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Myelination of neuronal axons is essential for nervous system development. Myelination requires dramatic cytoskeletal dynamics in oligodendrocytes, but how actin is regulated during myelination is poorly understood. We recently identified serum response factor (SRF)-a transcription factor known to regulate expression of actin and actin regulators in other cell types-as a critical driver of myelination in the aged brain. Yet, a major gap remains in understanding the mechanistic role of SRF in oligodendrocyte lineage cells. Here, we show that SRF is required cell autonomously in oligodendrocytes for myelination during development. Combining ChIP-seq with RNA-seq identifies SRF-target genes in oligodendrocyte precursor cells and oligodendrocytes that include actin and other key cytoskeletal genes. Accordingly, SRF knockout oligodendrocytes exhibit dramatically reduced actin filament levels early in differentiation, consistent with its role in actin-dependent myelin sheath initiation. Surprisingly, oligodendrocyte-restricted loss of SRF results in upregulation of gene signatures associated with aging and neurodegenerative diseases. Together, our findings identify SRF as a transcriptional regulator that controls the expression of cytoskeletal genes required in oligodendrocytes for myelination. This study identifies an essential pathway regulating oligodendrocyte biology with high relevance to brain development, aging, and disease.

BackgroundInfection by coronavirus SARS-CoV2 is a severe and often deadly disease that has implications for the respiratory system and multiple organs across the human body. While the effects in the lung have been extensively studied, less is known about the impact COVID-19 has across other organs.MethodsHere, we contribute a single-nuclei RNA-sequencing atlas comprising six human organs across 20 autopsies where we analyzed the transcriptional changes due to COVID-19 in multiple cell types. The integration of data from multiple organs enabled the identification of systemic transcriptional changes.ResultsComputational cross-organ analysis for endothelial cells and macrophages identified systemic transcriptional changes in these cell types in COVID-19 samples. In addition, analysis of gene modules showed enrichment of specific signaling pathways across multiple organs in COVID-19 autopsies.ConclusionsAltogether, the COVID Tissue Atlas enables the investigation of both cell type-specific and cross-organ transcriptional responses to COVID-19, providing insights into the molecular networks affected by the disease and highlighting novel potential targets for therapies and drug development.FundingThe Chan-Zuckerberg Initiative, The Chan-Zuckerberg Biohub.

Recent understanding of how the systemic environment shapes the brain throughout life has led to numerous intervention strategies to slow brain ageing1-3. Cerebrospinal fluid (CSF) makes up the immediate environment of brain cells, providing them with nourishing compounds4,5. We discovered that infusing young CSF directly into aged brains improves memory function. Unbiased transcriptome analysis of the hippocampus identified oligodendrocytes to be most responsive to this rejuvenated CSF environment. We further showed that young CSF boosts oligodendrocyte progenitor cell (OPC) proliferation and differentiation in the aged hippocampus and in primary OPC cultures. Using SLAMseq to metabolically label nascent mRNA, we identified serum response factor (SRF), a transcription factor that drives actin cytoskeleton rearrangement, as a mediator of OPC proliferation following exposure to young CSF. With age, SRF expression decreases in hippocampal OPCs, and the pathway is induced by acute injection with young CSF. We screened for potential SRF activators in CSF and found that fibroblast growth factor 17 (Fgf17) infusion is sufficient to induce OPC proliferation and long-term memory consolidation in aged mice while Fgf17 blockade impairs cognition in young mice. These findings demonstrate the rejuvenating power of young CSF and identify Fgf17 as a key target to restore oligodendrocyte function in the ageing brain.

The human brain vasculature is of great medical importance: its dysfunction causes disability and death1, and the specialized structure it forms-the blood-brain barrier-impedes the treatment of nearly all brain disorders2,3. Yet so far, we have no molecular map of the human brain vasculature. Here we develop vessel isolation and nuclei extraction for sequencing (VINE-seq) to profile the major vascular and perivascular cell types of the human brain through 143,793 single-nucleus transcriptomes from 25 hippocampus and cortex samples of 9 individuals with Alzheimer's disease and 8 individuals with no cognitive impairment. We identify brain-region- and species-enriched genes and pathways. We reveal molecular principles of human arteriovenous organization, recapitulating a gradual endothelial and punctuated mural cell continuum. We discover two subtypes of human pericytes, marked by solute transport and extracellular matrix (ECM) organization; and define perivascular versus meningeal fibroblast specialization. In Alzheimer's disease, we observe selective vulnerability of ECM-maintaining pericytes and gene expression patterns that implicate dysregulated blood flow. With an expanded survey of brain cell types, we find that 30 of the top 45 genes that have been linked to Alzheimer's disease risk by genome-wide association studies (GWASs) are expressed in the human brain vasculature, and we confirm this by immunostaining. Vascular GWAS genes map to endothelial protein transport, adaptive immune and ECM pathways. Many are microglia-specific in mice, suggesting a partial evolutionary transfer of Alzheimer's disease risk. Our work uncovers the molecular basis of the human brain vasculature, which will inform our understanding of overall brain health, disease and therapy.

The ability to slow or reverse biological ageing would have major implications for mitigating disease risk and maintaining vitality1. Although an increasing number of interventions show promise for rejuvenation2, their effectiveness on disparate cell types across the body and the molecular pathways susceptible to rejuvenation remain largely unexplored. Here we performed single-cell RNA sequencing on 20 organs to reveal cell-type-specific responses to young and aged blood in heterochronic parabiosis. Adipose mesenchymal stromal cells, haematopoietic stem cells and hepatocytes are among those cell types that are especially responsive. On the pathway level, young blood invokes new gene sets in addition to reversing established ageing patterns, with the global rescue of genes encoding electron transport chain subunits pinpointing a prominent role of mitochondrial function in parabiosis-mediated rejuvenation. We observed an almost universal loss of gene expression with age that is largely mimicked by parabiosis: aged blood reduces global gene expression, and young blood restores it in select cell types. Together, these data lay the groundwork for a systemic understanding of the interplay between blood-borne factors and cellular integrity.

Recent studies indicate that the adaptive immune system plays a role in Lewy body dementia (LBD). However, the mechanism regulating T cell brain homing in LBD is unknown. Here, we observed T cells adjacent to Lewy bodies and dopaminergic neurons in postmortem LBD brains. Single-cell RNA sequencing of cerebrospinal fluid (CSF) identified up-regulated expression of C-X-C motif chemokine receptor 4 (CXCR4) in CD4+ T cells in LBD. CSF protein levels of the CXCR4 ligand, C-X-C motif chemokine ligand 12 (CXCL12), were associated with neuroaxonal damage in LBD. Furthermore, we observed clonal expansion and up-regulated interleukin 17A expression by CD4+ T cells stimulated with a phosphorylated α-synuclein epitope. Thus, CXCR4-CXCL12 signaling may represent a mechanistic target for inhibiting pathological interleukin-17–producing T cell trafficking in LBD.

Although SARS-CoV-2 primarily targets the respiratory system, patients with and survivors of COVID-19 can suffer neurological symptoms1-3. However, an unbiased understanding of the cellular and molecular processes that are affected in the brains of patients with COVID-19 is missing. Here we profile 65,309 single-nucleus transcriptomes from 30 frontal cortex and choroid plexus samples across 14 control individuals (including 1 patient with terminal influenza) and 8 patients with COVID-19. Although our systematic analysis yields no molecular traces of SARS-CoV-2 in the brain, we observe broad cellular perturbations indicating that barrier cells of the choroid plexus sense and relay peripheral inflammation into the brain and show that peripheral T cells infiltrate the parenchyma. We discover microglia and astrocyte subpopulations associated with COVID-19 that share features with pathological cell states that have previously been reported in human neurodegenerative disease4-6. Synaptic signalling of upper-layer excitatory neurons-which are evolutionarily expanded in humans7 and linked to cognitive function8-is preferentially affected in COVID-19. Across cell types, perturbations associated with COVID-19 overlap with those found in chronic brain disorders and reside in genetic variants associated with cognition, schizophrenia and depression. Our findings and public dataset provide a molecular framework to understand current observations of COVID-19-related neurological disease, and any such disease that may emerge at a later date.

Abstract Background Human perception of the odour environment is highly variable. People vary both in their general olfactory acuity as well as in if and how they perceive specific odours. In recent years, it has been shown that genetic differences contribute to variability in both general olfactory acuity and the perception of specific odours. Odour perception also depends on other factors such as age and gender. Here we investigate the influence of these factors on both general olfactory acuity and on the perception of 66 structurally and perceptually different odours in a diverse subject population. Results We carried out a large human olfactory psychophysics study of 391 adult subjects in metropolitan New York City, an ethnically and culturally diverse North American metropolis. 210 of the subjects were women and the median age was 34.6 years (range 19–75). We recorded ~2,300 data points per subject to obtain a comprehensive perceptual phenotype, comprising multiple perceptual measures of 66 diverse odours. We show that general olfactory acuity correlates with gender, age, race, smoking habits, and body type. Young, female, non-smoking subjects had the highest average olfactory acuity. Deviations from normal body type in either direction were associated with decreased olfactory acuity. Beyond these factors we also show that, surprisingly, there are many odour-specific influences of race, age, and gender on olfactory perception. We show over 100 instances in which the intensity or pleasantness perception of an odour is significantly different between two demographic groups. Conclusions These data provide a comprehensive snapshot of the olfactory sense of a diverse population. Olfactory acuity in the population is most strongly influenced by age, followed by gender. We also show a large number of diverse correlations between demographic factors and the perception of individual odours that may reflect genetic differences as well as different prior experiences with these odours between demographic groups.

Abstract Chemosensory receptor genes encode G protein-coupled receptors with which animals sense their chemical environment. The large number of chemosensory receptor genes in the genome and their extreme genetic variability pose unusual challenges for understanding their evolution and function. Two articles in BMC Genomics explore the genetic variation of chemosensory receptor gene repertoires in humans and mice and provide unparalleled insight into the causes and consequences of this variability. See research articles http://www.biomedcentral.com/1471-2164/13/414 and http://www.biomedcentral.com/1471-2164/13/415

Abstract Background Compared to classical genotyping, targeted next-generation sequencing (tNGS) can be custom-designed to interrogate entire genomic regions of interest, in order to detect novel as well as known variants. To bring down the per-sample cost, one approach is to pool barcoded NGS libraries before sample enrichment. Still, we lack a complete understanding of how this multiplexed tNGS approach and the varying performance of the ever-evolving analytical tools can affect the quality of variant discovery. Therefore, we evaluated the impact of different software tools and analytical approaches on the discovery of single nucleotide polymorphisms (SNPs) in multiplexed tNGS data. To generate our own test model, we combined a sequence capture method with NGS in three experimental stages of increasing complexity (E. coli genes, multiplexed E. coli, and multiplexed HapMap BRCA1/2 regions). Results We successfully enriched barcoded NGS libraries instead of genomic DNA, achieving reproducible coverage profiles (Pearson correlation coefficients of up to 0.99) across multiplexed samples, with Conclusions We recommend applying our general ‘two-step’ mapping approach for more efficient SNP discovery in tNGS. Our study has also shown the benefit of computing inter-sample SNP-concordances and inspecting read alignments in order to attain more confident results.

Abstract Background Blood-born miRNA signatures have recently been reported for various tumor diseases. Here, we compared the miRNA signature in Wilms tumor patients prior and after preoperative chemotherapy according to SIOP protocol 2001. Results We did not find a significant difference between miRNA signature of both groups. However both, Wilms tumor patients prior and after chemotherapy showed a miRNA signature different from healthy controls. The signature of Wilms tumor patients prior to chemotherapy showed an accuracy of 97.5% and of patients after chemotherapy an accuracy of 97.0%, each as compared to healthy controls. Conclusion Our results provide evidence for a blood-born Wilms tumor miRNA signature largely independent of four weeks preoperative chemotherapy treatment.

Abstract Background Expression profiling provides new insights into regulatory and metabolic processes and in particular into pathogenic mechanisms associated with diseases. Besides genes, non-coding transcripts as microRNAs (miRNAs) gained increasing relevance in the last decade. To understand the regulatory processes of miRNAs on genes, integrative computer-aided approaches are essential, especially in the light of complex human diseases as cancer. Results Here, we present miRTrail, an integrative tool that allows for performing comprehensive analyses of interactions of genes and miRNAs based on expression profiles. The integrated analysis of mRNA and miRNA data should generate more robust and reliable results on deregulated pathogenic processes and may also offer novel insights into the regulatory interactions between miRNAs and genes. Our web-server excels in carrying out gene sets analysis, analysis of miRNA sets as well as the combination of both in a systems biology approach. To this end, miRTrail integrates information on 20.000 genes, almost 1.000 miRNAs, and roughly 280.000 putative interactions, for Homo sapiens and accordingly for Mus musculus and Danio rerio. The well-established, classical Chi-squared test is one of the central techniques of our tool for the joint consideration of miRNAs and their targets. For interactively visualizing obtained results, it relies on the network analyzers and viewers BiNA or Cytoscape-web, also enabling direct access to relevant literature. We demonstrated the potential of miRTrail by applying our tool to mRNA and miRNA data of malignant melanoma. MiRTrail identified several deregulated miRNAs that target deregulated mRNAs including miRNAs hsa-miR-23b and hsa-miR-223, which target the highest numbers of deregulated mRNAs and regulate the pathway "basal cell carcinoma". In addition, both miRNAs target genes like PTCH1 and RASA1 that are involved in many oncogenic processes. Conclusions The application on melanoma samples demonstrates that the miRTrail platform may open avenues for investigating the regulatory interactions between genes and miRNAs for a wide range of human diseases. Moreover, miRTrail cannot only be applied to microarray based expression profiles, but also to NGS-based transcriptomic data. The program is freely available as web-server at mirtrail.bioinf.uni-sb.de.

Abstract Background Autoantibodies against self-antigens have been associated not only with autoimmune diseases, but also with cancer and are even found in healthy individuals. The mechanism causing the autoantibody response remains elusive for the majority of the immunogenic antigens. To deepen the understanding of autoantibody responses, we ask whether natural-occurring, autoimmunity-associated and tumor-associated antigens have structural or biological features related to the immune response. To this end, we have carried out the most comprehensive in-silicio study of different groups of autoantigens including large antigen sets identified by our groups combined with publicly available antigen sets. Results We found evidence for an enrichment of genes with a larger exon length increasing the probability of the occurrence of potential immunogenic features such as mutations, SNPs, immunogenic sequence patterns and structural epitopes, or alternative splicing events. While SNPs seem to play a more central role in autoimmunity, somatic mutations seem to be stronger enriched in tumor-associated antigens. In addition, antigens of autoimmune diseases are different from other antigen sets in that they appear preferentially secreted, have frequently an extracellular location, and they are enriched in pathways associated with the immune system. Furthermore, for autoantibodies in general, we found enrichment of sequence-based properties including coiled-coils motifs, ELR motifs, and Zinc finger DNA-binding motifs. Moreover, we found enrichment of proteins binding to proteins or nucleic acids including RNA and enrichment of proteins that are part of ribosome or spliceosome. Both, homologies to proteins of other species and an enrichment of ancient protein domains indicate that immunogenic proteins are evolutionary conserved and that mimicry might play a central role. Conclusions Our results provide evidence that proteins which i) are evolutionary conserved, ii) show specific sequence motifs, and iii) are part of cellular structures show an increased likelihood to become autoimmunogenic.

Abstract Background High-throughput technologies have opened new avenues to study biological processes and pathways. The interpretation of the immense amount of data sets generated nowadays needs to be facilitated in order to enable biologists to identify complex gene networks and functional pathways. To cope with this task multiple computer-based programs have been developed. GeneTrail is a freely available online tool that screens comparative transcriptomic data for differentially regulated functional categories and biological pathways extracted from common data bases like KEGG, Gene Ontology (GO), TRANSPATH and TRANSFAC. Additionally, GeneTrail offers a feature that allows screening of individually defined biological categories that are relevant for the respective research topic. Results We have set up GeneTrail for the use of Arabidopsis thaliana. To test the functionality of this tool for plant analysis, we generated transcriptome data of root and leaf responses to Fe deficiency and the Arabidopsis metal homeostasis mutant nas4x-1. We performed Gene Set Enrichment Analysis (GSEA) with eight meaningful pairwise comparisons of transcriptome data sets. We were able to uncover several functional pathways including metal homeostasis that were affected in our experimental situations. Representation of the differentially regulated functional categories in Venn diagrams uncovered regulatory networks at the level of whole functional pathways. Over-Representation Analysis (ORA) of differentially regulated genes identified in pairwise comparisons revealed specific functional plant physiological categories as major targets upon Fe deficiency and in nas4x-1. Conclusion Here, we obtained supporting evidence, that the nas4x-1 mutant was defective in metal homeostasis. It was confirmed that nas4x-1 showed Fe deficiency in roots and signs of Fe deficiency and Fe sufficiency in leaves. Besides metal homeostasis, biotic stress, root carbohydrate, leaf photosystem and specific cell biological categories were discovered as main targets for regulated changes in response to - Fe and nas4x-1. Among 258 differentially expressed genes in response to - Fe and nas4x-1 five functional categories were enriched covering metal homeostasis, redox regulation, cell division and histone acetylation. We proved that GeneTrail offers a flexible and user-adapted way to identify functional categories in large-scale plant transcriptome data sets. The distinguished feature that allowed analysis of individually assembled functional categories facilitated the study of the Arabidopsis thaliana transcriptome.

Abstract Background MicroRNA (miRNA) signatures are not only found in cancer tissue but also in blood of cancer patients. Specifically, miRNA detection in blood offers the prospect of a non-invasive analysis tool. Methods Using a microarray based approach we screened almost 900 human miRNAs to detect miRNAs that are deregulated in their expression in blood cells of melanoma patients. We analyzed 55 blood samples, including 20 samples of healthy individuals, 24 samples of melanoma patients as test set, and 11 samples of melanoma patients as independent validation set. Results A hypothesis test based approch detected 51 differentially regulated miRNAs, including 21 miRNAs that were downregulated in blood cells of melanoma patients and 30 miRNAs that were upregulated in blood cells of melanoma patients as compared to blood cells of healthy controls. The tets set and the independent validation set of the melanoma samples showed a high correlation of fold changes (0.81). Applying hierarchical clustering and principal component analysis we found that blood samples of melanoma patients and healthy individuals can be well differentiated from each other based on miRNA expression analysis. Using a subset of 16 significant deregulated miRNAs, we were able to reach a classification accuracy of 97.4%, a specificity of 95% and a sensitivity of 98.9% by supervised analysis. MiRNA microarray data were validated by qRT-PCR. Conclusions Our study provides strong evidence for miRNA expression signatures of blood cells as useful biomarkers for melanoma.

Abstract Background While more than 700 microRNAs (miRNAs) are known in human, a comparably low number has been identified in swine. Because of the close phylogenetic distance to humans, pigs serve as a suitable model for studying e.g. intestinal development or disease. Recent studies indicate that miRNAs are key regulators of intestinal development and their aberrant expression leads to intestinal malignancy. Results Here, we present the identification of hundreds of apparently novel miRNAs in the porcine intestine. MiRNAs were first identified by means of deep sequencing followed by miRNA precursor prediction using the miRDeep algorithm as well as searching for conserved miRNAs. Second, the porcine miRNAome along the entire intestine (duodenum, proximal and distal jejunum, ileum, ascending and transverse colon) was unraveled using customized miRNA microarrays based on the identified sequences as well as known porcine and human ones. In total, the expression of 332 intestinal miRNAs was discovered, of which 201 represented assumed novel porcine miRNAs. The identified hairpin forming precursors were in part organized in genomic clusters, and most of the precursors were located on chromosomes 3 and 1, respectively. Hierarchical clustering of the expression data revealed subsets of miRNAs that are specific to distinct parts of the intestine pointing to their impact on cellular signaling networks. Conclusions In this study, we have applied a straight forward approach to decipher the porcine intestinal miRNAome for the first time in mammals using a piglet model. The high number of identified novel miRNAs in the porcine intestine points out their crucial role in intestinal function as shown by pathway analysis. On the other hand, the reported miRNAs may share orthologs in other mammals such as human still to be discovered.

Abstract Background Lung cancer is a very frequent and lethal tumor with an identifiable risk population. Cytological analysis and chest X-ray failed to reduce mortality, and CT screenings are still controversially discussed. Recent studies provided first evidence for the potential usefulness of autoantigens as markers for lung cancer. Methods We used extended panels of arrayed antigens and determined autoantibody signatures of sera from patients with different kinds of lung cancer, different common non-tumor lung pathologies, and controls without any lung disease by a newly developed computer aided image analysis procedure. The resulting signatures were classified using linear kernel Support Vector Machines and 10-fold cross-validation. Results The novel approach allowed for discriminating lung cancer patients from controls without any lung disease with a specificity of 97.0%, a sensitivity of 97.9%, and an accuracy of 97.6%. The classification of stage IA/IB tumors and controls yielded a specificity of 97.6%, a sensitivity of 75.9%, and an accuracy of 92.9%. The discrimination of lung cancer patients from patients with non-tumor lung pathologies reached an accuracy of 88.5%. Conclusion We were able to separate lung cancer patients from subjects without any lung disease with high accuracy. Furthermore, lung cancer patients could be seprated from patients with other non-tumor lung diseases. These results provide clear evidence that blood-based tests open new avenues for the early diagnosis of lung cancer.

Abstract Background Deregulated miRNAs are found in cancer cells and recently in blood cells of cancer patients. Due to their inherent stability miRNAs may offer themselves for blood based tumor diagnosis. Here we addressed the question whether there is a sufficient number of miRNAs deregulated in blood cells of cancer patients to be able to distinguish between cancer patients and controls. Methods We synthesized 866 human miRNAs and miRNA star sequences as annotated in the Sanger miRBase onto a microarray designed by febit biomed gmbh. Using the fully automated Geniom Real Time Analyzer platform, we analyzed the miRNA expression in 17 blood cell samples of patients with non-small cell lung carcinomas (NSCLC) and in 19 blood samples of healthy controls. Results Using t-test, we detected 27 miRNAs significantly deregulated in blood cells of lung cancer patients as compared to the controls. Some of these miRNAs were validated using qRT-PCR. To estimate the value of each deregulated miRNA, we grouped all miRNAs according to their diagnostic information that was measured by Mutual Information. Using a subset of 24 miRNAs, a radial basis function Support Vector Machine allowed for discriminating between blood cellsamples of tumor patients and controls with an accuracy of 95.4% [94.9%-95.9%], a specificity of 98.1% [97.3%-98.8%], and a sensitivity of 92.5% [91.8%-92.5%]. Conclusion Our findings support the idea that neoplasia may lead to a deregulation of miRNA expression in blood cells of cancer patients compared to blood cells of healthy individuals. Furthermore, we provide evidence that miRNA patterns can be used to detect human cancers from blood cells.

Abstract Background Chronic obstructive pulmonary disease (COPD) is a respiratory inflammatory condition with autoimmune features including IgG autoantibodies. In this study we analyze the complexity of the autoantibody response and reveal the nature of the antigens that are recognized by autoantibodies in COPD patients. Methods An array of 1827 gridded immunogenic peptide clones was established and screened with 17 sera of COPD patients and 60 healthy controls. Protein arrays were evaluated both by visual inspection and a recently developed computer aided image analysis technique. By this computer aided image analysis technique we computed the intensity values for each peptide clone and each serum and calculated the area under the receiver operator characteristics curve (AUC) for each clone and the separation COPD sera versus control sera. Results By visual evaluation we detected 381 peptide clones that reacted with autoantibodies of COPD patients including 17 clones that reacted with more than 60% of the COPD sera and seven clones that reacted with more than 90% of the COPD sera. The comparison of COPD sera and controls by the automated image analysis system identified 212 peptide clones with informative AUC values. By in silico sequence analysis we found an enrichment of sequence motives previously associated with immunogenicity. Conclusion The identification of a rather complex humoral immune response in COPD patients supports the idea of COPD as a disease with strong autoimmune features. The identification of novel immunogenic antigens is a first step towards a better understanding of the autoimmune component of COPD.

Abstract Background High-throughput methods that allow for measuring the expression of thousands of genes or proteins simultaneously have opened new avenues for studying biochemical processes. While the noisiness of the data necessitates an extensive pre-processing of the raw data, the high dimensionality requires effective statistical analysis methods that facilitate the identification of crucial biological features and relations. For these reasons, the evaluation and interpretation of expression data is a complex, labor-intensive multi-step process. While a variety of tools for normalizing, analysing, or visualizing expression profiles has been developed in the last years, most of these tools offer only functionality for accomplishing certain steps of the evaluation pipeline. Results Here, we present a web-based toolbox that provides rich functionality for all steps of the evaluation pipeline. Our tool GeneTrailExpress offers besides standard normalization procedures powerful statistical analysis methods for studying a large variety of biological categories and pathways. Furthermore, an integrated graph visualization tool, BiNA, enables the user to draw the relevant biological pathways applying cutting-edge graph-layout algorithms. Conclusion Our gene expression toolbox with its interactive visualization of the pathways and the expression values projected onto the nodes will simplify the analysis and interpretation of biochemical pathways considerably.

Context guides perception by influencing stimulus saliency. Accordingly, in visual cortex, responses to a stimulus are modulated by context, the visual scene surrounding the stimulus. Responses are suppressed when stimulus and surround are similar but not when they differ. The underlying mechanisms remain unclear. Here, we use optical recordings, manipulations, and computational modeling to show that disinhibitory circuits consisting of vasoactive intestinal peptide (VIP)-expressing and somatostatin (SOM)-expressing inhibitory neurons modulate responses in mouse visual cortex depending on similarity between stimulus and surround, primarily by modulating recurrent excitation. When stimulus and surround are similar, VIP neurons are inactive, and activity of SOM neurons leads to suppression of excitatory neurons. However, when stimulus and surround differ, VIP neurons are active, inhibiting SOM neurons, which leads to relief of excitatory neurons from suppression. We have identified a canonical cortical disinhibitory circuit that contributes to contextual modulation and may regulate perceptual saliency.

Abstract Background Gene Set Enrichment Analysis (GSEA) is a computational method for the statistical evaluation of sorted lists of genes or proteins. Originally GSEA was developed for interpreting microarray gene expression data, but it can be applied to any sorted list of genes. Given the gene list and an arbitrary biological category, GSEA evaluates whether the genes of the considered category are randomly distributed or accumulated on top or bottom of the list. Usually, significance scores (p-values) of GSEA are computed by nonparametric permutation tests, a time consuming procedure that yields only estimates of the p-values. Results We present a novel dynamic programming algorithm for calculating exact significance values of unweighted Gene Set Enrichment Analyses. Our algorithm avoids typical problems of nonparametric permutation tests, as varying findings in different runs caused by the random sampling procedure. Another advantage of the presented dynamic programming algorithm is its runtime and memory efficiency. To test our algorithm, we applied it not only to simulated data sets, but additionally evaluated expression profiles of squamous cell lung cancer tissue and autologous unaffected tissue.

Abstract Background The development of effective frameworks that permit an accurate diagnosis of tumors, especially in their early stages, remains a grand challenge in the field of bioinformatics. Our approach uses statistical learning techniques applied to multiple antigen tumor antigen markers utilizing the immune system as a very sensitive marker of molecular pathological processes. For validation purposes we choose the intracranial meningioma tumors as model system since they occur very frequently, are mostly benign, and are genetically stable. Results A total of 183 blood samples from 93 meningioma patients (WHO stages I-III) and 90 healthy controls were screened for seroreactivity with a set of 57 meningioma-associated antigens. We tested several established statistical learning methods on the resulting reactivity patterns using 10-fold cross validation. The best performance was achieved by Naïve Bayes Classifiers. With this classification method, our framework, called Minimally Invasive Multiple Marker (MIMM) approach, yielded a specificity of 96.2%, a sensitivity of 84.5%, and an accuracy of 90.3%, the respective area under the ROC curve was 0.957. Detailed analysis revealed that prediction performs particularly well on low-grade (WHO I) tumors, consistent with our goal of early stage tumor detection. For these tumors the best classification result with a specificity of 97.5%, a sensitivity of 91.3%, an accuracy of 95.6%, and an area under the ROC curve of 0.971 was achieved using a set of 12 antigen markers only. This antigen set was detected by a subset selection method based on Mutual Information. Remarkably, our study proves that the inclusion of non-specific antigens, detected not only in tumor but also in normal sera, increases the performance significantly, since non-specific antigens contribute additional diagnostic information. Conclusion Our approach offers the possibility to screen members of risk groups as a matter of routine such that tumors hopefully can be diagnosed immediately after their genesis. The early detection will finally result in a higher cure- and lower morbidity-rate.

Ageing is characterized by a progressive loss of physiological integrity, leading to impaired function and increased vulnerability to death1. Despite rapid advances over recent years, many of the molecular and cellular processes that underlie the progressive loss of healthy physiology are poorly understood2. To gain a better insight into these processes, here we generate a single-cell transcriptomic atlas across the lifespan of Mus musculus that includes data from 23 tissues and organs. We found cell-specific changes occurring across multiple cell types and organs, as well as age-related changes in the cellular composition of different organs. Using single-cell transcriptomic data, we assessed cell-type-specific manifestations of different hallmarks of ageing-such as senescence3, genomic instability4 and changes in the immune system2. This transcriptomic atlas-which we denote Tabula Muris Senis, or 'Mouse Ageing Cell Atlas'-provides molecular information about how the most important hallmarks of ageing are reflected in a broad range of tissues and cell types.

Animals sense the environment through pathways that link sensory organs to the brain. In the visual system, these feedforward pathways define the classical feedforward receptive field (ffRF), the area in space in which visual stimuli excite a neuron1. The visual system also uses visual context-the visual scene surrounding a stimulus-to predict the content of the stimulus2, and accordingly, neurons have been identified that are excited by stimuli outside their ffRF3-8. However, the mechanisms that generate excitation to stimuli outside the ffRF are unclear. Here we show that feedback projections onto excitatory neurons in the mouse primary visual cortex generate a second receptive field that is driven by stimuli outside the ffRF. The stimulation of this feedback receptive field (fbRF) elicits responses that are slower and are delayed in comparison with those resulting from the stimulation of the ffRF. These responses are preferentially reduced by anaesthesia and by silencing higher visual areas. Feedback inputs from higher visual areas have scattered receptive fields relative to their putative targets in the primary visual cortex, which enables the generation of the fbRF. Neurons with fbRFs are located in cortical layers that receive strong feedback projections and are absent in the main input layer, which is consistent with a laminar processing hierarchy. The observation that large, uniform stimuli-which cover both the fbRF and the ffRF-suppress these responses indicates that the fbRF and the ffRF are mutually antagonistic. Whereas somatostatin-expressing inhibitory neurons are driven by these large stimuli, inhibitory neurons that express parvalbumin and vasoactive intestinal peptide have mutually antagonistic fbRF and ffRF, similar to excitatory neurons. Feedback projections may therefore enable neurons to use context to estimate information that is missing from the ffRF and to report differences in stimulus features across visual space, regardless of whether excitation occurs inside or outside the ffRF. By complementing the ffRF, the fbRF that we identify here could contribute to predictive processing.