Identification of cell cycle-regulated genes in fission yeast

Functional characterization of fission yeast transcription factors by overexpression analysis

In Schizosaccharomyces pombe, over 90% of transcription factor genes are nonessential. Moreover, the majority do not exhibit significant growth defects under optimal conditions when deleted, complicating their functional characterization and target gene identification. Here, we systematically overexpressed 99 transcription factor genes with the nmt1 promoter and found that 64 transcription factor genes exhibited reduced fitness when ectopically expressed. Cell cycle defects were also often observed. We further investigated three uncharacterized transcription factor genes (toe1(+)-toe3(+)) that displayed cell elongation when overexpressed. Ectopic expression of toe1(+) resulted in a G1 delay while toe2(+) and toe3(+) overexpression produced an accumulation of septated cells with abnormalities in septum formation and nuclear segregation, respectively. Transcriptome profiling and ChIP-chip analysis of the transcription factor overexpression strains indicated that Toe1 activates target genes of the pyrimidine-salvage pathway, while Toe3 regulates target genes involved in polyamine synthesis. We also found that ectopic expression of the putative target genes SPBC3H7.05c, and dad5(+) and SPAC11D3.06 could recapitulate the cell cycle phenotypes of toe2(+) and toe3(+) overexpression, respectively. Furthermore, single deletions of the putative target genes urg2(+) and SPAC1399.04c, and SPBC3H7.05c, SPACUNK4.15, and rds1(+), could suppress the phenotypes of toe1(+) and toe2(+) overexpression, respectively. This study implicates new transcription factors and metabolism genes in cell cycle regulation and demonstrates the potential of systematic overexpression analysis to elucidate the function and target genes of transcription factors in S. pombe.

Comprehensive proteomics analysis reveals new substrates and regulators of the fission yeast clp1/cdc14 phosphatase

The conserved family of Cdc14 phosphatases targets cyclin-dependent kinase substrates in yeast, mediating late mitotic signaling events. To discover substrates and regulators of the Schizosaccharomyces pombe Cdc14 phosphatase Clp1, TAP-tagged Clp1, and a substrate trapping mutant (Clp1-C286S) were purified from asynchronous and mitotic (prometaphase and anaphase) cells and binding partners were identified by 2D-LC-MS/MS. Over 100 Clp1-interacting proteins were consistently identified, over 70 of these were enriched in Clp1-C286S-TAP (potential substrates) and we and others detected Cdk1 phosphorylation sites in over half (44/73) of these potential substrates. According to GO annotations, Clp1-interacting proteins are involved in many essential cellular processes including mitosis, cytokinesis, ribosome biogenesis, transcription, and trafficking among others. We confirmed association and dephosphorylation of multiple candidate substrates, including a key scaffolding component of the septation initiation network called Cdc11, an essential kinase of the conserved morphogenesis-related NDR kinase network named Shk1, and multiple Mlu1-binding factor transcriptional regulators. In addition, we identified Sal3, a nuclear β-importin, as the sole karyopherin required for Clp1 nucleoplasmic shuttling, a key mode of Cdc14 phosphatase regulation. Finally, a handful of proteins were more abundant in wild type Clp1-TAP versus Clp1-C286S-TAP, suggesting that they may directly regulate Clp1 signaling or serve as scaffolding platforms to localize Clp1 activity.

Mathematical modeling of fission yeast Schizosaccharomyces pombe cell cycle: exploring the role of multiple phosphatases

Cell cycle is the central process that regulates growth and division in all eukaryotes. Based on the environmental condition sensed, the cell lies in a resting phase G0 or proceeds through the cyclic cell division process (G1→S→G2→M). These series of events and phase transitions are governed mainly by the highly conserved Cyclin dependent kinases (Cdks) and its positive and negative regulators. The cell cycle regulation of fission yeast Schizosaccharomyces pombe is modeled in this study. The study exploits a detailed molecular interaction map compiled based on the published model and experimental data. There are accumulating evidences about the prominent regulatory role of specific phosphatases in cell cycle regulations. The current study emphasizes the possible role of multiple phosphatases that governs the cell cycle regulation in fission yeast S. pombe. The ability of the model to reproduce the reported regulatory profile for the wild-type and various mutants was verified though simulations.

ELECTRONIC SUPPLEMENTARY MATERIAL

The online version of this article (doi:10.1007/s11693-011-9090-7) contains supplementary material, which is available to authorized users.

An empirical Bayes approach for analysis of diverse periodic trends in time-course gene expression data

MOTIVATION

There is a substantial body of works in the biology literature that seeks to characterize the cyclic behavior of genes during cell division. Gene expression microarrays made it possible to measure the expression profiles of thousands of genes simultaneously in time-course experiments to assess changes in the expression levels of genes over time. In this context, the commonly used procedures for testing include the permutation test by de Lichtenberg et al. and the Fisher's G-test, both of which are designed to evaluate periodicity against noise. However, it is possible that a gene of interest may have expression that is neither cyclic nor just noise. Thus, there is a need for a new test for periodicity that can identify cyclic patterns against not only noise but also other non-cyclic patterns such as linear, quadratic or higher order polynomial patterns.

RESULTS

To address this weakness, we have introduced an empirical Bayes approach to test for periodicity and compare its performance in terms of sensitivity and specificity with that of the permutation test and Fisher's G-test through extensive simulations and by application to a set of time-course experiments on the Schizosaccharomyces pombe cell-cycle gene expression. We use 'conserved' and 'cycling' genes by Lu et al. to assess the sensitivity and CESR genes by Chenet al. to assess the specificity of our new empirical Bayes method.

AVAILABILITY AND IMPLEMENTATION

The SAS Macro for our empirical Bayes test for periodicity is included in the supplementary materials along with a sample run of the MACRO program.

CONTACT

mkocak1@uthsc.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Transcription factor oscillations induce differential gene expressions

Intracellular protein levels of diverse transcription factors (TFs) vary periodically with time. However, the effects of TF oscillations on gene expression, the primary role of TFs, are poorly understood. In this study, we determined these effects by comparing gene expression levels induced in the presence and in the absence of TF oscillations under same mean intracellular protein level of TF. For all the nonlinear TF transcription kinetics studied, an oscillatory TF is predicted to induce gene expression levels that are distinct from a nonoscillatory TF. The conditions dictating whether TF oscillations induce either higher or lower average gene expression levels were elucidated. Subsequently, the predicted effects from an oscillatory TF, which follows sigmoid transcription kinetics, were applied to demonstrate how oscillatory dynamics provide a mechanism for differential target gene transactivation. Generally, the mean TF concentration at which oscillations occur relative to the promoter binding affinity of a target gene determines whether the gene is up- or downregulated whereas the oscillation amplitude amplifies the magnitude of the differential regulation. Notably, the predicted trends of differential gene expressions induced by oscillatory NF-κB and glucocorticoid receptor match the reported experimental observations. Furthermore, the biological function of p53 oscillations is predicted to prime the cell for death upon DNA damage via differential upregulation of apoptotic genes. Lastly, given N target genes, an oscillatory TF can generate between (N-1) and (2N-1) distinct patterns of differential transactivation. This study provides insights into the mechanism for TF oscillations to induce differential gene expressions, and underscores the importance of TF oscillations in biological regulations.

DNA replication through hard-to-replicate sites, including both highly transcribed RNA Pol II and Pol III genes, requires the S. pombe Pfh1 helicase

Replication forks encounter impediments as they move through the genome, including natural barriers due to stable protein complexes and highly transcribed genes. Unlike lesions generated by exogenous damage, natural barriers are encountered in every S phase. Like humans, Schizosaccharomyces pombe encodes a single Pif1 family DNA helicase, Pfh1. Here, we show that Pfh1 is required for efficient fork movement in the ribosomal DNA, the mating type locus, tRNA, 5S ribosomal RNA genes, and genes that are highly transcribed by RNA polymerase II. In addition, converged replication forks accumulated at all of these sites in the absence of Pfh1. The effects of Pfh1 on DNA replication are likely direct, as it had high binding to sites whose replication was impaired in its absence. Replication in the absence of Pfh1 resulted in DNA damage specifically at those sites that bound high levels of Pfh1 in wild-type cells and whose replication was slowed in its absence. Cells depleted of Pfh1 were inviable if they also lacked the human TIMELESS homolog Swi1, a replisome component that stabilizes stalled forks. Thus, Pfh1 promotes DNA replication and separation of converged replication forks and suppresses DNA damage at hard-to-replicate sites.

Coordination of cell growth and division by the ubiquitin-proteasome system

The coupling of cellular growth and division is crucial for a cell to make an accurate copy of itself. Regulated protein degradation by the ubiquitin-proteasome system (UPS) plays an important role in the coordination of these two processes. Many ubiquitin ligases, in particular the Skp1-Cullin-F-box (SCF) family and the Anaphase-Promoting Complex (APC), couple growth and division by targeting cell cycle and metabolic regulators for degradation. However, many regulatory proteins are targeted by multiple ubiquitin ligases. As a result, we are only just beginning to understand the complexities of the proteolytic regulatory network that connects cell growth and the cell cycle.

A conserved cell growth cycle can account for the environmental stress responses of divergent eukaryotes

Transitions between the two phases of the cell growth cycle can account for the environmental stress response, the growth-rate response, and the cross-protection between slow growth and various types of stress factors. It is suggested that this mechanism is conserved across budding and fission yeast and normal human cells.

The respiratory metabolic cycle in budding yeast (Saccharomyces cerevisiae) consists of two phases that are most simply defined phenomenologically: low oxygen consumption (LOC) and high oxygen consumption (HOC). Each phase is associated with the periodic expression of thousands of genes, producing oscillating patterns of gene expression found in synchronized cultures and in single cells of slowly growing unsynchronized cultures. Systematic variation in the durations of the HOC and LOC phases can account quantitatively for well-studied transcriptional responses to growth rate differences. Here we show that a similar mechanism—transitions from the HOC phase to the LOC phase—can account for much of the common environmental stress response (ESR) and for the cross-protection by a preliminary heat stress (or slow growth rate) to subsequent lethal heat stress. Similar to the budding yeast metabolic cycle, we suggest that a metabolic cycle, coupled in a similar way to the ESR, in the distantly related fission yeast, Schizosaccharomyces pombe, and in humans can explain gene expression and respiratory patterns observed in these eukaryotes. Although metabolic cycling is associated with the G0/G1 phase of the cell division cycle of slowly growing budding yeast, transcriptional cycling was detected in the G2 phase of the division cycle in fission yeast, consistent with the idea that respiratory metabolic cycling occurs during the phases of the cell division cycle associated with mass accumulation in these divergent eukaryotes.

Local wavelet-vaguelette-based functional classification of gene expression data

This paper focuses on the problem of functional statistical classification of gene expression curves. A local-wavelet-vaguelette-based functional logistic regression approach is presented. This approach is specially suitable for the classification of non-stationary singular (non-differentiable) curves. The performance of the methodology proposed is illustrated by implementing it for the classification of yeast cell-cycle temporal gene expression profiles. A simulation study is also carried out for comparison with other functional classification methodologies.

Systematic localization study on novel proteins encoded by meiotically up-regulated ORFs in fission yeast

We conducted a mitotic localization study on gene products encoded by 56 uncharacterized fission yeast ORFs that were transcriptionally up-regulated during meiotic division. Despite meiotic gene induction, these genes were expressed during mitosis as well. Seven gene products were localized in the nucleus and/or chromatin; another one was a mitosis-specific spindle pole body component and, intriguingly, its human homologue was also localized in the centrosome of cultured HeLa cells. Two products appeared to be localized in cytoplasmic microtubules, whereas four were mitochondrial proteins. Three other proteins were found in the medial ring upon cytokinesis and another was localized on the entire cell periphery. The remaining 38 proteins were detected in the cytoplasm and showed varied spatial patterns. This systematic study helps our integrated understanding of all the protein functions in the fission yeast as a eukaryotic model.

Identification of a core set of signature cell cycle genes whose relative order of time to peak expression is conserved across species

A cell division cycle is a well-coordinated process in eukaryotes with cell cycle genes exhibiting a periodic expression over time. There is considerable interest among cell biologists to determine genes that are periodic in multiple organisms and whether such genes are also evolutionarily conserved in their relative order of time to peak expression. Interestingly, periodicity is not well-conserved evolutionarily. A conservative estimate of a number of periodic genes common to fission yeast (Schizosaccharomyces pombe) and budding yeast (Saccharomyces cerevisiae) (‘core set FB’) is 35, while those common to fission yeast and humans (Homo sapiens) (‘core set FH’) is 24. Using a novel statistical methodology, we discover that the relative order of peak expression is conserved in ∼80% of FB genes and in ∼40% of FH genes. We also discover that the order is evolutionarily conserved in six genes which are potentially the core set of signature cell cycle genes. These include ace2 (a transcription factor) and polo-kinase plo1, which are well-known hubs of early M-phase clusters, cdc18 a key component of pre-replication complexes, mik1 which is critical for the establishment and maintenance of DNA damage check point, and histones hhf1 and hta2.

Production, purification and characterization of mouse monoclonal antibodies against human mitochondrial transcription termination factor 2 (MTERF2)

Human mitochondrial transcription termination factor 2 (MTERF2) is a member of the mitochondrial transcription termination factors (MTERFs) family and a cell growth inhibitor. To create a specific mouse monoclonal antibody against human MTERF2, the full-length His-tag MTERF2 protein (1-385 aa) was expressed in Escherichia coli, and purified recombinant protein was injected into three BALB/c mice to perform an immunization procedure. Eight stable positive monoclonal cell lines were screened and established. ELISA results demonstrated that all antibody light chains were kappa, while the heavy chains displayed three subtypes IgG1, IgG2a, and IgG2b respectively. The sensitivity and specificity of the monoclonal antibodies against human MTERF2 were determined using immunoblotting, immunoprecipitation and immunofluorescence analyses. Furthermore, serum regulation of human MTERF2 protein expression levels in human glioma U251 cells was examined with these monoclonal antibodies and the results demonstrated that the expression level of MTERF2 protein was dramatically inhibited by the addition of serum to serum-starved cells. Taken together, our results demonstrate the functionality of these mouse anti-human MTERF2 monoclonal antibodies, which may provide a useful tool to elucidate the role of MTERF2 in human mitochondrial transcription as well as other potential activities. To our knowledge, this is the first report on the preparation and characterization of mouse monoclonal antibodies against human MTERF2.

Commitment to a cellular transition precedes genome-wide transcriptional change

In budding yeast, commitment to cell division corresponds to activating the positive feedback loop of G1 cyclins controlled by the transcription factors SBF and MBF. This pair of transcription factors has over 200 targets, implying that cell-cycle commitment coincides with genome-wide changes in transcription. Here, we find that genes within this regulon have a well-defined distribution of transcriptional activation times. Combinatorial use of SBF and MBF results in a logical OR function for gene expression and partially explains activation timing. Activation of G1 cyclin expression precedes the activation of the bulk of the G1/S regulon, ensuring that commitment to cell division occurs before large-scale changes in transcription. Furthermore, we find similar positive feedback-first regulation in the yeasts S. bayanus and S. cerevisiae, as well as human cells. The widespread use of the feedback-first motif in eukaryotic cell-cycle control, implemented by nonorthologous proteins, suggests its frequent deployment at cellular transitions.

Podbat: a novel genomic tool reveals Swr1-independent H2A.Z incorporation at gene coding sequences through epigenetic meta-analysis

Epigenetic regulation consists of a multitude of different modifications that determine active and inactive states of chromatin. Conditions such as cell differentiation or exposure to environmental stress require concerted changes in gene expression. To interpret epigenomics data, a spectrum of different interconnected datasets is needed, ranging from the genome sequence and positions of histones, together with their modifications and variants, to the transcriptional output of genomic regions. Here we present a tool, Podbat (Positioning database and analysis tool), that incorporates data from various sources and allows detailed dissection of the entire range of chromatin modifications simultaneously. Podbat can be used to analyze, visualize, store and share epigenomics data. Among other functions, Podbat allows data-driven determination of genome regions of differential protein occupancy or RNA expression using Hidden Markov Models. Comparisons between datasets are facilitated to enable the study of the comprehensive chromatin modification system simultaneously, irrespective of data-generating technique. Any organism with a sequenced genome can be accommodated. We exemplify the power of Podbat by reanalyzing all to-date published genome-wide data for the histone variant H2A.Z in fission yeast together with other histone marks and also phenotypic response data from several sources. This meta-analysis led to the unexpected finding of H2A.Z incorporation in the coding regions of genes encoding proteins involved in the regulation of meiosis and genotoxic stress responses. This incorporation was partly independent of the H2A.Z-incorporating remodeller Swr1. We verified an Swr1-independent role for H2A.Z following genotoxic stress in vivo. Podbat is open source software freely downloadable from www.podbat.org, distributed under the GNU LGPL license. User manuals, test data and instructions are available at the website, as well as a repository for third party-developed plug-in modules. Podbat requires Java version 1.6 or higher.

Mitochondrial transcription termination factor 2 binds to entire mitochondrial DNA and negatively regulates mitochondrial gene expression

Mitochondrial transcription termination factor 2 (mTERF2) is a mitochondrial matrix protein that binds to the mitochondrial DNA. Previous studies have shown that overexpression of mTERF2 can inhibit cell proliferation, but the mechanism has not been well defined so far. This study aimed to present the binding pattern of mTERF2 to the mitochondrial DNA (mtDNA) in vivo, and investigated the biological function of mTERF2 on the replication of mtDNA, mRNA transcription, and protein translation. The mTERF2 binding to entire mtDNA was identified via the chromatin immunoprecipitation analysis. The mtDNA replication efficiency and expression levels of mitochondria genes were significantly inhibited when the mTERF2 was overexpressed in HeLa cells. The inhibition level of mtDNA content was the same with the decreased levels of mRNA and mitochondrial protein expression. Overall, the mTERF2 might be a cell growth inhibitor based on its negative effect on mtDNA replication, which eventually down-regulated all of the oxidative phosphorylation components in the mitochondria that were essential for the cell's energy metabolism.

A homeodomain transcription factor regulates the DNA replication checkpoint in yeast

Checkpoints monitor the successful completion of cell cycle processes, such as DNA replication, and also regulate the expression of cell cycle-dependent genes that are required for responses. In the model yeast Schizosaccharomyces pombe G 1/S phase-specific gene expression is regulated by the MBF (also known as DSC1) transcription factor complex and is also activated by the mammalian ATM/ATR-related Rad3 DNA replication checkpoint. Here, we show that the Yox1 homeodomain transcription factor acts to co-ordinate the expression of MBF-regulated genes during the cell division cycle. Moreover, our data suggests that Yox1 is inactivated by the Rad3 DNA replication checkpoint via phosphorylation by the conserved Cds1 checkpoint kinase. Collectively, our data has implications for understanding the mechanisms underlying the coordination of cell cycle processes in eukaryotes.

Clusters of temporal discordances reveal distinct embryonic patterning mechanisms in Drosophila and anopheles

Evolutionary innovations can be driven by spatial and temporal changes in gene expression. Several such differences have been documented in the embryos of lower and higher Diptera. One example is the reduction of the ancient extraembryonic envelope composed of amnion and serosa as seen in mosquitoes to the single amnioserosa of fruit flies. We used transcriptional datasets collected during the embryonic development of the fruit fly, Drosophila melanogaster, and the malaria mosquito, Anopheles gambiae, to search for whole-genome changes in gene expression underlying differences in their respective embryonic morphologies. We found that many orthologous gene pairs could be clustered based on the presence of coincident discordances in their temporal expression profiles. One such cluster contained genes expressed specifically in the mosquito serosa. As shown previously, this cluster is re-deployed later in development at the time of cuticle synthesis. In addition, there is a striking difference in the temporal expression of a subset of maternal genes. Specifically, maternal transcripts that exhibit a sharp reduction at the time of the maternal-zygotic transition in Drosophila display sustained expression in the Anopheles embryo. We propose that gene clustering by local temporal discordance can be used for the de novo identification of the gene batteries underlying morphological diversity.

The fission yeast rDNA-binding protein Reb1 regulates G1 phase under nutritional stress

Yeast Reb1 and its mammalian ortholog TTF1 are conserved Myb-type DNA-binding proteins that bind to specific sites near the 3'-end of rRNA genes (rDNA). Here, they participate in the termination of transcription driven by RNA polymerase I and block DNA replication forks approaching in the opposite direction. We found that Schizosaccharomyces pombe Reb1 also upregulates transcription of the ste9(+) gene that is required for nitrogen-starvation-induced growth arrest with a G1 DNA content and sexual differentiation. Ste9 activates the anaphase-promoting complex or cyclosome ('APC/C') in G1, targeting B-cyclin for proteasomal degradation in response to nutritional stress. Reb1 binds in vivo and in vitro to a specific DNA sequence at the promoter of ste9(+), similar to the sequence recognized in the rDNA, and this binding is required for ste9(+) transcriptional activation and G1 arrest. This suggests that Reb1 acts as a link between rDNA metabolism and cell cycle control in response to nutritional stress. In agreement with this new role for Reb1 in the regulation of the G1-S transition, reb1Δ and wee1(ts) mutations are synthetically lethal owing to the inability of these cells to lengthen G1 before entering S phase. Similarly, reb1Δ cdc10(ts) cells are unable to arrest in G1 and die at the semi-permissive temperature.

Deconvolution of chromatin immunoprecipitation-microarray (ChIP-chip) analysis of MBF occupancies reveals the temporal recruitment of Rep2 at the MBF target genes

MBF (or DSC1) is known to regulate transcription of a set of G(1)/S-phase genes encoding proteins involved in regulation of DNA replication. Previous studies have shown that MBF binds not only the promoter of G(1)/S-phase genes, but also the constitutive genes; however, it was unclear if the MBF bindings at the G(1)/S-phase and constitutive genes were mechanistically distinguishable. Here, we report a chromatin immunoprecipitation-microarray (ChIP-chip) analysis of MBF binding in the Schizosaccharomyces pombe genome using high-resolution genome tiling microarrays. ChIP-chip analysis indicates that the majority of the MBF occupancies are located at the intragenic regions. Deconvolution analysis using Rpb1 ChIP-chip results distinguishes the Cdc10 bindings at the Rpb1-poor loci (promoters) from those at the Rpb1-rich loci (intragenic sequences). Importantly, Res1 binding at the Rpb1-poor loci, but not at the Rpb1-rich loci, is dependent on the Cdc10 function, suggesting a distinct binding mechanism. Most Cdc10 promoter bindings at the Rpb1-poor loci are associated with the G(1)/S-phase genes. While Res1 or Res2 is found at both the Cdc10 promoter and intragenic binding sites, Rep2 appears to be absent at the Cdc10 promoter binding sites but present at the intragenic sites. Time course ChIP-chip analysis demonstrates that Rep2 is temporally accumulated at the coding region of the MBF target genes, resembling the RNAP-II occupancies. Taken together, our results show that deconvolution analysis of Cdc10 occupancies refines the functional subset of genomic binding sites. We propose that the MBF activator Rep2 plays a role in mediating the cell cycle-specific transcription through the recruitment of RNAP-II to the MBF-bound G(1)/S-phase genes.

Genomic binding profiling of the fission yeast stress-activated MAPK Sty1 and the bZIP transcriptional activator Atf1 in response to H2O2

Background

The evolutionally conserved MAPK Sty1 and bZIP transcriptional activator Atf1 are known to play a pivotal role in response to the reactive oxygen species in S. pombe. However, it is unclear whether all of the H₂O₂-induced genes are directly regulated by the Sty1-Atf1 pathway and involved in growth fitness under H₂O₂-induced stress conditions.

Methodology/Principal Findings

Here we present the study on ChIP-chip mapping of the genomic binding sites for Sty1, Atf1, and the Atf1's binding partner Pcr1; the genome-wide transcriptional profiling of the atf1 and pcr1 strains in response to H₂O₂; and the phenotypic assessment of ∼90 Atf1/Pcr1-bound or unbound genes for growth fitness under H₂O₂ conditions. ChIP-chip analysis shows that Atf1 and Pcr1 binding sites are overlapped in the genome and constitutively present before H₂O₂ stress. On the other hand, Sty1 recruitment primarily occurs at the Atf1/Pcr1 binding sites and is induced by H₂O₂. We found that Atf1/Pcr1 is clearly responsible for the high-level transcriptional response to H₂O₂. Furthermore, phenotypic assessment indicates that among the H₂O₂-induced genes, Atf1/Pcr1-bound genes exhibit a higher likelihood of functional requirement for growth fitness under the stress condition than the Atf1/Pcr1-unbound genes do. Notably, we found that the Atf1/Pcr1-bound genes regardless of their responsiveness to H₂O₂ show a high probability of requirement for growth fitness.

Conclusion/Significance

Together, our analyses on global mapping of protein binding sites, genome-wide transcriptional profiling, and phenotypic assessment provide insight into mechanisms for global transcriptional regulation by the Sty1-Atf1 pathway in response to H₂O₂-induced reactive oxygen species.

A genetic engineering solution to the "arginine conversion problem" in stable isotope labeling by amino acids in cell culture (SILAC)

Stable isotope labeling by amino acids in cell culture (SILAC) provides a straightforward tool for quantitation in proteomics. However, one problem associated with SILAC is the in vivo conversion of labeled arginine to other amino acids, typically proline. We found that arginine conversion in the fission yeast Schizosaccharomyces pombe occurred at extremely high levels, such that labeling cells with heavy arginine led to undesired incorporation of label into essentially all of the proline pool as well as a substantial portion of glutamate, glutamine, and lysine pools. We found that this can be prevented by deleting genes involved in arginine catabolism using methods that are highly robust yet simple to implement. Deletion of both fission yeast arginase genes or of the single ornithine transaminase gene, together with a small modification to growth medium that improves arginine uptake in mutant strains, was sufficient to abolish essentially all arginine conversion. We demonstrated the usefulness of our approach in a large scale quantitative analysis of proteins before and after cell division; both up- and down-regulated proteins, including a novel protein involved in septation, were successfully identified. This strategy for addressing the "arginine conversion problem" may be more broadly applicable to organisms amenable to genetic manipulation.

Cyclebase.org: version 2.0, an updated comprehensive, multi-species repository of cell cycle experiments and derived analysis results

Cell division involves a complex series of events orchestrated by thousands of molecules. To study this process, researchers have employed mRNA expression profiling of synchronously growing cell cultures progressing through the cell cycle. These experiments, which have been carried out in several organisms, are not easy to access, combine and evaluate. Complicating factors include variation in interdivision time between experiments and differences in relative duration of each cell-cycle phase across organisms. To address these problems, we created Cyclebase, an online resource of cell-cycle-related experiments. This database provides an easy-to-use web interface that facilitates visualization and download of genome-wide cell-cycle data and analysis results. Data from different experiments are normalized to a common timescale and are complimented with key cell-cycle information and derived analysis results. In Cyclebase version 2.0, we have updated the entire database to reflect changes to genome annotations, included information on cyclin-dependent kinase (CDK) substrates, predicted degradation signals and loss-of-function phenotypes from genome-wide screens. The web interface has been improved and provides a single, gene-centric graph summarizing the available cell-cycle experiments. Finally, key information and links to orthologous and paralogous genes are now included to further facilitate comparison of cell-cycle regulation across species. Cyclebase version 2.0 is available at http://www.cyclebase.org.

From elements to modules: regulatory evolution in Ascomycota fungi

Regulatory divergence is likely a major driving force in evolution. Comparative transcriptomics provides a new glimpse into the evolution of gene regulation. Ascomycota fungi are uniquely suited among eukaryotes for studies of regulatory evolution, because of broad phylogenetic scope, many sequenced genomes, and facility of genomic analysis. Here we review the substantial divergence in gene expression in Ascomycota and how this is reconciled with the modular organization of transcriptional networks. We show that flexibility and redundancy in both cis-regulation and trans-regulation can lead to changes from altered expression of single genes to wholesale rewiring of regulatory modules. Redundancy thus emerges as a major driving force facilitating expression divergence while preserving the coherent functional organization of a transcriptional response.

Time warping of evolutionary distant temporal gene expression data based on noise suppression

Background

Comparative analysis of genome wide temporal gene expression data has a broad potential area of application, including evolutionary biology, developmental biology, and medicine. However, at large evolutionary distances, the construction of global alignments and the consequent comparison of the time-series data are difficult. The main reason is the accumulation of variability in expression profiles of orthologous genes, in the course of evolution.

Results

We applied Pearson distance matrices, in combination with other noise-suppression techniques and data filtering to improve alignments. This novel framework enhanced the capacity to capture the similarities between the temporal gene expression datasets separated by large evolutionary distances. We aligned and compared the temporal gene expression data in budding (Saccharomyces cerevisiae) and fission (Schizosaccharomyces pombe) yeast, which are separated by more then ~400 myr of evolution. We found that the global alignment (time warping) properly matched the duration of cell cycle phases in these distant organisms, which was measured in prior studies. At the same time, when applied to individual ortholog pairs, this alignment procedure revealed groups of genes with distinct alignments, different from the global alignment.

Conclusion

Our alignment-based predictions of differences in the cell cycle phases between the two yeast species were in a good agreement with the existing data, thus supporting the computational strategy adopted in this study. We propose that the existence of the alternative alignments, specific to distinct groups of genes, suggests presence of different synchronization modes between the two organisms and possible functional decoupling of particular physiological gene networks in the course of evolution.

Phase Coupled Meta-analysis: sensitive detection of oscillations in cell cycle gene expression, as applied to fission yeast

BACKGROUND

Many genes oscillate in their level of expression through the cell division cycle. Previous studies have identified such genes by applying Fourier analysis to cell cycle time course experiments. Typically, such analyses generate p-values; i.e., an oscillating gene has a small p-value, and the observed oscillation is unlikely due to chance. When multiple time course experiments are integrated, p-values from the individual experiments are combined using classical meta-analysis techniques. However, this approach sacrifices information inherent in the individual experiments, because the hypothesis that a gene is regulated according to the time in the cell cycle makes two independent predictions: first, that an oscillation in expression will be observed; and second, that gene expression will always peak in the same phase of the cell cycle, such as S-phase. Approaches that simply combine p-values ignore the second prediction.

RESULTS

Here, we improve the detection of cell cycle oscillating genes by systematically taking into account the phase of peak gene expression. We design a novel meta-analysis measure based on vector addition: when a gene peaks or troughs in all experiments in the same phase of the cell cycle, the representative vectors add to produce a large final vector. Conversely, when the peaks in different experiments are in various phases of the cycle, vector addition produces a small final vector. We apply the measure to ten genome-wide cell cycle time course experiments from the fission yeast Schizosaccharomyces pombe, and detect many new, weakly oscillating genes.

CONCLUSION

A very large fraction of all genes in S. pombe, perhaps one-quarter to one-half, show some cell cycle oscillation, although in many cases these oscillations may be incidental rather than adaptive.

Dissecting the fission yeast regulatory network reveals phase-specific control elements of its cell cycle

Background

Fission yeast Schizosaccharomyces pombe and budding yeast Saccharomyces cerevisiae are among the original model organisms in the study of the cell-division cycle. Unlike budding yeast, no large-scale regulatory network has been constructed for fission yeast. It has only been partially characterized. As a result, important regulatory cascades in budding yeast have no known or complete counterpart in fission yeast.

Results

By integrating genome-wide data from multiple time course cell cycle microarray experiments we reconstructed a gene regulatory network. Based on the network, we discovered in addition to previously known regulatory hubs in M phase, a new putative regulatory hub in the form of the HMG box transcription factor SPBC19G7.04. Further, we inferred periodic activities of several less known transcription factors over the course of the cell cycle, identified over 500 putative regulatory targets and detected many new phase-specific and conserved cis-regulatory motifs. In particular, we show that SPBC19G7.04 has highly significant periodic activity that peaks in early M phase, which is coordinated with the late G2 activity of the forkhead transcription factor fkh2. Finally, using an enhanced Bayesian algorithm to co-cluster the expression data, we obtained 31 clusters of co-regulated genes 1) which constitute regulatory modules from different phases of the cell cycle, 2) whose phase order is coherent across the 10 time course experiments, and 3) which lead to identification of phase-specific control elements at both the transcriptional and post-transcriptional levels in S. pombe. In particular, the ribosome biogenesis clusters expressed in G2 phase reveal new, highly conserved RNA motifs.

Conclusion

Using a systems-level analysis of the phase-specific nature of the S. pombe cell cycle gene regulation, we have provided new testable evidence for post-transcriptional regulation in the G2 phase of the fission yeast cell cycle. Based on this comprehensive gene regulatory network, we demonstrated how one can generate and investigate plausible hypotheses on fission yeast cell cycle regulation which can potentially be explored experimentally.

The fission yeast homeodomain protein Yox1p binds to MBF and confines MBF-dependent cell-cycle transcription to G1-S via negative feedback

The regulation of the G1- to S-phase transition is critical for cell-cycle progression. This transition is driven by a transient transcriptional wave regulated by transcription factor complexes termed MBF/SBF in yeast and E2F-DP in mammals. Here we apply genomic, genetic, and biochemical approaches to show that the Yox1p homeodomain protein of fission yeast plays a critical role in confining MBF-dependent transcription to the G1/S transition of the cell cycle. The yox1 gene is an MBF target, and Yox1p accumulates and preferentially binds to MBF-regulated promoters, via the MBF components Res2p and Nrm1p, when they are transcriptionally repressed during the cell cycle. Deletion of yox1 results in constitutively high transcription of MBF target genes and loss of their cell cycle-regulated expression, similar to deletion of nrm1. Genome-wide location analyses of Yox1p and the MBF component Cdc10p reveal dozens of genes whose promoters are bound by both factors, including their own genes and histone genes. In addition, Cdc10p shows promiscuous binding to other sites, most notably close to replication origins. This study establishes Yox1p as a new regulatory MBF component in fission yeast, which is transcriptionally induced by MBF and in turn inhibits MBF-dependent transcription. Yox1p may function together with Nrm1p to confine MBF-dependent transcription to the G1/S transition of the cell cycle via negative feedback. Compared to the orthologous budding yeast Yox1p, which indirectly functions in a negative feedback loop for cell-cycle transcription, similarities but also notable differences in the wiring of the regulatory circuits are evident.

A Cds1-mediated checkpoint protects the MBF activator Rep2 from ubiquitination by anaphase-promoting complex/cyclosome-Ste9 at S-phase arrest in fission yeast

Transcription of the MluI cell cycle box (MCB) motif-containing genes at G(1) phase is regulated by the MCB-binding factors (MBF) (also called DSC1) in Schizosaccharomyces pombe. Upon S-phase arrest, the MBF transcriptional activity is induced through the accumulation of the MBF activator Rep2. In this study, we show that the turnover of Rep2 is attributable to ubiquitin-mediated proteolysis. Levels of Rep2 oscillate during the cell cycle, with a peak at G(1) phase, coincident with the MBF activity. Furthermore, we show that Rep2 ubiquitination requires the function of the E3 ligase anaphase-promoting complex/cyclosome (APC/C). Ste9 can be phosphorylated by the checkpoint kinase Cds1 in vitro, and its inhibition/phosphorylation at S-phase arrest is dependent on the function of Cds1. Our data indicate that the Cds1-dependent stabilization of Rep2 is achieved through the inhibition/phosphorylation of APC/C-Ste9 at the onset of S-phase arrest. Stabilization of Rep2 is important for stimulating transcription of the MBF-dependent genes to ensure a sufficient supply of proteins essential for cell recovery from S-phase arrest. We propose that oscillation of Rep2 plays a role in regulation of periodic transcription of the MBF-dependent genes during cell cycle progression.

Maximum-likelihood model averaging to profile clustering of site types across discrete linear sequences

A major analytical challenge in computational biology is the detection and description of clusters of specified site types, such as polymorphic or substituted sites within DNA or protein sequences. Progress has been stymied by a lack of suitable methods to detect clusters and to estimate the extent of clustering in discrete linear sequences, particularly when there is no a priori specification of cluster size or cluster count. Here we derive and demonstrate a maximum likelihood method of hierarchical clustering. Our method incorporates a tripartite divide-and-conquer strategy that models sequence heterogeneity, delineates clusters, and yields a profile of the level of clustering associated with each site. The clustering model may be evaluated via model selection using the Akaike Information Criterion, the corrected Akaike Information Criterion, and the Bayesian Information Criterion. Furthermore, model averaging using weighted model likelihoods may be applied to incorporate model uncertainty into the profile of heterogeneity across sites. We evaluated our method by examining its performance on a number of simulated datasets as well as on empirical polymorphism data from diverse natural alleles of the Drosophila alcohol dehydrogenase gene. Our method yielded greater power for the detection of clustered sites across a breadth of parameter ranges, and achieved better accuracy and precision of estimation of clusters, than did the existing empirical cumulative distribution function statistics.

Transcriptional analysis of the Candida albicans cell cycle

We have examined the periodic expression of genes through the cell cycle in cultures of the human pathogenic fungus Candida albicans synchronized by mating pheromone treatment. Close to 500 genes show increased expression during the G1, S, G2, or M transitions of the C. albicans cell cycle. Comparisons of these C. albicans periodic genes with those already found in the budding and fission yeasts and in human cells reveal that of 2200 groups of homologous genes, close to 600 show periodicity in at least one organism, but only 11 are periodic in all four species. Overall, the C. albicans regulatory circuit most closely resembles that of Saccharomyces cerevisiae but contains a simplified structure. Although the majority of the C. albicans periodically regulated genes have homologues in the budding yeast, 20% (100 genes), most of which peak during the G1/S or M/G1 transitions, are unique to the pathogenic yeast.

BRNI: Modular analysis of transcriptional regulatory programs

BACKGROUND

Transcriptional responses often consist of regulatory modules - sets of genes with a shared expression pattern that are controlled by the same regulatory mechanisms. Previous methods allow dissecting regulatory modules from genomics data, such as expression profiles, protein-DNA binding, and promoter sequences. In cases where physical protein-DNA data are lacking, such methods are essential for the analysis of the underlying regulatory program.

RESULTS

Here, we present a novel approach for the analysis of modular regulatory programs. Our method - Biochemical Regulatory Network Inference (BRNI) - is based on an algorithm that learns from expression data a biochemically-motivated regulatory program. It describes the expression profiles of gene modules consisting of hundreds of genes using a small number of regulators and affinity parameters. We developed an ensemble learning algorithm that ensures the robustness of the learned model. We then use the topology of the learned regulatory program to guide the discovery of a library of cis-regulatory motifs, and determined the motif compositions associated with each module.We test our method on the cell cycle regulatory program of the fission yeast. We discovered 16 coherent modules, covering diverse processes from cell division to metabolism and associated them with 18 learned regulatory elements, including both known cell-cycle regulatory elements (MCB, Ace2, PCB, ACCCT box) and novel ones, some of which are associated with G2 modules. We integrate the regulatory relations from the expression- and motif-based models into a single network, highlighting specific topologies that result in distinct dynamics of gene expression in the fission yeast cell cycle.

CONCLUSION

Our approach provides a biologically-driven, principled way for deconstructing a set of genes into meaningful transcriptional modules and identifying their associated cis-regulatory programs. Our analysis sheds light on the architecture and function of the regulatory network controlling the fission yeast cell cycle, and a similar approach can be applied to the regulatory underpinnings of other modular transcriptional responses.

Role of the RNA-binding protein Nrd1 and Pmk1 mitogen-activated protein kinase in the regulation of myosin mRNA stability in fission yeast

Myosin II is an essential component of the actomyosin contractile ring and plays a crucial role in cytokinesis by generating the forces necessary for contraction of the actomyosin ring. Cdc4 is an essential myosin II light chain in fission yeast and is required for cytokinesis. In various eukaryotes, the phosphorylation of myosin is well documented as a primary means of activating myosin II, but little is known about the regulatory mechanisms of Cdc4. Here, we isolated Nrd1, an RNA-binding protein with RNA-recognition motifs, as a multicopy suppressor of cdc4 mutants. Notably, we demonstrated that Nrd1 binds and stabilizes Cdc4 mRNA, thereby suppressing the cytokinesis defects of the cdc4 mutants. Importantly, Pmk1 mitogen-activated protein kinase (MAPK) directly phosphorylates Nrd1, thereby negatively regulating the binding activity of Nrd1 to Cdc4 mRNA. Consistently, the inactivation of Pmk1 MAPK signaling, as well as Nrd1 overexpression, stabilized the Cdc4 mRNA level, thereby suppressing the cytokinesis defects associated with the cdc4 mutants. In addition, we demonstrated the cell cycle-dependent regulation of Pmk1/Nrd1 signaling. Together, our results indicate that Nrd1 plays a role in the regulation of Cdc4 mRNA stability; moreover, our study is the first to demonstrate the posttranscriptional regulation of myosin expression by MAPK signaling.

Estimation of Parameters Subject to Order Restrictions on a Circle With Application to Estimation of Phase Angles of Cell Cycle Genes

Motivated by a problem encountered in the analysis of cell cycle gene expression data, this article deals with the estimation of parameters subject to order restrictions on a unit circle. A normal eukaryotic cell cycle has four major phases during cell division, and a cell cycle gene has its peak expression (phase angle) during the phase that may correspond to its biological function. Because the phases are ordered along a circle, the phase angles of cell cycle genes are ordered unknown parameters on a unit circle. The problem of interest is to estimate the phase angles using the information regarding the order among them. We address this problem by developing a circular version of the well-known isotonic regression for Euclidean data. Because of the underlying geometry, the standard pool adjacent violator algorithm (PAVA) cannot be used for deriving the circular isotonic regression estimator (CIRE). However, PAVA can be modified to obtain a computationally efficient algorithm for deriving the CIRE. We illustrate the CIRE by estimating the phase angles of some of well-known cell cycle genes using the unrestricted estimators obtained in the literature.

A novel meta-analysis method exploiting consistency of high-throughput experiments

MOTIVATION

Large-scale biological experiments provide snapshots into the huge number of processes running in parallel within the organism. These processes depend on a large number of (hidden) (epi)genetic, social, environmental and other factors that are out of experimentalists' control. This makes it extremely difficult to identify the dominant processes and the elements involved in them based on a single experiment. It is therefore desirable to use multiple sets of experiments targeting the same phenomena while differing in some experimental parameters (hidden or controllable). Although such datasets are becoming increasingly common, their analysis is complicated by the fact that the various biological elements could be influenced by different sets of factors.

RESULTS

The central hypothesis of this article is that biologically related elements and processes are affected by changes in similar ways while unrelated ones are affected differently. Thus, the relations between related elements are more consistent across experiments. The method outlined here looks for groups of elements with robust intra-group relationships in the expectation that they are related. The major groups of elements may be identified in this way. The strengths of relationships per se are not valued, just their consistency. This represents a completely novel and unutilized source of information. In the analysis of time course microarray experiments, I found cell cycle- and ribosome-related genes to be the major groups. Despite not looking for these groups in particular, the identification of these genes rivals that of methods designed specifically for this purpose.

AVAILABILITY

A C++ implementation is available at http://www.rinst.org/ICS/ICS_Programs.tar.gz.

Periodic gene expression patterns during the highly synchronized cell nucleus and organelle division cycles in the unicellular red alga Cyanidioschyzon merolae

Previous cell cycle studies have been based on cell-nuclear proliferation only. Eukaryotic cells, however, have double membranes-bound organelles, such as the cell nucleus, mitochondrion, plastids and single-membrane-bound organelles such as ER, the Golgi body, vacuoles (lysosomes) and microbodies. Organelle proliferations, which are very important for cell functions, are poorly understood. To clarify this, we performed a microarray analysis during the cell cycle of Cyanidioschyzon merolae. C. merolae cells contain a minimum set of organelles that divide synchronously. The nuclear, mitochondrial and plastid genomes were completely sequenced. The results showed that, of 158 genes induced during the S or G2-M phase, 93 were known and contained genes related to mitochondrial division, ftsZ1-1, ftsz1-2 and mda1, and plastid division, ftsZ2-1, ftsZ2-2 and cmdnm2. Moreover, three genes, involved in vesicle trafficking between the single-membrane organelles such as vps29 and the Rab family protein, were identified and might be related to partitioning of single-membrane-bound organelles. In other genes, 46 were hypothetical and 19 were hypothetical conserved. The possibility of finding novel organelle division genes from hypothetical and hypothetical conserved genes in the S and G2-M expression groups is discussed.

The DNA replication checkpoint directly regulates MBF-dependent G1/S transcription

The DNA replication checkpoint transcriptionally upregulates genes that allow cells to adapt to and survive replication stress. Our results show that, in the fission yeast Schizosaccharomyces pombe, the replication checkpoint regulates the entire G(1)/S transcriptional program by directly regulating MBF, the G(1)/S transcription factor. Instead of initiating a checkpoint-specific transcriptional program, the replication checkpoint targets MBF to maintain the normal G(1)/S transcriptional program during replication stress. We propose a mechanism for this regulation, based on in vitro phosphorylation of the Cdc10 subunit of MBF by the Cds1 replication-checkpoint kinase. Replacement of two potential phosphorylation sites with phosphomimetic amino acids suffices to promote the checkpoint transcriptional program, suggesting that Cds1 phosphorylation directly regulates MBF-dependent transcription. The conservation of MBF between fission and budding yeast, and recent results implicating MBF as a target of the budding yeast replication checkpoint, suggests that checkpoint regulation of the MBF transcription factor is a conserved strategy for coping with replication stress. Furthermore, the structural and regulatory similarity between MBF and E2F, the metazoan G(1)/S transcription factor, suggests that this checkpoint mechanism may be broadly conserved among eukaryotes.

Circular reasoning rather than cyclic expression

A response to Combined analysis reveals a core set of cycling genes by Y Lu, S Mahony, PV Benos, R Rosenfeld, I Simon, LL Breeden and Z Bar-Joseph. Genome Biol 2007, 8:R146.

Combined analysis reveals a core set of cycling genes

The simultaneous analysis of expression data from multiple species reveals a core set of conserved cycling genes that is much larger than previously thought.

Background

Global transcript levels throughout the cell cycle have been characterized using microarrays in several species. Early analysis of these experiments focused on individual species. More recently, a number of studies have concluded that a surprisingly small number of genes conserved in two or more species are periodically transcribed in these species. Combining and comparing data from multiple species is challenging because of noise in expression data, the different synchronization and scoring methods used, and the need to determine an accurate set of homologs.

Results

To solve these problems, we developed and applied a new algorithm to analyze expression data from multiple species simultaneously. Unlike previous studies, we find that more than 20% of cycling genes in budding yeast have cycling homologs in fission yeast and 5% to 7% of cycling genes in each of four species have cycling homologs in all other species. These conserved cycling genes display much stronger cell cycle characteristics in several complementary high throughput datasets.

Essentiality analysis for yeast and human genes confirms these findings. Motif analysis indicates conservation in the corresponding regulatory mechanisms. Gene Ontology analysis and analysis of the genes in the conserved sets sheds light on the evolution of specific subfunctions within the cell cycle.

Conclusion

Our results indicate that the conservation in cyclic expression patterns is much greater than was previously thought. These genes are highly enriched for most cell cycle categories, and a large percentage of them are essential, supporting our claim that cross-species analysis can identify the core set of cycling genes.

Pxl1p, a paxillin-related protein, stabilizes the actomyosin ring during cytokinesis in fission yeast

Paxillins are a family of conserved LIM domain-containing proteins that play important roles in the function and integrity of the actin cytoskeleton. Although paxillins have been extensively characterized by cell biological and biochemical approaches, genetic studies are relatively scarce. Here, we identify and characterize a paxillin-related protein Pxl1p in the fission yeast Schizosaccharomyces pombe. Pxl1p is a component of the fission yeast actomyosin ring, a structure that is essential for cytokinesis. Cells deleted for pxl1 display a novel phenotype characterized by a splitting of the actomyosin ring in late anaphase, leading to the formation of two rings of which only one undergoes constriction. In addition, the rate of actomyosin ring constriction is slower in the absence of Pxl1p. pxl1Delta mutants display strong genetic interactions with mutants defective in IQGAP-related protein Rng2p and mutants defective in components of the fission yeast type II myosin machinery. Collectively, these results suggest that Pxl1p might cooperate with type II myosin and Rng2p-IQGAP to regulate actomyosin ring constriction as well as to maintain its integrity during constriction.

Genome-wide transcriptional analysis of the human cell cycle identifies genes differentially regulated in normal and cancer cells

Characterization of the transcriptional regulatory network of the normal cell cycle is essential for understanding the perturbations that lead to cancer. However, the complete set of cycling genes in primary cells has not yet been identified. Here, we report the results of genome-wide expression profiling experiments on synchronized primary human foreskin fibroblasts across the cell cycle. Using a combined experimental and computational approach to deconvolve measured expression values into "single-cell" expression profiles, we were able to overcome the limitations inherent in synchronizing nontransformed mammalian cells. This allowed us to identify 480 periodically expressed genes in primary human foreskin fibroblasts. Analysis of the reconstructed primary cell profiles and comparison with published expression datasets from synchronized transformed cells reveals a large number of genes that cycle exclusively in primary cells. This conclusion was supported by both bioinformatic analysis and experiments performed on other cell types. We suggest that this approach will help pinpoint genetic elements contributing to normal cell growth and cellular transformation.

Regulation of gene expression during M-G1-phase in fission yeast through Plo1p and forkhead transcription factors

In fission yeast the expression of several genes during M-G1 phase is controlled by binding of the PCB binding factor (PBF) transcription factor complex to Pombe cell cycle box (PCB) promoter motifs. Three components of PBF have been identified, including two forkhead-like proteins Sep1p and Fkh2p, and a MADS-box-like protein, Mbx1p. Here, we examine how PBF is controlled and reveal a role for the Polo kinase Plo1p. plo1(+) shows genetic interactions with sep1(+), fkh2(+) and mbx1(+), and overexpression of a kinase-domain mutant of plo1 abolishes M-G1-phase transcription. Plo1p binds to and directly phosphorylates Mbx1p, the first time a Polo kinase has been shown to phosphorylate a MADS box protein in any organism. Fkh2p and Sep1p interact in vivo and in vitro, and Fkh2p, Sep1p and Plo1p contact PCB promoters in vivo. However, strikingly, both Fkh2p and Plo1p bind to PCB promoters only when PCB-controlled genes are not expressed during S- and G2-phase, whereas by contrast Sep1p contacts PCBs coincident with M-G1-phase transcription. Thus, Plo1p, Fkh2p and Sep1p control M-G1-phase gene transcription through a combination of phosphorylation and cell-cycle-specific DNA binding to PCBs.

Novel algorithm for coexpression detection in time-varying microarray data sets

When analyzing the results of microarray experiments, biologists generally use unsupervised categorization tools. However, such tools regard each time point as an independent dimension and utilize the Euclidean distance to compute the similarities between expressions. Furthermore, some of these methods require the number of clusters to be determined in advance, which is clearly impossible in the case of a new dataset. Therefore, this study proposes a novel scheme, designated as the Variation-based Coexpression Detection (VCD) algorithm, to analyze the trends of expressions based on their variation over time. The proposed algorithm has two advantages. First, it is unnecessary to determine the number of clusters in advance since the algorithm automatically detects those genes whose profiles are grouped together and creates patterns for these groups. Second, the algorithm features a new measurement criterion for calculating the degree of change of the expressions between adjacent time points and evaluating their trend similarities. Three real-world microarray datasets are employed to evaluate the performance of the proposed algorithm.