An Integrated Approach to Identifying Cis-Regulatory Modules in the Human Genome

In eukaryotic genomes, it is challenging to accurately determine target sites of transcription factors (TFs) by only using sequence information. Previous efforts were made to tackle this task by considering the fact that TF binding sites tend to be more conserved than other functional sites and the binding sites of several TFs are often clustered. Recently, ChIP-chip and ChIP-sequencing experiments have been accumulated to identify TF binding sites as well as survey the chromatin modification patterns at the regulatory elements such as promoters and enhancers. We propose here a hidden Markov model (HMM) to incorporate sequence motif information, TF-DNA interaction data and chromatin modification patterns to precisely identify cis-regulatory modules (CRMs). We conducted ChIP-chip experiments on four TFs, CREB, E2F1, MAX, and YY1 in 1% of the human genome. We then trained a hidden Markov model (HMM) to identify the labels of the CRMs by incorporating the sequence motifs recognized by these TFs and the ChIP-chip ratio. Chromatin modification data was used to predict the functional sites and to further remove false positives. Cross-validation showed that our integrated HMM had a performance superior to other existing methods on predicting CRMs. Incorporating histone signature information successfully penalized false prediction and improved the whole performance. The dataset we used and the software are available at http://nash.ucsd.edu/CIS/

You had to be there: Anachronism and the limits of laughing at the Middle Ages

Comic medievalism is one of the most widespread but least examined forms of postmedieval response. Its combination of comic modality, modern sensibility and historical vision captures what postmedieval audiences have deemed amusing about medieval society. But some instances have been less successful. ‘You had to be there,’ the phrase marking the failure of a comic attempt, and the relationship of that failure to the loss of immediacy, is realized in comic medievalism through the temporal fragility of laughter, historical mediation and temporal paradox. This essay explores some limitpoints to the comic reception of the Middle Ages, focusing especially on its use of anachronism

Assessment of clusters of transcription factor binding sites in relationship to human promoter, CpG islands and gene expression

BACKGROUND: Gene expression is regulated mainly by transcription factors (TFs) that interact with regulatory cis-elements on DNA sequences. To identify functional regulatory elements, computer searching can predict TF binding sites (TFBS) using position weight matrices (PWMs) that represent positional base frequencies of collected experimentally determined TFBS. A disadvantage of this approach is the large output of results for genomic DNA. One strategy to identify genuine TFBS is to utilize local concentrations of predicted TFBS. It is unclear whether there is a general tendency for TFBS to cluster at promoter regions, although this is the case for certain TFBS. Also unclear is the identification of TFs that have TFBS concentrated in promoters and to what level this occurs. This study hopes to answer some of these questions. RESULTS: We developed the cluster score measure to evaluate the correlation between predicted TFBS clusters and promoter sequences for each PWM. Non-promoter sequences were used as a control. Using the cluster score, we identified a PWM group called PWM-PCP, in which TFBS clusters positively correlate with promoters, and another PWM group called PWM-NCP, in which TFBS clusters negatively correlate with promoters. The PWM-PCP group comprises 47% of the 199 vertebrate PWMs, while the PWM-NCP group occupied 11 percent. After reducing the effect of CpG islands (CGI) against the clusters using partial correlation coefficients among three properties (promoter, CGI and predicted TFBS cluster), we identified two PWM groups including those strongly correlated with CGI and those not correlated with CGI. CONCLUSION: Not all PWMs predict TFBS correlated with human promoter sequences. Two main PWM groups were identified: (1) those that show TFBS clustered in promoters associated with CGI, and (2) those that show TFBS clustered in promoters independent of CGI. Assessment of PWM matches will allow more positive interpretation of TFBS in regulatory regions

Description et évaluation d'un réseau d'épidémiosurveillance des pathologies porcines mis en place dans un district du Nord Vietnam

Background and objective: Early menarche is increasing in prevalence worldwide, prompting clinical andpublic health interest on its links with pulmonary function. We aimed to investigate the relationship betweenearly menarche and lung function in middle age.Methods: The population-based Tasmanian LongitudinalHealth Study (born 1961; n = 8583), was initiated in 1968.The 5th Decade follow-up data (mean age: 45 years)included age at menarche and complex lung function testing. The 6th Decade follow-up (age: 53 years) repeated spirometry and gas transfer factor. Multiple linear regressionand mediation analyses were performed to determine theassociation between age at menarche and adult lung function and investigate biological pathways, including the proportion mediated by adult-attained height.Results: Girls reporting an early menarche (Conclusion:Early menarche was associated withreduced adult lung function. This is the first study toinvestigate post-BD outcomes and quantify the partialrole of adult height in this association

Intra- and inter-individual genetic differences in gene expression

Genetic variation is known to influence the amount of mRNA produced by a gene. Given that the molecular machines control mRNA levels of multiple genes, we expect genetic variation in the components of these machines would influence multiple genes in a similar fashion. In this study we show that this assumption is correct by using correlation of mRNA levels measured independently in the brain, kidney or liver of multiple, genetically typed, mice strains to detect shared genetic influences. These correlating groups of genes (CGG) have collective properties that account for 40-90% of the variability of their constituent genes and in some cases, but not all, contain genes encoding functionally related proteins. Critically, we show that the genetic influences are essentially tissue specific and consequently the same genetic variations in the one animal may up-regulate a CGG in one tissue but down-regulate the same CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. The implication of this study is that this class of genetic variation can result in complex inter- and intra-individual and tissue differences and that this will create substantial challenges to the investigation of phenotypic outcomes, particularly in humans where multiple tissues are not readily available.

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Differentiating Protein-Coding and Noncoding RNA: Challenges and Ambiguities

The assumption that RNA can be readily classified into either protein-coding or non-protein–coding categories has pervaded biology for close to 50 years. Until recently, discrimination between these two categories was relatively straightforward: most transcripts were clearly identifiable as protein-coding messenger RNAs (mRNAs), and readily distinguished from the small number of well-characterized non-protein–coding RNAs (ncRNAs), such as transfer, ribosomal, and spliceosomal RNAs. Recent genome-wide studies have revealed the existence of thousands of noncoding transcripts, whose function and significance are unclear. The discovery of this hidden transcriptome and the implicit challenge it presents to our understanding of the expression and regulation of genetic information has made the need to distinguish between mRNAs and ncRNAs both more pressing and more complicated. In this Review, we consider the diverse strategies employed to discriminate between protein-coding and noncoding transcripts and the fundamental difficulties that are inherent in what may superficially appear to be a simple problem. Misannotations can also run in both directions: some ncRNAs may actually encode peptides, and some of those currently thought to do so may not. Moreover, recent studies have shown that some RNAs can function both as mRNAs and intrinsically as functional ncRNAs, which may be a relatively widespread phenomenon. We conclude that it is difficult to annotate an RNA unequivocally as protein-coding or noncoding, with overlapping protein-coding and noncoding transcripts further confounding this distinction. In addition, the finding that some transcripts can function both intrinsically at the RNA level and to encode proteins suggests a false dichotomy between mRNAs and ncRNAs. Therefore, the functionality of any transcript at the RNA level should not be discounted

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns

<p>Abstract</p> <p>Background</p> <p>Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods.</p> <p>Results</p> <p>Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values.</p> <p>Conclusions</p> <p>Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks.</p