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Exposure to ionizing radiation is considered by NASA to be a major health hazard for deep space exploration missions. Ionizing radiation sensitivity is modulated by both genomic and environmental factors. Understanding their contributions is crucial for designing experiments in model organisms, evaluating the risk of deep space (i.e. high-linear energy transfer, or LET, particle) radiation exposure in astronauts, and also selecting therapeutic irradiation regimes for cancer patients. We identified single nucleotide polymorphisms in 15 strains of mice, including 10 collaborative cross model strains and 5 founder strains, associated with spontaneous and ionizing radiation-inducedex vivoDNA damage quantified based on immunofluorescent 53BP1+nuclear foci. Statistical analysis suggested an association with pathways primarily related to cellular signaling, metabolism, tumorigenesis and nervous system damage. We observed different genomic associations in early (4 and 8 hour) responses to different LET radiation, while later (24 hour) DNA damage responses showed a stronger overlap across all LETs. Furthermore, a subset of pathways was associated with spontaneous DNA damage, suggesting 53BP1+foci as a potential biomarker for DNA integrity in mouse models. Based on our results, we suggest several mouse strains as new models to further study the impact of ionizing radiation and validate the identified genetic loci. We also highlight the importance of future humanex vivostudies to refine the association of genes and pathways with the DNA damage response to ionizing radiation and identify targets for space travel countermeasures.

Anthropologists and archaeologists increasingly use phylogenetic methods to test hypotheses involving cross-cultural traits, but the appropriateness of applying tree-based methods to analyze cultural traits is unclear. The authors developed a spatially explicit computer simulation model to investigate trait evolution in relation to phylogeny and geography and used the simulation to assess the sensitivity of two comparative methods (independent contrasts and partial Mantel tests) to different degrees of horizontal transmission. Simulation results show that (a) the method of independent contrasts is sensitive to even small amounts of horizontal transmission in cultural data sets, (b) Mantel tests fail to cleanly discriminate between datasets characterized by different levels of horizontal and vertical trait transmission, and (c) partial Mantel tests do not produce markedly improved statistical performance when testing for associations among traits (as compared to independent contrasts). The results highlight the need for empirical estimates of horizontal transmission and extinction rates in cross-cultural datasets.

In a screen for new DNA repair mutants, we tested 6275 Drosophila strains bearing homozygous mutagenized autosomes (obtained from C. Zuker) for hypersensitivity to methyl methanesulfonate (MMS) and nitrogen mustard (HN2). Testing of 2585 second-chromosome lines resulted in the recovery of 18 mutants, 8 of which were alleles of known genes. The remaining 10 second-chromosome mutants were solely sensitive to MMS and define 8 new mutagen-sensitive genes (mus212–mus219). Testing of 3690 third chromosomes led to the identification of 60 third-chromosome mutants, 44 of which were alleles of known genes. The remaining 16 mutants define 14 new mutagen-sensitive genes (mus314–mus327). We have initiated efforts to identify these genes at the molecular level and report here the first two identified. The HN2-sensitive mus322 mutant defines the Drosophila ortholog of the yeast snm1 gene, and the MMS- and HN2-sensitive mus301 mutant defines the Drosophila ortholog of the human HEL308 gene. We have also identified a second-chromosome mutant, mus215ZIII-2059, that uniformly reduces the frequency of meiotic recombination to

To improve the accuracy of tree reconstruction, phylogeneticists are extracting increasingly large multigene data sets from sequence databases. Determining whether a database contains at least k genes sampled from at least m species is an NP-complete problem. However, the skewed distribution of sequences in these databases permits all such data sets to be obtained in reasonable computing times even for large numbers of sequences. We developed an exact algorithm for obtaining the largest multigene data sets from a collection of sequences. The algorithm was then tested on a set of 100,000 protein sequences of green plants and used to identify the largest multigene ortholog data sets having at least 3 genes and 6 species. The distribution of sizes of these data sets forms a hollow curve, and the largest are surprisingly small, ranging from 62 genes by 6 species, to 3 genes by 65 species, with more symmetrical data sets of around 15 taxa by 15 genes. These upper bounds to sequence concatenation have important implications for building the tree of life from large sequence databases.