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© 2015 Macmillan Publishers Limited.Defects in primary cilium biogenesis underlie the ciliopathies, a growing group of genetic disorders. We describe a whole-genome siRNA-based reverse genetics screen for defects in biogenesis and/or maintenance of the pri

Abstract Background Classification and variable selection play an important role in knowledge discovery in high-dimensional data. Although Support Vector Machine (SVM) algorithms are among the most powerful classification and prediction methods with a wide range of scientific applications, the SVM does not include automatic feature selection and therefore a number of feature selection procedures have been developed. Regularisation approaches extend SVM to a feature selection method in a flexible way using penalty functions like LASSO, SCAD and Elastic Net. We propose a novel penalty function for SVM classification tasks, Elastic SCAD, a combination of SCAD and ridge penalties which overcomes the limitations of each penalty alone. Since SVM models are extremely sensitive to the choice of tuning parameters, we adopted an interval search algorithm, which in comparison to a fixed grid search finds rapidly and more precisely a global optimal solution. Results Feature selection methods with combined penalties (Elastic Net and Elastic SCAD SVMs) are more robust to a change of the model complexity than methods using single penalties. Our simulation study showed that Elastic SCAD SVM outperformed LASSO (L1) and SCAD SVMs. Moreover, Elastic SCAD SVM provided sparser classifiers in terms of median number of features selected than Elastic Net SVM and often better predicted than Elastic Net in terms of misclassification error. Finally, we applied the penalization methods described above on four publicly available breast cancer data sets. Elastic SCAD SVM was the only method providing robust classifiers in sparse and non-sparse situations. Conclusions The proposed Elastic SCAD SVM algorithm provides the advantages of the SCAD penalty and at the same time avoids sparsity limitations for non-sparse data. We were first to demonstrate that the integration of the interval search algorithm and penalized SVM classification techniques provides fast solutions on the optimization of tuning parameters. The penalized SVM classification algorithms as well as fixed grid and interval search for finding appropriate tuning parameters were implemented in our freely available R package 'penalizedSVM'. We conclude that the Elastic SCAD SVM is a flexible and robust tool for classification and feature selection tasks for high-dimensional data such as microarray data sets.

Abstract Background Interpreting the results of high-throughput experiments, such as those obtained from DNA-microarrays, is an often time-consuming task due to the high number of data-points that need to be analyzed in parallel. It is usually a matter of extensive testing and unknown beforehand, which of the possible approaches for the functional analysis will be the most informative Results To address this problem, we have developed the Flexible Annotation and Correlation Tool (FACT). FACT allows for detection of important patterns in large data sets by simplifying the integration of heterogeneous data sources and the subsequent application of different algorithms for statistical evaluation or visualization of the annotated data. The system is constantly extended to include additional annotation data and comparison methods. Conclusion FACT serves as a highly flexible framework for the explorative analysis of large genomic and proteomic result sets. The program can be used online; open source code and supplementary information are available at http://www.factweb.de.

Stress response pathways are critical for cellular homeostasis, promoting survival through adaptive changes in gene expression and metabolism. They play key roles in numerous diseases and are implicated in cancer progression and chemoresistance. However, the underlying mechanisms are only poorly understood. We have employed a multi-omics approach to monitor changes to gene expression after induction of a stress response pathway, the unfolded protein response (UPR), probing in parallel the transcriptome, the proteome, and changes to translation. Stringent filtering reveals the induction of 267 genes, many of which have not previously been implicated in stress response pathways. We experimentally demonstrate that UPR-mediated translational control induces the expression of enzymes involved in a pathway that diverts intermediate metabolites from glycolysis to fuel mitochondrial one-carbon metabolism. Concomitantly, the cells become resistant to the folate-based antimetabolites Methotrexate and Pemetrexed, establishing a direct link between UPR-driven changes to gene expression and resistance to pharmacological treatment.

The cilium is an essential organelle at the surface of mammalian cells whose dysfunction causes a wide range of genetic diseases collectively called ciliopathies. The current rate at which new ciliopathy genes are identified suggests that many ciliary components remain undiscovered. We generated and rigorously analyzed genomic, proteomic, transcriptomic and evolutionary data and systematically integrated these using Bayesian statistics into a predictive score for ciliary function. This resulted in 285 candidate ciliary genes. We generated independent experimental evidence of ciliary associations for 24 out of 36 analyzed candidate proteins using multiple cell and animal model systems (mouse, zebrafish and nematode) and techniques. For example, we show that OSCP1, which has previously been implicated in two distinct non-ciliary processes, causes ciliogenic and ciliopathy-associated tissue phenotypes when depleted in zebrafish. The candidate list forms the basis of CiliaCarta, a comprehensive ciliary compendium covering 956 genes. The resource can be used to objectively prioritize candidate genes in whole exome or genome sequencing of ciliopathy patients and can be accessed at http://bioinformatics.bio.uu.nl/john/syscilia/ciliacarta/., Competing Interests: The authors have declared that no competing interests exist.

Background: Recent research into ciliary structure and function provides important insights into inherited diseases termed ciliopathies and other cilia-related disorders. This wealth of knowledge needs to be translated into a computational representation to be fully exploitable by the research community. To this end, members of the Gene Ontology (GO) and SYSCILIA Consortia have worked together to improve representation of ciliary substructures and processes in GO., Methods: Members of the SYSCILIA and Gene Ontology Consortia suggested additions and changes to GO, to reflect new knowledge in the field. The project initially aimed to improve coverage of ciliary parts, and was then broadened to cilia-related biological processes. Discussions were documented in a public tracker. We engaged the broader cilia community via direct consultation and by referring to the literature. Ontology updates were implemented via ontology editing tools., Results: So far, we have created or modified 127 GO terms representing parts and processes related to eukaryotic cilia/flagella or prokaryotic flagella. A growing number of biological pathways are known to involve cilia, and we continue to incorporate this knowledge in GO. The resulting expansion in GO allows more precise representation of experimentally derived knowledge, and SYSCILIA and GO biocurators have created 199 annotations to 50 human ciliary proteins. The revised ontology was also used to curate mouse proteins in a collaborative project. The revised GO and annotations, used in comparative 'before and after' analyses of representative ciliary datasets, improve enrichment results significantly., Conclusions: Our work has resulted in a broader and deeper coverage of ciliary composition and function. These improvements in ontology and protein annotation will benefit all users of GO enrichment analysis tools, as well as the ciliary research community, in areas ranging from microscopy image annotation to interpretation of high-throughput studies. We welcome feedback to further enhance the representation of cilia biology in GO.

Cellular organelles provide opportunities to relate biological mechanisms to disease. Here we use affinity proteomics, genetics and cell biology to interrogate cilia: poorly understood organelles, where defects cause genetic diseases. Two hundred and seventeen tagged human ciliary proteins create a final landscape of 1,319 proteins, 4,905 interactions and 52 complexes. Reverse tagging, repetition of purifications and statistical analyses, produce a high-resolution network that reveals organelle-specific interactions and complexes not apparent in larger studies, and links vesicle transport, the cytoskeleton, signalling and ubiquitination to ciliary signalling and proteostasis. We observe sub-complexes in exocyst and intraflagellar transport complexes, which we validate biochemically, and by probing structurally predicted, disruptive, genetic variants from ciliary disease patients. The landscape suggests other genetic diseases could be ciliary including 3M syndrome. We show that 3M genes are involved in ciliogenesis, and that patient fibroblasts lack cilia. Overall, this organelle-specific targeting strategy shows considerable promise for Systems Medicine.

Ciliopathies are Mendelian disorders caused by dysfunction of cilia, ubiquitous organelles involved in fluid propulsion (motile cilia) or signal transduction (primary cilia). Retinal dystrophy is a common phenotypic characteristic of ciliopathies since photoreceptor outer segments are specialized primary cilia. These ciliary structures heavily rely on intracellular minus-end directed transport of cargo, mediated at least in part by the cytoplasmic dynein 1 motor complex, for their formation, maintenance and function. Ninein-like protein (NINL) is known to associate with this motor complex and is an important interaction partner of the ciliopathy-associated proteins lebercilin, USH2A and CC2D2A. Here, we scrutinize the function of NINL with combined proteomic and zebrafish in vivo approaches. We identify Double Zinc Ribbon and Ankyrin Repeat domains 1 (DZANK1) as a novel interaction partner of NINL and show that loss of Ninl, Dzank1 or both synergistically leads to dysmorphic photoreceptor outer segments, accumulation of trans-Golgi-derived vesicles and mislocalization of Rhodopsin and Ush2a in zebrafish. In addition, retrograde melanosome transport is severely impaired in zebrafish lacking Ninl or Dzank1. We further demonstrate that NINL and DZANK1 are essential for intracellular dynein-based transport by associating with complementary subunits of the cytoplasmic dynein 1 motor complex, thus shedding light on the structure and stoichiometry of this important motor complex. Altogether, our results support a model in which the NINL-DZANK1 protein module is involved in the proper assembly and folding of the cytoplasmic dynein 1 motor complex in photoreceptor cells, a process essential for outer segment formation and function.

Defects in primary cilium biogenesis underlie the ciliopathies, a growing group of genetic disorders. We describe a whole-genome siRNA-based reverse genetics screen for defects in biogenesis and/or maintenance of the primary cilium, obtaining a global resource. We identify 112 candidate ciliogenesis and ciliopathy genes, including 44 components of the ubiquitin-proteasome system, 12 G-protein-coupled receptors, and 3 pre-mRNA processing factors (PRPF6, PRPF8 and PRPF31) mutated in autosomal dominant retinitis pigmentosa. The PRPFs localize to the connecting cilium, and PRPF8- and PRPF31-mutated cells have ciliary defects. Combining the screen with exome sequencing data identified recessive mutations in PIBF1, also known as CEP90, and C21orf2, also known as LRRC76, as causes of the ciliopathies Joubert and Jeune syndromes. Biochemical approaches place C21orf2 within key ciliopathy-associated protein modules, offering an explanation for the skeletal and retinal involvement observed in individuals with C21orf2 variants. Our global, unbiased approaches provide insights into ciliogenesis complexity and identify roles for unanticipated pathways in human genetic disease.

Analyzing the molecular architecture of native multiprotein complexes via biochemical methods has so far been difficult and error prone. Protein complex isolation by affinity purification can define the protein repertoire of a given complex, yet, it remains difficult to gain knowledge of its substructure or modular composition. Here, we introduce SDS concentration gradient induced decomposition of protein complexes coupled to quantitative mass spectrometry and in silico elution profile distance analysis. By applying this new method to a cellular transport module, the IFT/lebercilin complex, we demonstrate its ability to determine modular composition as well as sensitively detect known and novel complex components. We show that the IFT/lebercilin complex can be separated into at least five submodules, the IFT complex A, the IFT complex B, the 14-3-3 protein complex and the CTLH complex, as well as the dynein light chain complex. Furthermore, we identify the protein TULP3 as a potential new member of the IFT complex A and showed that several proteins, classified as IFT complex B-associated, are integral parts of this complex. To further demonstrate EPASIS general applicability, we analyzed the modular substructure of two additional complexes, that of B-RAF and of 14-3-3-ε. The results show, that EPASIS provides a robust as well as sensitive strategy to dissect the substructure of large multiprotein complexes in a highly time- as well as cost-effective manner.

Invasion is a critical step in lung tumor progression. The interaction between tumor cells and their surroundings may play an important role in tumor invasion and metastasis. To better understand the mechanisms of tumor invasion and tumor-microenvironment interactions in lung tumors, total RNA was isolated from the inner tumor, tumor invasion front, adjacent lung, and distant normal lung tissue from 17 patients with primary squamous cell lung carcinoma using punch-aided laser capture microdissection. Messenger RNA expression profiles were obtained by microarray analysis, and microRNA profiles were generated from eight of these samples using TaqMan Low Density Arrays. Statistical analysis of the expression data showed extensive changes in gene expression in the inner tumor and tumor front compared with the normal lung and adjacent lung tissue. Only a few genes were differentially expressed between tumor front and the inner tumor. Several genes were validated by immunohistochemistry. Evaluation of the microRNA data revealed zonal expression differences in nearly a fourth of the microRNAs analyzed. Validation of selected microRNAs by in situ hybridization demonstrated strong expression of hsa-miR-196a in the inner tumor; moderate expression of hsa-miR-224 in the inner tumor and tumor front, and strong expression of hsa-miR-650 in the adjacent lung tissue. Pathway analysis placed the majority of genes differentially expressed between tumor and nontumor cells in intrinsic processes associated with inflammation and extrinsic processes related to lymphocyte physiology. Genes differentially expressed between the inner tumor and the adjacent lung/normal lung tissue affected pathways of arachidonic acid metabolism and eicosanoid signaling., (Copyright © 2012 Wiley Periodicals, Inc.)

Microtubule plus-end tracking proteins (+TIPs) are structurally and functionally diverse factors that accumulate at the growing microtubule plus-ends, connect them to various cellular structures, and control microtubule dynamics [1, 2]. EB1 and its homologs are +TIPs that can autonomously recognize growing microtubule ends and recruit to them a variety of other proteins. Numerous +TIPs bind to end binding (EB) proteins through natively unstructured basic and serine-rich polypeptide regions containing a core SxIP motif (serine-any amino acid-isoleucine-proline) [3]. The SxIP consensus sequence is short, and the surrounding sequences show high variability, raising the possibility that undiscovered SxIP containing +TIPs are encoded in mammalian genomes. Here, we performed a proteome-wide search for mammalian SxIP-containing +TIPs by combining biochemical and bioinformatics approaches. We have identified a set of previously uncharacterized EB partners that have the capacity to accumulate at the growing microtubule ends, including protein kinases, a small GTPase, centriole-, membrane-, and actin-associated proteins. We show that one of the newly identified +TIPs, CEP104, interacts with CP110 and CEP97 at the centriole and is required for ciliogenesis. Our study reveals the complexity of the mammalian +TIP interactome and provides a basis for investigating the molecular crosstalk between microtubule ends and other cellular structures., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Medulloblastoma is the most common malignant brain tumor in children. A subset of medulloblastoma originates from granule cell precursors (GCPs) of the developing cerebellum and demonstrates aberrant hedgehog signaling, typically due to inactivating mutations in the receptor PTCH1, a pathomechanism recapitulated in Ptch1(+/-) mice. As nitric oxide may regulate GCP proliferation and differentiation, we crossed Ptch1(+/-) mice with mice lacking inducible nitric oxide synthase (Nos2) to investigate a possible influence on tumorigenesis. We observed a two-fold higher medulloblastoma rate in Ptch1(+/-) Nos2(-/-) mice compared to Ptch1(+/-) Nos2(+/+) mice. To identify the molecular mechanisms underlying this finding, we performed gene expression profiling of medulloblastomas from both genotypes, as well as normal cerebellar tissue samples of different developmental stages and genotypes. Downregulation of hedgehog target genes was observed in postnatal cerebellum from Ptch1(+/+) Nos2(-/-) mice but not from Ptch1(+/-) Nos2(-/-) mice. The most consistent effect of Nos2 deficiency was downregulation of growth-associated protein 43 (Gap43). Functional studies in neuronal progenitor cells demonstrated nitric oxide dependence of Gap43 expression and impaired migration upon Gap43 knock-down. Both effects were confirmed in situ by immunofluorescence analyses on tissue sections of the developing cerebellum. Finally, the number of proliferating GCPs at the cerebellar periphery was decreased in Ptch1(+/+) Nos2(-/-) mice but increased in Ptch1(+/-) Nos2(-/) (-) mice relative to Ptch1(+/-) Nos2(+/+) mice. Taken together, these results indicate that Nos2 deficiency promotes medulloblastoma development in Ptch1(+/-) mice through retention of proliferating GCPs in the external granular layer due to reduced Gap43 expression. This study illustrates a new role of nitric oxide signaling in cerebellar development and demonstrates that the localization of pre-neoplastic cells during morphogenesis is crucial for their malignant progression., Competing Interests: The authors have declared that no competing interests exist.

Traditionally, protein-protein interactions were thought to be mediated by large, structured domains. However, it has become clear that the interactome comprises a wide range of binding interfaces with varying degrees of flexibility, ranging from rigid globular domains to disordered regions that natively lack structure. Enrichment for disorder in highly connected hub proteins and its correlation with organism complexity hint at the functional importance of disordered regions. Nevertheless, they have not yet been extensively characterised. Shifting the attention from globular domains to disordered regions of the proteome might bring us closer to elucidating the dense and complex connectivity of the interactome. An important class of disordered interfaces are the compact mono-partite, short linear motifs (SLiMs, or eukaryotic linear motifs (ELMs)). They are evolutionarily plastic and interact with relatively low affinity due to the limited number of residues that make direct contact with the binding partner. These features confer to SLiMs the ability to evolve convergently and mediate transient interactions, which is imperative to network evolution and to maintain robust cell signalling, respectively. The ability to discriminate biologically relevant SLiMs by means of different attributes will improve our understanding of the complexity of the interactome and aid development of bioinformatics tools for motif discovery. In this paper, the curated instances currently available in the Eukaryotic Linear Motif (ELM) database are analysed to provide a clear overview of the defining attributes of SLiMs. These analyses suggest that functional SLiMs have higher levels of conservation than their surrounding residues, frequently evolve convergently, preferentially occur in disordered regions and often form a secondary structure when bound to their interaction partner. These results advocate searching for small groupings of residues in disordered regions with higher relative conservation and a propensity to form the secondary structure. Finally, the most interesting conclusions are examined in regard to their functional consequences.

Background: Classification and variable selection play an important role in knowledge discovery in high-dimensional data. Although Support Vector Machine (SVM) algorithms are among the most powerful classification and prediction methods with a wide range of scientific applications, the SVM does not include automatic feature selection and therefore a number of feature selection procedures have been developed. Regularisation approaches extend SVM to a feature selection method in a flexible way using penalty functions like LASSO, SCAD and Elastic Net.We propose a novel penalty function for SVM classification tasks, Elastic SCAD, a combination of SCAD and ridge penalties which overcomes the limitations of each penalty alone.Since SVM models are extremely sensitive to the choice of tuning parameters, we adopted an interval search algorithm, which in comparison to a fixed grid search finds rapidly and more precisely a global optimal solution., Results: Feature selection methods with combined penalties (Elastic Net and Elastic SCAD SVMs) are more robust to a change of the model complexity than methods using single penalties. Our simulation study showed that Elastic SCAD SVM outperformed LASSO (L1) and SCAD SVMs. Moreover, Elastic SCAD SVM provided sparser classifiers in terms of median number of features selected than Elastic Net SVM and often better predicted than Elastic Net in terms of misclassification error.Finally, we applied the penalization methods described above on four publicly available breast cancer data sets. Elastic SCAD SVM was the only method providing robust classifiers in sparse and non-sparse situations., Conclusions: The proposed Elastic SCAD SVM algorithm provides the advantages of the SCAD penalty and at the same time avoids sparsity limitations for non-sparse data. We were first to demonstrate that the integration of the interval search algorithm and penalized SVM classification techniques provides fast solutions on the optimization of tuning parameters.The penalized SVM classification algorithms as well as fixed grid and interval search for finding appropriate tuning parameters were implemented in our freely available R package 'penalizedSVM'.We conclude that the Elastic SCAD SVM is a flexible and robust tool for classification and feature selection tasks for high-dimensional data such as microarray data sets.

To identify novel glioma-associated pathomechanisms and molecular markers, we performed an array-based comparative genomic hybridization analysis of 131 diffuse astrocytic gliomas, including 87 primary glioblastomas (pGBIV), 13 secondary glioblastomas (sGBIV), 19 anaplastic astrocytomas (AAIII) and 12 diffuse astrocytomas (AII). All tumors were additionally screened for IDH1 and IDH2 mutations. Expression profiling was performed for 74 tumors (42 pGBIV, 11 sGBIV, 13 AAIII, 8 AII). Unsupervised and supervised bioinformatic analyses revealed distinct genomic and expression profiles separating pGBIV from the other entities. Classifier expression signatures were strongly associated with the IDH1 gene mutation status. Within pGBIV, the rare subtype of IDH1 mutant tumors shared expression profiles with IDH1 mutant sGBIV and was associated with longer overall survival compared with IDH1 wild-type tumors. In patients with IDH1 wild-type pGBIV, PDGFRA gain or amplification as well as 19q gain were associated with patient outcome. Array-CGH analysis additionally revealed homozygous deletions of the FGFR2 gene at 10q26.13 in 2 pGBIV, with reduced FGFR2 mRNA levels being frequent in pGBIV and linked to poor outcome. In conclusion, we report that diffuse astrocytic gliomas can be separated into 2 major molecular groups with distinct genomic and mRNA profiles as well as IDH1 gene mutation status. In addition, our results suggest FGFR2 as a novel glioma-associated candidate tumor suppressor gene on the long arm of chromosome 10., (Copyright © 2010 UICC.)

Background: Chronic lymphocytic leukemia cells show prolonged survival in vivo, but rapidly die by spontaneous apoptosis in vitro, unless they are co-cultured with stromal cells or non-malignant leukocytes. The objective of this study was to characterize the survival-inducing cross-talk of chronic lymphocytic leukemia cells with their microenvironment to identify novel therapeutic targets., Design and Methods: We analyzed and compared microarray-based expression profiles of chronic lymphocytic leukemia cells before and after three different survival-inducing culture conditions: (i) stromal cell co-culture, (ii) stromal cell conditioned medium and (iii) high cell density cultures of unsorted peripheral blood mononuclear cells. Cytokine antibody arrays were applied to study the composition of soluble factors present in these cultures., Results: The different survival-supportive culture conditions induced distinct gene expression changes, the majority of which were common to all three conditions. Pathway analyses identified - in addition to known signaling networks in chronic lymphocytic leukemia - novel pathways, of which Toll-like receptor signaling, nuclear respiratory factor-2 (NRF2)-mediated oxidative stress response, and signaling via triggering receptor expressed on myeloid cells-1 (TREM1) were the most relevant. A high proportion of up-regulated genes were inflammatory cytokines, of which chemokine (C-C motif) ligand 2 (CCL2) was shown to be induced in monocytes by the presence of chronic lymphocytic leukemia cells in vitro. In addition, increased serum levels of this chemokine were detected in patients with chronic lymphocytic leukemia., Conclusions: Our data provide several lines of evidence that an inflammatory microenvironment is induced in survival-supportive cultures of chronic lymphocytic leukemia cells which might be directly or indirectly involved in the prolonged survival of the malignant cells.

Gene copy number aberrations are involved in oral squamous cell carcinoma (OSCC) development. To delineate candidate genes inside critical chromosomal regions, array-CGH was applied to 40 OSCC specimens using a microarray covering the whole human genome with an average resolution of 1 Mb. Gene copy number gains were predominantly found at 1q23 (9 cases), 3q26 (11), 5p15 (13), 7p11 (7), 8q24 (17), 11q13 (15), 14q32 (8), 19p13 (8), 19q12 (7), 19q13 (8), and 20q13 (9), whereas gene copy number losses were detected at 3p21-3p12 (15), 8p32 (11), 10p12 (8), and 18q21-q23 (10). Subsequent mRNA expression analyses by quantitative real time polymerase chain reaction found high mRNA expression of candidate genes SOX2 in 3q26.33, FSLT3 in 19p13.3, and CCNE1 in 19q12. Tissue microarray (TMA) analyses in a representative OSCC collection found gene copy number gain for SOX2 in 52% (115/223) and for CCNE1 in 31% (72/233) of the tumors. Immunohistochemical analyses on TMA sections of the corresponding proteins detected high expression of SOX2 in 18.1% (49/271) and of CyclinE1 in 23.3% (64/275) of tumors analyzed. These findings indicate that SOX2 and CCNE1 might be activated via gene copy number gain and participate in oral carcinogenesis. The combination of array-CGH with TMA analyses allows rapid pinpointing of novel promising candidate genes, which might be used as therapeutic stratification markers or target molecules for therapeutic interference.