Prediction of alternatively skipped exons and splicing enhancers from exon junction arrays

<p>Abstract</p> <p>Background</p> <p>Alternative splicing of exons in a pre-mRNA transcript is an important mechanism which contributes to protein diversity in human. Arrays for detecting alternative splicing are available using several different probe designs, including those based on exon-junctions. In this work, we introduce a new method for predicting alternatively skipped exons from exon-junction arrays. Predictions based on our method are compared against controls and their sequences are analyzed to identify motifs important for regulating alternative splicing.</p> <p>Results</p> <p>Our comparison of several alternative methods shows that an exon-skipping score based on neighboring junctions best discriminates between positive and negative controls. Sequence analysis of our predicted exons confirms the presence of known splicing regulatory sequences. In addition, we also derive a set of development-related alternatively spliced genes based on fetal versus adult tissue comparisons and find that our predictions are consistent with their functional annotations. <it>Ab initio </it>motif finding algorithms are applied to identify several motifs that may be relevant for splicing during development.</p> <p>Conclusion</p> <p>This work describes a new method for analyzing exon-junction arrays, identifies sequence motifs that are specific for alternative and constitutive splicing and suggests a role for several known splicing factors and their motifs in developmental regulation.</p

CompMoby: Comparative MobyDick for detection of cis-regulatory motifs

<p>Abstract</p> <p>Background</p> <p>The regulation of gene expression is complex and occurs at many levels, including transcriptional and post-transcriptional, in metazoans. Transcriptional regulation is mainly determined by sequence elements within the promoter regions of genes while sequence elements within the 3' untranslated regions of mRNAs play important roles in post-transcriptional regulation such as mRNA stability and translation efficiency. Identifying cis-regulatory elements, or motifs, in multicellular eukaryotes is more difficult compared to unicellular eukaryotes due to the larger intergenic sequence space and the increased complexity in regulation. Experimental techniques for discovering functional elements are often time consuming and not easily applied on a genome level. Consequently, computational methods are advantageous for genome-wide cis-regulatory motif detection. To decrease the search space in metazoans, many algorithms use cross-species alignment, although studies have demonstrated that a large portion of the binding sites for the same trans-acting factor do not reside in alignable regions. Therefore, a computational algorithm should account for both conserved and nonconserved cis-regulatory elements in metazoans.</p> <p>Results</p> <p>We present CompMoby (Comparative MobyDick), software developed to identify cis-regulatory binding sites at both the transcriptional and post-transcriptional levels in metazoans without prior knowledge of the trans-acting factors. The CompMoby algorithm was previously shown to identify cis-regulatory binding sites in upstream regions of genes co-regulated in embryonic stem cells. In this paper, we extend the software to identify putative cis-regulatory motifs in 3' UTR sequences and verify our results using experimentally validated data sets in mouse and human. We also detail the implementation of CompMoby into a user-friendly tool that includes a web interface to a streamlined analysis. Our software allows detection of motifs in the following three categories: one, those that are alignable and conserved; two, those that are conserved but not alignable; three, those that are species specific. One of the output files from CompMoby gives the user the option to decide what category of cis-regulatory element to experimentally pursue based on their biological problem. Using experimentally validated biological datasets, we demonstrate that CompMoby is successful in detecting cis-regulatory target sites of known and novel trans-acting factors at the transcriptional and post-transcriptional levels.</p> <p>Conclusion</p> <p>CompMoby is a powerful software tool for systematic <it>de novo </it>discovery of evolutionarily conserved and nonconserved cis-regulatory sequences involved in transcriptional or post-transcriptional regulation in metazoans. This software is freely available to users at <url>http://genome.ucsf.edu/compmoby/</url>.</p

MicroRNA Regulation of Cell Lineages in Mouse and Human Embryonic Stem Cells

SummaryCell fate decisions of pluripotent embryonic stem (ES) cells are dictated by activation and repression of lineage-specific genes. Numerous signaling and transcriptional networks progressively narrow and specify the potential of ES cells. Whether specific microRNAs help refine and limit gene expression and, thereby, could be used to manipulate ES cell differentiation has largely been unexplored. Here, we show that two serum response factor (SRF)-dependent muscle-specific microRNAs, miR-1 and miR-133, promote mesoderm formation from ES cells but have opposing functions during further differentiation into cardiac muscle progenitors. Furthermore, miR-1 and miR-133 were potent repressors of nonmuscle gene expression and cell fate during mouse and human ES cell differentiation. miR-1's effects were in part mediated by translational repression of the Notch ligand Delta-like 1 (Dll-1). Our findings indicate that muscle-specific miRNAs reinforce the silencing of nonmuscle genes during cell lineage commitment and suggest that miRNAs may have general utility in regulating cell-fate decisions from pluripotent ES cells

Pyrazole compound BPR1P0034 with potent and selective anti-influenza virus activity

<p>Abstract</p> <p>Background</p> <p>Influenza viruses are a major cause of morbidity and mortality around the world. More recently, a swine-origin influenza A (H1N1) virus that is spreading via human-to-human transmission has become a serious public concern. Although vaccination is the primary strategy for preventing infections, influenza antiviral drugs play an important role in a comprehensive approach to controlling illness and transmission. In addition, a search for influenza-inhibiting drugs is particularly important in the face of high rate of emergence of influenza strains resistant to several existing influenza antivirals.</p> <p>Methods</p> <p>We searched for novel anti-influenza inhibitors using a cell-based neutralization (inhibition of virus-induced cytopathic effect) assay. After screening 20,800 randomly selected compounds from a library from ChemDiv, Inc., we found that BPR1P0034 has sub-micromolar antiviral activity. The compound was resynthesized in five steps by conventional chemical techniques. Lead optimization and a structure-activity analysis were used to improve potency. Time-of-addition assay was performed to target an event in the virus life cycle.</p> <p>Results</p> <p>The 50% effective inhibitory concentration (IC₅₀) of BPR1P0034 was 0.42 ± 0.11 μM, when measured with a plaque reduction assay. Viral protein and RNA synthesis of A/WSN/33 (H1N1) was inhibited by BPR1P0034 and the virus-induced cytopathic effects were thus significantly reduced. BPR1P0034 exhibited broad inhibition spectrum for influenza viruses but showed no antiviral effect for enteroviruses and echovirus 9. In a time-of-addition assay, in which the compound was added at different stages along the viral replication cycle (such as at adsorption or after adsorption), its antiviral activity was more efficient in cells treated with the test compound between 0 and 2 h, right after viral infection, implying that an early step of viral replication might be the target of the compound. These results suggest that BPR1P0034 targets the virus during viral uncoating or viral RNA importation into the nucleus.</p> <p>Conclusions</p> <p>To the best of our knowledge, BPR1P0034 is the first pyrazole-based anti-influenza compound ever identified and characterized from high throughput screening to show potent (sub-μM) antiviral activity. We conclude that BPR1P0034 has potential antiviral activity, which offers an opportunity for the development of a new anti-influenza virus agent.</p

Aging and Environmental Exposures Alter Tissue-Specific DNA Methylation Dependent upon CpG Island Context

Epigenetic control of gene transcription is critical for normal human development and cellular differentiation. While alterations of epigenetic marks such as DNA methylation have been linked to cancers and many other human diseases, interindividual epigenetic variations in normal tissues due to aging, environmental factors, or innate susceptibility are poorly characterized. The plasticity, tissue-specific nature, and variability of gene expression are related to epigenomic states that vary across individuals. Thus, population-based investigations are needed to further our understanding of the fundamental dynamics of normal individual epigenomes. We analyzed 217 non-pathologic human tissues from 10 anatomic sites at 1,413 autosomal CpG loci associated with 773 genes to investigate tissue-specific differences in DNA methylation and to discern how aging and exposures contribute to normal variation in methylation. Methylation profile classes derived from unsupervised modeling were significantly associated with age (P<0.0001) and were significant predictors of tissue origin (P<0.0001). In solid tissues (n = 119) we found striking, highly significant CpG island–dependent correlations between age and methylation; loci in CpG islands gained methylation with age, loci not in CpG islands lost methylation with age (P<0.001), and this pattern was consistent across tissues and in an analysis of blood-derived DNA. Our data clearly demonstrate age- and exposure-related differences in tissue-specific methylation and significant age-associated methylation patterns which are CpG island context-dependent. This work provides novel insight into the role of aging and the environment in susceptibility to diseases such as cancer and critically informs the field of epigenomics by providing evidence of epigenetic dysregulation by age-related methylation alterations. Collectively we reveal key issues to consider both in the construction of reference and disease-related epigenomes and in the interpretation of potentially pathologically important alterations

SNPLogic: an interactive single nucleotide polymorphism selection, annotation, and prioritization system

SNPLogic (http://www.snplogic.org) brings together single nucleotide polymorphism (SNP) information from numerous sources to provide a comprehensive SNP selection, annotation and prioritization system for design and analysis of genotyping projects. SNPLogic integrates information about the genetic context of SNPs (gene, chromosomal region, functional location, haplotypes tags and overlap with transcription factor binding sites, splicing sites, miRNAs and evolutionarily conserved regions), genotypic data (allele frequencies per population and validation method), coverage of commercial arrays (ParAllele, Affymetrix and Illumina), functional predictions (modeled on structure and sequence) and connections or established associations (biological pathways, gene ontology terms and OMIM disease terms). The SNPLogic web interface facilitates construction and annotation of user-defined SNP lists that can be saved, shared and exported. Thus, SNPLogic can be used to identify and prioritize candidate SNPs, assess custom and commercial arrays panels and annotate new SNP data with publicly available information. We have found integration of SNP annotation in the context of pathway information and functional prediction scores to be a powerful approach to the analysis and interpretation of SNP-disease association data

Microcrystalline-Silicon-Oxide-Based N-Type Reflector Structure in Micromorph Tandem Solar Cells

N-type microcrystalline silicon oxide thin films (n-c-SiO:H) have been deposited by VHF-PECVD (40 MHz) with reactant gas mixtures of CO2/SiH4 and H2. N-c-SiO thin films exhibiting low refractive index value (n600nm∼2), and medium/high conductivity (≧10−9 S/cm) are suitable to be used as an “n-type reflector” in micromorph tandem solar cells. Transmission electron microscopy (TEM) results show that microstructures of n-c-SiO:H thin films contain nanocrystalline Si particles, which are randomly embedded in the a-SiO matrix. This specific microstructure provides n-c-SiO:H thin films excellent optoelectronic properties; therefore, n-c-SiO:H thin films are appropriate candidates for “n-type reflector” structures in Si tandem solar cells

Model-based clustering of DNA methylation array data: a recursive-partitioning algorithm for high-dimensional data arising as a mixture of beta distributions

<p>Abstract</p> <p>Background</p> <p>Epigenetics is the study of heritable changes in gene function that cannot be explained by changes in DNA sequence. One of the most commonly studied epigenetic alterations is cytosine methylation, which is a well recognized mechanism of epigenetic gene silencing and often occurs at tumor suppressor gene loci in human cancer. Arrays are now being used to study DNA methylation at a large number of loci; for example, the Illumina GoldenGate platform assesses DNA methylation at 1505 loci associated with over 800 cancer-related genes. Model-based cluster analysis is often used to identify DNA methylation subgroups in data, but it is unclear how to cluster DNA methylation data from arrays in a scalable and reliable manner.</p> <p>Results</p> <p>We propose a novel model-based recursive-partitioning algorithm to navigate clusters in a beta mixture model. We present simulations that show that the method is more reliable than competing nonparametric clustering approaches, and is at least as reliable as conventional mixture model methods. We also show that our proposed method is more computationally efficient than conventional mixture model approaches. We demonstrate our method on the normal tissue samples and show that the clusters are associated with tissue type as well as age.</p> <p>Conclusion</p> <p>Our proposed recursively-partitioned mixture model is an effective and computationally efficient method for clustering DNA methylation data.</p

ERCC2 2251A>C genetic polymorphism was highly correlated with early relapse in high-risk stage II and stage III colorectal cancer patients: A preliminary study

<p>Abstract</p> <p>Background</p> <p>Early relapse in colorectal cancer (CRC) patients is attributed mainly to the higher malignant entity (such as an unfavorable genotype, deeper tumor invasion, lymph node metastasis and advance cancer stage) and poor response to chemotherapy. Several investigations have demonstrated that genetic polymorphisms in drug-targeted genes, metabolizing enzymes, and DNA-repairing enzymes are all strongly correlated with inter-individual differences in the efficacy and toxicity of many treatment regimens. This preliminary study attempts to identify the correlation between genetic polymorphisms and clinicopathological features of CRC, and evaluates the relationship between genetic polymorphisms and chemotherapeutic susceptibility of Taiwanese CRC patients. To our knowledge, this study discusses, for the first time, early cancer relapse and its indication by multiple genes.</p> <p>Methods</p> <p>Six gene polymorphisms functional in drug-metabolism – <it>GSTP1 </it>Ile105Val, <it>ABCB1 </it>Ile1145Ile, <it>MTHFR </it>Ala222Val, <it>TYMS </it>double (2R) or triple (3R) tandem repeat – and DNA-repair genes – <it>ERCC2 </it>Lys751Gln and <it>XRCC1 A</it>rg399Gln – were assessed in 201 CRC patients using a polymerase chain reaction-restriction fragment-length polymorphism (PCR-RFLP) technique and DNA sequencing. Patients were diagnosed as either high-risk stage II (T2 and 3 N0 M0) or III (any T N1 and 2 M0) and were administered adjuvant chemotherapy regimens that included 5-fluorouracil (5FU) and leucovorin (LV). The correlations between genetic polymorphisms and patient clinicopathological features and relapses were investigated.</p> <p>Results</p> <p>In this study, the distributions of <it>GSTP1 </it>(<it>P </it>= 0.003), <it>ABCB1 </it>(<it>P </it>= 0.001), <it>TYMS </it>(<it>P </it>< 0.0001), <it>ERCC2 </it>(<it>P </it>< 0.0001) and <it>XRCC1 </it>(<it>P </it>= 0.006) genotypes in the Asian population, with the exception of <it>MTHFR </it>(<it>P </it>= 0.081), differed significantly from their distributions in a Caucasian population. However, the unfavorable genotype <it>ERCC2 </it>2251A>C (<it>P </it>= 0.006), tumor invasion depth (<it>P </it>= 0.025), lymph node metastasis (<it>P </it>= 0.011) and cancer stage (<it>P </it>= 0.008) were significantly correlated with early relapse. Patients carrying the <it>ERCC2 </it>2251AC or2251CC genotypes had a significantly increased risk of early relapse (OR = 3.294, 95% CI, 1.272–8.532).</p> <p>Conclusion</p> <p>We suggest that <it>ERCC2 </it>2251A>C alleles may be genetic predictors of early CRC relapse.</p