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The recent shift of computational biologists from bioinformatics service providers to leaders of cutting-edge programs highlights the accompanying cultural and conceptual changes that should be implemented by funding bodies and academic institutions.

The interaction between a pathogen and a host is a highly dynamic process in which both agents activate complex programs. Here, we introduce a single-cell RNA-sequencing method, scDual-Seq, that simultaneously captures both host and pathogen transcriptomes. We use it to study the process of infection of individual mouse macrophages with the intracellular pathogen Salmonella typhimurium. Among the infected macrophages, we find three subpopulations and we show evidence for a linear progression through these subpopulations, supporting a model in which these three states correspond to consecutive stages of infection.

Single-cell transcriptomics requires a method that is sensitive, accurate, and reproducible. Here, we present CEL-Seq2, a modified version of our CEL-Seq method, with threefold higher sensitivity, lower costs, and less hands-on time. We implemented CEL-Seq2 on Fluidigm's C1 system, providing its first single-cell, on-chip barcoding method, and we detected gene expression changes accompanying the progression through the cell cycle in mouse fibroblast cells. We also compare with Smart-Seq to demonstrate CEL-Seq2's increased sensitivity relative to other available methods. Collectively, the improvements make CEL-Seq2 uniquely suited to single-cell RNA-Seq analysis in terms of economics, resolution, and ease of use.

New methods employ RNA-seq to study single cells within complex tissues by in situ sequencing or mRNA capture from single photoactivated cells.

Background: Comparative genomics provides at least three methods beyond traditional sequence similarity for identifying functional links between genes: the examination of common phylogenetic distributions, the analysis of conserved proximity along the chromosomes of multiple genomes, and observations of fusions of genes into a multidomain gene in another organism. We have previously generated the links according to each of these methods individually for 43 known microbial genomes. Here we combine these results to construct networks of functional associations., Results: We show that the functional networks obtained by applying these methods have different topologies and that the information they provide is largely additive. In particular, the combined networks of functional links contain an average of 57% of an organism's complete genetic complement, uncover substantial portions of known pathways, and suggest the function of previously unannotated genes. In addition, the combined networks are qualitatively different from the networks obtained using individual methods. They have a dominant cluster that contains approximately 80%-90% of the genes, independent of genome size, and the dominant clusters show the small world behavior expected of a biological system, with global connectivity that is nearly random, and local properties that are highly ordered., Conclusions: When the information on functional linkage provided by three emerging computational methods is combined, the integrated network uncovers large numbers of conserved pathways and identifies clusters of functionally related genes. It therefore shows considerable utility and promise as a tool for understanding genomic structure, and for guiding high throughput experimental investigations.

Background: Gene fusions can be used as tools for functional prediction and also as evolutionary markers. Fused genes often show a scattered phyletic distribution, which suggests a role for processes other than vertical inheritance in their evolution., Results: The evolutionary history of gene fusions was studied by phylogenetic analysis of the domains in the fused proteins and the orthologous domains that form stand-alone proteins. Clustering of fusion components from phylogenetically distant species was construed as evidence of dissemination of the fused genes by horizontal transfer. Of the 51 examined gene fusions that are represented in at least two of the three primary kingdoms (Bacteria, Archaea and Eukaryota), 31 were most probably disseminated by cross-kingdom horizontal gene transfer, whereas 14 appeared to have evolved independently in different kingdoms and two were probably inherited from the common ancestor of modern life forms. On many occasions, the evolutionary scenario also involves one or more secondary fissions of the fusion gene. For approximately half of the fusions, stand-alone forms of the fusion components are encoded by juxtaposed genes, which are known or predicted to belong to the same operon in some of the prokaryotic genomes. This indicates that evolution of gene fusions often, if not always, involves an intermediate stage, during which the future fusion components exist as juxtaposed and co-regulated, but still distinct, genes within operons., Conclusion: These findings suggest a major role for horizontal transfer of gene fusions in the evolution of protein-domain architectures, but also indicate that independent fusions of the same pair of domains in distant species is not uncommon, which suggests positive selection for the multidomain architectures.