Gene expression profiling has uncovered the transcription factor Sox4 with upregulated activity during TGF-β-induced epithelial-mesenchymal transition (EMT) in normal and cancerous breast epithelial cells. Sox4 is indispensable for EMT and cell survival in vitro and for primary tumor growth and metastasis in vivo. Among several EMT-relevant genes, Sox4 directly regulates the expression of Ezh2, encoding the Polycomb group histone methyltransferase that trimethylates histone 3 lysine 27 (H3K27me3) for gene repression. Ablation of Ezh2 expression prevents EMT, whereas forced expression of Ezh2 restores EMT in Sox4-deficient cells. Ezh2-mediated H3K27me3 marks associate with key EMT genes, representing an epigenetic EMT signature that predicts patient survival. Our results identify Sox4 as a master regulator of EMT by governing the expression of the epigenetic modifier Ezh2.

Studies of microbial evolutionary dynamics are being transformed by the availability of affordable high-throughput sequencing technologies, which allow whole-genome sequencing of hundreds of related taxa in a single study. Reconstructing a phylogenetic tree of these taxa is generally a crucial step in any evolutionary analysis. Instead of constructing genome assemblies for all taxa, annotating these assemblies, and aligning orthologous genes, many recent studies 1) directly map raw sequencing reads to a single reference sequence, 2) extract single nucleotide polymorphisms (SNPs), and 3) infer the phylogenetic tree using maximum likelihood methods from the aligned SNP positions. However, here we show that, when using such methods to reconstruct phylogenies from sets of simulated sequences, both the exclusion of nonpolymorphic positions and the alignment to a single reference genome, introduce systematic biases and errors in phylogeny reconstruction. To address these problems, we developed a new method that combines alignments from mappings to multiple reference sequences and show that this successfully removes biases from the reconstructed phylogenies. We implemented this method as a web server named REALPHY (Reference sequence Alignment-based Phylogeny builder), which fully automates phylogenetic reconstruction from raw sequencing reads.

Accurate reconstruction of the regulatory networks that control gene expression is one of the key current challenges in molecular biology. Although gene expression and chromatin state dynamics are ultimately encoded by constellations of binding sites recognized by regulators such as transcriptions factors (TFs) and microRNAs (miRNAs), our understanding of this regulatory code and its context-dependent read-out remains very limited. Given that there are thousands of potential regulators in mammals, it is not practical to use direct experimentation to identify which of these play a key role for a particular system of interest. We developed a methodology that models gene expression or chromatin modifications in terms of genome-wide predictions of regulatory sites and completely automated it into a web-based tool called ISMARA (Integrated System for Motif Activity Response Analysis). Given only gene expression or chromatin state data across a set of samples as input, ISMARA identifies the key TFs and miRNAs driving expression/chromatin changes and makes detailed predictions regarding their regulatory roles. These include predicted activities of the regulators across the samples, their genome-wide targets, enriched gene categories among the targets, and direct interactions between the regulators. Applying ISMARA to data sets from well-studied systems, we show that it consistently identifies known key regulators ab initio. We also present a number of novel predictions including regulatory interactions in innate immunity, a master regulator of mucociliary differentiation, TFs consistently disregulated in cancer, and TFs that mediate specific chromatin modifications.

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.

In obesity, white adipose tissue (WAT) inflammation is linked to insulin resistance. Increased adipocyte chemokine (C-C motif) ligand 2 (CCL2) secretion may initiate adipose inflammation by attracting the migration of inflammatory cells into the tissue. Using an unbiased approach, we identified adipose microRNAs (miRNAs) that are dysregulated in human obesity and assessed their possible role in controlling CCL2 production. In subcutaneous WAT obtained from 56 subjects, 11 miRNAs were present in all subjects and downregulated in obesity. Of these, 10 affected adipocyte CCL2 secretion in vitro and for 2 miRNAs (miR-126 and miR-193b), regulatory circuits were defined. While miR-126 bound directly to the 3′-untranslated region of CCL2 mRNA, miR-193b regulated CCL2 production indirectly through a network of transcription factors, many of which have been identified in other inflammatory conditions. In addition, overexpression of miR-193b and miR-126 in a human monocyte/macrophage cell line attenuated CCL2 production. The levels of the two miRNAs in subcutaneous WAT were significantly associated with CCL2 secretion (miR-193b) and expression of integrin, α-X, an inflammatory macrophage marker (miR-193b and miR-126). Taken together, our data suggest that miRNAs may be important regulators of adipose inflammation through their effects on CCL2 release from human adipocytes and macrophages.

New cancer therapies are likely to arise from an in-depth understanding of the signaling networks influencing tumor initiation, progression and metastasis. We show a fundamental role for Src-homology 2 domain-containing phosphatase 2 (SHP2) in these processes in human epidermal growth factor receptor 2 (HER2)-positive and triple-negative breast cancers. Knockdown of SHP2 eradicated breast tumor-initiating cells in xenograft models, and SHP2 depletion also prevented invasion in three-dimensional cultures and in a transductal invasion assay in vivo. Notably, SHP2 knockdown in established breast tumors blocked their growth and reduced metastasis. Mechanistically, SHP2 activated stemness-associated transcription factors, including v-myc myelocytomatosis viral oncogene homolog (c-Myc) and zinc finger E-box binding homeobox 1 (ZEB1), which resulted in the repression of let-7 microRNA and the expression of a set of 'SHP2 signature' genes. We found these genes to be simultaneously activated in a large subset of human primary breast tumors that are associated with invasive behavior and poor prognosis. These results provide new insights into the signaling cascades influencing tumor-initiating cells as well as a rationale for targeting SHP2 in breast cancer.

We have identified the zinc-finger transcription factor Kruppel-like factor 4 (Klf4) among the transcription factors that are significantly downregulated in their expression during epithelial-mesenchymal transition (EMT) in mammary epithelial cells and in breast cancer cells. Loss and gain of function experiments demonstrate that the down-regulation of Klf4 expression is required for the induction of EMT in vitro and for metastasis in vivo. In addition, reduced Klf4 expression correlates with shorter disease-free survival of subsets of breast cancer patients. Yet, reduced expression of Klf4 also induces apoptosis in cells undergoing TGFβ-induced EMT. Chromatin immunoprecipitation/deep-sequencing in combination with gene expression profiling reveals direct Klf4 target genes, including E-cadherin (Cdh1), N-cadherin (Cdh2), vimentin (Vim), β-catenin (Ctnnb1), VEGF-A (Vegfa), endothelin-1 (Edn1) and Jnk1 (Mapk8). Thereby, Klf4 acts as a transcriptional activator of epithelial genes and as a repressor of mesenchymal genes. Specifically, increased expression of Jnk1 (Mapk8) upon down-regulation of its transcriptional repressor Klf4 is required for EMT cell migration and for the induction of apoptosis. The data demonstrate a central role of Klf4 in the maintenance of epithelial cell differentiation and the prevention of EMT and metastasis.

SwissRegulon () is a database containing genome-wide annotations of regulatory sites in the intergenic regions of genomes. The regulatory site annotations are produced using a number of recently developed algorithms that operate on multiple alignments of orthologous intergenic regions from related genomes in combination with, whenever available, known sites from the literature, and ChIP-on-chip binding data. Currently SwissRegulon contains annotations for yeast and 17 prokaryotic genomes. The database provides information about the sequence, location, orientation, posterior probability and, whenever available, binding factor of each annotated site. To enable easy viewing of the regulatory site annotations in the context of other features annotated on the genomes, the sites are displayed using the GBrowse genome browser interface and can be queried based on any annotated genomic feature. The database can also be queried for regulons, i.e. sites bound by a common factor.