Genome-wide prediction, display and refinement of binding sites with information theory-based models

BACKGROUND: We present Delila-genome, a software system for identification, visualization and analysis of protein binding sites in complete genome sequences. Binding sites are predicted by scanning genomic sequences with information theory-based (or user-defined) weight matrices. Matrices are refined by adding experimentally-defined binding sites to published binding sites. Delila-Genome was used to examine the accuracy of individual information contents of binding sites detected with refined matrices as a measure of the strengths of the corresponding protein-nucleic acid interactions. The software can then be used to predict novel sites by rescanning the genome with the refined matrices. RESULTS: Parameters for genome scans are entered using a Java-based GUI interface and backend scripts in Perl. Multi-processor CPU load-sharing minimized the average response time for scans of different chromosomes. Scans of human genome assemblies required 4–6 hours for transcription factor binding sites and 10–19 hours for splice sites, respectively, on 24- and 3-node Mosix and Beowulf clusters. Individual binding sites are displayed either as high-resolution sequence walkers or in low-resolution custom tracks in the UCSC genome browser. For large datasets, we applied a data reduction strategy that limited displays of binding sites exceeding a threshold information content to specific chromosomal regions within or adjacent to genes. An HTML document is produced listing binding sites ranked by binding site strength or chromosomal location hyperlinked to the UCSC custom track, other annotation databases and binding site sequences. Post-genome scan tools parse binding site annotations of selected chromosome intervals and compare the results of genome scans using different weight matrices. Comparisons of multiple genome scans can display binding sites that are unique to each scan and identify sites with significantly altered binding strengths. CONCLUSIONS: Delila-Genome was used to scan the human genome sequence with information weight matrices of transcription factor binding sites, including PXR/RXRα, AHR and NF-κB p50/p65, and matrices for RNA binding sites including splice donor, acceptor, and SC35 recognition sites. Comparisons of genome scans with the original and refined PXR/RXRα information weight matrices indicate that the refined model more accurately predicts the strengths of known binding sites and is more sensitive for detection of novel binding sites

Research Article

Mixed modeling and sample size calculations for identifying housekeeping gene

Genetic Variation in the Histamine Production, Response, and Degradation Pathway Is Associated with Histamine Pharmacodynamic Response in Children with Asthma

Introduction: There is growing knowledge of the wide ranging effects of histamine throughout the body therefore it is important to better understand the effects of this amine in patients with asthma. We aimed to explore the association between histamine pharmacodynamic (PD) response and genetic variation in the histamine pathway in children with asthma. Methods: Histamine Iontophoresis with Laser Doppler Monitoring (HILD) was performed in children with asthma and estimates for area under the effect curve (AUEC), maximal response over baseline (Emax), and time of Emax (Tmax) were calculated using non-compartmental analysis and non-linear mixed-effects model with a linked effect PK/PD model. DNA isolation and genotyping were performed among participants to detect known single nucleotide polymorphisms (SNPs) (n = 10) among genes (HDC, HNMT, ABP1, HRH1, HRH4) within the histamine pathway. General linear model was used to identify associations between histamine related genetic variants and measured histamine PD response parameters. Results: Genotyping and HILD response profiles were completed for 163 children. ABP1 47 C/T, ABP1 4107, and HNMT-1639 C/Twere associated with Emax (ABP1 47 CC genotype mean Emax 167.21 vs. CT/TT genotype mean Emax 139.20, p = 0.04; ABP1 4107 CC genotype mean Emax 141.72 vs. CG/GG genotype mean Emax 156.09, p = 0.005; HNMT-1639 CC genotype mean Emax 132.62 vs. CT/TT genotype mean Emax 155.3, p = 0.02). In a stratified analysis among African American children only, ABP1 and HNMT SNPs were also associated with PD response; HRH4 413 CC genotype was associated with lower Emax, p = 0.009. Conclusions: We show for the first time that histamine pathway genetic variation is associated with measureable changes in histamine response in children with asthma. The variability in histamine response and impact of histamine pathway genotype is important to further explore in patients with asthma so as to improve disease phenotyping leading to more personalized treatments

Genetic Variation in the Histamine Production, Response, and Degradation Pathway Is Associated with Histamine Pharmacodynamic Response in Children with Asthma

Introduction: There is growing knowledge of the wide ranging effects of histamine throughout the body therefore it is important to better understand the effects of this amine in patients with asthma. We aimed to explore the association between histamine pharmacodynamic (PD) response and genetic variation in the histamine pathway in children with asthma. Methods: Histamine Iontophoresis with Laser Doppler Monitoring (HILD) was performed in children with asthma and estimates for area under the effect curve (AUEC), maximal response over baseline (Emax), and time of Emax (Tmax) were calculated using non-compartmental analysis and non-linear mixed-effects model with a linked effect PK/PD model. DNA isolation and genotyping were performed among participants to detect known single nucleotide polymorphisms (SNPs) (n = 10) among genes (HDC, HNMT, ABP1, HRH1, HRH4) within the histamine pathway. General linear model was used to identify associations between histamine related genetic variants and measured histamine PD response parameters. Results: Genotyping and HILD response profiles were completed for 163 children. ABP1 47 C/T, ABP1 4107, and HNMT-1639 C/Twere associated with Emax (ABP1 47 CC genotype mean Emax 167.21 vs. CT/TT genotype mean Emax 139.20, p = 0.04; ABP1 4107 CC genotype mean Emax 141.72 vs. CG/GG genotype mean Emax 156.09, p = 0.005; HNMT-1639 CC genotype mean Emax 132.62 vs. CT/TT genotype mean Emax 155.3, p = 0.02). In a stratified analysis among African American children only, ABP1 and HNMT SNPs were also associated with PD response; HRH4 413 CC genotype was associated with lower Emax, p = 0.009. Conclusions: We show for the first time that histamine pathway genetic variation is associated with measureable changes in histamine response in children with asthma. The variability in histamine response and impact of histamine pathway genotype is important to further explore in patients with asthma so as to improve disease phenotyping leading to more personalized treatments

Maternal smoking and the retinoid pathway in the developing lung

Abstract Background Maternal smoking is a risk factor for pediatric lung disease, including asthma. Animal models suggest that maternal smoking causes defective alveolarization in the offspring. Retinoic acid signaling modulates both lung development and postnatal immune function. Thus, abnormalities in this pathway could mediate maternal smoking effects. We tested whether maternal smoking disrupts retinoic acid pathway expression and functioning in a murine model. Methods Female C57Bl/6 mice with/without mainstream cigarette smoke exposure (3 research cigarettes a day, 5 days a week) were mated to nonsmoking males. Cigarette smoke exposure continued throughout the pregnancy and after parturition. Lung tissue from the offspring was examined by mean linear intercept analysis and by quantitative PCR. Cell culture experiments using the type II cell-like cell line, A549, tested whether lipid-soluble cigarette smoke components affected binding and activation of retinoic acid response elements in vitro. Results Compared to tobacco-naïve mice, juvenile mice with tobacco toxin exposure had significantly (P  Conclusions A murine model of maternal cigarette smoking causes abnormal alveolarization in association with altered retinoic acid pathway element expression in the offspring. An in vitro cell culture model shows that lipid-soluble components of cigarette smoke decrease retinoic acid response element activation. It is feasible that disruption of retinoic acid signaling contributes to the pediatric lung dysfunction caused by maternal smoking.</p