Expression variability of co-regulated genes differentiates Saccharomyces cerevisiae strains

Background: Saccharomyces cerevisiae (Baker’s yeast) is found in diverse ecological niches and is characterized by high adaptive potential under challenging environments. In spite of recent advances on the study of yeast genome diversity, little is known about the underlying gene expression plasticity. In order to shed new light onto this biological question, we have compared transcriptome profiles of five environmental isolates, clinical and laboratorial strains at different time points of fermentation in synthetic must medium, during exponential and stationary growth phases. Results: Our data unveiled diversity in both intensity and timing of gene expression. Genes involved in glucose metabolism and in the stress response elicited during fermentation were among the most variable. This gene expression diversity increased at the onset of stationary phase (diauxic shift). Environmental isolates showed lower average transcript abundance of genes involved in the stress response, assimilation of nitrogen and vitamins, and sulphur metabolism, than other strains. Nitrogen metabolism genes showed significant variation in expression among the environmental isolates. Conclusions: Wild type yeast strains respond differentially to the stress imposed by nutrient depletion, ethanol accumulation and cell density increase, during fermentation of glucose in synthetic must medium. Our results support previous data showing that gene expression variability is a source of phenotypic diversity among closely related organisms.Fundação para a Ciência e TecnologiaThe authors wish to thank Adega Cooperativa da Bairrada, Cantanhede, Portugal, for providing the commercial strains

Effects of Craniofacial Structures on Mouse Palatal Closure In Vitro

Heads of Swiss-Webster mouse fetuses of four ages spanning days 12-13 of gestation, were partially dissected by removing the brain (B), tongue (T) and mandible (M) alone or in combination (BT, BM, BTM). Preparations were suspended in a gassed, circulating culture system such that palatal closure must take place against gravity. Closure occurred earlier than in vivo and required the posterior half of the mandible be intact and the tongue removed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68249/2/10.1177_00220345780570024401.pd

Genome-wide analysis of differential transcriptional and epigenetic variability across human immune cell types

Abstract Background A healthy immune system requires immune cells that adapt rapidly to environmental challenges. This phenotypic plasticity can be mediated by transcriptional and epigenetic variability. Results We apply a novel analytical approach to measure and compare transcriptional and epigenetic variability genome-wide across CD14+CD16− monocytes, CD66b+CD16+ neutrophils, and CD4+CD45RA+ naïve T cells from the same 125 healthy individuals. We discover substantially increased variability in neutrophils compared to monocytes and T cells. In neutrophils, genes with hypervariable expression are found to be implicated in key immune pathways and are associated with cellular properties and environmental exposure. We also observe increased sex-specific gene expression differences in neutrophils. Neutrophil-specific DNA methylation hypervariable sites are enriched at dynamic chromatin regions and active enhancers. Conclusions Our data highlight the importance of transcriptional and epigenetic variability for the key role of neutrophils as the first responders to inflammatory stimuli. We provide a resource to enable further functional studies into the plasticity of immune cells, which can be accessed from: http://blueprint-dev.bioinfo.cnio.es/WP10/hypervariability

YPA: an integrated repository of promoter features in Saccharomyces cerevisiae

This study presents the Yeast Promoter Atlas (YPA, http://ypa.ee.ncku.edu.tw/ or http://ypa.csbb.ntu.edu.tw/) database, which aims to collect comprehensive promoter features in Saccharomyces cerevisiae. YPA integrates nine kinds of promoter features including promoter sequences, genes’ transcription boundaries—transcription start sites (TSSs), five prime untranslated regions (5′-UTRs) and three prime untranslated regions (3′UTRs), TATA boxes, transcription factor binding sites (TFBSs), nucleosome occupancy, DNA bendability, transcription factor (TF) binding, TF knockout expression and TF–TF physical interaction. YPA is designed to present data in a unified manner as many important observations are revealed only when these promoter features are considered altogether. For example, DNA rigidity can prevent nucleosome packaging, thereby making TFBSs in the rigid DNA regions more accessible to TFs. Integrating nucleosome occupancy, DNA bendability, TF binding, TF knockout expression and TFBS data helps to identify which TFBS is actually functional. In YPA, various promoter features can be accessed in a centralized and organized platform. Researchers can easily view if the TFBSs in an interested promoter are occupied by nucleosomes or located in a rigid DNA segment and know if the expression of the downstream gene responds to the knockout of the corresponding TFs. Compared to other established yeast promoter databases, YPA collects not only TFBSs but also many other promoter features to help biologists study transcriptional regulation

Characterization of sINR, a strict version of the Initiator core promoter element

The proximal promoter consists of binding sites for transcription regulators and a core promoter. We identified an overrepresented motif in the proximal promoter of human genes with an Initiator (INR) positional bias. The core of the motif fits the INR consensus but its sequence is more strict and flanked by additional conserved sequences. This strict INR (sINR) is enriched in TATA-less genes that belong to specific functional categories. Analysis of the sINR-containing DHX9 and ATP5F1 genes showed that the entire sINR sequence, including the strict core and the conserved flanking sequences, is important for transcription. A conventional INR sequence could not substitute for DHX9 sINR whereas, sINR could replace a conventional INR. The minimal region required to create the major TSS of the DHX9 promoter includes the sINR and an upstream Sp1 site. In a heterologous context, sINR substituted for the TATA box when positioned downstream to several Sp1 sites. Consistent with that the majority of sINR promoters contain at least one Sp1 site. Thus, sINR is a TATA-less-specific INR that functions in cooperation with Sp1. These findings support the idea that the INR is a family of related core promoter motifs

Tight cooperation between Mot1p and NC2β in regulating genome-wide transcription, repression of transcription following heat shock induction and genetic interaction with SAGA

TATA-binding protein (TBP) is central to the regulation of eukaryotic transcription initiation. Recruitment of TBP to target genes can be positively regulated by one of two basal transcription factor complexes: SAGA or TFIID. Negative regulation of TBP promoter association can be performed by Mot1p or the NC2 complex. Recent evidence suggests that Mot1p, NC2 and TBP form a DNA-dependent protein complex. Here, we compare the functions of Mot1p and NC2βduring basal and activated transcription using the anchor-away technique for conditional nuclear depletion. Genome-wide expression analysis indicates that both proteins regulate a highly similar set of genes. Upregulated genes were enriched for SAGA occupancy, while downregulated genes preferred TFIID binding. Mot1p and NC2β depletion during heat shock resulted in failure to downregulate gene expression after initial activation, which was accompanied by increased TBP and RNA pol II promoter occupancies. Depletion of Mot1p or NC2β displayed preferential synthetic lethality with the TBP-interaction module of SAGA. Our results support the model that Mot1p and NC2β directly cooperate in vivo to regulate TBP function, and that they are involved in maintaining basal expression levels as well as in resetting gene expression after induction by stress

Dynamic Remodeling of Individual Nucleosomes Across a Eukaryotic Genome in Response to Transcriptional Perturbation

The eukaryotic genome is packaged as chromatin with nucleosomes comprising its basic structural unit, but the detailed structure of chromatin and its dynamic remodeling in terms of individual nucleosome positions has not been completely defined experimentally for any genome. We used ultra-high–throughput sequencing to map the remodeling of individual nucleosomes throughout the yeast genome before and after a physiological perturbation that causes genome-wide transcriptional changes. Nearly 80% of the genome is covered by positioned nucleosomes occurring in a limited number of stereotypical patterns in relation to transcribed regions and transcription factor binding sites. Chromatin remodeling in response to physiological perturbation was typically associated with the eviction, appearance, or repositioning of one or two nucleosomes in the promoter, rather than broader region-wide changes. Dynamic nucleosome remodeling tends to increase the accessibility of binding sites for transcription factors that mediate transcriptional changes. However, specific nucleosomal rearrangements were also evident at promoters even when there was no apparent transcriptional change, indicating that there is no simple, globally applicable relationship between chromatin remodeling and transcriptional activity. Our study provides a detailed, high-resolution, dynamic map of single-nucleosome remodeling across the yeast genome and its relation to global transcriptional changes

Computational Modelling of Genome-Side Transcription Assembly Networks Using a Fluidics Analogy

Understanding how a myriad of transcription regulators work to modulate mRNA output at thousands of genes remains a fundamental challenge in molecular biology. Here we develop a computational tool to aid in assessing the plausibility of gene regulatory models derived from genome-wide expression profiling of cells mutant for transcription regulators. mRNA output is modelled as fluid flow in a pipe lattice, with assembly of the transcription machinery represented by the effect of valves. Transcriptional regulators are represented as external pressure heads that determine flow rate. Modelling mutations in regulatory proteins is achieved by adjusting valves' on/off settings. The topology of the lattice is designed by the experimentalist to resemble the expected interconnection between the modelled agents and their influence on mRNA expression. Users can compare multiple lattice configurations so as to find the one that minimizes the error with experimental data. This computational model provides a means to test the plausibility of transcription regulation models derived from large genomic data sets

DeBi: Discovering Differentially Expressed Biclusters using a Frequent Itemset Approach

<p>Abstract</p> <p>Background</p> <p>The analysis of massive high throughput data via clustering algorithms is very important for elucidating gene functions in biological systems. However, traditional clustering methods have several drawbacks. Biclustering overcomes these limitations by grouping genes and samples simultaneously. It discovers subsets of genes that are co-expressed in certain samples. Recent studies showed that biclustering has a great potential in detecting marker genes that are associated with certain tissues or diseases. Several biclustering algorithms have been proposed. However, it is still a challenge to find biclusters that are significant based on biological validation measures. Besides that, there is a need for a biclustering algorithm that is capable of analyzing very large datasets in reasonable time.</p> <p>Results</p> <p>Here we present a fast biclustering algorithm called DeBi (Differentially Expressed BIclusters). The algorithm is based on a well known data mining approach called frequent itemset. It discovers maximum size homogeneous biclusters in which each gene is strongly associated with a subset of samples. We evaluate the performance of DeBi on a yeast dataset, on synthetic datasets and on human datasets.</p> <p>Conclusions</p> <p>We demonstrate that the DeBi algorithm provides functionally more coherent gene sets compared to standard clustering or biclustering algorithms using biological validation measures such as Gene Ontology term and Transcription Factor Binding Site enrichment. We show that DeBi is a computationally efficient and powerful tool in analyzing large datasets. The method is also applicable on multiple gene expression datasets coming from different labs or platforms.</p

Minimal components of the RNA polymerase II transcription apparatus determine the consensus TATA box

In Saccharomyces cerevisiae, multiple approaches have arrived at a consensus TATA box sequence of TATA(T/A)A(A/T)(A/G). TATA-binding protein (TBP) affinity alone does not determine TATA box function. To discover how a minimal set of factors required for basal and activated transcription contributed to the sequence requirements for a functional TATA box, we performed transcription reactions using highly purified proteins and CYC1 promoter TATA box mutants. The TATA box consensus sequence is a good predictor of promoter activity. However, several nonconsensus sequences are almost fully functional, indicating that mechanistic requirements are not the only selective pressure on the TATA box. We also found that the effect of a mutation at a certain position is often dependent on other bases within a particular TATA box. Although activators and coactivators strongly influence TBP recruitment and stability at promoters, neither Mediator, the activator Gal4-V16, nor TFIID specifically compensate for the low transcription levels of the weak TATA boxes. The addition of Mediator to purified transcription reactions did, however, increase the functional selectivity for certain consensus TATA sequences. Transcription in whole-cell extracts or in vivo with these TATA box mutants indicated that factors, other than those in our purified system, may help initiate transcription from weak TATA boxes