Quality assessment and data analysis for microRNA expression arrays.

MicroRNAs are small (approximately 22 nt) RNAs that regulate gene expression and play important roles in both normal and disease physiology. The use of microarrays for global characterization of microRNA expression is becoming increasingly popular and has the potential to be a widely used and valuable research tool. However, microarray profiling of microRNA expression raises a number of data analytic challenges that must be addressed in order to obtain reliable results. We introduce here a universal reference microRNA reagent set as well as a series of nonhuman spiked-in synthetic microRNA controls, and demonstrate their use for quality control and between-array normalization of microRNA expression data. We also introduce diagnostic plots designed to assess and compare various normalization methods. We anticipate that the reagents and analytic approach presented here will be useful for improving the reliability of microRNA microarray experiments.

Optimal conditions for synthesizing complementary DNA in the HIV-1 endogenous reverse transcriptase reaction.

Concentration of monovalent and divalent cations, anionic detergent, reducing agent and nucleotides, as well as pH, temperature, and incubation time were optimized for high levels of HIV-1 endogenous reverse transcriptase activity. In addition, mellitin, a peptide substitute for anionic detergent, and oligo(dT)12-18 were found to stimulate nucleic acid synthesis. This HIV-1 endogenous reaction demonstrated RNA- and DNA-dependent DNA polymerase activities. Nucleic acid intermediates and final products included RNA:DNA hybrids as well as single- and double-stranded DNA. The complementary DNA products formed were representative of all regions of the HIV-1 genome.

Delayed severe extrapyramidal disturbance following frequent depot phenothiazine administration.

The authors report the occurrence of a sever striopallidal disorder in a schizophrenic patient one week after he received fluphenazine enanthate injections on an every-other-day schedule. In view of current interest in depot psychopharmaceuticals, they recommend that careful attention be given to dosage and administration schedules and to the possibility of delayed pseudoparkinsonian symptoms. Emergency room physicians should be alerted to the possible side effects of such drugs.

A new implementation and detailed study of breakpoint analysis.

Phylogenies derived from gene order data may prove crucial in answering some fundamental open questions in biomolecular evolution. Yet very few techniques are available for such phylogenetic reconstructions. One method is breakpoint analysis, developed by Blanchette and Sankoff for solving the "breakpoint phylogeny." Our earlier studies confirmed the usefulness of this approach, but also found that BPAnalysis, the implementation developed by Sankoff and Blanchette, was too slow to use on all but very small datasets. We report here on a reimplementation of BPAnalysis using the principles of algorithmic engineering. Our faster (by 2 to 3 orders of magnitude) and flexible implementation allowed us to conduct studies on the characteristics of breakpoint analysis, in terms of running time, quality, and robustness, as well as to analyze datasets that had so far been considered out of reach. We report on these findings and also discuss future directions for our new implementation.

New approaches for reconstructing phylogenies from gene order data.

We report on new techniques we have developed for reconstructing phylogenies on whole genomes. Our mathematical techniques include new polynomial-time methods for bounding the inversion length of a candidate tree and new polynomial-time methods for estimating genomic distances which greatly improve the accuracy of neighbor-joining analyses. We demonstrate the power of these techniques through an extensive performance study based on simulating genome evolution under a wide range of model conditions. Combining these new tools with standard approaches (fast reconstruction with neighbor-joining, exploration of all possible refinements of strict consensus trees, etc.) has allowed us to analyze datasets that were previously considered computationally impractical. In particular, we have conducted a complete phylogenetic analysis of a subset of the Campanulaceae family, confirming various conjectures about the relationships among members of the subset and about the principal mechanism of evolution for their chloroplast genome. We give representative results of the extensive experimentation we conducted on both real and simulated datasets in order to validate and characterize our approaches. We find that our techniques provide very accurate reconstructions of the true tree topology even when the data are generated by processes that include a significant fraction of transpositions and when the data are close to saturation.

A new fast heuristic for computing the breakpoint phylogeny and experimental phylogenetic analyses of real and synthetic data.

The breakpoint phylogeny is an optimization problem proposed by Blanchette et al. for reconstructing evolutionary trees from gene order data. These same authors also developed and implemented BPAnalysis [3], a heuristic method (based upon solving many instances of the travelling salesman problem) for estimating the breakpoint phylogeny. We present a new heuristic for this purpose; although not polynomial-time, our heuristic is much faster in practice than BPAnalysis. We present and discuss the results of experimentation on synthetic datasets and on the flowering plant family Campanulaceae with three methods: our new method, BPAnalysis, and the neighbor-joining method [25] using several distance estimation techniques. Our preliminary results indicate that, on datasets with slow evolutionary rates and large numbers of genes in comparison with the number of taxa (genomes), all methods recover quite accurate reconstructions of the true evolutionary history (although BPAnalysis is too slow to be practical), but that on datasets where the rate of evolution is high relative to the number of genes, the accuracy of all three methods is poor.