In eukaryotic cells, cohesin holds sister chromatids together until they separate into daughter cells during mitosis. We have used chromatin immunoprecipitation coupled with microarray analysis (ChIP chip) to produce a genome-wide description of cohesin binding to meiotic and mitotic chromosomes of Saccharomyces cerevisiae. A computer program, PeakFinder, enables flexible, automated identification and annotation of cohesin binding peaks in ChIP chip data. Cohesin sites are highly conserved in meiosis and mitosis, suggesting that chromosomes share a common underlying structure during different developmental programs. These sites occur with a semiperiodic spacing of 11 kb that correlates with AT content. The number of sites correlates with chromosome size; however, binding to neighboring sites does not appear to be cooperative. We observed a very strong correlation between cohesin sites and regions between convergent transcription units. The apparent incompatibility between transcription and cohesin binding exists in both meiosis and mitosis. Further experiments reveal that transcript elongation into a cohesin-binding site removes cohesin. A negative correlation between cohesin sites and meiotic recombination sites suggests meiotic exchange is sensitive to the chromosome structure provided by cohesin. The genome-wide view of mitotic and meiotic cohesin binding provides an important framework for the exploration of cohesins and cohesion in other genomes.

The segmental pattern of the spine is established early in development, when the vertebral precursors, the somites, are rhythmically produced from the presomitic mesoderm. Microarray studies of the mouse presomitic mesoderm transcriptome reveal that the oscillator associated with this process, the segmentation clock, drives the periodic expression of a large network of cyclic genes involved in cell signaling. Mutually exclusive activation of the notch-fibroblast growth factor and Wnt pathways during each cycle suggests that coordinated regulation of these three pathways underlies the clock oscillator.

Treacher Collins syndrome (TCS) is a congenital disorder of craniofacial development arising from mutations in TCOF1, which encodes the nucleolar phosphoprotein Treacle. Haploinsufficiency of Tcof1 perturbs mature ribosome biogenesis, resulting in stabilization of p53 and the cyclin G1-mediated cell-cycle arrest that underpins the specificity of neuroepithelial apoptosis and neural crest cell hypoplasia characteristic of TCS. Here we show that inhibition of p53 prevents cyclin G1-driven apoptotic elimination of neural crest cells while rescuing the craniofacial abnormalities associated with mutations in Tcof1 and extending life span. These improvements, however, occur independently of the effects on ribosome biogenesis; thus suggesting that it is p53-dependent neuroepithelial apoptosis that is the primary mechanism underlying the pathogenesis of TCS. Our work further implies that neuroepithelial and neural crest cells are particularly sensitive to cellular stress during embryogenesis and that suppression of p53 function provides an attractive avenue for possible clinical prevention of TCS craniofacial birth defects and possibly those of other neurocristopathies.

SUMMARYThe vertebral column is a conserved anatomical structure that defines the vertebrate phylum. The periodic or segmental pattern of the vertebral column is established early in development when the vertebral precursors, the somites, are rhythmically produced from presomitic mesoderm (PSM). This rhythmic activity is controlled by a segmentation clock that is associated with the periodic transcription of cyclic genes in the PSM. Comparison of the mouse, chicken and zebrafish PSM oscillatory transcriptomes revealed networks of 40 to 100 cyclic genes mostly involved in Notch, Wnt and FGF signaling pathways. However, despite this conserved signaling oscillation, the identity of individual cyclic genes mostly differed between the three species, indicating a surprising evolutionary plasticity of the segmentation networks. the GeneChip Eukaryotic Small Sample Target Labeling Assay version II, and the second cycle of the Two-Cycle Eukaryotic Target Labeling Assay, as described in the Affymetrix GeneChip Expression Analysis Technical Manual rev5. Amplified RNA samples were hybridized to Affymetrix GeneChip Mouse Genome 430 2.0 arrays. For chicken and zebrafish, total RNA was extracted from PSM pieces using Trizol. PSM pieces contained ~4000 chicken cells or ~400 zebrafish cells. The mRNA of each sample was amplified following a two-cycle linear amplification protocol as described in the Two-Cycle Eukaryotic Target Labeling Assay in the Affymetrix GeneChip Expression Analysis Technical Manual rev5. Briefly, cDNA was synthesized from total RNA using T7 linked to oligo(dT) primers. After second-strand synthesis, cRNA was in vitro transcribed using unlabeled ribonucleotides. Upon a second round of cDNA synthesis using random priming, cRNA was made with biotin-labeled CTP and UTP, yielding 35-135 g of biotinylated cRNA for chicken and 3-6 g for zebrafish. RNA quality was checked after the second round of amplification by measuring the A 260 /A 280 ratio (which ranged from 1.8 to 2.1) and the fragment size with the Agilent Bioanalyser (mean size >1 kb). Five micrograms of RNA from good quality samples was fragmented to less than 200 bp, hybridized to Affymetrix GeneChip chicken genome arrays or GeneChip zebrafish genome arrays according to manufacturer's instructions and scanned with a GeneArray scanner (Agilent G2500A) at the Microarray Core Facility of the Stowers Institute for Medical Research. The array readout was processed using Affymetrix Microarray Suite (MAS) 5.0 and scaled by adjusting the average intensity of each array to a target intensity of 150. The quality control parameters from the Affymetrix array reports were within acceptable limits and highly similar between the arrays. The raw data are available on ArrayExpress with accession E-MTAB-406. Non-biological variance of the microarrays was controlled by two methods: the R package affyPLM (Bolstad et al., 2005) using the normalized unscaled standard error (NUSE) and relative expression (RLE) functions; and principal component analysis (PCA) using Partek ...

We analyzed the Plasmodium falciparum gene expression dataset. In the Quality Control Dataset of 5080 expression patterns, we found 4112 periodic probes. In addition, we identified 243 probes with periodic expression in the Complete Dataset, which could not be examined in the original study by the FFT analysis due to an excessive number of missing values. While most periodic genes had a period of 48 h, some had a period close to 24 h. Our approach should be applicable for detection and quantification of periodic patterns in any unevenly spaced gene expression time-series data.

To identify new molecular targets of rapamycin, an anticancer and immunosuppressive drug, we analyzed temporal changes in yeast over 6 h in response to rapamycin at the transcriptome and proteome levels and integrated the expression patterns with functional profiling. We show that the integration of transcriptomics, proteomics, and functional data sets provides novel insights into the molecular mechanisms of rapamycin action. We first observed a temporal delay in the correlation of mRNA and protein expression where mRNA expression at 1 and 2 h correlated best with protein expression changes after 6 h of rapamycin treatment. This was especially the case for the inhibition of ribosome biogenesis and induction of heat shock and autophagy essential to promote the cellular sensitivity to rapamycin. However, increased levels of vacuolar protease could enhance resistance to rapamycin. Of the 85 proteins identified as statistically significantly changing in abundance, most of the proteins that decreased in abundance were correlated with a decrease in mRNA expression. However, of the 56 proteins increasing in abundance, 26 were not correlated with an increase in mRNA expression. These protein changes were correlated with unchanged or down-regulated mRNA expression. These proteins, involved in mitochondrial genome maintenance, endocytosis, or drug export, represent new candidates effecting rapamycin action whose expression might be post-transcriptionally or post-translationally regulated. We identified GGC1, a mitochondrial GTP/GDP carrier, as a new component of the rapamycin/target of rapamycin (TOR) signaling pathway. We determined that the protein product of GGC1 was stabilized in the presence of rapamycin, and the deletion of the GGC1 enhanced growth fitness in the presence of rapamycin. A dynamic mRNA expression analysis of ⌬ggc1 and wildtype cells treated with rapamycin revealed a key role for Ggc1p in the regulation of ribosome biogenesis and cell cycle progression under TOR control. Molecular & Cellular Proteomics 9:271-284, 2010.

Telomerase adds telomeric repeat sequences to chromosome ends using a short region of its RNA subunit as a template. Telomerase RNA subunits are phylogenetically highly divergent, and different strategies have evolved to demarcate the boundary of the template region. The recent identification of the gene encoding telomerase RNA in the fission yeast Schizosaccharomyces pombe (ter1 ؉ ) has opened the door for structurefunction analyses in a model that shares many features with the telomere maintenance machinery of higher eukaryotes. Here we describe a structural element in TER1 that defines the 5 boundary of the template. Disruption of a predicted long range base pairing interaction between template-adjacent nucleotides and a sequence further upstream resulted in reverse transcription beyond the template region and caused telomere shortening. Normal telomere length was restored by combining complementary nucleotide substitutions in both elements, showing that base pairing, not a specific sequence, limits reverse transcription beyond the template. The template boundary described here resembles that of budding yeasts and some mammalian telomerases. However, unlike any previously characterized boundary element, part of the paired region overlaps with the template itself, thus necessitating disruption of these interactions during most reverse transcription cycles. We show that changes in the paired region directly affect the length of individual telomeric repeat units. Our data further illustrate that marginal alignment of the telomeric 3 end with RNA sequences downstream of the template is responsible for primer slippage, causing incorporation of strings of guanosines at the start of a subset of repeats.The reverse transcriptase telomerase replenishes terminal DNA sequences lost through incomplete DNA replication and nucleolytic degradation (1). Without functional telomerase, telomeres undergo progressive shortening with each cell division, a process that eventually limits the proliferative potential of affected cells. Mutations in human telomerase subunits cause dyskeratosis congenita, aplastic anemia, and idiopathic pulmonary fibrosis, a group of disorders characterized by insufficient renewal capacity of cells caused by shortening of telomeres (2-6). Conversely, activation of telomerase is critical for continued proliferation of most cancer cells, making the enzyme a promising target for anti-cancer drugs.At its core, telomerase is comprised of the catalytic protein subunit TERT (telomerase reverse transcriptase) and a TER (telomerase RNA) component (7). Together, TERT and TER are sufficient to reconstitute activity in vitro, but additional factors are required for telomere maintenance in vivo. Whereas TERT has a highly conserved catalytic domain, telomerase RNA subunits vary widely in size from ϳ150 nucleotides in ciliates and ϳ450 nucleotides in vertebrates to over 1,500 nucleotides in some yeasts (8, 9). Even among closely related species, substantial variation in telomerase RNA sequence exists. For example, th...

While genome-wide gene expression data are generated at an increasing rate, the repertoire of approaches for pattern discovery in these data is still limited. Identifying subtle patterns of interest in large amounts of data (tens of thousands of profiles) associated with a certain level of noise remains a challenge. A microarray time series was recently generated to study the transcriptional program of the mouse segmentation clock, a biological oscillator associated with the periodic formation of the segments of the body axis. A method related to Fourier analysis, the Lomb-Scargle periodogram, was used to detect periodic profiles in the dataset, leading to the identification of a novel set of cyclic genes associated with the segmentation clock. Here, we applied to the same microarray time series dataset four distinct mathematical methods to identify significant patterns in gene expression profiles. These methods are called: Phase consistency, Address reduction, Cyclohedron test and Stable persistence, and are based on different conceptual frameworks that are either hypothesis- or data-driven. Some of the methods, unlike Fourier transforms, are not dependent on the assumption of periodicity of the pattern of interest. Remarkably, these methods identified blindly the expression profiles of known cyclic genes as the most significant patterns in the dataset. Many candidate genes predicted by more than one approach appeared to be true positive cyclic genes and will be of particular interest for future research. In addition, these methods predicted novel candidate cyclic genes that were consistent with previous biological knowledge and experimental validation in mouse embryos. Our results demonstrate the utility of these novel pattern detection strategies, notably for detection of periodic profiles, and suggest that combining several distinct mathematical approaches to analyze microarray datasets is a valuable strategy for identifying genes that exhibit novel, interesting transcriptional patterns.