Temporal Transcriptome Analysis Reveals Dynamic Gene Expression Patterns Driving ß-Cell Maturation.

Newly differentiated pancreatic ß cells lack proper insulin secretion profiles of mature functional ß cells. The global gene expression differences between paired immature and mature ß cells have been studied, but the dynamics of transcriptional events, correlating with temporal development of glucose-stimulated insulin secretion (GSIS), remain to be fully defined. This aspect is important to identify which genes and pathways are necessary for ß-cell development or for maturation, as defective insulin secretion is linked with diseases such as diabetes. In this study, we assayed through RNA sequencing the global gene expression across six ß-cell developmental stages in mice, spanning from ß-cell progenitor to mature ß cells. A computational pipeline then selected genes differentially expressed with respect to progenitors and clustered them into groups with distinct temporal patterns associated with biological functions and pathways. These patterns were finally correlated with experimental GSIS, calcium influx, and insulin granule formation data. Gene expression temporal profiling revealed the timing of important biological processes across ß-cell maturation, such as the deregulation of ß-cell developmental pathways and the activation of molecular machineries for vesicle biosynthesis and transport, signal transduction of transmembrane receptors, and glucose-induced Ca2+ influx, which were established over a week before ß-cell maturation completes. In particular, ß cells developed robust insulin secretion at high glucose several days after birth, coincident with the establishment of glucose-induced calcium influx. Yet the neonatal ß cells displayed high basal insulin secretion, which decreased to the low levels found in mature ß cells only a week later. Different genes associated with calcium-mediated processes, whose alterations are linked with insulin resistance and deregulation of glucose homeostasis, showed increased expression across ß-cell stages, in accordance with the temporal acquisition of proper GSIS. Our temporal gene expression pattern analysis provided a comprehensive database of the underlying molecular components and biological mechanisms driving ß-cell maturation at different temporal stages, which are fundamental for better control of the in vitro production of functional ß cells from human embryonic stem/induced pluripotent cell for transplantation-based type 1 diabetes therapy.

Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project.

An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient's phenotype. The development of two new ontologies - the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation - will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.

Phospho-PTM proteomic discovery of novel EPO- modulated kinases and phosphatases, including PTPN18 as a positive regulator of EPOR/JAK2 Signaling.

The formation of erythroid progenitor cells depends sharply upon erythropoietin (EPO), its cell surface receptor (erythropoietin receptor, EPOR), and Janus kinase 2 (JAK2). Clinically, recombinant human EPO (rhEPO) additionally is an important anti-anemia agent for chronic kidney disease (CKD), myelodysplastic syndrome (MDS) and chemotherapy, but induces hypertension, and can exert certain pro-tumorigenic effects. Cellular signals transduced by EPOR/JAK2 complexes, and the nature of EPO-modulated signal transduction factors, therefore are of significant interest. By employing phospho-tyrosine post-translational modification (p-Y PTM) proteomics and human EPO- dependent UT7epo cells, we have identified 22 novel kinases and phosphatases as novel EPO targets, together with their specific sites of p-Y modification. New kinases modified due to EPO include membrane palmitoylated protein 1 (MPP1) and guanylate kinase 1 (GUK1) guanylate kinases, together with the cytoskeleton remodeling kinases, pseudopodium enriched atypical kinase 1 (PEAK1) and AP2 associated kinase 1 (AAK1). Novel EPO- modified phosphatases include protein tyrosine phosphatase receptor type A (PTPRA), phosphohistidine phosphatase 1 (PHPT1), tensin 2 (TENC1), ubiquitin associated and SH3 domain containing B (UBASH3B) and protein tyrosine phosphatase non-receptor type 18 (PTPN18). Based on PTPN18's high expression in hematopoietic progenitors, its novel connection to JAK kinase signaling, and a unique EPO- regulated PTPN18-pY389 motif which is modulated by JAK2 inhibitors, PTPN18's actions in UT7epo cells were investigated. Upon ectopic expression, wt-PTPN18 promoted EPO dose-dependent cell proliferation, and survival. Mechanistically, PTPN18 sustained the EPO- induced activation of not only mitogen-activated protein kinases 1 and 3 (ERK1/2), AKT serine/threonine kinase 1-3 (AKT), and signal transducer and activator of transcription 5A and 5B (STAT5), but also JAK2. Each effect further proved to depend upon PTPN18's EPO- modulated (p)Y389 site. In analyses of the EPOR and the associated adaptor protein RHEX (regulator of hemoglobinization and erythroid cell expansion), wt-PTPN18 increased high molecular weight EPOR forms, while sharply inhibiting the EPO-induced phosphorylation of RHEX-pY141. Each effect likewise depended upon PTPN18-Y389. PTPN18 thus promotes signals for EPO-dependent hematopoietic cell growth, and may represent a new druggable target for myeloproliferative neoplasms.

Pancreatic Inflammation Redirects Acinar to ß Cell Reprogramming.

Using a transgenic mouse model to express MafA, Pdx1, and Neurog3 (3TF) in a pancreatic acinar cell- and doxycycline-dependent manner, we discovered that the outcome of transcription factor-mediated acinar to ß-like cellular reprogramming is dependent on both the magnitude of 3TF expression and on reprogramming-induced inflammation. Overly robust 3TF expression causes acinar cell necrosis, resulting in marked inflammation and acinar-to-ductal metaplasia. Generation of new ß-like cells requires limiting reprogramming-induced inflammation, either by reducing 3TF expression or by eliminating macrophages. The new ß-like cells were able to reverse streptozotocin-induced diabetes 6 days after inducing 3TF expression but failed to sustain their function after removal of the reprogramming factors.

Stat and interferon genes identified by network analysis differentially regulate primitive and definitive erythropoiesis.

BACKGROUND: Hematopoietic ontogeny is characterized by overlapping waves of primitive, fetal definitive, and adult definitive erythroid lineages. Our aim is to identify differences in the transcriptional control of these distinct erythroid cell maturation pathways by inferring and analyzing gene-interaction networks from lineage-specific expression datasets. Inferred networks are strongly connected and do not fit a scale-free model, making it difficult to identify essential regulators using the hub-essentiality standard. RESULTS: We employed a semi-supervised machine learning approach to integrate measures of network topology with expression data to score gene essentiality. The algorithm was trained and tested on the adult and fetal definitive erythroid lineages. When applied to the primitive erythroid lineage, 144 high scoring transcription factors were found to be differentially expressed between the primitive and adult definitive erythroid lineages, including all expressed STAT-family members. Differential responses of primitive and definitive erythroblasts to a Stat3 inhibitor and IFNγ in vitro supported the results of the computational analysis. Further investigation of the original expression data revealed a striking signature of Stat1-related genes in the adult definitive erythroid network. Among the potential pathways known to utilize Stat1, interferon (IFN) signaling-related genes were expressed almost exclusively within the adult definitive erythroid network. CONCLUSIONS: In vitro results support the computational prediction that differential regulation and downstream effectors of STAT signaling are key factors that distinguish the transcriptional control of primitive and definitive erythroid cell maturation.

Ontogeny of erythroid gene expression.

Erythroid ontogeny is characterized by overlapping waves of primitive and definitive erythroid lineages that share many morphologic features during terminal maturation but have marked differences in cell size and globin expression. In the present study, we compared global gene expression in primitive, fetal definitive, and adult definitive erythroid cells at morphologically equivalent stages of maturation purified from embryonic, fetal, and adult mice. Surprisingly, most transcriptional complexity in erythroid precursors is already present by the proerythroblast stage. Transcript levels are markedly modulated during terminal erythroid maturation, but housekeeping genes are not preferentially lost. Although primitive and definitive erythroid lineages share a large set of nonhousekeeping genes, annotation of lineage-restricted genes shows that alternate gene usage occurs within shared functional categories, as exemplified by the selective expression of aquaporins 3 and 8 in primitive erythroblasts and aquaporins 1 and 9 in adult definitive erythroblasts. Consistent with the known functions of Aqp3 and Aqp8 as H2O2 transporters, primitive, but not definitive, erythroblasts preferentially accumulate reactive oxygen species after exogenous H2O2 exposure. We have created a user-friendly Web site (http://www.cbil.upenn.edu/ErythronDB) to make these global expression data readily accessible and amenable to complex search strategies by the scientific community.

Dual lineage-specific expression of Sox17 during mouse embryogenesis.

Sox17 is essential for both endoderm development and fetal hematopoietic stem cell (HSC) maintenance. While endoderm-derived organs are well known to originate from Sox17-expressing cells, it is less certain whether fetal HSCs also originate from Sox17-expressing cells. By generating a Sox17(GFPCre) allele and using it to assess the fate of Sox17-expressing cells during embryogenesis, we confirmed that both endodermal and a part of definitive hematopoietic cells are derived from Sox17-positive cells. Prior to E9.5, the expression of Sox17 is restricted to the endoderm lineage. However, at E9.5 Sox17 is expressed in the endothelial cells (ECs) at the para-aortic splanchnopleural region that contribute to the formation of HSCs at a later stage. The identification of two distinct progenitor cell populations that express Sox17 at E9.5 was confirmed using fluorescence-activated cell sorting together with RNA-Seq to determine the gene expression profiles of the two cell populations. Interestingly, this analysis revealed differences in the RNA processing of the Sox17 mRNA during embryogenesis. Taken together, these results indicate that Sox17 is expressed in progenitor cells derived from two different germ layers, further demonstrating the complex expression pattern of this gene and suggesting caution when using Sox17 as a lineage-specific marker.

Conservation and divergence of known apicomplexan transcriptional regulons.

BACKGROUND: The apicomplexans are a diverse phylum of parasites causing an assortment of diseases including malaria in a wide variety of animals and lymphoproliferation in cattle. Little is known about how these varied parasites regulate their transcriptional regulons. Even less is known about how regulon systems, consisting of transcription factors and target genes together with their associated biological process, evolve in these diverse parasites. RESULTS: In order to obtain insights into the differences in transcriptional regulation between these parasites we compared the orthology profiles of putative malaria transcription factors across species and examined the enrichment patterns of four binding sites across eleven apicomplexans. About three-fifths of the factors are broadly conserved in several phylogenetic orders of sequenced apicomplexans. This observation suggests the existence of regulons whose regulation is conserved across this ancient phylum. Transcription factors not broadly conserved across the phylum are possibly involved in regulon systems that have diverged between species. Examining binding site enrichment patterns in light of transcription factor conservation patterns suggests a second mode via which regulon systems may diverge - rewiring of existing transcription factors and their associated binding sites in specific ways. Integrating binding sites with transcription factor conservation patterns also facilitated prediction of putative regulators for one of the binding sites. CONCLUSIONS: Even though transcription factors are underrepresented in apicomplexans, the distribution of these factors and their associated regulons reflect common and family-specific transcriptional regulatory processes.

Systems biology-defined NF-kappaB regulons, interacting signal pathways and networks are implicated in the malignant phenotype of head and neck cancer cell lines differing in p53 status.

BACKGROUND: Aberrant activation of the nuclear factor kappaB (NF-kappaB) pathway has been previously implicated as a crucial signal promoting tumorigenesis. However, how NF-kappaB acts as a key regulatory node to modulate global gene expression, and contributes to the malignant heterogeneity of head and neck cancer, is not well understood. RESULTS: To address this question, we used a newly developed computational strategy, COGRIM (Clustering Of Gene Regulons using Integrated Modeling), to identify NF-kappaB regulons (a set of genes under regulation of the same transcription factor) for 1,265 genes differentially expressed by head and neck cancer cell lines differing in p53 status. There were 748 NF-kappaB targets predicted and individually annotated for RELA, NFkappaB1 or cREL regulation, and a prevalence of RELA related genes was observed in over-expressed clusters in a tumor subset. Using Ingenuity Pathway Analysis, the NF-kappaB targets were reverse-engineered into annotated signature networks and pathways, revealing relationships broadly altered in cancer lines (activated proinflammatory and down-regulated Wnt/beta-catenin and transforming growth factor-beta pathways), or specifically defective in cancer subsets (growth factors, cytokines, integrins, receptors and intermediate kinases). Representatives of predicted NF-kappaB target genes were experimentally validated through modulation by tumor necrosis factor-alpha or small interfering RNA for RELA or NFkappaB1. CONCLUSION: NF-kappaB globally regulates diverse gene programs that are organized in signal networks and pathways differing in cancer subsets with distinct p53 status. The concerted alterations in gene expression patterns reflect cross-talk among NF-kappaB and other pathways, which may provide a basis for molecular classifications and targeted therapeutics for heterogeneous subsets of head and neck or other cancers.

Assessing the significance of conserved genomic aberrations using high resolution genomic microarrays.

Genomic aberrations recurrent in a particular cancer type can be important prognostic markers for tumor progression. Typically in early tumorigenesis, cells incur a breakdown of the DNA replication machinery that results in an accumulation of genomic aberrations in the form of duplications, deletions, translocations, and other genomic alterations. Microarray methods allow for finer mapping of these aberrations than has previously been possible; however, data processing and analysis methods have not taken full advantage of this higher resolution. Attention has primarily been given to analysis on the single sample level, where multiple adjacent probes are necessarily used as replicates for the local region containing their target sequences. However, regions of concordant aberration can be short enough to be detected by only one, or very few, array elements. We describe a method called Multiple Sample Analysis for assessing the significance of concordant genomic aberrations across multiple experiments that does not require a-priori definition of aberration calls for each sample. If there are multiple samples, representing a class, then by exploiting the replication across samples our method can detect concordant aberrations at much higher resolution than can be derived from current single sample approaches. Additionally, this method provides a meaningful approach to addressing population-based questions such as determining important regions for a cancer subtype of interest or determining regions of copy number variation in a population. Multiple Sample Analysis also provides single sample aberration calls in the locations of significant concordance, producing high resolution calls per sample, in concordant regions. The approach is demonstrated on a dataset representing a challenging but important resource: breast tumors that have been formalin-fixed, paraffin-embedded, archived, and subsequently UV-laser capture microdissected and hybridized to two-channel BAC arrays using an amplification protocol. We demonstrate the accurate detection on simulated data, and on real datasets involving known regions of aberration within subtypes of breast cancer at a resolution consistent with that of the array. Similarly, we apply our method to previously published datasets, including a 250K SNP array, and verify known results as well as detect novel regions of concordant aberration. The algorithm has been fully implemented and tested and is freely available as a Java application at http://www.cbil.upenn.edu/MSA.

Expansion of adult beta-cell mass in response to increased metabolic demand is dependent on HNF-4alpha.

The failure to expand functional pancreatic beta-cell mass in response to increased metabolic demand is a hallmark of type 2 diabetes. Lineage tracing studies indicate that replication of existing beta-cells is the principle mechanism for beta-cell expansion in adult mice. Here we demonstrate that the proliferative response of beta-cells is dependent on the orphan nuclear receptor hepatocyte nuclear factor-4alpha (HNF-4alpha), the gene that is mutated in Maturity-Onset Diabetes of the Young 1 (MODY1). Computational analysis of microarray expression profiles from isolated islets of mice lacking HNF-4alpha in pancreatic beta-cells reveals that HNF-4alpha regulates selected genes in the beta-cell, many of which are involved in proliferation. Using a physiological model of beta-cell expansion, we show that HNF-4alpha is required for beta-cell replication and the activation of the Ras/ERK signaling cascade in islets. This phenotype correlates with the down-regulation of suppression of tumorigenicity 5 (ST5) in HNF-4alpha mutants, which we identify as a novel regulator of ERK phosphorylation in beta-cells and a direct transcriptional target of HNF-4alpha in vivo. Together, these results indicate that HNF-4alpha is essential for the physiological expansion of adult beta-cell mass in response to increased metabolic demand.

STAC: A method for testing the significance of DNA copy number aberrations across multiple array-CGH experiments.

Regions of gain and loss of genomic DNA occur in many cancers and can drive the genesis and progression of disease. These copy number aberrations (CNAs) can be detected at high resolution by using microarray-based techniques. However, robust statistical approaches are needed to identify nonrandom gains and losses across multiple experiments/samples. We have developed a method called Significance Testing for Aberrant Copy number (STAC) to address this need. STAC utilizes two complementary statistics in combination with a novel search strategy. The significance of both statistics is assessed, and P-values are assigned to each location on the genome by using a multiple testing corrected permutation approach. We validate our method by using two published cancer data sets. STAC identifies genomic alterations known to be of clinical and biological significance and provides statistical support for 85% of previously reported regions. Moreover, STAC identifies numerous additional regions of significant gain/loss in these data that warrant further investigation. The P-values provided by STAC can be used to prioritize regions for follow-up study in an unbiased fashion. We conclude that STAC is a powerful tool for identifying nonrandom genomic amplifications and deletions across multiple experiments. A Java version of STAC is freely available for download at http://cbil.upenn.edu/STAC.

The MGED Ontology: a resource for semantics-based description of microarray experiments.

MOTIVATION: The generation of large amounts of microarray data and the need to share these data bring challenges for both data management and annotation and highlights the need for standards. MIAME specifies the minimum information needed to describe a microarray experiment and the Microarray Gene Expression Object Model (MAGE-OM) and resulting MAGE-ML provide a mechanism to standardize data representation for data exchange, however a common terminology for data annotation is needed to support these standards. RESULTS: Here we describe the MGED Ontology (MO) developed by the Ontology Working Group of the Microarray Gene Expression Data (MGED) Society. The MO provides terms for annotating all aspects of a microarray experiment from the design of the experiment and array layout, through to the preparation of the biological sample and the protocols used to hybridize the RNA and analyze the data. The MO was developed to provide terms for annotating experiments in line with the MIAME guidelines, i.e. to provide the semantics to describe a microarray experiment according to the concepts specified in MIAME. The MO does not attempt to incorporate terms from existing ontologies, e.g. those that deal with anatomical parts or developmental stages terms, but provides a framework to reference terms in other ontologies and therefore facilitates the use of ontologies in microarray data annotation. AVAILABILITY: The MGED Ontology version.1.2.0 is available as a file in both DAML and OWL formats at http://mged.sourceforge.net/ontologies/index.php. Release notes and annotation examples are provided. The MO is also provided via the NCICB's Enterprise Vocabulary System (http://nciterms.nci.nih.gov/NCIBrowser/Dictionary.do). CONTACT: Stoeckrt@pcbi.upenn.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Fidelity and enhanced sensitivity of differential transcription profiles following linear amplification of nanogram amounts of endothelial mRNA.

Although mRNA amplification is necessary for microarray analyses from limited amounts of cells and tissues, the accuracy of transcription profiles following amplification has not been well characterized. We tested the fidelity of differential gene expression following linear amplification by T7-mediated transcription in a well-established in vitro model of cytokine [tumor necrosis factor alpha (TNFalpha)]-stimulated human endothelial cells using filter arrays of 13,824 human cDNAs. Transcriptional profiles generated from amplified antisense RNA (aRNA) (from 100 ng total RNA, approximately 1 ng mRNA) were compared with profiles generated from unamplified RNA originating from the same homogeneous pool. Amplification accurately identified TNFalpha-induced differential expression in 94% of the genes detected using unamplified samples. Furthermore, an additional 1,150 genes were identified as putatively differentially expressed using amplified RNA which remained undetected using unamplified RNA. Of genes sampled from this set, 67% were validated by quantitative real-time PCR as truly differentially expressed. Thus, in addition to demonstrating fidelity in gene expression relative to unamplified samples, linear amplification results in improved sensitivity of detection and enhances the discovery potential of high-throughput screening by microarrays.

A molecular profile of a hematopoietic stem cell niche.

The hematopoietic microenvironment provides a complex molecular milieu that regulates the self-renewal and differentiation activities of stem cells. We have characterized a stem cell supportive stromal cell line, AFT024, that was derived from murine fetal liver. Highly purified in vivo transplantable mouse stem cells are maintained in AFT024 cultures at input levels, whereas other primitive progenitors are expanded. In addition, human stem cells are very effectively supported by AFT024. We suggest that the AFT024 cell line represents a component of an in vivo stem cell niche. To determine the molecular signals elaborated in this niche, we undertook a functional genomics approach that combines extensive sequence mining of a subtracted cDNA library, high-density array hybridization and in-depth bioinformatic analyses. The data have been assembled into a biological process oriented database, and represent a molecular profile of a candidate stem cell niche.

Predicting gene ontology functions from ProDom and CDD protein domains.

A heuristic algorithm for associating Gene Ontology (GO) defined molecular functions to protein domains as listed in the ProDom and CDD databases is described. The algorithm generates rules for function-domain associations based on the intersection of functions assigned to gene products by the GO consortium that contain ProDom and/or CDD domains at varying levels of sequence similarity. The hierarchical nature of GO molecular functions is incorporated into rule generation. Manual review of a subset of the rules generated indicates an accuracy rate of 87% for ProDom rules and 84% for CDD rules. The utility of these associations is that novel sequences can be assigned a putative function if sufficient similarity exists to a ProDom or CDD domain for which one or more GO functions has been associated. Although functional assignments are increasingly being made for gene products from model organisms, it is likely that the needs of investigators will continue to outpace the efforts of curators, particularly for nonmodel organisms. A comparison with other methods in terms of coverage and agreement was performed, indicating the utility of the approach. The domain-function associations and function assignments are available from our website http://www.cbil.upenn.edu/GO.