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Data on replacement mutations in genes of disease patients exist in a variety of online resources. In addition, genome sequencing projects and individual gene sequencing efforts have led to the identification of disease gene homologs in diverse metazoan species. The availability of these two types of information provides unique opportunities to investigate factors that are important in the development of genetically based disease by contrasting long and short-term molecular evolutionary patterns. Therefore, we conducted an analysis of disease-associated human genetic variation for seven disease genes: the cystic fibrosis transmembrane conductance regulator, glucose-6-phosphate dehydrogenase, the neural cell adhesion molecule L1, phenylalanine hydroxylase, paired box 6, the X-linked retinoschisis gene and TSC2/tuberin. Our analyses indicate that disease mutations show definite patterns when examined from an evolutionary perspective. Human replacement mutations resulting in disease are overabundant at amino acid positions most conserved throughout the long-term history of metazoans. In contrast, human polymorphic replacement mutations and silent mutations are randomly distributed across sites with respect to the level of conservation of amino acid sites within genes. Furthermore, disease-causing amino acid changes are of types usually not observed among species. Using Grantham's chemical difference matrix, we find that amino acid changes observed in disease patients are far more radical than the variation found among species and in non-diseased humans. Overall, our results demonstrate the usefulness of evolutionary analyses for understanding patterns of human disease mutations and underscore the biomedical significance of sequence data currently being generated from various model organism genome sequencing projects.

Recently, techniques available for identifying clusters of individuals or boundaries between clusters using genetic data from natural populations have expanded rapidly. Consequently, there is a need to evaluate these different techniques. We used spatially-explicit simulation models to compare three spatial Bayesian clustering programs and two edge detection methods. Spatially-structured populations were simulated where a continuous population was subdivided by barriers. We evaluated the ability of each method to correctly identify boundary locations while varying: (i) time after divergence, (ii) strength of isolation by distance, (iii) level of genetic diversity, and (iv) amount of gene flow across barriers. To further evaluate the methods’ effectiveness to detect genetic clusters in natural populations, we used previously published data on North American pumas and a European shrub. Our results show that with simulated and empirical data, the Bayesian spatial clustering algorithms outperformed direct edge detection methods. All methods incorrectly detected boundaries in the presence of strong patterns of isolation by distance. Based on this finding, we support the application of Bayesian spatial clustering algorithms for boundary detection in empirical datasets, with necessary tests for the influence of isolation by distance.

SUMMARY 1. Dispersal ability is an important ecological factor that can influence population structure. In an attempt to determine the extent that the pattern of genetic differentiation is correlated with dispersal ability in stream‐dwelling aquatic insects, we used the amplified fragment length polymorphism (AFLP) technique to characterise genetic variation in four aquatic insect species: Gumaga griseola (Trichoptera: Sericostomatidae), Helicopsyche mexicana (Trichoptera: Helicopsychidae), Psephenus montanus (Coleoptera: Psephenidae) and Ambrysus thermarum (Hemiptera: Naucoridae). Individuals were sampled from several sites within two adjacent catchments in the Arizona White Mountains. In addition to the genetic analyses, a 20‐week‐long trapping study was used to determine the relative dispersal ability of adults of the four species examined. 2. We obtained hierarchical indicators of genetic differentiation for catchments, sites within catchments and sites across the region examined. Overall, average estimators of genetic differentiation (F‐statistics) were consistent with direct observations of organismal movement, although it was our direct observations on adult insect flight that permitted us to interpret our results correctly. This was because of the fact that a lack of genetic differentiation across watersheds can be interpreted in two ways. 3. In contrast to F‐statistics, patterns of genetic isolation by distance for each species more clearly reflected dispersal ability, suggesting that such analytical approaches provide less ambiguous information about the importance of gene flow in the hierarchical partitioning of genetic variation in stream organisms.

Phylogeographical analyses conducted in the Pacific Northwestern United States have often revealed concordant patterns of genetic diversity among taxa. These studies demonstrate distinct North/South genetic discontinuities that have been attributed to Pleistocene glaciation. We examined phylogeographical patterns of red tree voles (Phenacomys longicaudus) in western Oregon by analysing mitochondrial control region sequences for 169 individuals from 18 areas across the species’ range. Cytochrome b sequences were also analysed from a subset of our samples to confirm the presence of major haplotype groups. Phylogenetic network analyses suggested the presence of two haplotype groups corresponding to northern and southern regions of P. longicaudus’ range. Spatial genetic analyses (samova and Genetic Landscape Shapes) of control region sequences demonstrated a primary genetic discontinuity separating northern and southern sampling areas, while a secondary discontinuity separated northern sampling areas into eastern and western groups divided by the Willamette Valley. The North/South discontinuity likely corresponds to a region of secondary contact between lineages rather than an overt barrier. Although the Cordilleran ice sheet (maximum ∼12 000 years ago) did not move southward to directly affect the region occupied by P. longicaudus, climate change during glaciation fragmented the forest landscape that it inhabits. Signatures of historical fragmentation were reflected by positive associations between latitude and variables such as Tajima's D and patterns associated with location‐specific alleles. Genetic distances between southern sampling areas were smaller, suggesting that forest fragmentation was reduced in southern vs. northern regions.

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The emergence of pathogens resistant to existing antimicrobial drugs is a growing worldwide health crisis that threatens a return to the pre-antibiotic era. To decrease the overuse of antibiotics, molecular diagnostics systems are needed that can rapidly identify pathogens in a clinical sample and determine the presence of mutations that confer drug resistance at the point of care. We developed a fully integrated, miniaturized semiconductor biochip and closed-tube detection chemistry that performs multiplex nucleic acid amplification and sequence analysis. The approach had a high dynamic range of quantification of microbial load and was able to perform comprehensive mutation analysis on up to 1,000 sequences or strands simultaneously in <2 h. We detected and quantified multiple DNA and RNA respiratory viruses in clinical samples with complete concordance to a commercially available test. We also identified 54 drug-resistance-associated mutations that were present in six genes of Mycobacterium tuberculosis, all of which were confirmed by next-generation sequencing.