The most highly conserved noncoding elements (HCNEs) in mammalian genomes cluster within regions enriched for genes encoding developmentally important transcription factors (TFs). This suggests that HCNE-rich regions may contain key regulatory controls involved in development. We explored this by examining histone methylation in mouse embryonic stem (ES) cells across 56 large HCNE-rich loci. We identified a specific modification pattern, termed "bivalent domains," consisting of large regions of H3 lysine 27 methylation harboring smaller regions of H3 lysine 4 methylation. Bivalent domains tend to coincide with TF genes expressed at low levels. We propose that bivalent domains silence developmental genes in ES cells while keeping them poised for activation. We also found striking correspondences between genome sequence and histone methylation in ES cells, which become notably weaker in differentiated cells. These results highlight the importance of DNA sequence in defining the initial epigenetic landscape and suggest a novel chromatin-based mechanism for maintaining pluripotency.

Transcription factors (TFs) and their specific interactions with targets are crucial for specifying gene-expression programs. To gain insights into the transcriptional regulatory networks in embryonic stem (ES) cells, we use chromatin immunoprecipitation coupled with ultra-high-throughput DNA sequencing (ChIP-seq) to map the locations of 13 sequence-specific TFs (Nanog, Oct4, STAT3, Smad1, Sox2, Zfx, c-Myc, n-Myc, Klf4, Esrrb, Tcfcp2l1, E2f1, and CTCF) and 2 transcription regulators (p300 and Suz12). These factors are known to play different roles in ES-cell biology as components of the LIF and BMP signaling pathways, self-renewal regulators, and key reprogramming factors. Our study provides insights into the integration of the signaling pathways into the ES-cell-specific transcription circuitries. Intriguingly, we find specific genomic regions extensively targeted by different TFs. Collectively, the comprehensive mapping of TF-binding sites identifies important features of the transcriptional regulatory networks that define ES-cell identity.

Long-read single-molecule sequencing has revolutionized de novo genome assembly and enabled the automated reconstruction of reference-quality genomes. However, given the relatively high error rates of such technologies, efficient and accurate assembly of large repeats and closely related haplotypes remains challenging. We address these issues with Canu, a successor of Celera Assembler that is specifically designed for noisy single-molecule sequences. Canu introduces support for nanopore sequencing, halves depth-of-coverage requirements, and improves assembly continuity while simultaneously reducing runtime by an order of magnitude on large genomes versus Celera Assembler 8.2. These advances result from new overlapping and assembly algorithms, including an adaptive overlapping strategy based on tf-idf weighted MinHash and a sparse assembly graph construction that avoids collapsing diverged repeats and haplotypes. We demonstrate that Canu can reliably assemble complete microbial genomes and near-complete eukaryotic chromosomes using either Pacific Biosciences (PacBio) or Oxford Nanopore technologies and achieves a contig NG50 of >21 Mbp on both human and Drosophila melanogaster PacBio data sets. For assembly structures that cannot be linearly represented, Canu provides graph-based assembly outputs in graphical fragment assembly (GFA) format for analysis or integration with complementary phasing and scaffolding techniques. The combination of such highly resolved assembly graphs with long-range scaffolding information promises the complete and automated assembly of complex genomes.

The past decade has witnessed hundreds of reports declaring or refuting genetic association with putative Alzheimer disease susceptibility genes. This wealth of information has become increasingly difficult to follow, much less interpret. We have created a publicly available, continuously updated database that comprehensively catalogs all genetic association studies in the field of Alzheimer disease (http://www.alzgene.org). We performed systematic meta-analyses for each polymorphism with available genotype data in at least three case-control samples. In addition to identifying the epsilon4 allele of APOE and related effects, we pinpointed over a dozen potential Alzheimer disease susceptibility genes (ACE, CHRNB2, CST3, ESR1, GAPDHS, IDE, MTHFR, NCSTN, PRNP, PSEN1, TF, TFAM and TNF) with statistically significant allelic summary odds ratios (ranging from 1.11-1.38 for risk alleles and 0.92-0.67 for protective alleles). Our database provides a powerful tool for deciphering the genetics of Alzheimer disease, and it serves as a potential model for tracking the most viable gene candidates in other genetically complex diseases.

Members of the nuclear factor kappa B (NF-kappaB) family of dimeric transcription factors (TFs) regulate expression of a large number of genes involved in immune responses, inflammation, cell survival, and cancer. NF-kappaB TFs are rapidly activated in response to various stimuli, including cytokines, infectious agents, and radiation-induced DNA double-strand breaks. In nonstimulated cells, some NF-kappaB TFs are bound to inhibitory IkappaB proteins and are thereby sequestered in the cytoplasm. Activation leads to phosphorylation of IkappaB proteins and their subsequent recognition by ubiquitinating enzymes. The resulting proteasomal degradation of IkappaB proteins liberates IkappaB-bound NF-kappaB TFs, which translocate to the nucleus to drive expression of target genes. Two protein kinases with a high degree of sequence similarity, IKKalpha and IKKbeta, mediate phosphorylation of IkappaB proteins and represent a convergence point for most signal transduction pathways leading to NF-kappaB activation. Most of the IKKalpha and IKKbeta molecules in the cell are part of IKK complexes that also contain a regulatory subunit called IKKgamma or NEMO. Despite extensive sequence similarity, IKKalpha and IKKbeta have largely distinct functions, due to their different substrate specificities and modes of regulation. IKKbeta (and IKKgamma) are essential for rapid NF-kappaB activation by proinflammatory signaling cascades, such as those triggered by tumor necrosis factor alpha (TNFalpha) or lipopolysaccharide (LPS). In contrast, IKKalpha functions in the activation of a specific form of NF-kappaB in response to a subset of TNF family members and may also serve to attenuate IKKbeta-driven NF-kappaB activation. Moreover, IKKalpha is involved in keratinocyte differentiation, but this function is independent of its kinase activity. Several years ago, two protein kinases, one called IKKepsilon or IKK-i and one variously named TBK1 (TANK-binding kinase), NAK (NF-kappaB-activated kinase), or T2K (TRAF2-associated kinase), were identified that exhibit structural similarity to IKKalpha and IKKbeta. These protein kinases are important for the activation of interferon response factor 3 (IRF3) and IRF7, TFs that play key roles in the induction of type I interferon (IFN-I). Together, the IKKs and IKK-related kinases are instrumental for activation of the host defense system. This Review focuses on the functions of IKK and IKK-related kinases and the molecular mechanisms that regulate their activities.

BACKGROUND

Advances in high-throughput sequencing have resulted in rapid growth in large, high-quality datasets including those arising from transcription factor (TF) ChIP-seq experiments. While there are many existing tools for discovering TF binding site motifs in such datasets, most web-based tools cannot directly process such large datasets.

RESULTS

The MEME-ChIP web service is designed to analyze ChIP-seq 'peak regions'--short genomic regions surrounding declared ChIP-seq 'peaks'. Given a set of genomic regions, it performs (i) ab initio motif discovery, (ii) motif enrichment analysis, (iii) motif visualization, (iv) binding affinity analysis and (v) motif identification. It runs two complementary motif discovery algorithms on the input data--MEME and DREME--and uses the motifs they discover in subsequent visualization, binding affinity and identification steps. MEME-ChIP also performs motif enrichment analysis using the AME algorithm, which can detect very low levels of enrichment of binding sites for TFs with known DNA-binding motifs. Importantly, unlike with the MEME web service, there is no restriction on the size or number of uploaded sequences, allowing very large ChIP-seq datasets to be analyzed. The analyses performed by MEME-ChIP provide the user with a varied view of the binding and regulatory activity of the ChIP-ed TF, as well as the possible involvement of other DNA-binding TFs.

BACKGROUND

MEME-ChIP is available as part of the MEME Suite at http://meme.nbcr.net.

The epithelial-to-mesenchymal transition (EMT) produces cancer cells that are invasive, migratory, and exhibit stem cell characteristics, hallmarks of cells that have the potential to generate metastases. Inducers of the EMT include several transcription factors (TFs), such as Goosecoid, Snail, and Twist, as well as the secreted TGF-beta1. Each of these factors is capable, on its own, of inducing an EMT in the human mammary epithelial (HMLE) cell line. However, the interactions between these regulators are poorly understood. Overexpression of each of the above EMT inducers up-regulates a subset of other EMT-inducing TFs, with Twist, Zeb1, Zeb2, TGF-beta1, and FOXC2 being commonly induced. Up-regulation of Slug and FOXC2 by either Snail or Twist does not depend on TGF-beta1 signaling. Gene expression signatures (GESs) derived by overexpressing EMT-inducing TFs reveal that the Twist GES and Snail GES are the most similar, although the Goosecoid GES is the least similar to the others. An EMT core signature was derived from the changes in gene expression shared by up-regulation of Gsc, Snail, Twist, and TGF-beta1 and by down-regulation of E-cadherin, loss of which can also trigger an EMT in certain cell types. The EMT core signature associates closely with the claudin-low and metaplastic breast cancer subtypes and correlates negatively with pathological complete response. Additionally, the expression level of FOXC1, another EMT inducer, correlates strongly with poor survival of breast cancer patients.

For many compounds (neurotrophic factors, antibodies, growth factors, genetic vectors, enzymes) slow diffusion in the brain severely limits drug distribution and effect after direct drug administration into brain parenchyma. We investigated convection as a means to enhance the distribution of the large and small molecules 111In-labeled transferrin (111In-Tf; M(r), 80,000) and [14C]sucrose (M(r), 359) over centimeter distances by maintaining a pressure gradient during interstitial infusion into white matter to generate bulk flow through the brain interstitium. The volume of distribution (Vd) containing>> or = 1% concentration of infusion solution increased linearly with the infusion volume (Vi) for 111In-Tf(Vd/Vi, 6:1) and [14C]sucrose (Vd/Vi, 13:1). Twenty-four hours after infusion, the distribution of 111In-Tf was increased and more homogeneous, and penetration into gray matter had occurred. By using convection to supplement simple diffusion, enhanced distribution of large and small molecules can be obtained in the brain while achieving drug concentrations orders of magnitude greater than systemic levels.

Although the proteins that read the gene regulatory code, transcription factors (TFs), have been largely identified, it is not well known which sequences TFs can recognize. We have analyzed the sequence-specific binding of human TFs using high-throughput SELEX and ChIP sequencing. A total of 830 binding profiles were obtained, describing 239 distinctly different binding specificities. The models represent the majority of human TFs, approximately doubling the coverage compared to existing systematic studies. Our results reveal additional specificity determinants for a large number of factors for which a partial specificity was known, including a commonly observed A- or T-rich stretch that flanks the core motifs. Global analysis of the data revealed that homodimer orientation and spacing preferences, and base-stacking interactions, have a larger role in TF-DNA binding than previously appreciated. We further describe a binding model incorporating these features that is required to understand binding of TFs to DNA.

JASPAR (http://jaspar.genereg.net) is the leading open-access database of matrix profiles describing the DNA-binding patterns of transcription factors (TFs) and other proteins interacting with DNA in a sequence-specific manner. Its fourth major release is the largest expansion of the core database to date: the database now holds 457 non-redundant, curated profiles. The new entries include the first batch of profiles derived from ChIP-seq and ChIP-chip whole-genome binding experiments, and 177 yeast TF binding profiles. The introduction of a yeast division brings the convenience of JASPAR to an active research community. As binding models are refined by newer data, the JASPAR database now uses versioning of matrices: in this release, 12% of the older models were updated to improved versions. Classification of TF families has been improved by adopting a new DNA-binding domain nomenclature. A curated catalog of mammalian TFs is provided, extending the use of the JASPAR profiles to additional TFs belonging to the same structural family. The changes in the database set the system ready for more rapid acquisition of new high-throughput data sources. Additionally, three new special collections provide matrix profile data produced by recent alternative high-throughput approaches.

Transcription factors (TFs) direct gene expression by binding to DNA regulatory regions. To explore the evolution of gene regulation, we used chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq) to determine experimentally the genome-wide occupancy of two TFs, CCAAT/enhancer-binding protein alpha and hepatocyte nuclear factor 4 alpha, in the livers of five vertebrates. Although each TF displays highly conserved DNA binding preferences, most binding is species-specific, and aligned binding events present in all five species are rare. Regions near genes with expression levels that are dependent on a TF are often bound by the TF in multiple species yet show no enhanced DNA sequence constraint. Binding divergence between species can be largely explained by sequence changes to the bound motifs. Among the binding events lost in one lineage, only half are recovered by another binding event within 10 kilobases. Our results reveal large interspecies differences in transcriptional regulation and provide insight into regulatory evolution.

Th17 cells have critical roles in mucosal defense and are major contributors to inflammatory disease. Their differentiation requires the nuclear hormone receptor RORγt working with multiple other essential transcription factors (TFs). We have used an iterative systems approach, combining genome-wide TF occupancy, expression profiling of TF mutants, and expression time series to delineate the Th17 global transcriptional regulatory network. We find that cooperatively bound BATF and IRF4 contribute to initial chromatin accessibility and, with STAT3, initiate a transcriptional program that is then globally tuned by the lineage-specifying TF RORγt, which plays a focal deterministic role at key loci. Integration of multiple data sets allowed inference of an accurate predictive model that we computationally and experimentally validated, identifying multiple new Th17 regulators, including Fosl2, a key determinant of cellular plasticity. This interconnected network can be used to investigate new therapeutic approaches to manipulate Th17 functions in the setting of inflammatory disease.

Regulatory networks orchestrated by key transcription factors (TFs) have been proposed to play a central role in the determination of stem cell states. However, the master transcriptional regulators of adult stem cells are poorly understood. We have identified two TFs, Slug and Sox9, that act cooperatively to determine the mammary stem cell (MaSC) state. Inhibition of either Slug or Sox9 blocks MaSC activity in primary mammary epithelial cells. Conversely, transient coexpression of exogenous Slug and Sox9 suffices to convert differentiated luminal cells into MaSCs with long-term mammary gland-reconstituting ability. Slug and Sox9 induce MaSCs by activating distinct autoregulatory gene expression programs. We also show that coexpression of Slug and Sox9 promotes the tumorigenic and metastasis-seeding abilities of human breast cancer cells and is associated with poor patient survival, providing direct evidence that human breast cancer stem cells are controlled by key regulators similar to those operating in normal murine MaSCs.

The epithelial-mesenchymal transition (EMT) confers mesenchymal properties on epithelial cells and has been closely associated with the acquisition of aggressive traits by carcinoma cells. EMT programs are orchestrated by a set of pleiotropically acting transcription factors (TFs). The actions of these EMT-TFs enable the early steps of metastasis: local invasion and subsequent dissemination of carcinoma cells to distant sites. However, in most malignancies, the subsequent outgrowth of micrometastatic deposits into macroscopic metastases has the greatest impact on clinical progression. Such metastatic "colonization" reflects the ability of disseminated tumor cells to adapt to a foreign tissue microenvironment. The outgrowth of a metastasis is also thought to be associated with self-renewal, the defining cellular trait of cancer stem cells (CSCs), also termed tumor-initiating cells. Importantly, molecular links between EMT-TFs and self-renewal have emerged, suggesting that EMT programs play critical roles both early and late in the metastatic cascade. The genetic and epigenetic mechanisms that regulate the activation of EMT-TFs and the traits they induce are areas under intensive investigation. Such studies may provide new opportunities for therapeutic intervention and help to overcome tumor heterogeneity and therapeutic resistance.

Deep vein thrombosis (DVT) is a major cause of cardiovascular death. The sequence of events that promote DVT remains obscure, largely as a result of the lack of an appropriate rodent model. We describe a novel mouse model of DVT which reproduces a frequent trigger and resembles the time course, histological features, and clinical presentation of DVT in humans. We demonstrate by intravital two-photon and epifluorescence microscopy that blood monocytes and neutrophils crawling along and adhering to the venous endothelium provide the initiating stimulus for DVT development. Using conditional mutants and bone marrow chimeras, we show that intravascular activation of the extrinsic pathway of coagulation via tissue factor (TF) derived from myeloid leukocytes causes the extensive intraluminal fibrin formation characteristic of DVT. We demonstrate that thrombus-resident neutrophils are indispensable for subsequent DVT propagation by binding factor XII (FXII) and by supporting its activation through the release of neutrophil extracellular traps (NETs). Correspondingly, neutropenia, genetic ablation of FXII, or disintegration of NETs each confers protection against DVT amplification. Platelets associate with innate immune cells via glycoprotein Ibα and contribute to DVT progression by promoting leukocyte recruitment and stimulating neutrophil-dependent coagulation. Hence, we identified a cross talk between monocytes, neutrophils, and platelets responsible for the initiation and amplification of DVT and for inducing its unique clinical features.

Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.

Chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) has become the dominant technique for mapping transcription factor (TF) binding regions genome-wide. We performed an integrative analysis centered around 457 ChIP-seq data sets on 119 human TFs generated by the ENCODE Consortium. We identified highly enriched sequence motifs in most data sets, revealing new motifs and validating known ones. The motif sites (TF binding sites) are highly conserved evolutionarily and show distinct footprints upon DNase I digestion. We frequently detected secondary motifs in addition to the canonical motifs of the TFs, indicating tethered binding and cobinding between multiple TFs. We observed significant position and orientation preferences between many cobinding TFs. Genes specifically expressed in a cell line are often associated with a greater occurrence of nearby TF binding in that cell line. We observed cell-line-specific secondary motifs that mediate the binding of the histone deacetylase HDAC2 and the enhancer-binding protein EP300. TF binding sites are located in GC-rich, nucleosome-depleted, and DNase I sensitive regions, flanked by well-positioned nucleosomes, and many of these features show cell type specificity. The GC-richness may be beneficial for regulating TF binding because, when unoccupied by a TF, these regions are occupied by nucleosomes in vivo. We present the results of our analysis in a TF-centric web repository Factorbook (http://factorbook.org) and will continually update this repository as more ENCODE data are generated.

Combinatorial transcription factor (TF) interactions control cellular phenotypes and, therefore, underpin stem cell formation, maintenance, and differentiation. Here, we report the genome-wide binding patterns and combinatorial interactions for ten key regulators of blood stem/progenitor cells (SCL/TAL1, LYL1, LMO2, GATA2, RUNX1, MEIS1, PU.1, ERG, FLI-1, and GFI1B), thus providing the most comprehensive TF data set for any adult stem/progenitor cell type to date. Genome-wide computational analysis of complex binding patterns, followed by functional validation, revealed the following: first, a previously unrecognized combinatorial interaction between a heptad of TFs (SCL, LYL1, LMO2, GATA2, RUNX1, ERG, and FLI-1). Second, we implicate direct protein-protein interactions between four key regulators (RUNX1, GATA2, SCL, and ERG) in stabilizing complex binding to DNA. Third, Runx1(+/-)::Gata2(+/-) compound heterozygous mice are not viable with severe hematopoietic defects at midgestation. Taken together, this study demonstrates the power of genome-wide analysis in generating novel functional insights into the transcriptional control of stem and progenitor cells.

BACKGROUND

Transcription factor (TF) ChIP-seq datasets have particular characteristics that provide unique challenges and opportunities for motif discovery. Most existing motif discovery algorithms do not scale well to such large datasets, or fail to report many motifs associated with cofactors of the ChIP-ed TF.

RESULTS

We present DREME, a motif discovery algorithm specifically designed to find the short, core DNA-binding motifs of eukaryotic TFs, and optimized to analyze very large ChIP-seq datasets in minutes. Using DREME, we discover the binding motifs of the the ChIP-ed TF and many cofactors in mouse ES cell (mESC), mouse erythrocyte and human cell line ChIP-seq datasets. For example, in mESC ChIP-seq data for the TF Esrrb, we discover the binding motifs for eight cofactor TFs important in the maintenance of pluripotency. Several other commonly used algorithms find at most two cofactor motifs in this same dataset. DREME can also perform discriminative motif discovery, and we use this feature to provide evidence that Sox2 and Oct4 do not bind in mES cells as an obligate heterodimer. DREME is much faster than many commonly used algorithms, scales linearly in dataset size, finds multiple, non-redundant motifs and reports a reliable measure of statistical significance for each motif found. DREME is available as part of the MEME Suite of motif-based sequence analysis tools (http://meme.nbcr.net).

Differences in gene expression may play a major role in speciation and phenotypic diversity. We examined genome-wide differences in transcription factor (TF) binding in several humans and a single chimpanzee by using chromatin immunoprecipitation followed by sequencing. The binding sites of RNA polymerase II (PolII) and a key regulator of immune responses, nuclear factor kappaB (p65), were mapped in 10 lymphoblastoid cell lines, and 25 and 7.5% of the respective binding regions were found to differ between individuals. Binding differences were frequently associated with single-nucleotide polymorphisms and genomic structural variants, and these differences were often correlated with differences in gene expression, suggesting functional consequences of binding variation. Furthermore, comparing PolII binding between humans and chimpanzee suggests extensive divergence in TF binding. Our results indicate that many differences in individuals and species occur at the level of TF binding, and they provide insight into the genetic events responsible for these differences.

Three defining clinical symptoms of autism are aberrant reciprocal social interactions, deficits in social communication, and repetitive behaviors, including motor stereotypies and insistence on sameness. We developed a set of behavioral tasks designed to model components of these core symptoms in mice. Male mice from 10 inbred strains were characterized in assays for sociability, preference for social novelty, and reversal of the spatial location of the reinforcer in T-maze and Morris water maze tasks. Six strains, C57BL/6J, C57L/J, DBA/2J, FVB/NJ, C3H/HeJ, and AKR/J, showed significant levels of sociability, while A/J, BALB/cByJ, BTBR T(+)tf/J, and 129S1/SvImJ mice did not. C57BL/6J, C57L/J, DBA/2J, FVB/NJ, BALB/cByJ, and BTBR T(+)tf/J showed significant preference for social novelty, while C3H/HeJ, AKR/J, A/J, and 129S1/SvImJ did not. Normal scores on relevant control measures confirmed general health and physical abilities in all strains, ruling out artifactual explanations for social deficits. Elevated plus maze scores confirmed high anxiety-like behaviors in A/J, BALB/cByJ, and 129S1/SvImJ, which could underlie components of their low social approach. Strains that showed high levels of performance on acquisition of a T-maze task were also able to reach criterion for reversal learning. On the Morris water maze task, DBA/2J, AKR/J, BTBR T(+)tf/J, and 129S1/SvImJ failed to show significant quadrant preference during the reversal probe trial. These results highlight a dissociation between social task performance and reversal learning. BTBR T(+)tf/J is a particularly interesting strain, displaying both low social approach and resistance to change in routine on the water maze, consistent with an autism-like phenotype. Our multitask strategy for modeling symptoms of autism will be useful for investigating targeted and random gene mutations, QTLs, and microarray analyses.

Transcription factors (TFs) interact with specific DNA regulatory sequences to control gene expression throughout myriad cellular processes. However, the DNA binding specificities of only a small fraction of TFs are sufficiently characterized to predict the sequences that they can and cannot bind. We present a maximally compact, synthetic DNA sequence design for protein binding microarray (PBM) experiments that represents all possible DNA sequence variants of a given length k (that is, all 'k-mers') on a single, universal microarray. We constructed such all k-mer microarrays covering all 10-base pair (bp) binding sites by converting high-density single-stranded oligonucleotide arrays to double-stranded (ds) DNA arrays. Using these microarrays we comprehensively determined the binding specificities over a full range of affinities for five TFs of different structural classes from yeast, worm, mouse and human. The unbiased coverage of all k-mers permits high-throughput interrogation of binding site preferences, including nucleotide interdependencies, at unprecedented resolution.

MicroRNAs (miRs) are small noncoding RNAs that regulate gene expression primarily through translational repression. In erythropoietic (E) culture of cord blood CD34+ progenitor cells, the level of miR 221 and 222 is gradually and sharply down-modulated. Hypothetically, this decline could promote erythropoiesis by unblocking expression of key functional proteins. Indeed, (i) bioinformatic analysis suggested that miR 221 and 222 target the 3' UTR of kit mRNA; (ii) the luciferase assay confirmed that both miRs directly interact with the kit mRNA target site; and (iii) in E culture undergoing exponential cell growth, miR down-modulation is inversely related to increasing kit protein expression, whereas the kit mRNA level is relatively stable. Functional studies show that treatment of CD34+ progenitors with miR 221 and 222, via oligonucleotide transfection or lentiviral vector infection, causes impaired proliferation and accelerated differentiation of E cells, coupled with down-modulation of kit protein: this phenomenon, observed in E culture releasing endogenous kit ligand, is magnified in E culture supplemented with kit ligand. Furthermore, transplantation experiments in NOD-SCID mice reveal that miR 221 and 222 treatment of CD34+ cells impairs their engraftment capacity and stem cell activity. Finally, miR 221 and 222 gene transfer impairs proliferation of the kit+ TF-1 erythroleukemic cell line. Altogether, our studies indicate that the decline of miR 221 and 222 during exponential E growth unblocks kit protein production at mRNA level, thus leading to expansion of early erythroblasts. Furthermore, the results on kit+ erythroleukemic cells suggest a potential role of these miRs in cancer therapy.

Tissue factor (TF), the primary cellular initiator of the coagulation protease cascade, is implicated in having important roles in hemostasis, thrombogenesis, inflammation, and the cellular immune response, although the cytologic distribution of TF in tissues has yet to be described. This study used epitope-defined monoclonal antibodies to human tissue factor for immunohistochemical localization of TF in normal human tissues. TF was selectively expressed in tissues and was associated with cells rather than extracellular matrix. It was anatomically sequestered from blood, being undetectable in endothelium and peripheral blood cells. TF was present in vascular adventitia, organ capsules, epidermis, and mucosal epithelium. Most dermal and submucosal fibroblasts were negative. Except for alveolar macrophages and possibly dendritic cells of some lymphoid follicles, tissue macrophages did not express TF; (expression was demonstrable in LPS stimulated monocytes). Cerebral cortex, renal glomeruli, and cardiac myocytes were additional sites of prominent TF expression. Based on the cellular distribution of TF, it is hypothesized that intravascular initiation of coagulation requires induced expression by intravascular cells, and that the normal distribution of TF represents a hemostatic "envelope" ready to activate coagulation when vascular integrity is disrupted.