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Background: During microRNA (miRNA) maturation in humans and flies, Drosha and Dicer cut the precursor transcript, thereby producing a short RNA duplex. One strand of this duplex becomes a functional component of the RNA-Induced Silencing Complex (RISC), while the other is eliminated. While thermodynamic asymmetry of the duplex ends appears to play a decisive role in the strand selection process, the details of the selection mechanism are not yet understood. Results: Here, we assess miRNA strand selection bias in humans and fruit flies by analyzing the sequence composition and relative expression levels of the two strands of the precursor duplex in these species. We find that the sequence elements associated with preferential miRNA strand selection and/or rejection differ between the two species. Further, we identify another feature that distinguishes human and fly miRNA processing machinery: the relative accuracy of the Drosha and Dicer enzymes. Conclusion: Our result provides clues to the mechanistic aspects of miRNA strand selection in humans and other mammals. Further, it indicates that human and fly miRNA processing pathways are more distinct than currently recognized. Finally, the observed strand selection determinants are instrumental in the rational design of efficient miRNA-based expression regulators. [ABSTRACT FROM AUTHOR]

Mapping biological pathways across microbial genomes is a highly important technique in functional studies of biological systems. Existing methods mainly rely on sequence-based orthologous gene mapping, which often leads to suboptimal mapping results because sequence-similarity information alone does not contain sufficient information for accurate identification of orthology relationship. Here we present an algorithm for pathway mapping across microbial genomes. The algorithm takes into account both sequence similarity and genomic structure information such as operons and regulons. One basic premise of our approach is that a microbial pathway could generally be decomposed into a few operons or regulons. We formulated the pathway-mapping problem to map genes across genomes to maximize their sequence similarity under the constraint that the mapped genes be grouped into a few operons, preferably coregulated in the target genome. We have developed an integer-programming algorithm for solving this constrained optimization problem and implemented the algorithm as a computer software program, P-MAP. We have tested P-MAP on a number of known homologous pathways. We conclude that using genomic structure information as constraints could greatly improve the pathway-mapping accuracy over methods that use sequence-similarity information alone. [ABSTRACT FROM AUTHOR]