MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing

We have developed a novel machine-learning approach, MutPred Splice, for the identification of coding region substitutions that disrupt pre-mRNA splicing. Applying MutPred Splice to human disease-causing exonic mutations suggests that 16% of mutations causing inherited disease and 10 to 14% of somatic mutations in cancer may disrupt pre-mRNA splicing. For inherited disease, the main mechanism responsible for the splicing defect is splice site loss, whereas for cancer the predominant mechanism of splicing disruption is predicted to be exon skipping via loss of exonic splicing enhancers or gain of exonic splicing silencer elements. MutPred Splice is available at http://mutdb.org/mutpredsplice.     

LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources

MOTIVATION: The NCBI dbSNP database lists over 9 million single nucleotide polymorphisms (SNPs) in the human genome, but currently contains limited annotation information. SNPs that result in amino acid residue changes (nsSNPs) are of critical importance in variation between individuals, including disease and drug sensitivity. RESULTS: We have developed LS-SNP, a genomic scale software pipeline to annotate nsSNPs. LS-SNP comprehensively maps nsSNPs onto protein sequences, functional pathways and comparative protein structure models, and predicts positions where nsSNPs destabilize proteins, interfere with the formation of domain-domain interfaces, have an effect on protein-ligand binding or severely impact human health. It currently annotates 28,043 validated SNPs that produce amino acid residue substitutions in human proteins from the SwissProt/TrEMBL database. Annotations can be viewed via a web interface either in the context of a genomic region or by selecting sets of SNPs, genes, proteins or pathways. These results are useful for identifying candidate functional SNPs within a gene, haplotype or pathway and in probing molecular mechanisms responsible for functional impacts of nsSNPs. AVAILABILITY: http://www.salilab.org/LS-SNP CONTACT: rachelk@salilab.org SUPPLEMENTARY INFORMATION: http://salilab.org/LS-SNP/supp-info.pdf.     

Apple gene function and gene family database: an integrated bioinformatics database for apple research

The apple (Malus domestica) is one of the most economically important fruit crops in the world, due its importance to human nutrition and health. To analyze the function and evolution of different apple genes, we developed apple gene function and gene family database (AppleGFDB) for collecting, storing, arranging, and integrating functional genomics information of the apple. The AppleGFDB provides several layers of information about the apple genes, including nucleotide and protein sequences, chromosomal locations, gene structures, and any publications related to these annotations. To further analyze the functional genomics data of apple genes, the AppleGFDB was designed to enable users to easily retrieve information through a suite of interfaces, including gene ontology, protein domain and InterPro. In addition, the database provides tools for analyzing the expression profiles and microRNAs of the apple. Moreover, all of the analyzed and collected data can be downloaded from the database. The database can also be accessed using a convenient web server that supports a full-text search, a BLAST sequence search, and database browsing. Furthermore, to facilitate cooperation among apple researchers, AppleGFDB is presented in a user-interactive platform, which provides users with the opportunity to modify apple gene annotations and submit publication information for related genes. AppleGFDB is available at http://www.applegene.org or http://gfdb.sdau.edu.cn/.     

Automatic recognition and annotation of gene expression patterns of fly embryos

MOTIVATION: Gene expression patterns obtained by in situ mRNA hybridization provide important information about different genes during Drosophila embryogenesis. So far, annotations of these images are done by manually assigning a subset of anatomy ontology terms to an image. This time-consuming process depends heavily on the consistency of experts. RESULTS: We develop a system to automatically annotate a fruitfly's embryonic tissue in which a gene has expression. We formulate the task as an image pattern recognition problem. For a new fly embryo image, our system answers two questions: (1) Which stage range does an image belong to? (2) Which annotations should be assigned to an image? We propose to identify the wavelet embryo features by multi-resolution 2D wavelet discrete transform, followed by min-redundancy max-relevance feature selection, which yields optimal distinguishing features for an annotation. We then construct a series of parallel bi-class predictors to solve the multi-objective annotation problem since each image may correspond to multiple annotations. SUPPLEMENTARY INFORMATION: The complete annotation prediction results are available at: http://www.cs.niu.edu/~jzhou/papers/fruitfly and http://research.janelia.org/peng/proj/fly_embryo_annotation/. The datasets used in experiments will be available upon request to the correspondence author.     

Influence of IL-6, IL-10, IFN-γ and TNF-α genetic variants on susceptibility to diabetic kidney disease in type 2 diabetes mellitus patients

Background: Data from previous studies on the role of inflammatory cytokines as biomarkers for diabetic kidney disease (DKD) are contradictory. The association of a particular inflammatory cytokine single nucleotide polymorphism (SNP) with susceptibility to DKD has not been consistently replicated. We aimed to investigate the utility of inflammatory cytokines as biomarkers for DKD in type 2 diabetes mellitus (T2DM) patients. Association of inflammatory cytokine gene SNPs with the development of DKD was also explored.

Subjects and Methods: One hundred and fifty-nine Kuwaiti subjects were recruited in this study, including 50 T2DM patients without DKD, 67 diabetic DKD patients and 42 healthy subjects. Plasma levels of interleukin-6 (IL-6), IL-10, interferon gamma (IFN-γ) and tumor necrosis factor alpha (TNF-α) were measured by enzyme-linked immunosorbent assays. Nine SNPs, including 2 SNPs in IL-6, 3 SNPs in IL-10, 1 SNP in IFN-γ and 3 SNPs in TNF-α, were genotyped using TaqMan SNP genotyping assays.

Results: Diabetic DKD patients showed higher IL-6, IL-10, IFN-γ and TNF-α levels than those without DKD. Diabetic DKD patients had a significantly higher frequency of IL-10???1082?A allele than those without DKD (p?=?0.001). No significant association of IL-6???174/?597 haplotypes with DKD risk was detected (p?=?0.188). Distribution of IL-10???592/?819/?1082 haplotypes differ significantly between T2DM patients with/without DKD (p?=?0.014). Diabetic DKD patients had a significantly lower frequency of IL-10???592C/?819C/?1082G haplotype than those without DKD (p?=?0.002).

Conclusions: Although inflammatory cytokine genotypes and, more importantly, haplotypes may have the potential to identify those patients at risk of DKD, hence, improving DKD predisposition prediction, further investigations regarding their real clinical significance is warranted in a large cohort of patients.     

POLYVIEW: a flexible visualization tool for structural and functional annotations of proteins

The POLYVIEW visualization server can be used to generate protein sequence annotations, including secondary structures, relative solvent accessibilities, functional motifs and polymorphic sites. Two-dimensional graphical representations in a customizable format may be generated for both known protein structures and predictions obtained using protein structure prediction servers. POLYVIEW may be used for automated generation of pictures with structural and functional annotations for publications and proteomic on-line resources. AVAILABILITY: http://polyview.cchmc.org.     

SNAP: predict effect of non-synonymous polymorphisms on function

Many genetic variations are single nucleotide polymorphisms (SNPs). Non-synonymous SNPs are 'neutral' if the resulting point-mutated protein is not functionally discernible from the wild type and 'non-neutral' otherwise. The ability to identify non-neutral substitutions could significantly aid targeting disease causing detrimental mutations, as well as SNPs that increase the fitness of particular phenotypes. Here, we introduced comprehensive data sets to assess the performance of methods that predict SNP effects. Along we introduced SNAP (screening for non-acceptable polymorphisms), a neural network-based method for the prediction of the functional effects of non-synonymous SNPs. SNAP needs only sequence information as input, but benefits from functional and structural annotations, if available. In a cross-validation test on over 80,000 mutants, SNAP identified 80% of the non-neutral substitutions at 77% accuracy and 76% of the neutral substitutions at 80% accuracy. This constituted an important improvement over other methods; the improvement rose to over ten percentage points for mutants for which existing methods disagreed. Possibly even more importantly SNAP introduced a well-calibrated measure for the reliability of each prediction. This measure will allow users to focus on the most accurate predictions and/or the most severe effects. Available at http://www.rostlab.org/services/SNAP.     

Genetic variance of transforming growth factor β2 gene in conotruncal heart defects

Objective: The aim of this study was to evaluate the association between two haplotype-tag single nucleotide polymorphisms (SNPs) (rs6658835 and rs10495098) of TGF-β2 and conotruncal heart defects (CTDs).

Methods: Two polymorphisms of TGF-β2 gene were genotyped by polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) from 259 CTDs patients and 310 control subjects.

Results: The association between SNP rs6658835 in TGF-β2 and CTDs has been found. The frequency of G allele in CTDs patients was significantly higher than that in control subjects (52.7% versus 40.3%, p?<?0.001, OR =1.649).

Conclusion: TGF-β2 gene polymorphisms may serve as a novel genetic marker for the risk of CTDs.     

The application of gene silencing in proteomics: from laboratory to clinic

Introduction: Since the completion of genome sequencing, gene silencing technologies have emerged as powerful tools to study gene functions in various biological processes, both in vivo and in vitro. Moreover, they have also been proposed as therapeutic agents to inhibit selected genes in a variety of pathological conditions, such as cancer, neurodegenerative, and cardiovascular diseases.

Area covered: This review summarizes the mechanisms of action and applications of genome editing tools, from RNA interference to clustered regularly interspaced short palindromic repeats-based systems, in research and in clinics. We describe their essential role in high-throughput genetic screens and, in particular, in functional proteomics studies, to identify diagnostic markers and therapeutic targets. Indeed, gene silencing and proteomics have been extensively integrated to study global proteome changes, posttranslational modifications, and protein–protein interactions.

Expert commentary: Functional proteomics approaches that leverage gene silencing tools have been successfully applied to examine the role of several genes in various contexts, leading to a deeper knowledge of biological pathways and disease mechanisms. Recent developments of gene silencing tools have improved their performance, also in terms of off-targets effects reduction, paving the way for a wider therapeutic application of these systems.     

Cigarette smoking affects microRNAs and inflammatory biomarkers in healthy individuals and an association to single nucleotide polymorphisms is indicated

Background: Cigarette smoke induces inflammation and remodels immune response. Genetic and epigenetic alterations might be involved in the pathogenesis of smoking related diseases. In this study, we investigated the effect of smoking on systemic inflammation biomarkers and epigenetic changes at microRNA (miRNA) expression level. We also examined if the levels of inflammatory biomarkers were associated with selected single nucleotide polymorphisms (SNPs).

Method: From 39 smokers and 101 non-smokers, levels of total white blood cells (WBCs) and its subpopulations, plasma cytokines/chemokines/proteins and miRNAs were analysed. For three biomarkers, C-reactive protein (CRP), MCP-1 and IFN-γ that were affected by smoking, the influence of SNPs was analyzed.

Result: Elevated levels of total WBCs, neutrophils, monocytes, lymphocytes, CRP, MCP-1, IFN-γ and lower levels of miR-21 were detected in smokers. The elevated levels of IFN-γ in smokers was only statistically significantly associated with rs2069705 AG/GG SNP-genotype.

Conclusions: A lower level of oncomir miRNA-21 and a higher level of immune modelling cytokine IFN-γ detected in smokers could be a protective immune response to cigarette smoke. The higher level of IFN-γ in smokers with a specific SNP genotype also suggests that a genetic interaction with smoking might predict the pathobiology of smoking related disease.     

BioGRID REST Service, BiogridPlugin2 and BioGRID WebGraph: new tools for access to interaction data at BioGRID

The Biological General Repository for Interaction Datasets (BioGRID) representational state transfer (REST) service allows full URL-based access to curated protein and genetic interaction data at the BioGRID database. Appending URL parameters allows filtering of data by various attributes including gene names and identifiers, PubMed ID and evidence type. We also describe two visualization tools that interface with the REST service, the BiogridPlugin2 for Cytoscape and the BioGRID WebGraph. Availability and implementation: BioGRID data and applications are completely free for commercial and non-commercial use. http://webservice.thebiogrid.org/resources/interactions (REST Service), http://wiki.thebiogrid.org/doku.php/biogridrest(REST Service parameter list and help), http://webservice.thebiogrid.org/resources/application.wadl(REST Service WADL), http://thebiogrid.org/download.php (BiogridPlugin2, v2.1 download), http://wiki.thebiogrid.org/doku.php/biogridplugin2 (BiogridPlugin2 help) and http://tyerslab.bio.ed.ac.uk/tools/BioGRID_webgraph.php(BioGRID WebGraph).     

Novel ortho ester-based,pH-sensitive cationic lipid for gene delivery in vitro and in vivo

Context: Cationic lipoplexes are less toxic than viral gene vectors and more convenient to prepare but their efficiencies of gene delivery are generally lower.

Objective: To develop ortho ester-based, pH-sensitive lipoplexes for efficient gene delivery both in cultured cells and in vivo.

Materials and methods: A novel cationic and acid-labile lipid (DOC) containing a cationic headgroup and a cholesterol-derived lipid tail joined together by an acid-labile ortho ester linker was designed and synthesized. DOC was formulated into liposomes with the conical helper lipid DOPE, and then into lipoplexes with plasmid DNA encoding a luciferase reporter gene. The physicochemical properties of the lipoplexes (size, surface charge and pH-sensitivity) were characterized. Gene delivery by DOC/DOPE/DNA lipoplexes was also evaluated in CV-1 cells and in CD-1 mice following intratracheal injection. Lipoplexes consisting of the acid-stable cationic lipid DC-Chol were characterized as a control.

Results: DOC formed cationic lipoplexes with DOPE and DNA. After incubation at acidic pH 4.6, DOC/DOPE/DNA lipoplexes lost their positive charges and aggregated with one another as a result of DOC hydrolysis. Both in CV-1 cell culture and in CD-1 mice, DOC/DOPE/DNA lipoplexes increased the luciferase gene expression by 5- to 10-fold compared with the analogous but acid-stable DC-Chol/DOPE/DNA lipoplexes.

Discussion and conclusion: Incorporation of an acid-labile ortho ester linker into a cationic lipid is a viable approach to enhance gene delivery by the corresponding lipoplexes both in cultured cells and in vivo.     

Adding some SPICE to DAS

The distributed annotation system (DAS) defines a communication protocol used to exchange biological annotations. It is motivated by the idea that annotations should not be provided by single centralized databases but instead be spread over multiple sites. Data distribution, performed by DAS servers, is separated from visualization, which is carried out by DAS clients. The original DAS protocol was designed to serve annotation of genomic sequences. We have extended the protocol to be applicable to macromolecular structures. Here we present SPICE, a new DAS client that can be used to visualize protein sequence and structure annotations. AVAILABILITY: http://www.efamily.org.uk/software/dasclients/spice/     

Monitoring proteolytic processing events by quantitative mass spectrometry

Introduction: Protease activity plays a key role in a wide variety of biological processes including gene expression, protein turnover and development. misregulation of these proteins has been associated with many cancer types such as prostate, breast, and skin cancer. thus, the identification of protease substrates will provide key information to understand proteolysis-related pathologies.

Areas covered: Proteomics-based methods to investigate proteolysis activity, focusing on substrate identification, protease specificity and their applications in systems biology are reviewed. Their quantification strategies, challenges and pitfalls are underlined and the biological implications of protease malfunction are highlighted.

Expert commentary: Dysregulated protease activity is a hallmark for some disease pathologies such as cancer. Current biochemical approaches are low throughput and some are limited by the amount of sample required to obtain reliable results. Mass spectrometry based proteomics provides a suitable platform to investigate protease activity, providing information about substrate specificity and mapping cleavage sites.     

Gene note. Characterization of a tomato karyopherin {alpha} that interacts with the Tomato Yellow Leaf Curl Virus (TYLCV) capsid protein

A karyopherin (LeKAP1) cDNA was isolated from tomato plants. The deduced LeKAP1 protein sequence of 527 amino acids showed similarity to other plant karyopherin proteins. When LeKAP1 was expressed in a yeast two-hybrid system together with the gene coding for the capsid protein (CP) of the tomato yellow curl leaf virus (TYLCV), it interacted directly with CP. Thus, LeKAP1 may be involved in the nuclear import of TYLCV CP and, potentially, the TYLCV genomes during viral infection of the host tomato cells.     

GOAT

Understanding the composition of gene lists that result from high-throughput experiments requires elaborate processing of gene annotation lists. In this article we present GOAT (Gene Ontology Analysis Tool), a tool based on the statistical software 'R' for analysing Gene Ontologytrade mark (GO) term enrichment in gene lists. Given a gene list, GOAT calculates the enrichment and statistical significance of every GO term and generates graphical presentations of significantly enriched terms. GOAT works for any organism with a genome-scale GO annotation and allows easy updates of ontologies and annotations. AVAILABILITY: GOAT is freely available from http://dictygenome.org/software/GOAT/ CONTACT: Gad Shaulsky (gadi@bcm.tmc.edu).