated with disease, and are evolutionarily more conserved than human SSDs.

Conclusions

Our study suggests that human WGD duplicates are more divergent and entails the adaptation of WGDs to novel and important functions that consequently lead to their evolutionary conservation in the course of evolution.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2392-0) contains supplementary material, which is available to authorized users.

Expression Atlas update--an integrated database of gene and protein expression in humans, animals and plants

Expression Atlas (http://www.ebi.ac.uk/gxa) provides information about gene and protein expression in animal and plant samples of different cell types, organism parts, developmental stages, diseases and other conditions. It consists of selected microarray and RNA-sequencing studies from ArrayExpress, which have been manually curated, annotated with ontology terms, checked for high quality and processed using standardised analysis methods. Since the last update, Atlas has grown seven-fold (1572 studies as of August 2015), and incorporates baseline expression profiles of tissues from Human Protein Atlas, GTEx and FANTOM5, and of cancer cell lines from ENCODE, CCLE and Genentech projects. Plant studies constitute a quarter of Atlas data. For genes of interest, the user can view baseline expression in tissues, and differential expression for biologically meaningful pairwise comparisons-estimated using consistent methodology across all of Atlas. Our first proteomics study in human tissues is now displayed alongside transcriptomics data in the same tissues. Novel analyses and visualisations include: 'enrichment' in each differential comparison of GO terms, Reactome, Plant Reactome pathways and InterPro domains; hierarchical clustering (by baseline expression) of most variable genes and experimental conditions; and, for a given gene-condition, distribution of baseline expression across biological replicates.