Let-7 restrains an oncogenic epigenetic circuit in AT2 cells to prevent ectopic formation of fibrogenic transitional cell intermediates and pulmonary fibrosis.

Analysis of lung alveolar type 2 (AT2) progenitor stem cells has highlighted fundamental mechanisms that direct their differentiation into alveolar type 1 cells (AT1s) in lung repair and disease. However, microRNA (miRNA) mediated post-transcriptional mechanisms which govern this nexus remain understudied. We show here that the let-7 miRNA family serves a homeostatic role in governance of AT2 quiescence, specifically by preventing the uncontrolled accumulation of AT2 transitional cells and by promoting AT1 differentiation to safeguard the lung from spontaneous alveolar destruction and fibrosis. Using mice and organoid models with genetic ablation of let-7a1/let-7f1/let-7d cluster (let-7afd) in AT2 cells, we demonstrate prevents AT1 differentiation and results in aberrant accumulation of AT2 transitional cells in progressive pulmonary fibrosis. Integration of enhanced AGO2 UV-crosslinking and immunoprecipitation sequencing (AGO2-eCLIP) with RNA-sequencing from AT2 cells uncovered the induction of direct targets of let-7 in an oncogene feed-forward regulatory network including BACH1/EZH2 which drives an aberrant fibrotic cascade. Additional analyses by CUT&RUN-sequencing revealed loss of let-7afd hampers AT1 differentiation by eliciting aberrant histone EZH2 methylation which prevents the exit of AT2 transitional cells into terminal AT1s. This study identifies let-7 as a key gatekeeper of post-transcriptional and epigenetic chromatin signals to prevent AT2-driven pulmonary fibrosis.

Histone proteoform analysis reveals epigenetic changes in adult mouse brown adipose tissue in response to cold stress.

BACKGROUND: Regulation of the thermogenic response by brown adipose tissue (BAT) is an important component of energy homeostasis with implications for the treatment of obesity and diabetes. Our preliminary analyses of RNA-Seq data uncovered many nodes representing epigenetic modifiers that are altered in BAT in response to chronic thermogenic activation. Thus, we hypothesized that chronic thermogenic activation broadly alters epigenetic modifications of DNA and histones in BAT. RESULTS: Motivated to understand how BAT function is regulated epigenetically, we developed a novel method for the first-ever unbiased top-down proteomic quantitation of histone modifications in BAT and validated our results with a multi-omic approach. To test our hypothesis, wildtype male C57BL/6J mice were housed under chronic conditions of thermoneutral temperature (TN, 28°C), mild cold/room temperature (RT, 22°C), or severe cold (SC, 8°C) and BAT was analyzed for DNA methylation and histone modifications. Methylation of promoters and intragenic regions in genomic DNA decrease in response to chronic cold exposure. Integration of DNA methylation and RNA expression datasets suggest a role for epigenetic modification of DNA in regulation of gene expression in response to cold. In response to cold housing, we observe increased bulk acetylation of histones H3.2 and H4, increased histone H3.2 proteoforms with di- and trimethylation of lysine 9 (K9me2 and K9me3), and increased histone H4 proteoforms with acetylation of lysine 16 (K16ac) in BAT. CONCLUSIONS: Our results reveal global epigenetically-regulated transcriptional "on" and "off" signals in murine BAT in response to varying degrees of chronic cold stimuli and establish a novel methodology to quantitatively study histones in BAT, allowing for direct comparisons to decipher mechanistic changes during the thermogenic response. Additionally, we make histone PTM and proteoform quantitation, RNA splicing, RRBS, and transcriptional footprint datasets available as a resource for future research.

Histone proteoform analysis reveals epigenetic changes in adult mouse brown adipose tissue in response to cold stress.

Regulation of the thermogenic response by brown adipose tissue (BAT) is an important component of energy homeostasis with implications for the treatment of obesity and diabetes. Our preliminary analyses uncovered many nodes representing epigenetic modifiers that are altered in BAT in response to chronic thermogenic activation. Thus, we hypothesized that chronic thermogenic activation broadly alters epigenetic modifications of DNA and histones in BAT. Motivated to understand how BAT function is regulated epigenetically, we developed a novel method for the first-ever unbiased top-down proteomic quantitation of histone modifications in BAT and validated our results with a multi-omic approach. To test our hypothesis, wildtype male C57BL/6J mice were housed under chronic conditions of thermoneutral temperature (TN, 28.8°C), mild cold/room temperature (RT, 22°C), or severe cold (SC, 8°C) and BAT was analyzed for DNA methylation and histone modifications. Methylation of promoters and intragenic regions in genomic DNA decrease in response to chronic cold exposure. Integration of DNA methylation and RNA expression data suggest a role for epigenetic modification of DNA in gene regulation in response to cold. In response to cold housing, we observe increased bulk acetylation of histones H3.2 and H4, increased histone H3.2 proteoforms with di- and trimethylation of lysine 9 (K9me2 and K9me3), and increased histone H4 proteoforms with acetylation of lysine 16 (K16ac) in BAT. Taken together, our results reveal global epigenetically-regulated transcriptional "on" and "off" signals in murine BAT in response to varying degrees of chronic cold stimuli and establish a novel methodology to quantitatively study histones in BAT, allowing for direct comparisons to decipher mechanistic changes during the thermogenic response. Additionally, we make histone PTM and proteoform quantitation, RNA splicing, RRBS, and transcriptional footprint datasets available as a resource for future research.

Spatial Transcriptomics Resolve an Emphysema-Specific Lymphoid Follicle B Cell Signature in Chronic Obstructive Pulmonary Disease.

Rationale: Within chronic obstructive pulmonary disease (COPD), emphysema is characterized by a significant yet partially understood B cell immune component. Objectives: To characterize the transcriptomic signatures from lymphoid follicles (LFs) in ever-smokers without COPD and patients with COPD with varying degrees of emphysema. Methods: Lung sections from 40 patients with COPD and ever-smokers were used for LF proteomic and transcriptomic spatial profiling. Formalin- and O.C.T.-fixed lung samples obtained from biopsies or lung explants were assessed for LF presence. Emphysema measurements were obtained from clinical chest computed tomographic scans. High-confidence transcriptional target intersection analyses were conducted to resolve emphysema-induced transcriptional networks. Measurements and Main Results: Overall, 115 LFs from ever-smokers and Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-2 and GOLD 3-4 patients were analyzed. No LFs were found in never-smokers. Differential gene expression analysis revealed significantly increased expression of LF assembly and B cell marker genes in subjects with severe emphysema. High-confidence transcriptional analysis revealed activation of an abnormal B cell activity signature in LFs (q-value = 2.56E-111). LFs from patients with GOLD 1-2 COPD with emphysema showed significantly increased expression of genes associated with antigen presentation, inflammation, and B cell activation and proliferation. LFs from patients with GOLD 1-2 COPD without emphysema showed an antiinflammatory profile. The extent of centrilobular emphysema was significantly associated with genes involved in B cell maturation and antibody production. Protein-RNA network analysis showed that LFs in emphysema have a unique signature skewed toward chronic B cell activation. Conclusions: An off-targeted B cell activation within LFs is associated with autoimmune-mediated emphysema pathogenesis.

Spatial Transcriptomics Resolve an Emphysema-specific Lymphoid Follicle B Cell Signature in COPD.

RATIONALE: Within chronic obstructive pulmonary disease (COPD), emphysema is characterized by a significant yet partially understood B cell immune component. OBJECTIVE: To characterize the transcriptomic signatures from lymphoid follicles (LFs) in ever-smokers without COPD and COPD patients with varying degrees of emphysema. METHODS: Lung sections from 40 COPD patients and ever-smokers were used for LF proteomic and transcriptomic spatial profiling. Formalin and OCT-fixed lung samples obtained from biopsies or lung explants, were assessed for LF presence. Emphysema measurements were obtained from clinical chest CT scans. High confidence transcriptional (HCT) target intersection analyses were conducted to resolve emphysema-induced transcriptional networks. MEASUREMENTS AND MAIN RESULTS: Overall, 115 LFs from ever-smokers and GOLD 1-2 and GOLD 3-4 patients were analyzed. No LFs were found in never-smokers. Differential gene expression analysis revealed significantly increased expression of LF assembly and B cell markers genes in subjects with severe emphysema. HCT analysis revealed activation of abnormal B cell activity signature in LFs (q-value: 2.56E-111). LFs from GOLD 1-2 COPD patients with emphysema showed significantly increased expression of genes associated with antigen presentation, inflammation, and B cell activation and proliferation. LFs from GOLD 1-2 COPD patients without emphysema showed an anti-inflammatory profile. The extent of centrilobular emphysema was significantly associated with genes involved in B cell maturation and antibody production. Protein-RNA network analysis showed that LFs in emphysema have a unique signature skewed towards chronic B cell activation. CONCLUSIONS: An off-targeted B cell activation within LFs is associated with autoimmune-mediated emphysema pathogenesis.

SHP2 promotes sarcoidosis severity by inhibiting SKP2-targeted ubiquitination of TBET in CD8+ T cells.

Sarcoidosis is an interstitial lung disease (ILD) characterized by interferon-γ (IFN-γ) and T-box expressed in T cells (TBET) dysregulation. Although one-third of patients progress from granulomatous inflammation to severe lung damage, the molecular mechanisms underlying this process remain unclear. Here, we found that pharmacological inhibition of phosphorylated SH2-containing protein tyrosine phosphatase-2 (pSHP2), a facilitator of aberrant IFN-γ abundance, decreased large granuloma formation and macrophage infiltration in the lungs of mice with sarcoidosis-like disease. Positive treatment outcomes were dependent on the effective enhancement of TBET ubiquitination within CD8+ T cells. Mechanistically, we identified a posttranslational modification pathway in which the E3 F-box protein S-phase kinase-associated protein 2 (SKP2) targets TBET for ubiquitination in T cells under normal conditions. However, this pathway was disrupted by aberrant pSHP2 signaling in CD8+ T cells from patients with progressive pulmonary sarcoidosis and end-stage disease. Ex vivo inhibition of pSHP2 in CD8+ T cells from patients with end-stage sarcoidosis enhanced TBET ubiquitination and suppressed IFN-γ and collagen synthesis. Therefore, these studies provided new mechanistic insights into the SHP2-dependent posttranslational regulation of TBET and identified SHP2 inhibition as a potential therapeutic intervention against severe sarcoidosis. Furthermore, these studies also suggest that the small-molecule SHP2 inhibitor SHP099 might be used as a therapeutic measure against human diseases linked to TBET or ubiquitination.

Vitamin B2 enables regulation of fasting glucose availability.

Flavin adenine dinucleotide (FAD) interacts with flavoproteins to mediate oxidation-reduction reactions required for cellular energy demands. Not surprisingly, mutations that alter FAD binding to flavoproteins cause rare inborn errors of metabolism (IEMs) that disrupt liver function and render fasting intolerance, hepatic steatosis, and lipodystrophy. In our study, depleting FAD pools in mice with a vitamin B2-deficient diet (B2D) caused phenotypes associated with organic acidemias and other IEMs, including reduced body weight, hypoglycemia, and fatty liver disease. Integrated discovery approaches revealed B2D tempered fasting activation of target genes for the nuclear receptor PPARα, including those required for gluconeogenesis. We also found PPARα knockdown in the liver recapitulated B2D effects on glucose excursion and fatty liver disease in mice. Finally, treatment with the PPARα agonist fenofibrate activated the integrated stress response and refilled amino acid substrates to rescue fasting glucose availability and overcome B2D phenotypes. These findings identify metabolic responses to FAD availability and nominate strategies for the management of organic acidemias and other rare IEMs.

IL17A Blockade with Ixekizumab Suppresses MuvB Signaling in Clinical Psoriasis.

Unbiased informatics approaches have the potential to generate insights into uncharacterized signaling pathways in human disease. In this study, we generated longitudinal transcriptomic profiles of plaque psoriasis lesions from patients enrolled in a clinical trial of the anti-IL17A antibody ixekizumab (IXE). This dataset was then computed against a curated matrix of over 700 million data points derived from published psoriasis and signaling node perturbation transcriptomic and chromatin immunoprecipitation-sequencing datasets. We observed substantive enrichment within both psoriasis-induced and IXE-repressed gene sets of transcriptional targets of members of the MuvB complex, a master regulator of the mitotic cell cycle. These gene sets were similarly enriched for pathways involved in the regulation of the G2/M transition of the cell cycle. Moreover, transcriptional targets for MuvB nodes were strongly enriched within IXE-repressed genes whose expression levels correlated strongly with the extent and severity of the psoriatic disease. In models of human keratinocyte proliferation, genes encoding MuvB nodes were transcriptionally repressed by IXE, and depletion of MuvB nodes reduced cell proliferation. Finally, we made the expression and regulatory networks that supported this study available as a freely accessible, cloud-based hypothesis generation platform. Our study positions inhibition of MuvB signaling as an important determinant of the therapeutic impact of IXE in psoriasis.

Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase.

Investigator-generated transcriptomic datasets interrogating circulating immune cell (CIC) gene expression in clinical type 1 diabetes (T1D) have underappreciated re-use value. Here, we repurposed these datasets to create an open science environment for the generation of hypotheses around CIC signaling pathways whose gain or loss of function contributes to T1D pathogenesis. We firstly computed sets of genes that were preferentially induced or repressed in T1D CICs and validated these against community benchmarks. We then inferred and validated signaling node networks regulating expression of these gene sets, as well as differentially expressed genes in the original underlying T1D case:control datasets. In a set of three use cases, we demonstrated how informed integration of these networks with complementary digital resources supports substantive, actionable hypotheses around signaling pathway dysfunction in T1D CICs. Finally, we developed a federated, cloud-based web resource that exposes the entire data matrix for unrestricted access and re-use by the research community.

Conserved immunomodulatory transcriptional networks underlie antipsychotic-induced weight gain.

Although antipsychotics, such as olanzapine, are effective in the management of psychiatric conditions, some patients experience excessive antipsychotic-induced weight gain (AIWG). To illuminate pathways underlying AIWG, we compared baseline blood gene expression profiles in two cohorts of mice that were either prone (AIWG-P) or resistant (AIWG-R) to weight gain in response to olanzapine treatment for two weeks. We found that transcripts elevated in AIWG-P mice relative to AIWG-R are enriched for high-confidence transcriptional targets of numerous inflammatory and immunomodulatory signaling nodes. Moreover, these nodes are themselves enriched for genes whose disruption in mice is associated with reduced body fat mass and slow postnatal weight gain. In addition, we identified gene expression profiles in common between our mouse AIWG-P gene set and an existing human AIWG-P gene set whose regulation by immunomodulatory transcription factors is highly conserved between species. Finally, we identified striking convergence between mouse AIWG-P transcriptional regulatory networks and those associated with body weight and body mass index in humans. We propose that immunomodulatory transcriptional networks drive AIWG, and that these networks have broader conserved roles in whole body-metabolism.

A human liver chimeric mouse model for non-alcoholic fatty liver disease.

BACKGROUND & AIMS: The accumulation of neutral lipids within hepatocytes underlies non-alcoholic fatty liver disease (NAFLD), which affects a quarter of the world's population and is associated with hepatitis, cirrhosis, and hepatocellular carcinoma. Despite insights gained from both human and animal studies, our understanding of NAFLD pathogenesis remains limited. To better study the molecular changes driving the condition we aimed to generate a humanised NAFLD mouse model. METHODS: We generated TIRF (transgene-free Il2rg -/-/Rag2 -/-/Fah -/-) mice, populated their livers with human hepatocytes, and fed them a Western-type diet for 12 weeks. RESULTS: Within the same chimeric liver, human hepatocytes developed pronounced steatosis whereas murine hepatocytes remained normal. Unbiased metabolomics and lipidomics revealed signatures of clinical NAFLD. Transcriptomic analyses showed that molecular responses diverged sharply between murine and human hepatocytes, demonstrating stark species differences in liver function. Regulatory network analysis indicated close agreement between our model and clinical NAFLD with respect to transcriptional control of cholesterol biosynthesis. CONCLUSIONS: These NAFLD xenograft mice reveal an unexpected degree of evolutionary divergence in food metabolism and offer a physiologically relevant, experimentally tractable model for studying the pathogenic changes invoked by steatosis. LAY SUMMARY: Fatty liver disease is an emerging health problem, and as there are no good experimental animal models, our understanding of the condition is poor. We here describe a novel humanised mouse system and compare it with clinical data. The results reveal that the human cells in the mouse liver develop fatty liver disease upon a Western-style fatty diet, whereas the mouse cells appear normal. The molecular signature (expression profiles) of the human cells are distinct from the mouse cells and metabolic analysis of the humanised livers mimic the ones observed in humans with fatty liver. This novel humanised mouse system can be used to study human fatty liver disease.

Steroid receptor coactivator 3 (SRC-3/AIB1) is enriched and functional in mouse and human Tregs.

A subset of CD4 + lymphocytes, regulatory T cells (Tregs), are necessary for central tolerance and function as suppressors of autoimmunity against self-antigens. The SRC-3 coactivator is an oncogene in multiple cancers and is capable of potentiating numerous transcription factors in a wide variety of cell types. Src-3 knockout mice display broad lymphoproliferation and hypersensitivity to systemic inflammation. Using publicly available bioinformatics data and directed cellular approaches, we show that SRC-3 also is highly enriched in Tregs in mice and humans. Human Tregs lose phenotypic characteristics when SRC-3 is depleted or pharmacologically inhibited, including failure of induction from resting T cells and loss of the ability to suppress proliferation of stimulated T cells. These data support a model for SRC-3 as a coactivator that actively participates in protection from autoimmunity and may support immune evasion of cancers by contributing to the biology of Tregs.

Adipocyte-Specific Ablation of PU.1 Promotes Energy Expenditure and Ameliorates Metabolic Syndrome in Aging Mice.

Objective: Although PU.1/Spi1 is known as a master regulator for macrophage development and function, we have reported previously that it is also expressed in adipocytes and is transcriptionally induced in obesity. Here, we investigated the role of adipocyte PU.1 in the development of the age-associated metabolic syndrome. Methods: We generated mice with adipocyte-specific PU.1 knockout, assessed metabolic changes in young and older adult PU.1fl/fl (control) and AdipoqCre PU.1fl/fl (aPU.1KO) mice, including body weight, body composition, energy expenditure, and glucose homeostasis. We also performed transcriptional analyses using RNA-Sequencing of adipocytes from these mice. Results: aPU.1KO mice have elevated energy expenditure at a young age and decreased adiposity and increased insulin sensitivity in later life. Corroborating these observations, transcriptional network analysis indicated the existence of validated, adipocyte PU.1-modulated regulatory hubs that direct inflammatory and thermogenic gene expression programs. Conclusion: Our data provide evidence for a previously uncharacterized role of PU.1 in the development of age-associated obesity and insulin resistance.

Consensus transcriptional regulatory networks of coronavirus-infected human cells.

Establishing consensus around the transcriptional interface between coronavirus (CoV) infection and human cellular signaling pathways can catalyze the development of novel anti-CoV therapeutics. Here, we used publicly archived transcriptomic datasets to compute consensus regulatory signatures, or consensomes, that rank human genes based on their rates of differential expression in MERS-CoV (MERS), SARS-CoV-1 (SARS1) and SARS-CoV-2 (SARS2)-infected cells. Validating the CoV consensomes, we show that high confidence transcriptional targets (HCTs) of MERS, SARS1 and SARS2 infection intersect with HCTs of signaling pathway nodes with known roles in CoV infection. Among a series of novel use cases, we gather evidence for hypotheses that SARS2 infection efficiently represses E2F family HCTs encoding key drivers of DNA replication and the cell cycle; that progesterone receptor signaling antagonizes SARS2-induced inflammatory signaling in the airway epithelium; and that SARS2 HCTs are enriched for genes involved in epithelial to mesenchymal transition. The CoV infection consensomes and HCT intersection analyses are freely accessible through the Signaling Pathways Project knowledgebase, and as Cytoscape-style networks in the Network Data Exchange repository.

Consensus transcriptional regulatory networks of coronavirus-infected human cells.

Establishing consensus around the transcriptional interface between coronavirus (CoV) infection and human cellular signaling pathways can catalyze the development of novel anti-CoV therapeutics. Here, we used publicly archived transcriptomic datasets to compute consensus regulatory signatures, or consensomes, that rank human genes based on their rates of differential expression in MERS-CoV (MERS), SARS-CoV-1 (SARS1) and SARS-CoV-2 (SARS2)-infected cells. Validating the CoV consensomes, we show that high confidence transcriptional targets (HCTs) of CoV infection intersect with HCTs of signaling pathway nodes with known roles in CoV infection. Among a series of novel use cases, we gather evidence for hypotheses that SARS2 infection efficiently represses E2F family target genes encoding key drivers of DNA replication and the cell cycle; that progesterone receptor signaling antagonizes SARS2-induced inflammatory signaling in the airway epithelium; and that SARS2 HCTs are enriched for genes involved in epithelial to mesenchymal transition. The CoV infection consensomes and HCT intersection analyses are freely accessible through the Signaling Pathways Project knowledgebase, and as Cytoscape-style networks in the Network Data Exchange repository.

No Dataset Left Behind: Mechanistic Insights into Thyroid Receptor Signaling Through Transcriptomic Consensome Meta-Analysis.

Background: Discovery-scale omics datasets relevant to thyroid receptors (TRs) and their physiological and synthetic bioactive small-molecule ligands allow for genome-wide interrogation of TR-regulated genes. These datasets have considerable collective value as a reference resource to allow researchers to routinely generate hypotheses addressing the mechanisms underlying the cell biology and physiology of TR signaling in normal and disease states. Methods: Here, we searched the Gene Expression Omnibus database to identify a population of publicly archived transcriptomic datasets involving genetic or pharmacological manipulation of either TR isoform in a mouse tissue or cell line. After initial quality control, samples were organized into contrasts (experiments), and transcript differential expression values and associated measures of significance were generated and committed to a consensome (for consensus omics) meta-analysis pipeline. To gain insight into tissue-selective functions of TRs, we generated liver- and central nervous system (CNS)-specific consensomes and identified evidence for genes that were selectively responsive to TR signaling in each organ. Results: The TR transcriptomic consensome ranks genes based on the frequency of their significant differential expression over the entire group of experiments. The TR consensome assigns elevated rankings both to known TR-regulated genes and to genes previously uncharacterized as TR-regulated, which shed mechanistic light on known cellular and physiological roles of TR signaling in different organs. We identify evidence for unreported genomic targets of TR signaling for which it exhibits strikingly distinct regulatory preferences in the liver and CNS. Moreover, the intersection of the TR consensome with consensomes for other cellular receptors sheds light on transcripts potentially mediating crosstalk between TRs and these other signaling paradigms. Conclusions: The mouse TR datasets and consensomes are freely available in the Signaling Pathways Project website for hypothesis generation, data validation, and modeling of novel mechanisms of TR regulation of gene expression. Our results demonstrate the insights into the mechanistic basis of thyroid hormone action that can arise from an ongoing commitment on the part of the research community to the deposition of discovery-scale datasets.

The Signaling Pathways Project, an integrated 'omics knowledgebase for mammalian cellular signaling pathways.

Mining of integrated public transcriptomic and ChIP-Seq (cistromic) datasets can illuminate functions of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates community classifications of signaling pathway nodes (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules. We then mapped over 10,000 public transcriptomic or cistromic experiments to their pathway node or biosample of study. To enable prediction of pathway node-gene target transcriptional regulatory relationships through SPP, we generated consensus 'omics signatures, or consensomes, which ranked genes based on measures of their significant differential expression or promoter occupancy across transcriptomic or cistromic experiments mapped to a specific node family. Consensomes were validated using alignment with canonical literature knowledge, gene target-level integration of transcriptomic and cistromic data points, and in bench experiments confirming previously uncharacterized node-gene target regulatory relationships. To expose the SPP knowledgebase to researchers, a web browser interface was designed that accommodates numerous routine data mining strategies. SPP is freely accessible at https://www.signalingpathways.org .

Developing a framework for digital objects in the Big Data to Knowledge (BD2K) commons: Report from the Commons Framework Pilots workshop.

The volume and diversity of data in biomedical research have been rapidly increasing in recent years. While such data hold significant promise for accelerating discovery, their use entails many challenges including: the need for adequate computational infrastructure, secure processes for data sharing and access, tools that allow researchers to find and integrate diverse datasets, and standardized methods of analysis. These are just some elements of a complex ecosystem that needs to be built to support the rapid accumulation of these data. The NIH Big Data to Knowledge (BD2K) initiative aims to facilitate digitally enabled biomedical research. Within the BD2K framework, the Commons initiative is intended to establish a virtual environment that will facilitate the use, interoperability, and discoverability of shared digital objects used for research. The BD2K Commons Framework Pilots Working Group (CFPWG) was established to clarify goals and work on pilot projects that address existing gaps toward realizing the vision of the BD2K Commons. This report reviews highlights from a two-day meeting involving the BD2K CFPWG to provide insights on trends and considerations in advancing Big Data science for biomedical research in the United States.

Discovering relationships between nuclear receptor signaling pathways, genes, and tissues in Transcriptomine.

We previously developed a web tool, Transcriptomine, to explore expression profiling data sets involving small-molecule or genetic manipulations of nuclear receptor signaling pathways. We describe advances in biocuration, query interface design, and data visualization that enhance the discovery of uncharacterized biology in these pathways using this tool. Transcriptomine currently contains about 45 million data points encompassing more than 2000 experiments in a reference library of nearly 550 data sets retrieved from public archives and systematically curated. To make the underlying data points more accessible to bench biologists, we classified experimental small molecules and gene manipulations into signaling pathways and experimental tissues and cell lines into physiological systems and organs. Incorporation of these mappings into Transcriptomine enables the user to readily evaluate tissue-specific regulation of gene expression by nuclear receptor signaling pathways. Data points from animal and cell model experiments and from clinical data sets elucidate the roles of nuclear receptor pathways in gene expression events accompanying various normal and pathological cellular processes. In addition, data sets targeting non-nuclear receptor signaling pathways highlight transcriptional cross-talk between nuclear receptors and other signaling pathways. We demonstrate with specific examples how data points that exist in isolation in individual data sets validate each other when connected and made accessible to the user in a single interface. In summary, Transcriptomine allows bench biologists to routinely develop research hypotheses, validate experimental data, or model relationships between signaling pathways, genes, and tissues.

Improving the discoverability, accessibility, and citability of omics datasets: a case report.

Although omics datasets represent valuable assets for hypothesis generation, model testing, and data validation, the infrastructure supporting their reuse lacks organization and consistency. Using nuclear receptor signaling transcriptomic datasets as proof of principle, we developed a model to improve the discoverability, accessibility, and citability of published omics datasets. Primary datasets were retrieved from archives, processed to extract data points, then subjected to metadata enrichment and gap filling. The resulting secondary datasets were exposed on responsive web pages to support mining of gene lists, discovery of related datasets, and single-click citation integration with popular reference managers. Automated processes were established to embed digital object identifier-driven links to the secondary datasets in associated journal articles, small molecule and gene-centric databases, and a dataset search engine. Our model creates multiple points of access to reprocessed and reannotated derivative datasets across the digital biomedical research ecosystem, promoting their visibility and usability across disparate research communities.