A Visual Data Mining Tool that Facilitates Reconstruction of Transcription Regulatory Networks

Background: Although the use of microarray technology has seen exponential growth, analysis of microarray data remains a challenge to many investigators. One difficulty lies in the interpretation of a list of differentially expressed genes, or in how to plan new experiments given that knowledge. Clustering methods can be used to identify groups of genes with similar expression patterns, and genes with unknown function can be provisionally annotated based on the concept of ‘‘guilt by association’’, where function is tentatively inferred from the known functions of genes with similar expression patterns. These methods frequently suffer from two limitations: (1) visualization usually only gives access to group membership, rather than specific information about nearest neighbors, and (2) the resolution or quality of the relationships are not easily inferred. Methodology/Principal Findings: We have addressed these issues by improving the precision of similarity detection over that of a single experiment and by creating a tool to visualize tractable association networks: we (1) performed metaanalysis computation of correlation coefficients for all gene pairs in a heterogeneous data set collected from 2,145 publicly available micorarray samples in mouse, (2) filtered the resulting distribution of over 130 million correlation coefficients to build new, more tractable distributions from the strongest correlations, and (3) designed and implemented a new Web based tool (StarNet

CpG site degeneration triggered by the loss of functional constraint created a highly polymorphic macaque drug-metabolizing gene, CYP1A2

<p>Abstract</p> <p>Background</p> <p>Elucidating the pattern of evolutionary changes in drug-metabolizing genes is an important subject not only for evolutionary but for biomedical research. We investigated the pattern of divergence and polymorphisms of macaque <it>CYP1A1 </it>and <it>CYP1A2 </it>genes, which are major drug-metabolizing genes in humans. In humans, <it>CYP1A2 </it>is specifically expressed in livers while <it>CYP1A1 </it>has a wider gene expression pattern in extrahepatic tissues. In contrast, macaque <it>CYP1A2 </it>is expressed at a much lower level than <it>CYP1A1 </it>in livers. Interestingly, a previous study has shown that <it>Macaca fascicularis CYP1A2 </it>harbored unusually high genetic diversity within species. Genomic regions showing high genetic diversity within species is occasionally interpreted as a result of balancing selection, where natural selection maintains highly diverged alleles with different functions. Nevertheless many other forces could create such signatures.</p> <p>Results</p> <p>We found that the <it>CYP1A1/2 </it>gene copy number and orientation has been highly conserved among mammalian genomes. The signature of gene conversion between <it>CYP1A1 </it>and <it>CYP1A2 </it>was detected, but the last gene conversion event in the simian primate lineage occurred before the <it>Catarrhini-Platyrrhini </it>divergence. The high genetic diversity of macaque <it>CYP1A2 </it>therefore cannot be explained by gene conversion between <it>CYP1A1 </it>and <it>CYP1A2</it>. By surveying <it>CYP1A2 </it>polymorphisms in total 91 <it>M. fascicularis </it>and <it>M. mulatta</it>, we found several null alleles segregating in these species, indicating functional constraint on <it>CYP1A2 </it>in macaques may have weakened after the divergence between humans and macaques. We propose that the high genetic diversity in macaque <it>CYP1A2 </it>is partly due to the degeneration of CpG sites, which had been maintained at a high level by purifying selection, and the rapid degeneration process was initiated by the loss of functional constraint on macaque <it>CYP1A2</it>.</p> <p>Conclusions</p> <p>Our findings show that the highly polymorphic <it>CYP1A2 </it>gene in macaques has not been created by balancing selection but by the burst of CpG site degeneration after loss of functional constraint. Because the functional importance of <it>CYP1A1/2 </it>genes is different between humans and macaques, we have to be cautious in extrapolating a drug-testing data using substrates metabolized by <it>CYP1A </it>genes from macaques to humans, despite of their somewhat overlapping substrate specificity.</p

Comparative Microbial Modules Resource: Generation and Visualization of Multi-species Biclusters

The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures – results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation

TRAM (Transcriptome Mapper): database-driven creation and analysis of transcriptome maps from multiple sources

<p>Abstract</p> <p>Background</p> <p>Several tools have been developed to perform global gene expression profile data analysis, to search for specific chromosomal regions whose features meet defined criteria as well as to study neighbouring gene expression. However, most of these tools are tailored for a specific use in a particular context (e.g. they are species-specific, or limited to a particular data format) and they typically accept only gene lists as input.</p> <p>Results</p> <p>TRAM (Transcriptome Mapper) is a new general tool that allows the simple generation and analysis of quantitative transcriptome maps, starting from any source listing gene expression values for a given gene set (e.g. expression microarrays), implemented as a relational database. It includes a parser able to assign univocal and updated gene symbols to gene identifiers from different data sources. Moreover, TRAM is able to perform intra-sample and inter-sample data normalization, including an original variant of quantile normalization (scaled quantile), useful to normalize data from platforms with highly different numbers of investigated genes. When in 'Map' mode, the software generates a quantitative representation of the transcriptome of a sample (or of a pool of samples) and identifies if segments of defined lengths are over/under-expressed compared to the desired threshold. When in 'Cluster' mode, the software searches for a set of over/under-expressed consecutive genes. Statistical significance for all results is calculated with respect to genes localized on the same chromosome or to all genome genes. Transcriptome maps, showing differential expression between two sample groups, relative to two different biological conditions, may be easily generated. We present the results of a biological model test, based on a meta-analysis comparison between a sample pool of human CD34+ hematopoietic progenitor cells and a sample pool of megakaryocytic cells. Biologically relevant chromosomal segments and gene clusters with differential expression during the differentiation toward megakaryocyte were identified.</p> <p>Conclusions</p> <p>TRAM is designed to create, and statistically analyze, quantitative transcriptome maps, based on gene expression data from multiple sources. The release includes FileMaker Pro database management runtime application and it is freely available at <url>http://apollo11.isto.unibo.it/software/</url>, along with preconfigured implementations for mapping of human, mouse and zebrafish transcriptomes.</p

Thymic stromal lymphopoietin (TSLP) is associated with allergic rhinitis in children with asthma

<p>Abstract</p> <p>Background</p> <p>Allergic rhinitis (AR) affects up to 80% of children with asthma and increases asthma severity. Thymic stromal lymphopoietin (TSLP) is a key mediator of allergic inflammation. The role of the TSLP gene (<it>TSLP</it>) in the pathogenesis of AR has not been studied.</p> <p>Objective</p> <p>To test for associations between variants in <it>TSLP</it>, <it>TSLP</it>-related genes, and AR in children with asthma.</p> <p>Methods</p> <p>We genotyped 15 single nucleotide polymorphisms (SNPs) in <it>TSLP, OX40L, IL7R</it>, and <it>RXRα </it>in three independent cohorts: 592 asthmatic Costa Rican children and their parents, 422 nuclear families of North American children with asthma, and 239 Swedish children with asthma. We tested for associations between these SNPs and AR. As we previously reported sex-specific effects for <it>TSLP</it>, we performed overall and sex-stratified analyses. We additionally performed secondary analyses for gene-by-gene interactions.</p> <p>Results</p> <p>Across the three cohorts, the T allele of <it>TSLP </it>SNP rs1837253 was undertransmitted in boys with AR and asthma as compared to boys with asthma alone. The SNP was associated with reduced odds for AR (odds ratios ranging from 0.56 to 0.63, with corresponding Fisher's combined P value of 1.2 × 10^-4). Our findings were significant after accounting for multiple comparisons. SNPs in <it>OX40L, IL7R</it>, and <it>RXRα </it>were not consistently associated with AR in children with asthma. There were nominally significant interactions between gene pairs.</p> <p>Conclusions</p> <p><it>TSLP </it>SNP rs1837253 is associated with reduced odds for AR in boys with asthma. Our findings support a role for <it>TSLP </it>in the pathogenesis of AR in children with asthma.</p

Challenges in the association of human single nucleotide polymorphism mentions with unique database identifiers

Thomas PE, Klinger R, Furlong LI, Hofmann-Apitius M, Friedrich CM. Challenges in the association of human single nucleotide polymorphism mentions with unique database identifiers. BMC Bioinformatics. 2011;12(Suppl 4): S4

Lineage-Specific Biology Revealed by a Finished Genome Assembly of the Mouse

A finished clone-based assembly of the mouse genome reveals extensive recent sequence duplication during recent evolution and rodent-specific expansion of certain gene families. Newly assembled duplications contain protein-coding genes that are mostly involved in reproductive function

Diffuse glioma growth: a guerilla war

In contrast to almost all other brain tumors, diffuse gliomas infiltrate extensively in the neuropil. This growth pattern is a major factor in therapeutic failure. Diffuse infiltrative glioma cells show some similarities with guerilla warriors. Histopathologically, the tumor cells tend to invade individually or in small groups in between the dense network of neuronal and glial cell processes. Meanwhile, in large areas of diffuse gliomas the tumor cells abuse pre-existent “supply lines” for oxygen and nutrients rather than constructing their own. Radiological visualization of the invasive front of diffuse gliomas is difficult. Although the knowledge about migration of (tumor)cells is rapidly increasing, the exact molecular mechanisms underlying infiltration of glioma cells in the neuropil have not yet been elucidated. As the efficacy of conventional methods to fight diffuse infiltrative glioma cells is limited, a more targeted (“search & destroy”) tactic may be needed for these tumors. Hopefully, the study of original human glioma tissue and of genotypically and phenotypically relevant glioma models will soon provide information about the Achilles heel of diffuse infiltrative glioma cells that can be used for more effective therapeutic strategies