Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels and spotted DNA microarrays

BACKGROUND: The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge requires careful examination of the performance of a range of statistical models, as well as empirical examination of the effect of replication on the power to resolve these differences. RESULTS: New models are derived and software is developed for the analysis of microarray ratio data. These models incorporate multiplicative small error terms, and error standard deviations that are proportional to expression level. The fastest and most powerful method incorporates additive small error terms and error standard deviations proportional to expression level. Data from four studies are profiled for the degree to which they reveal statistically significant differences in gene expression. The gene expression level at which there is an empirical 50% probability of a significant call is presented as a summary statistic for the power to detect small differences in gene expression. CONCLUSIONS: Understanding the resolution of difference in gene expression that is detectable as significant is a vital component of experimental design and evaluation. These small differences in gene expression level are readily detected with a Bayesian analysis of gene expression level that has additive error terms and constrains samples to have a common error coefficient of variation. The power to detect small differences in a study may then be determined by logistic regression

Multifactorial experimental design and the transitivity of ratios with spotted DNA microarrays

BACKGROUND: Multifactorial experimental designs using DNA microarrays are becoming increasingly common, but the extent of the transitivity of cDNA microarray expression measurements across multiple samples has yet to be explored. RESULTS: A strong correlation between direct and transitive inference for significantly differentially expressed genes is demonstrated, using subsets of a dye-swap loop design. CONCLUSIONS: In experimental design, opportunities for transitive inference should be exploited, while always ensuring that comparisons of greatest interest comprise direct hybridizations

Bayesian Analysis of Gene Expression Levels: Statistical Quantification of Relative mRNA Level across Multiple Strains or Treatments

Background: Methods of microarray analysis that suit experimentalists using the technology are vital. Many methodologies discard the quantitative results inherent in cDNA microarray comparisons or cannot be flexibly applied to multifactorial experimental design. Here we present a flexible, quantitative Bayesian framework. This framework can be used to analyze normalized microarray data acquired by any replicated experimental design in which any number of treatments, genotypes, or developmental states are studied using a continuous chain of comparisons. Results: We apply this method to Saccharomyces cerevisiae microarray datasets on the transcriptional response to ethanol shock, to SNF2 and SWI1 deletion in rich and minimal media, and to wild-type and zap1 expression in media with high, medium, and low levels of zinc. The method is highly robust to missing data, and yields estimates of the magnitude of expression differences and experimental error variances on a per-gene basis. It reveals genes of interest that are differentially expressed at below the twofold level, genes with high 'fold-change' that are not statistically significantly different, and genes differentially regulated in quantitatively unanticipated ways. Conclusions: Anyone with replicated normalized cDNA microarray ratio datasets can use the freely available MacOS and Windows software, which yields increased biological insight by taking advantage of replication to discern important changes in expression level both above and below a twofold threshold. Not only does the method have utility at the moment, but also, within the Bayesian framework, there will be considerable opportunity for future development.Organismic and Evolutionary Biolog

Potential for rabies control through dog vaccination in wildlife-abundant communities of Tanzania

Canine vaccination has been successful in controlling rabies in diverse settings worldwide. However, concerns remain that coverage levels which have previously been sufficient might be insufficient in systems where transmission occurs both between and within populations of domestic dogs and other carnivores. To evaluate the effectiveness of vaccination targeted at domestic dogs when wildlife also contributes to transmission, we applied a next-generation matrix model based on contract tracing data from the Ngorongoro and Serengeti Districts in northwest Tanzania. We calculated corresponding values of R0, and determined, for policy purposes, the probabilities that various annual vaccination targets would control the disease, taking into account the empirical uncertainty in our field data. We found that transition rate estimates and corresponding probabilities of vaccination-based control indicate that rabies transmission in this region is driven by transmission within domestic dogs. Different patterns of rabies transmission between the two districts exist, with wildlife playing a more important part in Ngorongoro and leading to higher recommended coverage levels in that district. Nonetheless, our findings indicate that an annual dog vaccination campaign achieving the WHO-recommended target of 70% will control rabies in both districts with a high level of certainty. Our results support the feasibility of controlling rabies in Tanzania through dog vaccination

Detecting rare gene transfer events in bacterial populations

This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permissio

Testing for COVID-19 is Much More Effective When Performed Immediately Prior to Social Mixing

Objective: To quantify the utility of RT-PCR and rapid antigen tests in preventing post-arrival transmission based on timing of the pre-departure test.Methods: We derived analytical expressions to compute post-arrival transmission when no test is performed, and when either an RT-PCR or any of 18 rapid antigen tests is performed at specified times before arrival. We determined the diagnostic sensitivity of the rapid antigen tests by propagating their RT-PCR percent positive agreement onto known RT-PCR diagnostic sensitivity.Results: Depending on the rapid antigen test used, conducting a rapid antigen test immediately before departure reduces post-arrival transmission between 37.4% (95% CrI: 28.2%–40.7%) and 46.7% (95% CrI:40.0%–49.3%), compared to a 31.1% (95% CrI: 26.3%–33.5%) reduction using an RT-PCR 12 h before arrival. Performance of each rapid antigen test differed by diagnostic sensitivity over the course of disease. However, these differences were smaller than those engendered by testing too early.Conclusion: Testing closer to arrival—ideally on the day of arrival—is more effective at reducing post-arrival transmission than testing earlier. Rapid antigen tests perform the best in this application due to their short turnaround time

Optimized primers and other critical conditions for efficient fusion PCR to generate knockout vectors in filamentous fungi.

Methods to streamline functional studies of large numbers of genes are essential to fully utilize the significant genomic resources now available for fungi. Fusion PCR is often used to join pieces of DNA together, particularly in the construction of DNA fragments for gene replacement in fungi. Here we present high-efficiency primers which reliably direct fusion and amplification to generate constructs for gene knockouts. Addendum: The authors communicated this omission post publication: We inadvertently left out the 3HS sequence with which we had such great success. The 5HS sequence, as seen in Figure 2D, is 5\u27-AGTCGACGACAACTACCATCGATCTGACG. The 3HS sequence which was missing from the original paper is 5\u27-ACACTGGTGACGGCTAACCAGAACTGTCA

Integrating Community-Based Interventions to Reverse the Convergent TB/HIV Epidemics in Rural South Africa.

The WHO recommends integrating interventions to address the devastating TB/HIV co-epidemics in South Africa, yet integration has been poorly implemented and TB/HIV control efforts need strengthening. Identifying infected individuals is particularly difficult in rural settings. We used mathematical modeling to predict the impact of community-based, integrated TB/HIV case finding and additional control strategies on South Africa's TB/HIV epidemics. We developed a model incorporating TB and HIV transmission to evaluate the effectiveness of integrating TB and HIV interventions in rural South Africa over 10 years. We modeled the impact of a novel screening program that integrates case finding for TB and HIV in the community, comparing it to status quo and recommended TB/HIV control strategies, including GeneXpert, MDR-TB treatment decentralization, improved first-line TB treatment cure rate, isoniazid preventive therapy, and expanded ART. Combining recommended interventions averted 27% of expected TB cases (95% CI 18-40%) 18% HIV (95% CI 13-24%), 60% MDR-TB (95% CI 34-83%), 69% XDR-TB (95% CI 34-90%), and 16% TB/HIV deaths (95% CI 12-29). Supplementing these interventions with annual community-based TB/HIV case finding averted a further 17% of TB cases (44% total; 95% CI 31-56%), 5% HIV (23% total; 95% CI 17-29%), 8% MDR-TB (68% total; 95% CI 40-88%), 4% XDR-TB (73% total; 95% CI 38-91%), and 8% TB/HIV deaths (24% total; 95% CI 16-39%). In addition to increasing screening frequency, we found that improving TB symptom questionnaire sensitivity, second-line TB treatment delays, default before initiating TB treatment or ART, and second-line TB drug efficacy were significantly associated with even greater reductions in TB and HIV cases. TB/HIV epidemics in South Africa were most effectively curtailed by simultaneously implementing interventions that integrated community-based TB/HIV control strategies and targeted drug-resistant TB. Strengthening existing TB and HIV treatment programs is needed to further reduce disease incidence

Phylogenetic informativeness reconciles ray-finned fish molecular divergence times

BACKGROUND: Discordance among individual molecular age estimates, or between molecular age estimates and the fossil record, is observed in many clades across the Tree of Life. This discordance is attributed to a variety of variables including calibration age uncertainty, calibration placement, nucleotide substitution rate heterogeneity, or the specified molecular clock model. However, the impact of changes in phylogenetic informativeness of individual genes over time on phylogenetic inferences is rarely analyzed. Using nuclear and mitochondrial sequence data for ray-finned fishes (Actinopterygii) as an example, we extend the utility of phylogenetic informativeness profiles to predict the time intervals when nucleotide substitution saturation results in discordance among molecular ages estimated. RESULTS: We demonstrate that even with identical calibration regimes and molecular clock methods, mitochondrial based molecular age estimates are systematically older than those estimated from nuclear sequences. This discordance is most severe for highly nested nodes corresponding to more recent (i.e., Jurassic-Recent) divergences. By removing data deemed saturated, we reconcile the competing age estimates and highlight that the older mtDNA based ages were driven by nucleotide saturation. CONCLUSIONS: Homoplasious site patterns in a DNA sequence alignment can systematically bias molecular divergence time estimates. Our study demonstrates that PI profiles can provide a non-arbitrary criterion for data exclusion to mitigate the influence of homoplasy on time calibrated branch length estimates. Analyses of actinopterygian molecular clocks demonstrate that scrutiny of the time scale on which sequence data is informative is a fundamental, but generally overlooked, step in molecular divergence time estimation