Statistical approaches in landscape genetics: an evaluation of methods for linking landscape and genetic data

The goal of landscape genetics is to detect and explain landscape effects on genetic diversity and structure. Despite the increasing popularity of landscape genetic approaches, the statistical methods for linking genetic and landscape data remain largely untested. This lack of method evaluation makes it difficult to compare studies utilizing different statistics, and compromises the future development and application of the field. To investigate the suitability and comparability of various statistical approaches used in landscape genetics, we simulated data sets corresponding to five landscape-genetic scenarios. We then analyzed these data with eleven methods, and compared the methods based on their statistical power, type-1 error rates, and their overall ability to lead researchers to accurate conclusions about landscape-genetic relationships. Results suggest that some of the most commonly applied techniques (e.g. Mantel and partial Mantel tests) have high type-1 error rates, and that multivariate, non-linear methods are better suited for landscape genetic data analysis. Furthermore, different methods generally show only moderate levels of agreement. Thus, analyzing a data set with only one method could yield method-dependent results, potentially leading to erroneous conclusions. Based on these findings, we give recommendations for choosing optimal combinations of statistical methods, and identify future research needs for landscape genetic data analyses.     

Assessing allelic dropout and genotype reliability using maximum likelihood.

A growing number of population genetic studies utilize nuclear DNA microsatellite data from museum specimens and noninvasive sources. Genotyping errors are elevated in these low quantity DNA sources, potentially compromising the power and accuracy of the data. The most conservative method for addressing this problem is effective, but requires extensive replication of individual genotypes. In search of a more efficient method, we developed a maximum-likelihood approach that minimizes errors by estimating genotype reliability and strategically directing replication at loci most likely to harbor errors. The model assumes that false and contaminant alleles can be removed from the dataset and that the allelic dropout rate is even across loci. Simulations demonstrate that the proposed method marks a vast improvement in efficiency while maintaining accuracy. When allelic dropout rates are low (0-30%), the reduction in the number of PCR replicates is typically 40-50%. The model is robust to moderate violations of the even dropout rate assumption. For datasets that contain false and contaminant alleles, a replication strategy is proposed. Our current model addresses only allelic dropout, the most prevalent source of genotyping error. However, the developed likelihood framework can incorporate additional error-generating processes as they become more clearly understood.     

Little fox on the prairie: genetic structure and diversity throughout the distribution of a grassland carnivore in the United States

The Great Plains region is fragmented by natural and anthropogenic sources, yet the interaction between habitat fragmentation and genetic structure in this region has received limited study. Swift fox (Vulpes velox) are closely associated with short and mixed grass ecosystems, providing an opportunity to study patterns of gene flow, diversity and genetic structure in this area. We collected 589 samples throughout the species’ distribution in the United States and analyzed these samples using 15 microsatellite loci and a 250 base pair sequence of the mitochondrial DNA control region. We detected three levels of spatial genetic structure using microsatellite markers and identified six mitochondrial haplotypes, five of which showed spatial clustering. Differentiation between groups was significant while genetic diversity within groups was generally high. Anthropogenic influences, particularly agriculture, appear to reducing gene flow, especially in the central portion of the species’ range. Conservation measures should be taken to remediate these impacts and to maintain future gene flow in light of expected agricultural expansion in the Great Plains. Potential evolutionary significant units are identified, although further investigation using ecological indicators and adaptive loci is recommended to characterize the adaptive distinctiveness of swift fox populations.     

Determination of phenolic benzo(a)pyrene metabolites formed by human hair follicles

A modified fluoreometric procedure for the determination of basal arly hydrocarbon hydroxylase activity in human hair follicles is described. The method is also applicable for measurement of induction of the enzyme in primary cultures of keratinocytes originating from hair follicles. For good sensitivity of the assay the use of small incubation and extraction volumes, ultrapure chemicals, and adaptations in the measurement of the fluorescent signal are required. Moreover a sensitive micromethod for measuring DNA as a reference variable has to be employed. The sensitivity of the assay permits the measurement of aryl hydrocarbon hydroxylase in 20 hair follicles or in the outgrowth of 6 cultured hair follicles with good reproducibility. The method gives the opportunity to identify individuals with genetically controlled differences in the metabolism of polycyclic aromatic hydrocarbons, using an easily obtainable biopsy tissue of epithelial origin.     

Asymptomatic Middle East Respiratory Syndrome Coronavirus Infection in Rabbits

The ability of Middle East respiratory syndrome coronavirus (MERS-CoV) to infect small animal species may be restricted given the fact that mice, ferrets, and hamsters were shown to resist MERS-CoV infection. We inoculated rabbits with MERS-CoV. Although virus was detected in the lungs, neither significant histopathological changes nor clinical symptoms were observed. Infectious virus, however, was excreted from the upper respiratory tract, indicating a potential route of MERS-CoV transmission in some animal species.     

Mortality in cardiogenic shock is stronger associated to clinical factors than contemporary biomarkers reflecting neurohormonal stress and inflammatory activation

Abstract

Purpose

To validate the IABP-SHOCK II risk score in a Danish cohort and assess the association between the IABP-SHOCK II risk score and admission concentration of biomarkers reflecting neurohormonal – (Copeptin, Pro-atrial natriuretic peptide (proANP), Mid-regional pro-adrenomedullin (MRproADM)) and inflammatory (ST2) activation in patients with CS complicating ST segment elevation myocardial infarction (STEMI).