Feasibility Study of a Low-Carbohydrate/Time-Restricted Eating Protocol for Insulin-Using Type 2 Diabetic Patients.

INTRODUCTION: Low-carbohydrate diets and time-restricted eating are methods to improve hemoglobin A1C in patients with type 2 diabetes. However, insulin-using patients are often counseled against these practices due to hypoglycemia concerns. This observational study evaluated a protocol utilizing both methods coupled with proactive insulin titration. OBJECTIVES: To evaluate the safety and feasibility of a timed eating protocol for insulin-using patients and to assess its impact on outcomes, including insulin use and hemoglobin A1C. METHODS: Participants included insulin-using adults ages 49 to 77 years with type 2 diabetes. They were counseled to eat 2 meals per day in a 6- to 8-hour window of their choosing, with a goal intake of ≤ 30 grams of carbohydrates per day. Glucose was closely monitored, and insulin was adjusted per study protocol. Primary outcomes included hypoglycemic events and compliance with timed eating. Insulin use, hemoglobin A1C, body mass index, blood pressure, and quality of life also were measured. RESULTS: Nineteen of the 20 participants completed the 6-month study. No hypoglycemic events requiring urgent medical care occurred. Symptomatic episodes with glucose between 47 and 80 mg/dl were reported by 37% (7/19) of participants. Average daily insulin use decreased by 62.2 U (P < 0.001) and insulin was discontinued for 14 participants. Average hemoglobin A1C remained unchanged. Average body mass index decreased by 4.0 (P = 0.01), systolic blood pressure decreased by 9.9 mm Hg (P = 0.02), and diabetes-related quality-of-life metrics improved significantly. CONCLUSIONS: These results demonstrate that a time-restricted eating protocol is feasible and safe for insulin-using patients with type 2 diabetes when paired with a proactive insulin titration.

Singularity and Commonality in Response to SARS-CoV-2 in Lung and Colon Cell Models.

The systemic nature of COVID-19 with multiple extrapulmonary manifestations of disease, largely due to the wide tissue expression of SARS-CoV-2 major entry factors, as well as the patient-specific features of COVID-19 pathobiology, determine important directions for basic and translational research. In the current study, we addressed the questions of singularities and commonalities in cellular responses to SARS-CoV-2 and related SARS-CoV on the basis of compendium-wide analysis of publicly available transcriptomic datasets as part of the herein implemented multi-modular UNCOVIDING approach. We focused on cellular models attributed to the epithelial cells of the respiratory system, the Calu-3 cell line, and epithelial cells of the gastrointestinal tract, the Caco-2 cell line, infected with either SARS-CoV-2 or SARS-CoV. Here, we report the outcome of a comparative analysis based on differentially expressed genes in terms of perturbations and diseases, Canonical pathways, and Upstream Regulators. We furthermore performed compendium-wide analysis across more than 19,000 mRNASeq datasets and dissected the condition-specific gene signatures. Information was gained with respect to common and unique cellular responses and molecular events. We identified that in cell lines of colon or lung origin, both viruses show similarities in cellular responses; by contrast, there are cell type-specific regulators that differed for Calu-3 and Caco-2 cells. Among the major findings is the impact of the interferon system for lung Calu-3 cells and novel links to the liver- and lipid-metabolism-associated responses for colon Caco-2 cells as part of the extrapulmonary pathomechanisms in the course of COVID-19. Among differently expressed genes, we specifically dissected the expression pattern of the APOBEC family members and propose APOBEC3G as a promising intrinsic antiviral factor of the host response to SARS-CoV-2. Overall, our study provides gene expression level evidence for the cellular responses attributed to pulmonary and gastrointestinal manifestations of COVID-19.

AID and APOBECs as Multifaceted Intrinsic Virus-Restricting Factors: Emerging Concepts in the Light of COVID-19.

The AID (activation-induced cytidine deaminase)/APOBEC (apolipoprotein B mRNA editing enzyme catalytic subunit) family with its multifaceted mode of action emerges as potent intrinsic host antiviral system that acts against a variety of DNA and RNA viruses including coronaviruses. All family members are cytosine-to-uracil deaminases that either have a profound role in driving a strong and specific humoral immune response (AID) or restricting the virus itself by a plethora of mechanisms (APOBECs). In this article, we highlight some of the key aspects apparently linking the AID/APOBECs and SARS-CoV-2. Among those is our discovery that APOBEC4 shows high expression in cell types and anatomical parts targeted by SARS-CoV-2. Additional focus is given by us to the lymphoid structures and AID as the master regulator of germinal center reactions, which result in antibody production by plasma and memory B cells. We propose the dissection of the AID/APOBECs gene signature towards decisive determinants of the patient-specific and/or the patient group-specific antiviral response. Finally, the patient-specific mapping of the AID/APOBEC polymorphisms should be considered in the light of COVID-19.

The Immune Phenotype of Isolated Lymphoid Structures in Non-Tumorous Colon Mucosa Encrypts the Information on Pathobiology of Metastatic Colorectal Cancer.

The gut-associated lymphoid tissue represents an integral part of the immune system. Among the powerful players of the mucosa-associated lymphoid tissue are isolated lymphoid structures (ILSs), which as information centers, drive the local (and systemic) adaptive immune responses. Germinal center reactions, taking place within ILSs, involve the coordinated action of various immune cell types with a central role given to B cells. In the current study, we aimed at dissecting the impact of ILSs within non-tumorous colon tissue (NT) on the pathobiology of colorectal cancer (CRC) with metastasis in the liver (CRCLM). In particular, we focused on the immune phenotypes of ILSs and ectopic lymphoid structures (ELSs), built up at matching primary and metastatic tumor sites. We implemented an integrative analysis strategy on the basis of tissue image cytometry and clonality assessment to explore the immune phenotype of ILS/ELS at three tissue entities: NT, CRC, and CRCLM (69 specimens in total). Applying a panel of lineage markers used for immunostaining, we characterized and compared the anatomical features, the cellular composition, the activation, and proliferation status of ILSs and ELSs, and assessed the clinical relevance of staining-derived data sets. Our major discovery was that ILS characteristics at the NT site predefine the immune phenotype of ELSs at CRC and CRCLM. Thereby, B-cell-enriched (CD20) and highly proliferative (Ki67) ILSs and ELSs were found to be associated with improved clinical outcome in terms of survival and enabled patient stratification into risk groups. Moreover, the data revealed a linkage between B-cell clonality at the NT site and the metastatic characteristics of the tumor in the distant liver tissue. Consolidation of immunostaining-based findings with the results of compendium-wide transcriptomic analysis furthermore proposed CD27 as a novel marker of T follicular helper cells within lymphoid structures. Overall, the study nominates the ILS immune phenotype as a novel prognostic marker for patients with metastatic CRC.

Interrelations of Sphingolipid and Lysophosphatidate Signaling with Immune System in Ovarian Cancer.

The sphingolipid and lysophosphatidate regulatory networks impact diverse mechanisms attributed to cancer cells and the tumor immune microenvironment. Deciphering the complexity demands implementation of a holistic approach combined with higher-resolution techniques. We implemented a multi-modular integrative approach consolidating the latest accomplishments in gene expression profiling, prognostic/predictive modeling, next generation digital pathology, and systems biology for epithelial ovarian cancer. We assessed patient-specific transcriptional profiles using the sphingolipid/lysophosphatidate/immune-associated signature. This revealed novel sphingolipid/lysophosphatidate-immune gene-gene associations and distinguished tumor subtypes with immune high/low context. These were characterized by robust differences in sphingolipid-/lysophosphatidate-related checkpoints and the drug response. The analysis also nominates novel survival models for stratification of patients with CD68, LPAR3, SMPD1, PPAP2B, and SMPD2 emerging as the most prognostically important genes. Alignment of proprietary data with curated transcriptomic data from public databases across a variety of malignancies (over 600 categories; over 21,000 arrays) showed specificity for ovarian carcinoma. Our systems approach identified novel sphingolipid-lysophosphatidate-immune checkpoints and networks underlying tumor immune heterogeneity and disease outcomes. This holds great promise for delivering novel stratifying and targeting strategies.

AID/APOBEC-network reconstruction identifies pathways associated with survival in ovarian cancer.

BACKGROUND: Building up of pathway-/disease-relevant signatures provides a persuasive tool for understanding the functional relevance of gene alterations and gene network associations in multifactorial human diseases. Ovarian cancer is a highly complex heterogeneous malignancy in respect of tumor anatomy, tumor microenvironment including pro-/antitumor immunity and inflammation; still, it is generally treated as single disease. Thus, further approaches to investigate novel aspects of ovarian cancer pathogenesis aiming to provide a personalized strategy to clinical decision making are of high priority. Herein we assessed the contribution of the AID/APOBEC family and their associated genes given the remarkable ability of AID and APOBECs to edit DNA/RNA, and as such, providing tools for genetic and epigenetic alterations potentially leading to reprogramming of tumor cells, stroma and immune cells. RESULTS: We structured the study by three consecutive analytical modules, which include the multigene-based expression profiling in a cohort of patients with primary serous ovarian cancer using a self-created AID/APOBEC-associated gene signature, building up of multivariable survival models with high predictive accuracy and nomination of top-ranked candidate/target genes according to their prognostic impact, and systems biology-based reconstruction of the AID/APOBEC-driven disease-relevant mechanisms using transcriptomics data from ovarian cancer samples. We demonstrated that inclusion of the AID/APOBEC signature-based variables significantly improves the clinicopathological variables-based survival prognostication allowing significant patient stratification. Furthermore, several of the profiling-derived variables such as ID3, PTPRC/CD45, AID, APOBEC3G, and ID2 exceed the prognostic impact of some clinicopathological variables. We next extended the signature-/modeling-based knowledge by extracting top genes co-regulated with target molecules in ovarian cancer tissues and dissected potential networks/pathways/regulators contributing to pathomechanisms. We thereby revealed that the AID/APOBEC-related network in ovarian cancer is particularly associated with remodeling/fibrotic pathways, altered immune response, and autoimmune disorders with inflammatory background. CONCLUSIONS: The herein study is, to our knowledge, the first one linking expression of entire AID/APOBECs and interacting genes with clinical outcome with respect to survival of cancer patients. Overall, data propose a novel AID/APOBEC-derived survival model for patient risk assessment and reconstitute mapping to molecular pathways. The established study algorithm can be applied further for any biologically relevant signature and any type of diseased tissue.

Exploring the role of sphingolipid machinery during the epithelial to mesenchymal transition program using an integrative approach.

The epithelial to mesenchymal transition (EMT) program is activated in epithelial cancer cells and facilitates their ability to metastasize based on enhanced migratory, proliferative, anti-apoptotic, and pluripotent capacities. Given the fundamental impact of sphingolipid machinery to each individual process, the sphingolipid-related mechanisms might be considered among the most prominent drivers/players of EMT; yet, there is still limited knowledge. Given the complexity of the interconnected sphingolipid system, which includes distinct sphingolipid mediators, their synthesizing enzymes, receptors and transporters, we herein apply an integrative approach for assessment of the sphingolipid-associated mechanisms underlying EMT program. We created the sphingolipid-/EMT-relevant 41-gene/23-gene signatures which were applied to denote transcriptional events in a lung cancer cell-based EMT model. Based on defined 35-gene sphingolipid/EMT-attributed signature of regulated genes, we show close associations between EMT markers, genes comprising the sphingolipid network at multiple levels and encoding sphingosine 1-phosphate (S1P)-/ceramide-metabolizing enzymes, S1P and lysophosphatidic acid (LPA) receptors and S1P transporters, pluripotency genes and inflammation-related molecules, and demonstrate the underlying biological pathways and regulators. Mass spectrometry-based sphingolipid analysis revealed an EMT-attributed shift towards increased S1P and LPA accompanied by reduced ceramide levels. Notably, using transcriptomics data across various cell-based perturbations and neoplastic tissues (24193 arrays), we identified the sphingolipid/EMT signature primarily in lung adenocarcinoma tissues; besides, bladder, colorectal and prostate cancers were among the top-ranked. The findings also highlight novel regulatory associations between influenza virus and the sphingolipid/EMT-associated mechanisms. In sum, data propose the multidimensional contribution of sphingolipid machinery to pathological EMT and may yield new biomarkers and therapeutic targets.

ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions.

Reference datasets are often used to compare, interpret or validate experimental data and analytical methods. In the field of gene expression, several reference datasets have been published. Typically, they consist of individual baseline or spike-in experiments carried out in a single laboratory and representing a particular set of conditions. Here, we describe a new type of standardized datasets representative for the spatial and temporal dimensions of gene expression. They result from integrating expression data from a large number of globally normalized and quality controlled public experiments. Expression data is aggregated by anatomical part or stage of development to yield a representative transcriptome for each category. For example, we created a genome-wide expression dataset representing the FDA tissue panel across 35 tissue types. The proposed datasets were created for human and several model organisms and are publicly available at http://www.expressiondata.org.

Large-scale gene expression profiling data for the model moss Physcomitrella patens aid understanding of developmental progression, culture and stress conditions.

The moss Physcomitrella patens is an important model organism for studying plant evolution, development, physiology and biotechnology. Here we have generated microarray gene expression data covering the principal developmental stages, culture forms and some environmental/stress conditions. Example analyses of developmental stages and growth conditions as well as abiotic stress treatments demonstrate that (i) growth stage is dominant over culture conditions, (ii) liquid culture is not stressful for the plant, (iii) low pH might aid protoplastation by reduced expression of cell wall structure genes, (iv) largely the same gene pool mediates response to dehydration and rehydration, and (v) AP2/EREBP transcription factors play important roles in stress response reactions. With regard to the AP2 gene family, phylogenetic analysis and comparison with Arabidopsis thaliana shows commonalities as well as uniquely expressed family members under drought, light perturbations and protoplastation. Gene expression profiles for P. patens are available for the scientific community via the easy-to-use tool at https://www.genevestigator.com. By providing large-scale expression profiles, the usability of this model organism is further enhanced, for example by enabling selection of control genes for quantitative real-time PCR. Now, gene expression levels across a broad range of conditions can be accessed online for P. patens.

Global regulatory architecture of human, mouse and rat tissue transcriptomes.

BACKGROUND: Predicting molecular responses in human by extrapolating results from model organisms requires a precise understanding of the architecture and regulation of biological mechanisms across species. RESULTS: Here, we present a large-scale comparative analysis of organ and tissue transcriptomes involving the three mammalian species human, mouse and rat. To this end, we created a unique, highly standardized compendium of tissue expression. Representative tissue specific datasets were aggregated from more than 33,900 Affymetrix expression microarrays. For each organism, we created two expression datasets covering over 55 distinct tissue types with curated data from two independent microarray platforms. Principal component analysis (PCA) revealed that the tissue-specific architecture of transcriptomes is highly conserved between human, mouse and rat. Moreover, tissues with related biological function clustered tightly together, even if the underlying data originated from different labs and experimental settings. Overall, the expression variance caused by tissue type was approximately 10 times higher than the variance caused by perturbations or diseases, except for a subset of cancers and chemicals. Pairs of gene orthologs exhibited higher expression correlation between mouse and rat than with human. Finally, we show evidence that tissue expression profiles, if combined with sequence similarity, can improve the correct assignment of functionally related homologs across species. CONCLUSION: The results demonstrate that tissue-specific regulation is the main determinant of transcriptome composition and is highly conserved across mammalian species.

Controlled vocabularies for plant anatomical parts optimized for use in data analysis tools and for cross-species studies.

BACKGROUND: It is generally accepted that controlled vocabularies are necessary to systematically integrate data from various sources. During the last decade, several plant ontologies have been developed, some of which are community specific or were developed for a particular purpose. In most cases, the practical application of these ontologies has been limited to systematically storing experimental data. Due to technical constraints, complex data structures and term redundancies, it has been difficult to apply them directly into analysis tools. RESULTS: Here, we describe a simplified and cross-species compatible set of controlled vocabularies for plant anatomy, focussing mainly on monocotypledonous and dicotyledonous crop and model plants. Their content was designed primarily for their direct use in graphical visualization tools. Specifically, we created annotation vocabularies that can be understood by non-specialists, are minimally redundant, simply structured, have low tree depth, and we tested them practically in the frame of Genevestigator. CONCLUSIONS: The application of the proposed ontologies enabled the aggregation of data from hundreds of experiments to visualize gene expression across tissue types. It also facilitated the comparison of expression across species. The described controlled vocabularies are maintained by a dedicated curation team and are available upon request.

A multilevel gamma-clustering layout algorithm for visualization of biological networks.

Visualization of large complex networks has become an indispensable part of systems biology, where organisms need to be considered as one complex system. The visualization of the corresponding network is challenging due to the size and density of edges. In many cases, the use of standard visualization algorithms can lead to high running times and poorly readable visualizations due to many edge crossings. We suggest an approach that analyzes the structure of the graph first and then generates a new graph which contains specific semantic symbols for regular substructures like dense clusters. We propose a multilevel gamma-clustering layout visualization algorithm (MLGA) which proceeds in three subsequent steps: (i) a multilevel γ -clustering is used to identify the structure of the underlying network, (ii) the network is transformed to a tree, and (iii) finally, the resulting tree which shows the network structure is drawn using a variation of a force-directed algorithm. The algorithm has a potential to visualize very large networks because it uses modern clustering heuristics which are optimized for large graphs. Moreover, most of the edges are removed from the visual representation which allows keeping the overview over complex graphs with dense subgraphs.

The Arabidopsis Rho of plants GTPase AtROP6 functions in developmental and pathogen response pathways.

How plants coordinate developmental processes and environmental stress responses is a pressing question. Here, we show that Arabidopsis (Arabidopsis thaliana) Rho of Plants6 (AtROP6) integrates developmental and pathogen response signaling. AtROP6 expression is induced by auxin and detected in the root meristem, lateral root initials, and leaf hydathodes. Plants expressing a dominant negative AtROP6 (rop6(DN)) under the regulation of its endogenous promoter are small and have multiple inflorescence stems, twisted leaves, deformed leaf epidermis pavement cells, and differentially organized cytoskeleton. Microarray analyses of rop6(DN) plants revealed that major changes in gene expression are associated with constitutive salicylic acid (SA)-mediated defense responses. In agreement, their free and total SA levels resembled those of wild-type plants inoculated with a virulent powdery mildew pathogen. The constitutive SA-associated response in rop6(DN) was suppressed in mutant backgrounds defective in SA signaling (nonexpresser of PR genes1 [npr1]) or biosynthesis (salicylic acid induction deficient2 [sid2]). However, the rop6(DN) npr1 and rop6(DN) sid2 double mutants retained the aberrant developmental phenotypes, indicating that the constitutive SA response can be uncoupled from ROP function(s) in development. rop6(DN) plants exhibited enhanced preinvasive defense responses to a host-adapted virulent powdery mildew fungus but were impaired in preinvasive defenses upon inoculation with a nonadapted powdery mildew. The host-adapted powdery mildew had a reduced reproductive fitness on rop6(DN) plants, which was retained in mutant backgrounds defective in SA biosynthesis or signaling. Our findings indicate that both the morphological aberrations and altered sensitivity to powdery mildews of rop6(DN) plants result from perturbations that are independent from the SA-associated response. These perturbations uncouple SA-dependent defense signaling from disease resistance execution.

Integrative genome-wide expression profiling identifies three distinct molecular subgroups of renal cell carcinoma with different patient outcome.

BACKGROUND: Renal cell carcinoma (RCC) is characterized by a number of diverse molecular aberrations that differ among individuals. Recent approaches to molecularly classify RCC were based on clinical, pathological as well as on single molecular parameters. As a consequence, gene expression patterns reflecting the sum of genetic aberrations in individual tumors may not have been recognized. In an attempt to uncover such molecular features in RCC, we used a novel, unbiased and integrative approach. METHODS: We integrated gene expression data from 97 primary RCC of different pathologic parameters, 15 RCC metastases as well as 34 cancer cell lines for two-way nonsupervised hierarchical clustering using gene groups suggested by the PANTHER Classification System. We depicted the genomic landscape of the resulted tumor groups by means of Single Nuclear Polymorphism (SNP) technology. Finally, the achieved results were immunohistochemically analyzed using a tissue microarray (TMA) composed of 254 RCC. RESULTS: We found robust, genome wide expression signatures, which split RCC into three distinct molecular subgroups. These groups remained stable even if randomly selected gene sets were clustered. Notably, the pattern obtained from RCC cell lines was clearly distinguishable from that of primary tumors. SNP array analysis demonstrated differing frequencies of chromosomal copy number alterations among RCC subgroups. TMA analysis with group-specific markers showed a prognostic significance of the different groups. CONCLUSION: We propose the existence of characteristic and histologically independent genome-wide expression outputs in RCC with potential biological and clinical relevance.

The importance of size: successful recanalization by intravenous thrombolysis in acute anterior stroke depends on thrombus length.

BACKGROUND AND PURPOSE: We hypothesize that in acute middle cerebral artery stroke, thrombus lengths measured in thin-slice nonenhanced CT images define a limit beyond which systemic thrombolysis will fail to recanalize occluded arteries. METHODS: In 138 patients who presented with acute middle cerebral artery stroke and who were treated with intravenous thrombolysis (IVT), we measured lengths of thrombotic clots depicted as arterial hyperdensities in admission nonenhanced CT images with 2.5-mm slice width. Vascular recanalization was investigated after thrombolysis and recanalization results were related to thrombus lengths by logistic regression. RESULTS: In 62 patients, IVT resulted in recanalization; among these patients, no thrombus length exceeded 8 mm. The median modified Rankin scale score at hospital discharge was 2. In the remaining 76 patients, thrombus lengths mostly exceeded 8 mm and IVT failed in recanalization. These patients were discharged with a median modified Rankin scale score of 5. CONCLUSIONS: This study shows that in acute middle cerebral artery stroke, IVT has nearly no potential to recanalize occluded vessels if thrombus length exceeds 8 mm.

RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization.

BACKGROUND: RT-qPCR is a sensitive and increasingly used method for gene expression quantification. To normalize RT-qPCR measurements between samples, most laboratories use endogenous reference genes as internal controls. There is increasing evidence, however, that the expression of commonly used reference genes can vary significantly in certain contexts. RESULTS: Using the Genevestigator database of normalized and well-annotated microarray experiments, we describe the expression stability characteristics of the transciptomes of several organisms. The results show that a) no genes are universally stable, b) most commonly used reference genes yield very high transcript abundances as compared to the entire transcriptome, and c) for each biological context a subset of stable genes exists that has smaller variance than commonly used reference genes or genes that were selected for their stability across all conditions. CONCLUSION: We therefore propose the normalization of RT-qPCR data using reference genes that are specifically chosen for the conditions under study. RefGenes is a community tool developed for that purpose. Validation RT-qPCR experiments across several organisms showed that the candidates proposed by RefGenes generally outperformed commonly used reference genes. RefGenes is available within Genevestigator at http://www.genevestigator.com.

The hyperdense anterior cerebral artery sign (HACAS) as a computed tomography marker for acute ischemia in the anterior cerebral artery territory.

BACKGROUND: Hyperdense arteries in cranial CT of acute stroke patients have been described as a sign for acute ischemia in various brain-feeding arteries. However, only 1 case of a hyperdense anterior cerebral artery sign (HACAS) has been published to date. In this study, the frequency and association of HACAS with clinical symptoms and outcome are described. METHODS: Our radiological databases were searched for patients with infarcts in the territory of the anterior cerebral artery (ACA). Only patients who received an initial CT and a follow-up CT or MRI were included. The presence of a HACAS was rated by 2 independent observers using the Cohen kappa-statistics. Further data recorded were early ischemic signs, final size of infarct, symptoms, initial NIHSS (National Institute of Health Stroke Scale) score, latency between symptom onset and initial CT, etiology, modified Rankin Scale (mRS) score at discharge and secondary hemorrhage. RESULTS: A HACAS could be visualized in 11/24 patients (46%). Interobserver agreement was substantial with Cohen's kappa = 0.66. Patients with a HACAS had a significantly higher NIHSS score (9.45 +/- 8.41; median: 8) than those without (3.69 +/- 2.09; median: 4). A HACAS was visible more frequently when the CT was performed early (<2.5 h after symptom onset). There was no correlation with single symptoms, size of infarct, etiology, mRS or the tendency to hemorrhage. CONCLUSIONS: HACAS is associated with a higher NIHSS score. It is an early sign of ischemia which can be reversible over time. It can be helpful in the detection of ischemia in the territory of the ACA.

Genome-scale proteomics reveals Arabidopsis thaliana gene models and proteome dynamics.

We have assembled a proteome map for Arabidopsis thaliana from high-density, organ-specific proteome catalogs that we generated for different organs, developmental stages, and undifferentiated cultured cells. We matched 86,456 unique peptides to 13,029 proteins and provide expression evidence for 57 gene models that are not represented in the TAIR7 protein database. Analysis of the proteome identified organ-specific biomarkers and allowed us to compile an organ-specific set of proteotypic peptides for 4105 proteins to facilitate targeted quantitative proteomics surveys. Quantitative information for the identified proteins was used to establish correlations between transcript and protein accumulation in different plant organs. The Arabidopsis proteome map provides information about genome activity and proteome assembly and is available as a resource for plant systems biology.

Genevestigator transcriptome meta-analysis and biomarker search using rice and barley gene expression databases.

The wide-spread use of microarray technologies to study plant transcriptomes has led to important discoveries and to an accumulation of profiling data covering a wide range of different tissues, developmental stages, perturbations, and genotypes. Querying a large number of microarray experiments can provide insights that cannot be gained by analyzing single experiments. However, such a meta-analysis poses significant challenges with respect to data comparability and normalization, systematic sample annotation, and analysis tools. Genevestigator addresses these issues using a large curated expression database and a set of specifically developed analysis tools that are accessible over the internet. This combination has already proven to be useful in the area of plant research based on a large set of Arabidopsis data (Grennan, 2006). Here, we present the release of the Genevestigator rice and barley gene expression databases that contain quality-controlled and well annotated microarray experiments using ontologies. The databases currently comprise experiments from pathology, plant nutrition, abiotic stress, hormone treatment, genotype, and spatial or temporal analysis, but are expected to cover a broad variety of research areas as more experimental data become available. The transcriptome meta-analysis of the model species rice and barley is expected to deliver results that can be used for functional genomics and biotechnological applications in cereals.