Quantitative and Molecular Genetic Analyses of Mutations Increasing Drosophila Life Span

Understanding the genetic and environmental factors that affect variation in life span and senescence is of major interest for human health and evolutionary biology. Multiple mechanisms affect longevity, many of which are conserved across species, but the genetic networks underlying each mechanism and cross-talk between networks are unknown. We report the results of a screen for mutations affecting Drosophila life span. One third of the 1,332 homozygous P–element insertion lines assessed had quantitative effects on life span; mutations reducing life span were twice as common as mutations increasing life span. We confirmed 58 mutations with increased longevity, only one of which is in a gene previously associated with life span. The effects of the mutations increasing life span were highly sex-specific, with a trend towards opposite effects in males and females. Mutations in the same gene were associated with both increased and decreased life span, depending on the location and orientation of the P–element insertion, and genetic background. We observed substantial—and sex-specific—epistasis among a sample of ten mutations with increased life span. All mutations increasing life span had at least one deleterious pleiotropic effect on stress resistance or general health, with different patterns of pleiotropy for males and females. Whole-genome transcript profiles of seven of the mutant lines and the wild type revealed 4,488 differentially expressed transcripts, 553 of which were common to four or more of the mutant lines, which include genes previously associated with life span and novel genes implicated by this study. Therefore longevity has a large mutational target size; genes affecting life span have variable allelic effects; alleles affecting life span exhibit antagonistic pleiotropy and form epistatic networks; and sex-specific mutational effects are ubiquitous. Comparison of transcript profiles of long-lived mutations and the control line reveals a transcriptional signature of increased life span

Identification of Protein Secretion Systems in Bacterial Genomes Using MacSyFinder.

International audienceProtein secretion systems are complex molecular machineries that translocate proteins through the outer membrane, and sometimes through multiple other barriers. They have evolved by co-option of components from other envelope-associated cellular machineries, making them sometimes difficult to identify and discriminate. Here, we describe how to identify protein secretion systems in bacterial genomes using MacSyFinder. This flexible computational tool uses the knowledge stemming from experimental studies to identify homologous systems in genome data. It can be used with a set of predefined models-"TXSScan"-to identify all major secretion systems of diderm bacteria (i.e., with inner and with LPS-containing outer membranes). For this, it identifies and clusters colocalized components of secretion systems using sequence similarity searches with hidden Markov model protein profiles. Finally, it checks whether the genetic content and organization of clusters satisfy the constraints of the model. TXSScan models can be customized to search for variants of known systems. The models can also be built from scratch to identify novel systems. In this chapter, we describe a complete pipeline of analysis, including the identification of a reference set of experimentally studied systems, the identification of components and the construction of their protein profiles, the definition of the models, their optimization, and, finally, their use as tools to search genomic data