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Reconstructing a metabolic model from the genome sequence of an organism is a useful but arduous approach for predicting phenotypes. Henry et al. describe a resource that automates most of this process and apply it to create >100 new metabolic models of microbes.
Tang et al. present the first large-scale, gene-specific library of knockout mice. They disrupt 472 genes encoding secreted or transmembrane proteins and report the results of a comprehensive phenotypic analysis.
Genome-wide single-gene deletion libraries can be important tools for understanding the molecular workings of an organism, but have only been created for a single eukaryotic species, Saccharomyces cerevisiae. Now, Kim et al. present a second collection of deletion mutants that covers 98.4% of the genes of Schizosaccharomyces pombe, allowing a systematic comparison of gene essentiality and knockout phenotypes between two eukaryotic species.
Cultured human embryonic stem cells often acquire chromosomal abnormalities that could be detrimental in certain applications. Närvä et al. report the highest-resolution genetic analysis of these cells to date and identify genes whose expression is altered by culture-induced genetic changes.
Lee et al. have created the largest functional gene network for plants by combining existing data on Arabidopsis thaliana with data gathered from other organisms. Although the genetics of many A. thaliana traits has been thoroughly studied, the authors succeed in discovering new genes associated with root development and drought resistance.
We have yet to identify the functions of the majority of genes of Plasmodium falciparum, the causative agent of malaria. Hu et al. profile transcriptional changes after chemically induced growth perturbations to assemble a protein network that predicts P. faliciparum gene function.
Sequencing a person's genome may reveal large DNA insertions and other structural rearrangements, but assessing their effects requires pinpointing them to nucleotide resolution. Lam et al. use a library of previously discovered rearrangements to map and analyze genetic variation.