Nav1.7 is essential for nociceptor action potentials in the mouse in a manner independent of endogenous opioids

Loss-of-function mutations in Nav1.7, a voltage-gated sodium channel, cause congenital insensitivity to pain (CIP) in humans, demonstrating that Nav1.7 is essential for the perception of pain. However, the mechanism by which loss of Nav1.7 results in insensitivity to pain is not entirely clear. It has been suggested that loss of Nav1.7 induces overexpression of enkephalin, an endogenous opioid receptor agonist, leading to opioid-dependent analgesia. Using behavioral pharmacology and single-cell RNA-seq analysis, we find that overexpression of enkephalin occurs only in cLTMR neurons, a subclass of sensory neurons involved in low-threshold touch detection, and that this overexpression does not play a role in the analgesia observed following genetic removal of Nav1.7. Furthermore, we demonstrate using laser speckle contrast imaging (LSCI) and in vivo electrophysiology that Nav1.7 function is required for the initiation of C-fiber action potentials (APs), which explains the observed insensitivity to pain following genetic removal or inhibition of Nav1.7.

Single-Cell Transcriptomic Analysis Links Nonmyelinating Schwann Cells to Proinflammatory Response in the Lung

The lung is a barrier tissue with constant exposure to the inhaled environment. Therefore, innate immunity against particulates and pathogens is of critical importance to maintain tissue homeostasis. Although the lung harbors both myelinating and nonmyelinating Schwann cells (NMSCs), NMSCs represent the most abundant Schwann cell (SC) population in the lung. However, their contribution to lung physiology remains largely unknown. In this study, we used the human glial fibrillary acidic protein promoter driving tdTomato expression in mice to identify SCs in the peripheral nervous system and determine their location within the lung. Single-cell transcriptomic analysis revealed the existence of two NMSC populations (NMSC1 and NMSC2) that may participate in pathogen recognition. We demonstrated that these pulmonary SCs produce chemokines and cytokines upon LPS stimulation using in vitro conditions. Furthermore, we challenged mouse lungs with LPS and found that NMSC1 exhibits an enriched proinflammatory response among all SC subtypes. Collectively, these findings define the molecular profiles of lung SCs and suggest a potential role for NMSCs in lung inflammation.

Whole genome sequencing across clinical trials identifies rare coding variants in GPR68 associated with chemotherapy-induced peripheral neuropathy

BACKGROUND

Dose-limiting toxicities significantly impact the benefit/risk profile of many drugs. Whole genome sequencing (WGS) in patients receiving drugs with dose-limiting toxicities can identify therapeutic hypotheses to prevent these toxicities. Chemotherapy-induced peripheral neuropathy (CIPN) is a common dose-limiting neurological toxicity of chemotherapies with no effective approach for prevention.

METHODS

We conducted a genetic study of time-to-first peripheral neuropathy event using 30× germline WGS data from whole blood samples from 4900 European-ancestry cancer patients in 14 randomized controlled trials. A substantial number of patients in these trials received taxane and platinum-based chemotherapies as part of their treatment regimen, either standard of care or in combination with the PD-L1 inhibitor atezolizumab. The trials spanned several cancers including renal cell carcinoma, triple negative breast cancer, non-small cell lung cancer, small cell lung cancer, bladder cancer, ovarian cancer, and melanoma.

RESULTS

We identified a locus consisting of low-frequency variants in intron 13 of GRID2 associated with time-to-onset of first peripheral neuropathy (PN) indexed by rs17020773 (p = 2.03 × 10^-8, all patients, p = 6.36 × 10^-9, taxane treated). Gene-level burden analysis identified rare coding variants associated with increased PN risk in the C-terminus of GPR68 (p = 1.59 × 10^-6, all patients, p = 3.47 × 10^-8, taxane treated), a pH-sensitive G-protein coupled receptor (GPCR). The variants driving this signal were found to alter predicted arrestin binding motifs in the C-terminus of GPR68. Analysis of snRNA-seq from human dorsal root ganglia (DRG) indicated that expression of GPR68 was highest in mechano-thermo-sensitive nociceptors.

CONCLUSIONS

Our genetic study provides insight into the impact of low-frequency and rare coding genetic variation on PN risk and suggests that further study of GPR68 in sensory neurons may yield a therapeutic hypothesis for prevention of CIPN.

A systems biology approach uncovers novel disease mechanisms in age-related macular degeneration

Age-related macular degeneration (AMD) is a leading cause of blindness, affecting 200 million people worldwide. To identify genes that could be targeted for treatment, we created a molecular atlas at different stages of AMD. Our resource is comprised of RNA sequencing (RNA-seq) and DNA methylation microarrays from bulk macular retinal pigment epithelium (RPE)/choroid of clinically phenotyped normal and AMD donor eyes (n = 85), single-nucleus RNA-seq (164,399 cells), and single-nucleus assay for transposase-accessible chromatin (ATAC)-seq (125,822 cells) from the retina, RPE, and choroid of 6 AMD and 7 control donors. We identified 23 genome-wide significant loci differentially methylated in AMD, over 1,000 differentially expressed genes across different disease stages, and an AMD Müller state distinct from normal or gliosis. Chromatin accessibility peaks in genome-wide association study (GWAS) loci revealed putative causal genes for AMD, including HTRA1 and C6orf223. Our systems biology approach uncovered molecular mechanisms underlying AMD, including regulators of WNT signaling, FRZB and TLE2, as mechanistic players in disease.

Cross-species transcriptomic atlas of dorsal root ganglia reveals species-specific programs for sensory function

Sensory neurons of the dorsal root ganglion (DRG) are critical for maintaining tissue homeostasis by sensing and initiating responses to stimuli. While most preclinical studies of DRGs are conducted in rodents, much less is known about the mechanisms of sensory perception in primates. We generated a transcriptome atlas of mouse, guinea pig, cynomolgus monkey, and human DRGs by implementing a common laboratory workflow and multiple data-integration approaches to generate high-resolution cross-species mappings of sensory neuron subtypes. Using our atlas, we identified conserved core modules highlighting subtype-specific biological processes related to inflammatory response. We also identified divergent expression of key genes involved in DRG function, suggesting species-specific adaptations specifically in nociceptors that likely point to divergent function of nociceptors. Among these, we validated that TAFA4, a member of the druggable genome, was expressed in distinct populations of DRG neurons across species, highlighting species-specific programs that are critical for therapeutic development.

Disease-associated oligodendrocyte responses across neurodegenerative diseases

Oligodendrocyte dysfunction has been implicated in the pathogenesis of neurodegenerative diseases, so understanding oligodendrocyte activation states would shed light on disease processes. We identify three distinct activation states of oligodendrocytes from single-cell RNA sequencing (RNA-seq) of mouse models of Alzheimer's disease (AD) and multiple sclerosis (MS): DA1 (disease-associated1, associated with immunogenic genes), DA2 (disease-associated2, associated with genes influencing survival), and IFN (associated with interferon response genes). Spatial analysis of disease-associated oligodendrocytes (DAOs) in the cuprizone model reveals that DA1 and DA2 are established outside of the lesion area during demyelination and that DA1 repopulates the lesion during remyelination. Independent meta-analysis of human single-nucleus RNA-seq datasets reveals that the transcriptional responses of MS oligodendrocytes share features with mouse models. In contrast, the oligodendrocyte activation signature observed in human AD is largely distinct from those observed in mice. This catalog of oligodendrocyte activation states (http://research-pub.gene.com/OligoLandscape/) will be important to understand disease progression and develop therapeutic interventions.

NMDA receptor-dependent prostaglandin-endoperoxide synthase 2 induction in neurons promotes glial proliferation during brain development and injury

Astrocytes play critical roles in brain development and disease, but the mechanisms that regulate astrocyte proliferation are poorly understood. We report that astrocyte proliferation is bi-directionally regulated by neuronal activity via NMDA receptor (NMDAR) signaling in neurons. Prolonged treatment with an NMDAR antagonist reduced expression of cell-cycle-related genes in astrocytes in hippocampal cultures and suppressed astrocyte proliferation in vitro and in vivo, whereas neuronal activation promoted astrocyte proliferation, dependent on neuronal NMDARs. Expression of prostaglandin-endoperoxide synthase 2 (Ptgs2) is induced specifically in neurons by NMDAR activation and is required for activity-dependent astrocyte proliferation through its product, prostaglandin E₂ (PGE₂). NMDAR inhibition or Ptgs2 genetic ablation in mice reduced the proliferation of astrocytes and microglia induced by mild traumatic brain injury in the absence of secondary excitotoxicity-induced neuronal death. Our study defines an NMDAR-mediated signaling mechanism that allows trans-cellular control of glial proliferation by neurons in brain development and injury.

MicrobiomeExplorer: an R package for the analysis and visualization of microbial communities

SUMMARY

We developed the MicrobiomeExplorer R package to facilitate the analysis and visualization of microbial communities. The MicrobiomeExplorer R package allows a user to perform typical microbiome analytic workflows and visualize their results, either through the command line or an interactive Shiny application included with the package. In addition to applying common analytical workflows, the application enables automated analysis report generation.

AVAILABILITY AND IMPLEMENTATION

Available at https://github.com/zoecastillo/microbiomeExplorer.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Diverse Brain Myeloid Expression Profiles Reveal Distinct Microglial Activation States and Aspects of Alzheimer's Disease Not Evident in Mouse Models

Microglia, the CNS-resident immune cells, play important roles in disease, but the spectrum of their possible activation states is not well understood. We derived co-regulated gene modules from transcriptional profiles of CNS myeloid cells of diverse mouse models, including new tauopathy model datasets. Using these modules to interpret single-cell data from an Alzheimer's disease (AD) model, we identified microglial subsets-distinct from previously reported "disease-associated microglia"-expressing interferon-related or proliferation modules. We then analyzed whole-tissue RNA profiles from human neurodegenerative diseases, including a new AD dataset. Correcting for altered cellular composition of AD tissue, we observed elevated expression of the neurodegeneration-related modules, but also modules not implicated using expression profiles from mouse models alone. We provide a searchable, interactive database for exploring gene expression in all these datasets (http://research-pub.gene.com/BrainMyeloidLandscape). Understanding the dimensions of CNS myeloid cell activation in human disease may reveal opportunities for therapeutic intervention.

Progranulin deficiency causes impairment of autophagy and TDP-43 accumulation

It is unclear how progranulin deficiency causes frontotemporal dementia, a neurodegenerative disease characterized by TDP-43 inclusions. Chang et al. show that loss of progranulin causes impairment of autophagy and autophagy signaling, which leads to accumulation of pathological TDP-43 in neurons.

Loss-of-function mutations in GRN cause frontotemporal dementia (FTD) with transactive response DNA-binding protein of 43 kD (TDP-43)–positive inclusions and neuronal ceroid lipofuscinosis (NCL). There are no disease-modifying therapies for either FTD or NCL, in part because of a poor understanding of how mutations in genes such as GRN contribute to disease pathogenesis and neurodegeneration. By studying mice lacking progranulin (PGRN), the protein encoded by GRN, we discovered multiple lines of evidence that PGRN deficiency results in impairment of autophagy, a key cellular degradation pathway. PGRN-deficient mice are sensitive to Listeria monocytogenes because of deficits in xenophagy, a specialized form of autophagy that mediates clearance of intracellular pathogens. Cells lacking PGRN display reduced autophagic flux, and pathological forms of TDP-43 typically cleared by autophagy accumulate more rapidly in PGRN-deficient neurons. Our findings implicate autophagy as a novel therapeutic target for GRN-associated NCL and FTD and highlight the emerging theme of defective autophagy in the broader FTD/amyotrophic lateral sclerosis spectrum of neurodegenerative disease.

Dual leucine zipper kinase-dependent PERK activation contributes to neuronal degeneration following insult

The PKR-like endoplasmic reticulum kinase (PERK) arm of the Integrated Stress Response (ISR) is implicated in neurodegenerative disease, although the regulators and consequences of PERK activation following neuronal injury are poorly understood. Here we show that PERK signaling is a component of the mouse MAP kinase neuronal stress response controlled by the Dual Leucine Zipper Kinase (DLK) and contributes to DLK-mediated neurodegeneration. We find that DLK-activating insults ranging from nerve injury to neurotrophin deprivation result in both c-Jun N-terminal Kinase (JNK) signaling and the PERK- and ISR-dependent upregulation of the Activating Transcription Factor 4 (ATF4). Disruption of PERK signaling delays neurodegeneration without reducing JNK signaling. Furthermore, DLK is both sufficient for PERK activation and necessary for engaging the ISR subsequent to JNK-mediated retrograde injury signaling. These findings identify DLK as a central regulator of not only JNK but also PERK stress signaling in neurons, with both pathways contributing to neurodegeneration.

A Common Variant of IL-6R is Associated with Elevated IL-6 Pathway Activity in Alzheimer's Disease Brains

The common p.D358A variant (rs2228145) in IL-6R is associated with risk for multiple diseases and with increased levels of soluble IL-6R in the periphery and central nervous system (CNS). Here, we show that the p.D358A allele leads to increased proteolysis of membrane bound IL-6R and demonstrate that IL-6R peptides with A358 are more susceptible to cleavage by ADAM10 and ADAM17. IL-6 responsive genes were identified in primary astrocytes and microglia and an IL-6 gene signature was increased in the CNS of late onset Alzheimer's disease subjects in an IL6R allele dependent manner. We conducted a screen to identify variants associated with the age of onset of Alzheimer's disease in APOE ɛ4 carriers. Across five datasets, p.D358A had a meta P = 3 ×10-4 and an odds ratio = 1.3, 95% confidence interval 1.12 -1.48. Our study suggests that a common coding region variant of the IL-6 receptor results in neuroinflammatory changes that may influence the age of onset of Alzheimer's disease in APOE ɛ4 carriers.

Untangling the brain's neuroinflammatory and neurodegenerative transcriptional responses

A common approach to understanding neurodegenerative disease is comparing gene expression in diseased versus healthy tissues. We illustrate that expression profiles derived from whole tissue RNA highly reflect the degenerating tissues' altered cellular composition, not necessarily transcriptional regulation. To accurately understand transcriptional changes that accompany neuropathology, we acutely purify neurons, astrocytes and microglia from single adult mouse brains and analyse their transcriptomes by RNA sequencing. Using peripheral endotoxemia to establish the method, we reveal highly specific transcriptional responses and altered RNA processing in each cell type, with Tnfr1 required for the astrocytic response. Extending the method to an Alzheimer's disease model, we confirm that transcriptomic changes observed in whole tissue are driven primarily by cell type composition, not transcriptional regulation, and identify hundreds of cell type-specific changes undetected in whole tissue RNA. Applying similar methods to additional models and patient tissues will transform our understanding of aberrant gene expression in neurological disease.

Whole tissue RNA profiling can help identify altered molecular pathways underlying neurodegenerative disease, but often masks cell type-specific transcriptional changes. Here, the authors compare transcriptomes of neurons, astrocytes, and microglia from Alzheimer's disease model brains and identify hundreds of cell-type specific changes.

Complex regulation of ADAR-mediated RNA-editing across tissues

Background

RNA-editing is a tightly regulated, and essential cellular process for a properly functioning brain. Dysfunction of A-to-I RNA editing can have catastrophic effects, particularly in the central nervous system. Thus, understanding how the process of RNA-editing is regulated has important implications for human health. However, at present, very little is known about the regulation of editing across tissues, and individuals.

Results

Here we present an analysis of RNA-editing patterns from 9 different tissues harvested from a single mouse. For comparison, we also analyzed data for 5 of these tissues harvested from 15 additional animals. We find that tissue specificity of editing largely reflects differential expression of substrate transcripts across tissues. We identified a surprising enrichment of editing in intronic regions of brain transcripts, that could account for previously reported higher levels of editing in brain. There exists a small but remarkable amount of editing which is tissue-specific, despite comparable expression levels of the edit site across multiple tissues. Expression levels of editing enzymes and their isoforms can explain some, but not all of this variation.

Conclusions

Together, these data suggest a complex regulation of the RNA-editing process beyond transcript expression levels.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2291-9) contains supplementary material, which is available to authorized users.

A resource for cell line authentication, annotation and quality control

Cell line misidentification, contamination and poor annotation affect scientific reproducibility. Here we outline simple measures to detect or avoid cross-contamination, present a framework for cell line annotation linked to short tandem repeat and single nucleotide polymorphism profiles, and provide a catalogue of synonymous cell lines. This resource will enable our community to eradicate the use of misidentified lines and generate credible cell-based data.

ReportingTools: an automated result processing and presentation toolkit for high-throughput genomic analyses

It is common for computational analyses to generate large amounts of complex data that are difficult to process and share with collaborators. Standard methods are needed to transform such data into a more useful and intuitive format. We present ReportingTools, a Bioconductor package, that automatically recognizes and transforms the output of many common Bioconductor packages into rich, interactive, HTML-based reports. Reports are not generic, but have been individually designed to reflect content specific to the result type detected. Tabular output included in reports is sortable, filterable and searchable and contains context-relevant hyperlinks to external databases. Additionally, in-line graphics have been developed for specific analysis types and are embedded by default within table rows, providing a useful visual summary of underlying raw data. ReportingTools is highly flexible and reports can be easily customized for specific applications using the well-defined API.

AVAILABILITY

The ReportingTools package is implemented in R and available from Bioconductor (version ≥ 2.11) at the URL: http://bioconductor.org/packages/release/bioc/html/ReportingTools.html. Installation instructions and usage documentation can also be found at the above URL.

Histone deacetylase (HDAC) inhibitor kinetic rate constants correlate with cellular histone acetylation but not transcription and cell viability

Histone deacetylases (HDACs) are critical in the control of gene expression, and dysregulation of their activity has been implicated in a broad range of diseases, including cancer, cardiovascular, and neurological diseases. HDAC inhibitors (HDACi) employing different zinc chelating functionalities such as hydroxamic acids and benzamides have shown promising results in cancer therapy. Although it has also been suggested that HDACi with increased isozyme selectivity and potency may broaden their clinical utility and minimize side effects, the translation of this idea to the clinic remains to be investigated. Moreover, a detailed understanding of how HDACi with different pharmacological properties affect biological functions in vitro and in vivo is still missing. Here, we show that a panel of benzamide-containing HDACi are slow tight-binding inhibitors with long residence times unlike the hydroxamate-containing HDACi vorinostat and trichostatin-A. Characterization of changes in H2BK5 and H4K14 acetylation following HDACi treatment in the neuroblastoma cell line SH-SY5Y revealed that the timing and magnitude of histone acetylation mirrored both the association and dissociation kinetic rates of the inhibitors. In contrast, cell viability and microarray gene expression analysis indicated that cell death induction and changes in transcriptional regulation do not correlate with the dissociation kinetic rates of the HDACi. Therefore, our study suggests that determining how the selective and kinetic inhibition properties of HDACi affect cell function will help to evaluate their therapeutic utility.

Identification and analysis of in vivo VEGF downstream markers link VEGF pathway activity with efficacy of anti-VEGF therapies

PURPOSE

The aim of this study was to identify conserved pharmacodynamic and potential predictive biomarkers of response to anti-VEGF therapy using gene expression profiling in preclinical tumor models and in patients.

EXPERIMENTAL DESIGN

Surrogate markers of VEGF inhibition [VEGF-dependent genes or VEGF-dependent vasculature (VDV)] were identified by profiling gene expression changes induced in response to VEGF blockade in preclinical tumor models and in human biopsies from patients treated with anti-VEGF monoclonal antibodies. The potential value of VDV genes as candidate predictive biomarkers was tested by correlating high or low VDV gene expression levels in pretreatment clinical samples with the subsequent clinical efficacy of bevacizumab (anti-VEGF)-containing therapy.

RESULTS

We show that VDV genes, including direct and more distal VEGF downstream endothelial targets, enable detection of VEGF signaling inhibition in mouse tumor models and human tumor biopsies. Retrospective analyses of clinical trial data indicate that patients with higher VDV expression in pretreatment tumor samples exhibited improved clinical outcome when treated with bevacizumab-containing therapies.

CONCLUSIONS

In this work, we identified surrogate markers (VDV genes) for in vivo VEGF signaling in tumors and showed clinical data supporting a correlation between pretreatment VEGF bioactivity and the subsequent efficacy of anti-VEGF therapy. We propose that VDV genes are candidate biomarkers with the potential to aid the selection of novel indications as well as patients likely to respond to anti-VEGF therapy. The data presented here define a diagnostic biomarker hypothesis based on translational research that warrants further evaluation in additional retrospective and prospective trials.

Spatially coordinated kinase signaling regulates local axon degeneration

In addition to being a hallmark of neurodegenerative disease, axon degeneration is used during development of the nervous system to prune unwanted connections. In development, axon degeneration is tightly regulated both temporally and spatially. Here, we provide evidence that degeneration cues are transduced through various kinase pathways functioning in spatially distinct compartments to regulate axon degeneration. Intriguingly, glycogen synthase kinase-3 (GSK3) acts centrally, likely modulating gene expression in the cell body to regulate distally restricted axon degeneration. Through a combination of genetic and pharmacological manipulations, including the generation of an analog-sensitive kinase allele mutant mouse for GSK3β, we show that the β isoform of GSK3, not the α isoform, is essential for developmental axon pruning in vitro and in vivo. Additionally, we identify the dleu2/mir15a/16-1 cluster, previously characterized as a regulator of B-cell proliferation, and the transcription factor tbx6, as likely downstream effectors of GSK3β in axon degeneration.

Death receptors DR6 and TROY regulate brain vascular development

Signaling events that regulate central nervous system (CNS) angiogenesis and blood-brain barrier (BBB) formation are only beginning to be elucidated. By evaluating the gene expression profile of mouse vasculature, we identified DR6/TNFRSF21 and TROY/TNFRSF19 as regulators of CNS-specific angiogenesis in both zebrafish and mice. Furthermore, these two death receptors interact both genetically and physically and are required for vascular endothelial growth factor (VEGF)-mediated JNK activation and subsequent human brain endothelial sprouting in vitro. Increasing beta-catenin levels in brain endothelium upregulate DR6 and TROY, indicating that these death receptors are downstream target genes of Wnt/beta-catenin signaling, which has been shown to be required for BBB development. These findings define a role for death receptors DR6 and TROY in CNS-specific vascular development.

Inferring the functional effects of mutation through clusters of mutations in homologous proteins

Inferring functional consequences is a bottleneck in high-throughput cancer mutation discovery and genetic association studies. Most polymorphisms and germline mutations are unlikely to have functionally significant consequences. Most cancer somatic mutations do not contribute to tumorigenesis and are not under selective pressure. Identifying and understanding functionally important mutations can clarify disease biology and lead to new therapeutic and diagnostic opportunities. We investigated the extent to which protein mutations with functional consequences are enriched in clusters at conserved positions across related proteins. We found that disease-causing mutations form clusters more than random mutations or single nucleotide polymorphisms, confirming that mutation hotspots occur at the domain level. In addition to helping to identify functionally significant mutations, analysis of clustered mutations can indicate the mechanism and consequences for protein function. Our analysis focused on somatic cancer mutations suggests functional impact for many, including singleton mutations in FGFR1, FGFR3, GFI1B, PIK3CG, RALB, RAP2B, and STK11. This provides evidence and generates mechanistic hypotheses for the contribution of such mutations to cancer. The same approach can be applied to mutations suspected of involvement in other diseases. An interactive Web application for browsing mutation clusters is available at http://www.mcluster.org.

High-resolution analysis of copy number alterations and associated expression changes in ovarian tumors

Background

DNA copy number alterations are frequently observed in ovarian cancer, but it remains a challenge to identify the most relevant alterations and the specific causal genes in those regions.

Methods

We obtained high-resolution 500K SNP array data for 52 ovarian tumors and identified the most statistically significant minimal genomic regions with the most prevalent and highest-level copy number alterations (recurrent CNAs). Within a region of recurrent CNA, comparison of expression levels in tumors with a given CNA to tumors lacking that CNA and to whole normal ovary samples was used to select genes with CNA-specific expression patterns. A public expression array data set of laser capture micro-dissected (LCM) non-malignant fallopian tube epithelia and LCM ovarian serous adenocarcinoma was used to evaluate the effect of cell-type mixture biases.

Results

Fourteen recurrent deletions were detected on chromosomes 4, 6, 9, 12, 13, 15, 16, 17, 18, 22 and most prevalently on X and 8. Copy number and expression data suggest several apoptosis mediators as candidate drivers of the 8p deletions. Sixteen recurrent gains were identified on chromosomes 1, 2, 3, 5, 8, 10, 12, 15, 17, 19, and 20, with the most prevalent gains localized to 8q and 3q. Within the 8q amplicon, PVT1, but not MYC, was strongly over-expressed relative to tumors lacking this CNA and showed over-expression relative to normal ovary. Likewise, the cell polarity regulators PRKCI and ECT2 were identified as putative drivers of two distinct amplicons on 3q. Co-occurrence analyses suggested potential synergistic or antagonistic relationships between recurrent CNAs. Genes within regions of recurrent CNA showed an enrichment of Cancer Census genes, particularly when filtered for CNA-specific expression.

Conclusion

These analyses provide detailed views of ovarian cancer genomic changes and highlight the benefits of using multiple reference sample types for the evaluation of CNA-specific expression changes.

Computational prediction of the functional effects of amino acid substitutions in signal peptides using a model-based approach

Signal peptides are N-terminal sequences that mediate the targeting and translocation of secreted or cell-surface proteins to the endoplasmic reticulum (ER) membrane. Because of the variability among signal peptides, traditional methods for predicting the effects of an amino acid substitution based on sequence conservation methods may be limited in their use. To address this, we present a scoring function that assesses the effects of an amino acid change within the signal peptide by using data from SignalP, a signal peptide prediction algorithm. Our score incorporates the maximum alterations of the C- and S-scores from SignalP between original and changed versions of the signal peptide. We demonstrate that this metric can discriminate disease-associated mutations from single nucleotide polymorphisms (SNPs) in signal peptides. We further show that polymorphisms with low minor allele frequency (MAF) are more likely to affect the function of the signal peptide. In conjunction with Sorting Intolerant From Tolerant (SIFT), a conservation-based amino acid substitution prediction method, our approach classifies such changes to signal peptides more accurately than other known alternatives, including D-score-based methods. We also examine experimentally characterized mutations and find that our metric minimizes false positives and can predict whether the mutation will affect cleavage or translocation. Finally, we apply our approach to a set of recently produced large-scale cancer somatic mutations from colon and breast cancers and generate a prioritized list of mutations in signal peptides that might impair protein function.

The genomic landscapes of human breast and colorectal cancers

Human cancer is caused by the accumulation of mutations in oncogenes and tumor suppressor genes. To catalog the genetic changes that occur during tumorigenesis, we isolated DNA from 11 breast and 11 colorectal tumors and determined the sequences of the genes in the Reference Sequence database in these samples. Based on analysis of exons representing 20,857 transcripts from 18,191 genes, we conclude that the genomic landscapes of breast and colorectal cancers are composed of a handful of commonly mutated gene "mountains" and a much larger number of gene "hills" that are mutated at low frequency. We describe statistical and bioinformatic tools that may help identify mutations with a role in tumorigenesis. These results have implications for understanding the nature and heterogeneity of human cancers and for using personal genomics for tumor diagnosis and therapy.

CanPredict: a computational tool for predicting cancer-associated missense mutations

Various cancer genome projects are underway to identify novel mutations that drive tumorigenesis. While these screens will generate large data sets, the majority of identified missense changes are likely to be innocuous passenger mutations or polymorphisms. As a result, it has become increasingly important to develop computational methods for distinguishing functionally relevant mutations from other variations. We previously developed an algorithm, and now present the web application, CanPredict (http://www.canpredict.org/ or http://www.cgl.ucsf.edu/Research/genentech/canpredict/), to allow users to determine if particular changes are likely to be cancer-associated. The impact of each change is measured using two known methods: Sorting Intolerant From Tolerant (SIFT) and the Pfam-based LogR.E-value metric. A third method, the Gene Ontology Similarity Score (GOSS), provides an indication of how closely the gene in which the variant resides resembles other known cancer-causing genes. Scores from these three algorithms are analyzed by a random forest classifier which then predicts whether a change is likely to be cancer-associated. CanPredict fills an important need in cancer biology and will enable a large audience of biologists to determine which mutations are the most relevant for further study.

Distinguishing cancer-associated missense mutations from common polymorphisms

Missense variants are commonly identified in genomic sequence but only a small fraction directly contribute to oncogenesis. The ability to distinguish those missense changes that contribute to cancer progression from those that do not is a difficult problem usually only accomplished through functional in vivo analyses. Using two computational algorithms, Sorting Intolerant from Tolerant (SIFT) and the Pfam-based LogR.E-value method, we have identified features that distinguish cancer-associated missense mutations from other classes of missense change. Our data reveal that cancer mutants behave similarly to Mendelian disease mutations, but are clearly distinct from either complex disease mutations or common single-nucleotide polymorphisms. We show that both activating and inactivating oncogenic mutations are predicted to be deleterious, although activating changes are likely to increase protein activity. Using the Gene Ontology and data from the SIFT and LogR.E-value metrics, a classifier was built that predicts cancer-associated missense mutations with a very low false-positive rate. The classifier does remarkably well in a number of different experiments designed to distinguish polymorphisms from true cancer-associated mutations. We also show that recurrently observed mutations are much more likely to be predicted to be cancer-associated than rare mutations, suggesting that our classifier will be useful in distinguishing causal from passenger mutations. In addition, from an expressed sequence tag-based screen, we identified a previously unknown germ line change (P1104A) in tumor tissues that is predicted to disrupt the function of the TYK2 protein. The data presented here show that this novel bioinformatics approach to classifying cancer-associated variants is robust and can be used for large-scale analyses.

Control of photoreceptor axon target choice by transcriptional repression of Runt

Drosophila photoreceptor neurons (R cells) project their axons to one of two layers in the optic lobe, the lamina or the medulla. The transcription factor Runt (Run) is normally expressed in the two inner R cells (R7 and R8) that project their axons to the medulla. Here we examine the relationship between Run and the ubiquitously expressed nuclear protein Brakeless (Bks), which has previously been shown to be important for axon termination in the lamina. We report that Bks represses Run in two of the outer R cells: R2 and R5. Expression of Run in R2 and R5 causes axonal mistargeting of all six outer R cells (R1-R6) to the inappropriate layer, without altering expression of cell-specific developmental markers.

Heterochromatic sequences in a Drosophila whole-genome shotgun assembly

BACKGROUND

Most eukaryotic genomes include a substantial repeat-rich fraction termed heterochromatin, which is concentrated in centric and telomeric regions. The repetitive nature of heterochromatic sequence makes it difficult to assemble and analyze. To better understand the heterochromatic component of the Drosophila melanogaster genome, we characterized and annotated portions of a whole-genome shotgun sequence assembly.

RESULTS

WGS3, an improved whole-genome shotgun assembly, includes 20.7 Mb of draft-quality sequence not represented in the Release 3 sequence spanning the euchromatin. We annotated this sequence using the methods employed in the re-annotation of the Release 3 euchromatic sequence. This analysis predicted 297 protein-coding genes and six non-protein-coding genes, including known heterochromatic genes, and regions of similarity to known transposable elements. Bacterial artificial chromosome (BAC)-based fluorescence in situ hybridization analysis was used to correlate the genomic sequence with the cytogenetic map in order to refine the genomic definition of the centric heterochromatin; on the basis of our cytological definition, the annotated Release 3 euchromatic sequence extends into the centric heterochromatin on each chromosome arm.

CONCLUSIONS

Whole-genome shotgun assembly produced a reliable draft-quality sequence of a significant part of the Drosophila heterochromatin. Annotation of this sequence defined the intron-exon structures of 30 known protein-coding genes and 267 protein-coding gene models. The cytogenetic mapping suggests that an additional 150 predicted genes are located in heterochromatin at the base of the Release 3 euchromatic sequence. Our analysis suggests strategies for improving the sequence and annotation of the heterochromatic portions of the Drosophila and other complex genomes.

An integrated computational pipeline and database to support whole-genome sequence annotation

We describe here our experience in annotating the Drosophila melanogaster genome sequence, in the course of which we developed several new open-source software tools and a database schema to support large-scale genome annotation. We have developed these into an integrated and reusable software system for whole-genome annotation. The key contributions to overall annotation quality are the marshalling of high-quality sequences for alignments and the design of a system with an adaptable and expandable flexible architecture.

Apollo: a sequence annotation editor

The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them. FlyBase biologists successfully used Apollo to annotate the Drosophila melanogaster genome and it is increasingly being used as a starting point for the development of customized annotation editing tools for other genome projects.

The transposable elements of the Drosophila melanogaster euchromatin: a genomics perspective

BACKGROUND

Transposable elements are found in the genomes of nearly all eukaryotes. The recent completion of the Release 3 euchromatic genomic sequence of Drosophila melanogaster by the Berkeley Drosophila Genome Project has provided precise sequence for the repetitive elements in the Drosophila euchromatin. We have used this genomic sequence to describe the euchromatic transposable elements in the sequenced strain of this species.

RESULTS

We identified 85 known and eight novel families of transposable element varying in copy number from one to 146. A total of 1,572 full and partial transposable elements were identified, comprising 3.86% of the sequence. More than two-thirds of the transposable elements are partial. The density of transposable elements increases an average of 4.7 times in the centromere-proximal regions of each of the major chromosome arms. We found that transposable elements are preferentially found outside genes; only 436 of 1,572 transposable elements are contained within the 61.4 Mb of sequence that is annotated as being transcribed. A large proportion of transposable elements is found nested within other elements of the same or different classes. Lastly, an analysis of structural variation from different families reveals distinct patterns of deletion for elements belonging to different classes.

CONCLUSIONS

This analysis represents an initial characterization of the transposable elements in the Release 3 euchromatic genomic sequence of D. melanogaster for which comparison to the transposable elements of other organisms can begin to be made. These data have been made available on the Berkeley Drosophila Genome Project website for future analyses.

Annotation of the Drosophila melanogaster euchromatic genome: a systematic review

BACKGROUND

The recent completion of the Drosophila melanogaster genomic sequence to high quality and the availability of a greatly expanded set of Drosophila cDNA sequences, aligning to 78% of the predicted euchromatic genes, afforded FlyBase the opportunity to significantly improve genomic annotations. We made the annotation process more rigorous by inspecting each gene visually, utilizing a comprehensive set of curation rules, requiring traceable evidence for each gene model, and comparing each predicted peptide to SWISS-PROT and TrEMBL sequences.

RESULTS

Although the number of predicted protein-coding genes in Drosophila remains essentially unchanged, the revised annotation significantly improves gene models, resulting in structural changes to 85% of the transcripts and 45% of the predicted proteins. We annotated transposable elements and non-protein-coding RNAs as new features, and extended the annotation of untranslated (UTR) sequences and alternative transcripts to include more than 70% and 20% of genes, respectively. Finally, cDNA sequence provided evidence for dicistronic transcripts, neighboring genes with overlapping UTRs on the same DNA sequence strand, alternatively spliced genes that encode distinct, non-overlapping peptides, and numerous nested genes.

CONCLUSIONS

Identification of so many unusual gene models not only suggests that some mechanisms for gene regulation are more prevalent than previously believed, but also underscores the complex challenges of eukaryotic gene prediction. At present, experimental data and human curation remain essential to generate high-quality genome annotations.

Redundant function of Runt Domain binding partners, Big brother and Brother, during Drosophila development

The Core Binding Factor is a heterodimeric transcription factor complex in vertebrates that is composed of a DNA binding α-subunit and a non-DNA binding β-subunit. The α-subunit is encoded by members of the Runt Domain family of proteins and the β-subunit is encoded by the CBFβ gene. In Drosophila, two genes encoding α-subunits, runt and lozenge, and two genes encoding β-subunits, Big brother and Brother, have been previously identified. Here, a sensitized genetic screen was used to isolate mutant alleles of the Big brother gene. Expression studies show that Big brother is a nuclear protein that co-localizes with both Lozenge and Runt in the eye imaginal disc. The nuclear localization and stability of Big brother protein is mediated through the formation of heterodimeric complexes between Big brother and either Lozenge or Runt. Big brother functions with Lozenge during cell fate specification in the eye, and is also required for the development of the embryonic PNS. ds-RNA-mediated genetic interference experiments show that Brother and Big brother are redundant and function together with Runt during segmentation of the embryo. These studies highlight a mechanism for transcriptional control by a Runt Domain protein and a redundant pair of partners in the specification of cell fate during development.