The effect of gene flow from unsampled demes in landscape genetic analysis.

An assumption of correlative landscape genetic methods is that genetic differentiation at neutral markers arises solely from the degree to which the intervening landscape between individuals or populations resists gene flow. However, this assumption is violated when gene flow occurs into the sampled population from an unsampled, differentiated deme. This may happen when sampling within only a portion of a population's extent or when closely related species hybridize with the sampled population. In both cases, violation of the modelling assumptions has the potential to reduce landscape genetic model selection accuracy and result in poor inferences. We used individual-based population genetic simulations in complex landscapes within a model selection framework to explore the potential confounding effect of gene flow from unsampled demes. We hypothesized that as gene flow from outside the sampling extent increased, model selection accuracy would decrease due to the formation of a hybrid zone where allele frequencies were perturbed in a way that was not correlated with effective distances between sampled individuals. Surprisingly, we found this expectation was unfounded, because the reduced accuracy due to admixture was counteracted by an increase in allelic diversity as alleles spread from the unsampled deme into the sampled population. These new alleles increased the power to detect landscape genetic relationships and even slightly improving model selection accuracy overall. This is a reassuring result, suggesting that sampling the full extent of a population or related species that may hybridize may be unnecessary, as long as other well-established sampling requirements are met.

Modelling multilocus selection in an individual-based, spatially-explicit landscape genetics framework.

We implemented multilocus selection in a spatially-explicit, individual-based framework that enables multivariate environmental gradients to drive selection in many loci as a new module for the landscape genetics programs, CDPOP and CDMetaPOP. Our module simulates multilocus selection using a linear additive model, providing a flexible platform to evaluate a wide range of genotype-environment associations. Importantly, the module allows simulation of selection in any number of loci under the influence of any number of environmental variables. We validated the module with individual-based selection simulations under Wright-Fisher assumptions. We then evaluated results for simulations under a simple landscape selection model. Next, we simulated individual-based multilocus selection across a complex selection landscape with three loci linked to three different environmental variables. Finally, we demonstrated how the program can be used to simulate multilocus selection under varying selection strengths across different levels of gene flow in a landscape genetics framework. This new module provides a valuable addition to the study of landscape genetics, allowing for explicit evaluation of the contributions and interactions between gene flow and selection-driven processes across complex, multivariate environmental and landscape conditions.

A comparison of regression methods for model selection in individual-based landscape genetic analysis.

Anthropogenic migration barriers fragment many populations and limit the ability of species to respond to climate-induced biome shifts. Conservation actions designed to conserve habitat connectivity and mitigate barriers are needed to unite fragmented populations into larger, more viable metapopulations, and to allow species to track their climate envelope over time. Landscape genetic analysis provides an empirical means to infer landscape factors influencing gene flow and thereby inform such conservation actions. However, there are currently many methods available for model selection in landscape genetics, and considerable uncertainty as to which provide the greatest accuracy in identifying the true landscape model influencing gene flow among competing alternative hypotheses. In this study, we used population genetic simulations to evaluate the performance of seven regression-based model selection methods on a broad array of landscapes that varied by the number and type of variables contributing to resistance, the magnitude and cohesion of resistance, as well as the functional relationship between variables and resistance. We also assessed the effect of transformations designed to linearize the relationship between genetic and landscape distances. We found that linear mixed effects models had the highest accuracy in every way we evaluated model performance; however, other methods also performed well in many circumstances, particularly when landscape resistance was high and the correlation among competing hypotheses was limited. Our results provide guidance for which regression-based model selection methods provide the most accurate inferences in landscape genetic analysis and thereby best inform connectivity conservation actions.

Spatiotemporal variation in resource selection: insights from the American marten (Martes americana).

Behavioral and genetic adaptations to spatiotemporal variation in habitat conditions allow species to maximize their biogeographic range and persist over time in dynamic environments. An understanding of these local adaptations can be used to guide management and conservation of populations over broad extents encompassing diverse habitats. This understanding is often achieved by identifying covariates related to species' occurrence in multiple independent studies conducted in relevant habitats and seasons. However, synthesis across studies is made difficult by differences in the model covariates evaluated and analytical frameworks employed. Furthermore, inferences may be confounded by spatiotemporal variation in which habitat attributes are limiting to the species' ecological requirements. In this study, we sought to quantify spatiotemporal variation in resource selection by the American marten (Martes americana) in forest ecosystems of the Pacific Northwest, USA. We developed resource selection functions for both summer and winter based on occurrence data collected in mesic and xeric forest habitats. Use of a consistent analytical framework facilitated comparisons. Habitat attributes predicting marten occurrence differed strongly between the two study areas, but not between seasons. Moreover, the spatial scale over which covariates were calculated greatly influenced their predictive power. In the mesic environment, marten resource selection was strongly tied to riparian habitats, whereas in the xeric environment, marten responded primarily to canopy cover and forest fragmentation. These differences in covariates associated with marten occurrence reflect differences in which factors were limiting to marten ecology in each study area, as well as local adaptations to habitat variability. Our results highlight the benefit of controlled meta-replication studies in which analyses of multiple study areas and seasons at varying spatial scales are integrated into a single framework.

Multiple major increases and decreases in mitochondrial substitution rates in the plant family Geraniaceae.

BACKGROUND: Rates of synonymous nucleotide substitutions are, in general, exceptionally low in plant mitochondrial genomes, several times lower than in chloroplast genomes, 10-20 times lower than in plant nuclear genomes, and 50-100 times lower than in many animal mitochondrial genomes. Several cases of moderate variation in mitochondrial substitution rates have been reported in plants, but these mostly involve correlated changes in chloroplast and/or nuclear substitution rates and are therefore thought to reflect whole-organism forces rather than ones impinging directly on the mitochondrial mutation rate. Only a single case of extensive, mitochondrial-specific rate changes has been described, in the angiosperm genus Plantago. RESULTS: We explored a second potential case of highly accelerated mitochondrial sequence evolution in plants. This case was first suggested by relatively poor hybridization of mitochondrial gene probes to DNA of Pelargonium hortorum (the common geranium). We found that all eight mitochondrial genes sequenced from P. hortorum are exceptionally divergent, whereas chloroplast and nuclear divergence is unexceptional in P. hortorum. Two mitochondrial genes were sequenced from a broad range of taxa of variable relatedness to P. hortorum, and absolute rates of mitochondrial synonymous substitutions were calculated on each branch of a phylogenetic tree of these taxa. We infer one major, approximately 10-fold increase in the mitochondrial synonymous substitution rate at the base of the Pelargonium family Geraniaceae, and a subsequent approximately 10-fold rate increase early in the evolution of Pelargonium. We also infer several moderate to major rate decreases following these initial rate increases, such that the mitochondrial substitution rate has returned to normally low levels in many members of the Geraniaceae. Finally, we find unusually little RNA editing of Geraniaceae mitochondrial genes, suggesting high levels of retroprocessing in their history. CONCLUSION: The existence of major, mitochondrial-specific changes in rates of synonymous substitutions in the Geraniaceae implies major and reversible underlying changes in the mitochondrial mutation rate in this family. Together with the recent report of a similar pattern of rate heterogeneity in Plantago, these findings indicate that the mitochondrial mutation rate is a more plastic character in plants than previously realized. Many molecular factors could be responsible for these dramatic changes in the mitochondrial mutation rate, including nuclear gene mutations affecting the fidelity and efficacy of mitochondrial DNA replication and/or repair and--consistent with the lack of RNA editing--exceptionally high levels of "mutagenic" retroprocessing. That the mitochondrial mutation rate has returned to normally low levels in many Geraniaceae raises the possibility that, akin to the ephemerality of mutator strains in bacteria, selection favors a low mutation rate in plant mitochondria.

SIMPLE interacts with NEDD4 and TSG101: evidence for a role in lysosomal sorting and implications for Charcot-Marie-Tooth disease.

Mutation of the SIMPLE gene (small integral membrane protein of the lysosome/late endosome) is the molecular basis of Charcot-Marie-Tooth disease type 1C (CMT1C), a demyelinating peripheral neuropathy. Although the precise function of SIMPLE is unknown, prior reports suggest it localizes to the lysosome/late endosome. Furthermore, murine Simple interacts with Nedd4 (neural precursor cell expressed, developmentally downregulated 4), an E3 ubiquitin ligase that is important for regulating lysosomal degradation of plasma membrane proteins. To bring insights into the biochemical function of human SIMPLE, we confirmed that human SIMPLE interacts with NEDD4 and also report a novel interaction with tumor susceptibility gene 101 (TSG101), a class E vacuolar sorting protein. TSG101 is known to function downstream of NEDD4, sorting ubiquitinated substrates into multivesicular bodies (MVBs), which then deliver their cargo into the lysosomal lumen for degradation. Given the interaction with NEDD4 and TSG101, and the localization of SIMPLE along the lysosomal degradation pathway, we hypothesize that SIMPLE plays a role in the lysosomal sorting of plasma membrane proteins. We examine three CMT1C-associated SIMPLE mutations and show that they do not affect the interaction with NEDD4 or TSG101, nor do they lead to altered subcellular localization.

Epidermal growth factor mediates detachment from and invasion through collagen I and Matrigel in Capan-1 pancreatic cancer cells.

BACKGROUND: Pancreatic adenocarcinoma is a highly invasive neoplasm. Epidermal growth factor (EGF) and its receptor are over expressed in pancreatic cancer, and expression correlates with invasion and metastasis. We hypothesized that EGF receptor and integrin signalling pathways interact in mediating cellular adhesion and invasion in pancreatic cancer, and that invasiveness correlates temporally with detachment from extracellular matrix. METHODS: We tested this hypothesis by investigating the role of EGF in mediating adhesion to and invasion through collagen I and Matrigel in the metastatic pancreatic adenocarcinoma cell line Capan-1. Adhesion and invasion were measured using in vitro assays of fluorescently-labeled cells. Adhesion and invasion assays were also performed in the primary pancreatic adenocarcinoma cell line MIA PaCa-2. RESULTS: EGF inhibited adhesion to collagen I and Matrigel in Capan-1 cells. The loss of adhesion was reversed by AG825, an inhibitor of erbB2 receptor signalling and by wortmannin, a PI3K inhibitor, but not by the protein synthesis inhibitor cycloheximide. EGF stimulated invasion through collagen I and Matrigel at concentrations and time courses similar to those mediating detachment from these extracellular matrix components. Adhesion to collagen I was different in MIA PaCa-2 cells, with no significant change elicited following EGF treatment, whereas treatment with the EGF family member heregulin-alpha elicited a marked increase in adhesion. Invasion through Matrigel in response to EGF, however, was similar to that observed in Capan-1 cells. CONCLUSION: An inverse relationship exists between adhesion and invasion capabilities in Capan-1 cells but not in MIA PaCa-2 cells. EGF receptor signalling involving the erbB2 and PI3K pathways plays a role in mediating these events in Capan-1 cells.

SIMPLE mutation in demyelinating neuropathy and distribution in sciatic nerve.

Charcot-Marie-Tooth neuropathy type 1C (CMT1C) is an autosomal dominant demyelinating peripheral neuropathy caused by missense mutations in the small integral membrane protein of lysosome/late endosome (SIMPLE) gene. To investigate the prevalence of SIMPLE mutations, we screened a cohort of 152 probands with various types of demyelinating or axonal and pure motor or sensory inherited neuropathies. SIMPLE mutations were found only in CMT1 patients, including one G112S and one W116G missense mutations. A novel I74I polymorphism was identified, yet no splicing defect of SIMPLE is likely. Haplotype analysis of STR markers and intragenic SNPs linked to the gene demonstrated that families with the same mutation are unlikely to be related. The clustering of the G112S, T115N, and W116G mutations within five amino acids suggests this domain may be critical to peripheral nerve myelination. Electrophysiological studies showed that CMT1C patients from six pedigrees (n = 38) had reduced nerve conduction velocities ranging from 7.5 to 27.0m/sec (peroneal). Two patients had temporal dispersion of nerve conduction and irregularity of conduction slowing, which is unusual for CMT1 patients. We report the expression of SIMPLE in various cell types of the sciatic nerve, including Schwann cells, the affected cell type in CMT1C.