Cohesin complexes mediate sister-chromatid cohesion in dividing cells but may also contribute to gene regulation in postmitotic cells. How cohesin regulates gene expression is not known. Here we describe cohesin-binding sites in the human genome and show that most of these are associated with the CCCTC-binding factor (CTCF), a zinc-finger protein required for transcriptional insulation. CTCF is dispensable for cohesin loading onto DNA, but is needed to enrich cohesin at specific binding sites. Cohesin enables CTCF to insulate promoters from distant enhancers and controls transcription at the H19/IGF2 (insulin-like growth factor 2) locus. This role of cohesin seems to be independent of its role in cohesion. We propose that cohesin functions as a transcriptional insulator, and speculate that subtle deficiencies in this function contribute to 'cohesinopathies' such as Cornelia de Lange syndrome.

Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the ,21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community.To target the ,21,000 protein-coding genes in the human genome, we used a chemically synthesized short interfering RNA (siRNA) library designed to uniquely target each gene with 2-3 independent sequences (Supplementary Methods). The siRNAs in this library were tested individually and reduced the messenger RNAs of targeted genes to below 30% of original levels (to an average of 13%) for 97% of more than 1,000 genes tested (Supplementary Table 1). To allow high-throughput phenotyping of each individual siRNA in triplicates by live-cell imaging, we used a previously established workflow for solid-phase transfection using siRNA microarrays coupled to automatic time-lapse microscopy 1 . As a high-content phenotypic assay we chose to monitor fluorescent chromosomes in a human cell line stably expressing core histone 2B tagged with green fluorescent protein (GFP) 1 . After seeding on the siRNA microarrays, on average 67 (630) cells for each siRNA of the library were imaged in triplicates for 2 days, thus documenting many of their basic functions such as cell division, proliferation, survival and migration. Image processing reveals mitotic hitsThis resulted in a large data set of ,190,000 time-lapse movies providing time-resolved records of over 19 million cell divisions. To automatically score and annotate phenotypes in this large data set, we developed a computational pipeline 2 ( Fig. 1) extending previously established methods of morphology recognition by supervised machine learning [3][4][5][6] . In brief, after segmentation, about 200 quantitative features were extracted from each nucleus and used for classification into one of 16 morphological classes ( Fig. 1 and Supplementary Movies 1-30) by a support vector machine classifier previously trained on a set of ,3,000 manually annotated nuclei (Supplementary Methods). This classifier automatically recognizes changes in nuclear morphology due to the cell cycle, cell death or other phenotypic changes with an overall accuracy of 87% (Supplementary Fig. 1) and allows us to convert each time-lapse movie into a phenotypic profile that quantifies the response to each siRNA ...

Fine-mapping of the cell-division cycle, notably the identification of mitotic kinase signaling pathways, provides novel opportunities for cancer-drug discovery. As a key regulator of multiple steps during mitotic progression across eukaryotic species, the serine/threonine-specific Polo-like kinase 1 (Plk1) is highly expressed in malignant cells and serves as a negative prognostic marker in specific human cancer types . Here, we report the discovery of a potent small-molecule inhibitor of mammalian Plk1, BI 2536, which inhibits Plk1 enzyme activity at low nanomolar concentrations. The compound potently causes a mitotic arrest and induces apoptosis in human cancer cell lines of diverse tissue origin and oncogenome signature. BI 2536 inhibits growth of human tumor xenografts in nude mice and induces regression of large tumors with well-tolerated intravenous dose regimens. In treated tumors, cells arrest in prometaphase, accumulate phosphohistone H3, and contain aberrant mitotic spindles. This mitotic arrest is followed by a surge in apoptosis, detectable by immunohistochemistry and noninvasive optical and magnetic resonance imaging. For addressing the therapeutic potential of Plk1 inhibition, BI 2536 has progressed into clinical studies in patients with locally advanced or metastatic cancers.

The interpretation of genome sequences requires reliable and standardized methods to assess protein function at high throughput. Here we describe a fast and reliable pipeline to study protein function in mammalian cells based on protein tagging in bacterial artificial chromosomes (BACs). The large size of the BAC transgenes ensures the presence of most, if not all, regulatory elements and results in expression that closely matches that of the endogenous gene. We show that BAC transgenes can be rapidly and reliably generated using 96-well-format recombineering. After stable transfection of these transgenes into human tissue culture cells or mouse embryonic stem URL.The BACFinder clone search and oligo design tool is available online at http://www.mitocheck.org/cgi-bin/BACfinder.Database accession codes. The ChIP/chip data has been submitted to the Gene Expression Omnibus database with accession number GSE10845. COMPETING INTERESTS STATEMENTThe authors declare competing financial interests: details accompany the full-text HTML version of the paper at http:// www.nature.com/naturemethods/. Europe PMC Funders GroupAuthor Manuscript Nat Methods. Author manuscript; available in PMC 2010 May 17. Europe PMC Funders Author ManuscriptsEurope PMC Funders Author Manuscripts cells, the localization, protein-protein and/or protein-DNA interactions of the tagged protein are studied using generic, tag-based assays. The same high-throughput approach will be generally applicable to other model systems.At a time when the 'thousand-dollar genome' seems a realistic goal for the near future, methods for dissecting the functions of the encoded genetic information lag far behind the genome sequence, both in throughput and in quality of the produced data. Genome sequencing and subsequent bioinformatics analysis have made it possible to study the function of genes in mammalian tissue culture cells using systematic reverse-genetic approaches1-3 and have radically improved researchers' ability to identify human disease genes. Such studies typically identify single genes, whose biological function has often not yet been described. In order to place the proteins these genes encode in pathways, these studies must be followed by detailed molecular-level analysis, of which the most powerful types are protein localization and protein-protein interaction. The power of protein localization and protein-protein interaction studies can be seen from the genome-wide application of GFP localization and tandem affinity tag-based complex purification in the yeast Saccharomyces cerevisiae, which has produced a comprehensive picture of the core proteome of a simple, well-studied model system4-8. The key advantage of yeast for these studies was their efficient intrinsic homologous recombination, which allowed the same tagcoding sequence to be introduced at the endogenous locus of nearly every gene of the genome. The tagged proteins were then systematically analyzed through standardized, generic, tag-based assays.To transfer this approach to mammali...

Mammalian genomes are spatially organized by CCCTC-binding factor (CTCF) and cohesin into chromatin loops and topologically associated domains, which have important roles in gene regulation and recombination. By binding to specific sequences, CTCF defines contact points for cohesin-mediated long-range chromosomal cis-interactions. Cohesin is also present at these sites, but has been proposed to be loaded onto DNA elsewhere and to extrude chromatin loops until it encounters CTCF bound to DNA. How cohesin is recruited to CTCF sites, according to this or other models, is unknown. Here we show that the distribution of cohesin in the mouse genome depends on transcription, CTCF and the cohesin release factor Wings apart-like (Wapl). In CTCF-depleted fibroblasts, cohesin cannot be properly recruited to CTCF sites but instead accumulates at transcription start sites of active genes, where the cohesin-loading complex is located. In the absence of both CTCF and Wapl, cohesin accumulates in up to 70 kilobase-long regions at 3'-ends of active genes, in particular if these converge on each other. Changing gene expression modulates the position of these 'cohesin islands'. These findings indicate that transcription can relocate mammalian cohesin over long distances on DNA, as previously reported for yeast cohesin, that this translocation contributes to positioning cohesin at CTCF sites, and that active genes can be freed from cohesin either by transcription-mediated translocation or by Wapl-mediated release.