Effects of thermal fluctuation and the receptor-receptor interaction in bacterial chemotactic signalling and adaptation

Bacterial chemotaxis is controlled by the conformational changes of the receptors, in response to the change of the ambient chemical concentration. In a statistical mechanical approach, the signalling due to the conformational changes is a thermodynamic average quantity, dependent on the temperature and the total energy of the system, including both ligand-receptor interaction and receptor-receptor interaction. This physical theory suggests to biology a new understanding of cooperation in ligand binding and receptor signalling problems. How much experimental support of this approach can be obtained from the currently available data? What are the parameter values? What is the practical information for experiments? Here we make comparisons between the theory and recent experimental results. Although currently comparisons can only be semi-quantitative or qualitative, consistency is clearly shown. The theory also helps to sort a variety of data.Comment: 26 pages, revtex. Journal version. Analysis on another set of data on adaptation time is adde

rnaSeqMap: a Bioconductor package for RNA sequencing data exploration

BACKGROUND: The throughput of commercially available sequencers has recently significantly increased. It has reached the point where measuring the RNA expression by the depth of coverage has become feasible even for largest genomes. The development of software tools is constantly following the progress of biological hardware. In particular, as RNA sequencing software can be regarded genome browsers, exon junction tools and statistical tools operating on counts of reads in predefined regions. The library rnaSeqMap, freely available via Bioconductor, is an RNA sequencing software which is independent of any biological hardware platform. It is based upon standard Bioconductor infrastructure for sequencing data and includes several novel features focused on deeper understanding of coverage expression profiles and discovery of novel transcription regions. RESULTS: rnaSeqMap is a toolbox for analyses that may be performed with the use of gene annotations or alternatively, in an unsupervised mode, on any genomic region to find novel or non-standard transcripts. The data back-end may be a MySQL database or a set of files in standard BAM format. The processing in R can be run on a machine without any particular hardware requirements, and scales linearly with the number of genomic loci and number of samples analyzed. The main features of rnaSeqMap include coverage operations, discovering irreducible regions of high expression, significance search and splicing analyses with nucleotide granularity. CONCLUSIONS: This software may be used for a range of applications related to RNA sequencing by building customized analysis pipelines. The applicability and precision is expected to increase in parallel with the progress of the genome coverage in sequencers

Comprehensive Analysis of Affymetrix Exon Arrays Using BioConductor

ISSN:1553-734XISSN:1553-735

Coding potential of the products of alternative splicing in human

Background: Analysis of the human genome has revealed that as much as an order of magnitude more of the genomic sequence is transcribed than accounted for by the predicted and characterized genes. A number of these transcripts are alternatively spliced forms of known protein coding genes; however, it is becoming clear that many of them do not necessarily correspond to a functional protein. Results: In this study we analyze alternative splicing isoforms of human gene products that are unambiguously identified by mass spectrometry and compare their properties with those of isoforms of the same genes for which no peptide was found in publicly available mass spectrometry datasets. We analyze them in detail for the presence of uninterrupted functional domains, active sites as well as the plausibility of their predicted structure. We report how well each of these strategies and their combination can correctly identify translated isoforms and derive a lower limit for their specificity, that is, their ability to correctly identify non-translated products. Conclusions: The most effective strategy for correctly identifying translated products relies on the conservation of active sites, but it can only be applied to a small fraction of isoforms, while a reasonably high coverage, sensitivity and specificity can be achieved by analyzing the presence of non-truncated functional domains. Combining the latter with an assessment of the plausibility of the modeled structure of the isoform increases both coverage and specificity with a moderate cost in terms of sensitivity

Differential splicing using whole-transcript microarrays

<p>Abstract</p> <p>Background</p> <p>The latest generation of Affymetrix microarrays are designed to interrogate expression over the entire length of every locus, thus giving the opportunity to study alternative splicing genome-wide. The Exon 1.0 ST (sense target) platform, with versions for Human, Mouse and Rat, is designed primarily to probe every known or predicted exon. The smaller Gene 1.0 ST array is designed as an expression microarray but still interrogates expression with probes along the full length of each well-characterized transcript. We explore the possibility of using the Gene 1.0 ST platform to identify differential splicing events.</p> <p>Results</p> <p>We propose a strategy to score differential splicing by using the auxiliary information from fitting the statistical model, RMA (robust multichip analysis). RMA partitions the probe-level data into probe effects and expression levels, operating robustly so that if a small number of probes behave differently than the rest, they are downweighted in the fitting step. We argue that adjacent poorly fitting probes for a given sample can be evidence of <it>differential </it>splicing and have designed a statistic to search for this behaviour. Using a public tissue panel dataset, we show many examples of tissue-specific alternative splicing. Furthermore, we show that evidence for putative alternative splicing has a strong correspondence between the Gene 1.0 ST and Exon 1.0 ST platforms.</p> <p>Conclusion</p> <p>We propose a new approach, FIRMAGene, to search for differentially spliced genes using the Gene 1.0 ST platform. Such an analysis complements the search for differential expression. We validate the method by illustrating several known examples and we note some of the challenges in interpreting the probe-level data.</p> <p>Software implementing our methods is freely available as an <monospace>R</monospace> package.</p

Splice variants as novel targets in pancreatic ductal adenocarcinoma

The study was funded by the MolDiagPaCa European Union Framework Programme and CR-UK Programme grant A12008 from CR-UK (C. Chelala, T. Crnogorac-Jurcevic, and N.R. Lemoine). Italian Cancer Genome Project – Ministry of University [FIRB RBAP10AHJB]; Associazione Italiana Ricerca Cancro [grant number: 12182]; FP7 European Community Grant Cam-Pac [no: 602783]; Italian Ministry of Health [FIMPCUP_J33G13000210001]. The funders were not involved in the design of the study, collection, analysis, and interpretation of data and in writing of the manuscript. We thank Tracy Chaplin-Perkins for help with running the Affymetrix experiments

TumorBoost: Normalization of allele-specific tumor copy numbers from a single pair of tumor-normal genotyping microarrays

<p>Abstract</p> <p>Background</p> <p>High-throughput genotyping microarrays assess both total DNA copy number and allelic composition, which makes them a tool of choice for copy number studies in cancer, including total copy number and loss of heterozygosity (LOH) analyses. Even after state of the art preprocessing methods, allelic signal estimates from genotyping arrays still suffer from systematic effects that make them difficult to use effectively for such downstream analyses.</p> <p>Results</p> <p>We propose a method, TumorBoost, for normalizing allelic estimates of one tumor sample based on estimates from a single matched normal. The method applies to any paired tumor-normal estimates from any microarray-based technology, combined with any preprocessing method. We demonstrate that it increases the signal-to-noise ratio of allelic signals, making it significantly easier to detect allelic imbalances.</p> <p>Conclusions</p> <p>TumorBoost increases the power to detect somatic copy-number events (including copy-neutral LOH) in the tumor from allelic signals of Affymetrix or Illumina origin. We also conclude that high-precision allelic estimates can be obtained from a single pair of tumor-normal hybridizations, if TumorBoost is combined with single-array preprocessing methods such as (allele-specific) CRMA v2 for Affymetrix or BeadStudio's (proprietary) XY-normalization method for Illumina. A bounded-memory implementation is available in the open-source and cross-platform R package <it>aroma.cn</it>, which is part of the Aroma Project (<url>http://www.aroma-project.org/</url>).</p

Implementation of exon arrays: alternative splicing during T-cell proliferation as determined by whole genome analysis

<p>Abstract</p> <p>Background</p> <p>The contribution of alternative splicing and isoform expression to cellular response is emerging as an area of considerable interest, and the newly developed exon arrays allow for systematic study of these processes. We use this pilot study to report on the feasibility of exon array implementation looking to replace the 3' <it>in vitro </it>transcription expression arrays in our laboratory.</p> <p>One of the most widely studied models of cellular response is T-cell activation from exogenous stimulation. Microarray studies have contributed to our understanding of key pathways activated during T-cell stimulation. We use this system to examine whole genome transcription and alternate exon usage events that are regulated during lymphocyte proliferation in an attempt to evaluate the exon arrays.</p> <p>Results</p> <p>Peripheral blood mononuclear cells form healthy donors were activated using phytohemagglutinin, IL2 and ionomycin and harvested at 5 points over a 7 day period. Flow cytometry measured cell cycle events and the Affymetrix exon array platform was used to identify the gene expression and alternate exon usage changes. Gene expression changes were noted in a total of 2105 transcripts, and alternate exon usage identified in 472 transcript clusters. There was an overlap of 263 transcripts which showed both differential expression and alternate exon usage over time. Gene ontology enrichment analysis showed a broader range of biological changes in biological processes for the differentially expressed genes, which include cell cycle, cell division, cell proliferation, chromosome segregation, cell death, component organization and biogenesis and metabolic process ontologies. The alternate exon usage ontological enrichments are in metabolism and component organization and biogenesis. We focus on alternate exon usage changes in the transcripts of the spliceosome complex. The real-time PCR validation rates were 86% for transcript expression and 71% for alternate exon usage.</p> <p>Conclusions</p> <p>This study illustrates that the Exon array technology has the potential to provide information on both transcript expression and isoform usage, with very little increase in expense.</p

Diverse Splicing Patterns of Exonized Alu Elements in Human Tissues

Exonization of Alu elements is a major mechanism for birth of new exons in primate genomes. Prior analyses of expressed sequence tags show that almost all Alu-derived exons are alternatively spliced, and the vast majority of these exons have low transcript inclusion levels. In this work, we provide genomic and experimental evidence for diverse splicing patterns of exonized Alu elements in human tissues. Using Exon array data of 330 Alu-derived exons in 11 human tissues and detailed RT-PCR analyses of 38 exons, we show that some Alu-derived exons are constitutively spliced in a broad range of human tissues, and some display strong tissue-specific switch in their transcript inclusion levels. Most of such exons are derived from ancient Alu elements in the genome. In SEPN1, mutations of which are linked to a form of congenital muscular dystrophy, the muscle-specific inclusion of an Alu-derived exon may be important for regulating SEPN1 activity in muscle. Realtime qPCR analysis of this SEPN1 exon in macaque and chimpanzee tissues indicates human-specific increase in its transcript inclusion level and muscle specificity after the divergence of humans and chimpanzees. Our results imply that some Alu exonization events may have acquired adaptive benefits during the evolution of primate transcriptomes