Genome-wide expression profiling, in vivo DNA binding analysis, and probabilistic motif prediction reveal novel Abf1 target genes during fermentation, respiration, and sporulation in yeast

Nucleosome remodeling at origins of global genome-nucleotide excision repair occurs at the boundaries of higher-order chromatin structure

Repair of UV-induced DNA damage requires chromatin remodeling. How repair is initiated in chromatin remains largely unknown. We recently demonstrated that global genome–nucleotide excision repair (GG-NER) in chromatin is organized into domains in relation to open reading frames. Here, we define these domains, identifying the genomic locations from which repair is initiated. By examining DNA damage–induced changes in the linear structure of nucleosomes at these sites, we demonstrate how chromatin remodeling is initiated during GG-NER. In undamaged cells, we show that the GG-NER complex occupies chromatin, establishing the nucleosome structure at these genomic locations, which we refer to as GG-NER complex binding sites (GCBSs). We demonstrate that these sites are frequently located at genomic boundaries that delineate chromosomally interacting domains (CIDs). These boundaries define domains of higher-order nucleosome–nucleosome interaction. We demonstrate that initiation of GG-NER in chromatin is accompanied by the disruption of dynamic nucleosomes that flank GCBSs by the GG-NER complex.

A global function for transcription factors in assisting RNA polymerase II termination

The role of transcription factors (TFs) on nucleosome positioning, RNA polymerase recruitment, and transcription initiation has been extensively characterized. Here, we propose that a subset of TFs such as Reb1, Abf1, Rap1, and TFIIIB also serve a major function in partitioning transcription units by assisting the Nrd1p-Nab3p-Sen1p Pol II termination pathway.

Abf1 and other general regulatory factors control ribosome biogenesis gene expression in budding yeast

Ribosome biogenesis in Saccharomyces cerevisiae involves a regulon of >200 genes (Ribi genes) coordinately regulated in response to nutrient availability and cellular growth rate. Two cis-acting elements called PAC and RRPE are known to mediate Ribi gene repression in response to nutritional downshift. Here, we show that most Ribi gene promoters also contain binding sites for one or more General Regulatory Factors (GRFs), most frequently Abf1 and Reb1, and that these factors are enriched in vivo at Ribi promoters. Abf1/Reb1/Tbf1 promoter association was required for full Ribi gene expression in rich medium and for its modulation in response to glucose starvation, characterized by a rapid drop followed by slow recovery. Such a response did not entail changes in Abf1 occupancy, but it was paralleled by a quick increase, followed by slow decrease, in Rpd3L histone deacetylase occupancy. Remarkably, Abf1 site disruption also abolished Rpd3L complex recruitment in response to starvation. Extensive mutational analysis of the DBP7 promoter revealed a complex interplay of Tbf1 sites, PAC and RRPE in the transcriptional regulation of this Ribi gene. Our observations point to GRFs as new multifaceted players in Ribi gene regulation both during exponential growth and under repressive conditions.

Global genome nucleotide excision repair is organized into domains that promote efficient DNA repair in chromatin

The rates at which lesions are removed by DNA repair can vary widely throughout the genome, with important implications for genomic stability. To study this, we measured the distribution of nucleotide excision repair (NER) rates for UV-induced lesions throughout the budding yeast genome. By plotting these repair rates in relation to genes and their associated flanking sequences, we reveal that, in normal cells, genomic repair rates display a distinctive pattern, suggesting that DNA repair is highly organized within the genome. Furthermore, by comparing genome-wide DNA repair rates in wild-type cells and cells defective in the global genome-NER (GG-NER) subpathway, we establish how this alters the distribution of NER rates throughout the genome. We also examined the genomic locations of GG-NER factor binding to chromatin before and after UV irradiation, revealing that GG-NER is organized and initiated from specific genomic locations. At these sites, chromatin occupancy of the histone acetyl-transferase Gcn5 is controlled by the GG-NER complex, which regulates histone H3 acetylation and chromatin structure, thereby promoting efficient DNA repair of UV-induced lesions. Chromatin remodeling during the GG-NER process is therefore organized into these genomic domains. Importantly, loss of Gcn5 significantly alters the genomic distribution of NER rates; this has implications for the effects of chromatin modifiers on the distribution of mutations that arise throughout the genome.

Multiple roles of the general regulatory factor Abf1 in yeast ribosome biogenesis

In Saccharomyces cerevisiae, the large majority of the genes coding for cytoplasmic ribosomal proteins (RPs) depend on the general regulatory factor Rap1 for their transcription, but a small cohort of them relies on Abf1 regulatory activity. A recent study showed that unlike Rap1, whose association with RP gene promoters is not affected by environmental changes causing RP gene repression/reactivation, Abf1 association with both RP gene and ribosome biogenesis (Ribi) gene promoters dynamically responds to changes in growth conditions. This observation changes the paradigm of general regulatory factors as relatively static DNA-binding proteins constitutively bound to highly active promoters, and point to Abf1, which binds hundreds of non-RPG promoters within the yeast genome, as a possible key regulatory switch in nutrient- and stress-dependent transcriptional modulation. Moreover, the frequent presence of Abf1 binding sites in the promoters of mitochondrial RP genes evokes the possibility that Abf1 might orchestrate still unexplored levels of co-regulation involving growth-related gene networks in yeast cells.

Exploring the roles of basal transcription factor 3 in eukaryotic growth and development

Basal transcription factor 3 (BTF3) has been reported to play a significant part in the transcriptional regulation linking with eukaryotes growth and development. Alteration in the BTF3 gene expression patterns or variation in their activities adds to the explanation of different signaling pathways and regulatory networks. Moreover, BTF3s often respond to numerous stresses, and subsequently they are involved in regulation of various mechanisms. BTF3 proteins also function through protein-protein contact, which can assist us to identify the multifaceted processes of signaling and transcriptional regulation controlled by BTF3 proteins. In this review, we discuss current advances made in starting to explore the roles of BTF3 transcription factors in eukaryotes especially in plant growth and development.

Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure

ChIP-chip is a microarray based technology for determining the genomic locations of chromatin bound factors of interest, such as proteins. Standard ChIP-chip analyses employ peak detection methodologies to generate lists of genomic binding sites. No previously published method exists to enable comparative analyses of enrichment levels derived from datasets examining different experimental conditions. This restricts the use of the technology to binary comparisons of presence or absence of features between datasets. Here we present the R package Sandcastle — Software for the Analysis and Normalisation of Data from ChIP-chip AssayS of Two or more Linked Experiments — which allows for comparative analyses of data from multiple experiments by normalising all datasets to a common background. Relative changes in binding levels between experimental datasets can thus be determined, enabling the extraction of latent information from ChIP-chip experiments. Novel enrichment detection and peak calling algorithms are also presented, with a range of graphical tools, which facilitate these analyses. The software and documentation are available for download from http://reedlab.cardiff.ac.uk/sandcastle.

Decoupling of divergent gene regulation by sequence-specific DNA binding factors

Divergent gene pairs (DGPs) are abundant in eukaryotic genomes. Since two genes in a DGP potentially share the same regulatory sequence, one might expect that they should be co-regulated. However, an inspection of yeast DGPs containing cell-cycle or stress response genes revealed that most DGPs are differentially-regulated. The mechanism underlying DGP differential regulation is not understood. Here, we showed that co- versus differential regulation cannot be explained by genetic features including promoter length, binding site orientation, TATA elements, nucleosome distribution, or presence of non-coding RNAs. Using time-lapse fluorescence microscopy, we carried out an in-depth study of a differentially regulated DGP, PFK26-MOB1. We found that their differential regulation is mainly achieved through two DNA-binding factors, Tbf1 and Mcm1. Similar to 'enhancer-blocking insulators' in higher eukaryotes, these factors shield the proximal promoter from the action of more distant transcription regulators. We confirmed the blockage function of Tbf1 using synthetic promoters. We further presented evidence that the blockage mechanism is widely used among genome-wide DGPs. Besides elucidating the DGP regulatory mechanism, our work revealed a novel class of insulators in yeast.

Chromatin mediation of a transcriptional memory effect in yeast

Previous studies have described a transcriptional "memory effect," whereby transcript levels of many Abf1-regulated genes in the budding yeast Saccharomyces cerevisiae are undiminished even after Abf1 has dissociated from its regulatory sites. Here we provide additional support for this effect and investigate its molecular basis. We show that the effect is observed in a distinct abf1 ts mutant from that used in earlier studies, demonstrating that it is robust, and use chromatin immunoprecipitation to show that Abf1 association is decreased similarly from memory effect and transcriptionally responsive genes at the restrictive temperature. We also demonstrate that the association of TATA-binding protein and Pol II decreases after the loss of Abf1 binding for transcriptionally responsive genes but not for memory effect genes. Examination of genome-wide nucleosome occupancy data reveals that although transcriptionally responsive genes exhibit increased nucleosome occupancy in abf1 ts yeast, the promoter regions of memory effect targets show no change in abf1 ts mutants, maintaining an open chromatin conformation even after Abf1 eviction. This contrasting behavior reflects different inherent propensity for nucleosome formation between the two classes, driven by the presence of A/T-rich sequences upstream of the Abf1 site in memory effect gene promoters. These sequence-based differences show conservation in closely related fungi and also correlate with different gene expression noise, suggesting a physiological basis for greater access to "memory effect" promoter regions. Thus, our results establish a conserved mechanism underlying a transcriptional memory effect whereby sequences surrounding Abf1 binding sequences affect local nucleosome occupancy following loss of Abf1 binding. Furthermore, these findings demonstrate that sequence-based differences in the propensity for nucleosome occupancy can influence the transcriptional response of genes to an altered regulatory signal.

Research resource: the dynamic transcriptional profile of sertoli cells during the progression of spermatogenesis

Sertoli cells (SCs), the only somatic cells within seminiferous tubules, associate intimately with developing germ cells. They not only provide physical and nutritional support but also secrete factors essential to the complex developmental processes of germ cell proliferation and differentiation. The SC transcriptome must therefore adapt rapidly during the different stages of spermatogenesis. We report comprehensive genome-wide expression profiles of pure populations of SCs isolated at 5 distinct stages of the first wave of mouse spermatogenesis, using RNA sequencing technology. We were able to reconstruct about 13 901 high-confidence, nonredundant coding and noncoding transcripts, characterized by complex alternative splicing patterns with more than 45% comprising novel isoforms of known genes. Interestingly, roughly one-fifth (2939) of these genes exhibited a dynamic expression profile reflecting the evolving role of SCs during the progression of spermatogenesis, with stage-specific expression of genes involved in biological processes such as cell cycle regulation, metabolism and energy production, retinoic acid synthesis, and blood-testis barrier biogenesis. Finally, regulatory network analysis identified the transcription factors endothelial PAS domain-containing protein 1 (EPAS1/Hif2α), aryl hydrocarbon receptor nuclear translocator (ARNT/Hif1β), and signal transducer and activator of transcription 1 (STAT1) as potential master regulators driving the SC transcriptional program. Our results highlight the plastic transcriptional landscape of SCs during the progression of spermatogenesis and provide valuable resources to better understand SC function and spermatogenesis and its related disorders, such as male infertility.

Promoter architectures in the yeast ribosomal expression program

Ribosome biogenesis begins with the orchestrated expression of hundreds of genes, including the three large classes of ribosomal protein, ribosome biogenesis and snoRNA genes. Current knowledge about the corresponding promoters suggests the existence of novel class-specific transcriptional strategies and crosstalk between telomere length and cell growth control.

Genome-wide identification of Sox8-, and Sox9-dependent genes during early post-natal testis development in the mouse

The SOX8 and SOX9 transcription factors are involved in, among others, sex differentiation, male gonad development and adult maintenance of spermatogenesis. Sox8(-/-) mice lacking Sox9 in Sertoli cells fail to form testis cords and cannot establish spermatogenesis. Although genetic and histological data show an important role for these transcription factors in regulating spermatogenesis, it is not clear which genes depend upon them at a genome-wide level. To identify transcripts that respond to the absence of Sox8 in all cells and Sox9 in Sertoli cells we measured mRNA concentrations in testicular samples from mice at 0, 6 and 18 days post-partum. In total, 621 and 629 transcripts were found at decreased or increased levels, respectively, at different time points in the mutant as compared to the control samples. These mRNAs were categorized as preferentially expressed in Sertoli cells or germ cells using data obtained with male and female gonad samples and enriched testicular cell populations. Five candidate genes were validated at the protein level. Furthermore, we identified putative direct SOX8 and SOX9 target genes by integrating predicted SOX-binding sites present in potential regulatory regions upstream of the transcription start site. Finally, we used protein network data to gain insight into the effects on regulatory interactions that occur when Sox8 and Sox9 are absent in developing Sertoli cells. The integration of testicular samples with enriched Sertoli cells, germ cells and female gonads enabled us to broadly distinguish transcripts directly affected in Sertoli cells from others that respond to secondary events in testicular cell types. Thus, combined RNA profiling signals, motif predictions and network data identified putative SOX8/SOX9 target genes in Sertoli cells and yielded insight into regulatory interactions that depend upon these transcription factors. In addition, our results will facilitate the interpretation of genome-wide in vivo SOX8 and SOX9 DNA binding data.

Cationic amphiphilic drugs are potent inhibitors of yeast sporulation

Meiosis is a highly regulated developmental process that occurs in all eukaryotes that engage in sexual reproduction. Previous epidemiological work shows that male and female infertility is rising and environmental factors, including pollutants such as organic solvents, are thought to play a role in this phenomenon. To better understand how organic compounds interfere with meiotic development, the model organism Saccharomyces cerevisiae was exposed to 446 bioactive molecules while undergoing meiotic development, and sporulation efficiency was quantified employing two different high-throughput assays. 12 chemicals were identified that strongly inhibited spore formation but did not interfere with vegetative growth. Many of these chemicals are known to bind to monoamine-receptors in higher eukaryotes and are cationic amphiphilic drugs. A detailed analysis of one of these drugs, tripelennamine, revealed that it induces sporulation-specific cytotoxicity and a strong inhibition of meiotic M phase. The drug, however, only mildly interfered with pre-meiotic DNA synthesis and the early meiotic transcriptional program. Chemical-genomic screening identified genes involved in autophagy as hypersensitive to tripelennamine. In addition, we found that growing and sporulating yeast cells heterozygous for the aminophospholipid translocase, NEO1, are haploinsufficient in the presence of the drug.

The bioinformatics tool box for reproductive biology

Genetics and molecular biology have been instrumental for a better understanding of heritable defects causing human infertility over the past decades. More recently, the field of reproductive biology has harnessed genome biological approaches to gain insight into molecular processes underlying normal and pathological gametogenesis and gamete function. We are currently witnessing yet another quantum leap in our ability to monitor the flow of information from the genome via the transcriptome to the proteome: tiling arrays that cover both strands of a given target genome and RNA-Seq, a method based on ultra-high throughput DNA sequencing, enable us to study noncoding and protein-coding transcripts with unprecedented precision and depth at a reasonable cost. These technologies have spawned a thriving discipline within the bioinformatics field that employs information technology for managing and interpreting biological high-throughput data. This review outlines database projects and online analysis tools useful for life scientists in general and discusses in detail selected projects that have specifically been developed for researchers and clinicians in the field of reproductive biology. This article is part of a Special Issue entitled: Molecular Genetics of Human Reproductive Failure.

A hierarchical combination of factors shapes the genome-wide topography of yeast meiotic recombination initiation

The nonrandom distribution of meiotic recombination influences patterns of inheritance and genome evolution, but chromosomal features governing this distribution are poorly understood. Formation of the DNA double-strand breaks (DSBs) that initiate recombination results in the accumulation of Spo11 protein covalently bound to small DNA fragments. By sequencing these fragments, we uncover a genome-wide DSB map of unprecedented resolution and sensitivity. We use this map to explore how DSB distribution is influenced by large-scale chromosome structures, chromatin, transcription factors, and local sequence composition. Our analysis offers mechanistic insight into DSB formation and early processing steps, supporting the view that the recombination terrain is molded by combinatorial and hierarchical interaction of factors that work on widely different size scales. This map illuminates the occurrence of DSBs in repetitive DNA elements, repair of which can lead to chromosomal rearrangements. We also discuss implications for evolutionary dynamics of recombination hot spots.

GermOnline 4.0 is a genomics gateway for germline development, meiosis and the mitotic cell cycle

GermOnline 4.0 is a cross-species database portal focusing on high-throughput expression data relevant for germline development, the meiotic cell cycle and mitosis in healthy versus malignant cells. It is thus a source of information for life scientists as well as clinicians who are interested in gene expression and regulatory networks. The GermOnline gateway provides unlimited access to information produced with high-density oligonucleotide microarrays (3'-UTR GeneChips), genome-wide protein-DNA binding assays and protein-protein interaction studies in the context of Ensembl genome annotation. Samples used to produce high-throughput expression data and to carry out genome-wide in vivo DNA binding assays are annotated via the MIAME-compliant Multiomics Information Management and Annotation System (MIMAS 3.0). Furthermore, the Saccharomyces Genomics Viewer (SGV) was developed and integrated into the gateway. SGV is a visualization tool that outputs genome annotation and DNA-strand specific expression data produced with high-density oligonucleotide tiling microarrays (Sc_tlg GeneChips) which cover the complete budding yeast genome on both DNA strands. It facilitates the interpretation of expression levels and transcript structures determined for various cell types cultured under different growth and differentiation conditions. Database URL: www.germonline.org/

Extensive role of the general regulatory factors, Abf1 and Rap1, in determining genome-wide chromatin structure in budding yeast

The packaging of eukaryotic DNA into chromatin has profound consequences for gene regulation, as well as for other DNA transactions such as recombination, replication and repair. Understanding how this packaging is determined is consequently a pressing problem in molecular genetics. DNA sequence, chromatin remodelers and transcription factors affect chromatin structure, but the scope of these influences on genome-wide nucleosome occupancy patterns remains uncertain. Here, we use high resolution tiling arrays to examine the contributions of two general regulatory factors, Abf1 and Rap1, to nucleosome occupancy in Saccharomyces cerevisiae. These factors have each been shown to bind to a few hundred promoters, but we find here that thousands of loci show localized regions of altered nucleosome occupancy within 1 h of loss of Abf1 or Rap1 binding, and that altered chromatin structure can occur via binding sites having a wide range of affinities. These results indicate that DNA-binding transcription factors affect chromatin structure, and probably dynamics, throughout the genome to a much greater extent than previously appreciated.

Correlating gene expression variation with cis-regulatory polymorphism in Saccharomyces cerevisiae

Identifying the nucleotides that cause gene expression variation is a critical step in dissecting the genetic basis of complex traits. Here, we focus on polymorphisms that are predicted to alter transcription factor binding sites (TFBSs) in the yeast, Saccharomyces cerevisiae. We assembled a confident set of transcription factor motifs using recent protein binding microarray and ChIP-chip data and used our collection of motifs to predict a comprehensive set of TFBSs across the S. cerevisiae genome. We used a population genomics analysis to show that our predictions are accurate and significantly improve on our previous annotation. Although predicting gene expression from sequence is thought to be difficult in general, we identified a subset of genes for which changes in predicted TFBSs correlate well with expression divergence between yeast strains. Our analysis thus demonstrates both the accuracy of our new TFBS predictions and the feasibility of using simple models of gene regulation to causally link differences in gene expression to variation at individual nucleotides.

Mitotic expression of Spo13 alters M-phase progression and nucleolar localization of Cdc14 in budding yeast

Spo13 is a key meiosis-specific regulator required for centromere cohesion and coorientation, and for progression through two nuclear divisions. We previously reported that it causes a G2/M arrest and may delay the transition from late anaphase to G1, when overexpressed in mitosis. Yet its mechanism of action has remained elusive. Here we show that Spo13, which is phosphorylated and stabilized at G2/M in a Cdk/Clb-dependent manner, acts at two stages during mitotic cell division. Spo13 provokes a G2/M arrest that is reversible and largely independent of the Mad2 spindle checkpoint. Since mRNAs whose induction requires Cdc14 activation are reduced, we propose that its anaphase delay results from inhibition of Cdc14 function. Indeed, the Spo13-induced anaphase delay correlates with Cdc14 phosphatase retention in the nucleolus and with cyclin B accumulation, which both impede anaphase exit. At the onset of arrest, Spo13 is primarily associated with the nucleolus, where Cdc14 accumulates. Significantly, overexpression of separase (Esp1), which promotes G2/M and anaphase progression, suppresses Spo13 effects in mitosis, arguing that Spo13 acts upstream or parallel to Esp1. Given that Spo13 overexpression reduces Pds1 and cyclin B degradation, our findings are consistent with a role for Spo13 in regulating APC, which controls both G2/M and anaphase. Similar effects of Spo13 during meiotic MI may prevent cell cycle exit and initiation of DNA replication prior to MII, thereby ensuring two successive chromosome segregation events without an intervening S phase.

Impact of DNA-binding position variants on yeast gene expression

Transcription factors (TFs) regulate gene expression by binding to specific binding sites (TFBSs) in gene promoters. TFBS motifs may contain one or more variable positions. Although the prevailing assumption is that nucleotide variants at such positions are functionally equivalent, there is increasing evidence that such variants play a role in regulation of gene expression. In this article, we propose a method for studying the relationship between the expression of target genes and nucleotide variants in TFBS motifs at a genome-wide scale in Saccharomyces cerevisiae, especially the combinatorial effects of variants at two positions. Our analysis shows that nucleotide variations in more than one-third of variable positions and in 20% of dependent position pairs are highly correlated to gene expression. We define such positions as 'functional'. However, some positions are only functional as dependent pairs, but not individually. In addition, a significant proportion of the functional positions have been well conserved across all yeast-related species studied. We also find that some positions require the presence of co-occurring TFs, while others maintain their functionality in the absence of a co-occurring TF. Our analysis supports the importance of nucleotide variants at variable positions of TFBSs in gene regulation.

Uncovering transcriptional interactions via an adaptive fuzzy logic approach

BACKGROUND

To date, only a limited number of transcriptional regulatory interactions have been uncovered. In a pilot study integrating sequence data with microarray data, a position weight matrix (PWM) performed poorly in inferring transcriptional interactions (TIs), which represent physical interactions between transcription factors (TF) and upstream sequences of target genes. Inferring a TI means that the promoter sequence of a target is inferred to match the consensus sequence motifs of a potential TF, and their interaction type such as AT or RT is also predicted. Thus, a robust PWM (rPWM) was developed to search for consensus sequence motifs. In addition to rPWM, one feature extracted from ChIP-chip data was incorporated to identify potential TIs under specific conditions. An interaction type classifier was assembled to predict activation/repression of potential TIs using microarray data. This approach, combining an adaptive (learning) fuzzy inference system and an interaction type classifier to predict transcriptional regulatory networks, was named AdaFuzzy.

RESULTS

AdaFuzzy was applied to predict TIs using real genomics data from Saccharomyces cerevisiae. Following one of the latest advances in predicting TIs, constrained probabilistic sparse matrix factorization (cPSMF), and using 19 transcription factors (TFs), we compared AdaFuzzy to four well-known approaches using over-representation analysis and gene set enrichment analysis. AdaFuzzy outperformed these four algorithms. Furthermore, AdaFuzzy was shown to perform comparably to 'ChIP-experimental method' in inferring TIs identified by two sets of large scale ChIP-chip data, respectively. AdaFuzzy was also able to classify all predicted TIs into one or more of the four promoter architectures. The results coincided with known promoter architectures in yeast and provided insights into transcriptional regulatory mechanisms.

CONCLUSION

AdaFuzzy successfully integrates multiple types of data (sequence, ChIP, and microarray) to predict transcriptional regulatory networks. The validated success in the prediction results implies that AdaFuzzy can be applied to uncover TIs in yeast.

Cis-regulatory elements in plant cell signaling

Plant cell signaling pathways are in part dependent on transcriptional regulatory networks comprising circuits of transcription factors (TFs) and regulatory DNA elements that control the expression of target genes. Here, we describe experimental and bioinformatic approaches for identifying potential cis-regulatory elements. We also discuss recent integrative genomics studies aimed at elucidating the functions of cis-regulatory elements in aspects of plant biology, including the circadian clock, interactions with the environment, stress responses, and regulation of growth and development by phytohormones. Finally, we discuss emerging technologies and approaches that offer great potential for accelerating the discovery and functional characterization of cis-elements and interacting TFs--which will help realize the promise of systems biology.

Identification of yeast transcriptional regulation networks using multivariate random forests

The recent availability of whole-genome scale data sets that investigate complementary and diverse aspects of transcriptional regulation has spawned an increased need for new and effective computational approaches to analyze and integrate these large scale assays. Here, we propose a novel algorithm, based on random forest methodology, to relate gene expression (as derived from expression microarrays) to sequence features residing in gene promoters (as derived from DNA motif data) and transcription factor binding to gene promoters (as derived from tiling microarrays). We extend the random forest approach to model a multivariate response as represented, for example, by time-course gene expression measures. An analysis of the multivariate random forest output reveals complex regulatory networks, which consist of cohesive, condition-dependent regulatory cliques. Each regulatory clique features homogeneous gene expression profiles and common motifs or synergistic motif groups. We apply our method to several yeast physiological processes: cell cycle, sporulation, and various stress conditions. Our technique displays excellent performance with regard to identifying known regulatory motifs, including high order interactions. In addition, we present evidence of the existence of an alternative MCB-binding pathway, which we confirm using data from two independent cell cycle studies and two other physioloigical processes. Finally, we have uncovered elaborate transcription regulation refinement mechanisms involving PAC and mRRPE motifs that govern essential rRNA processing. These include intriguing instances of differing motif dosages and differing combinatorial motif control that promote regulatory specificity in rRNA metabolism under differing physiological processes.

MIMAS 3.0 is a Multiomics Information Management and Annotation System

Background

DNA sequence integrity, mRNA concentrations and protein-DNA interactions have been subject to genome-wide analyses based on microarrays with ever increasing efficiency and reliability over the past fifteen years. However, very recently novel technologies for Ultra High-Throughput DNA Sequencing (UHTS) have been harnessed to study these phenomena with unprecedented precision. As a consequence, the extensive bioinformatics environment available for array data management, analysis, interpretation and publication must be extended to include these novel sequencing data types.

Description

MIMAS was originally conceived as a simple, convenient and local Microarray Information Management and Annotation System focused on GeneChips for expression profiling studies. MIMAS 3.0 enables users to manage data from high-density oligonucleotide SNP Chips, expression arrays (both 3'UTR and tiling) and promoter arrays, BeadArrays as well as UHTS data using MIAME-compliant standardized vocabulary. Importantly, researchers can export data in MAGE-TAB format and upload them to the EBI's ArrayExpress certified data repository using a one-step procedure.

Conclusion

We have vastly extended the capability of the system such that it processes the data output of six types of GeneChips (Affymetrix), two different BeadArrays for mRNA and miRNA (Illumina) and the Genome Analyzer (a popular Ultra-High Throughput DNA Sequencer, Illumina), without compromising on its flexibility and user-friendliness. MIMAS, appropriately renamed into Multiomics Information Management and Annotation System, is currently used by scientists working in approximately 50 academic laboratories and genomics platforms in Switzerland and France. MIMAS 3.0 is freely available via .