Assessing methods to improve benthic fish sampling in a stony headwater stream

Electrofishing is a well-established and widely used method for surveying fish populations. Nonetheless, its effectiveness is impacted by numerous factors, including water chemistry, habitat type and fish species. Both physiological and behavioural responses make bottom-dwelling ‘benthic’ fish which lack swim bladders (e.g. European bullhead Cottus gobio) particularly difficult to survey by electrofishing. We compare the performance and practicalities of electrofishing for benthic fish at a rocky northern English headwater stream with two sampling methods originally designed for crayfish surveys; the triple drawdown method which involves repeated dewatering of a site, and the Pritchard Trap method which involves sunken traps filled with natural substrate that samples a small, fixed (0.25 m2) area of river bed. Both the Pritchard trapping and triple drawdown methods provided similar high-density population density estimates for bullhead which were at least 2.5–5 times higher than predicted from electrofishing derived sweep depletion curves. Electrofishing and the triple drawdown method are both resource-intensive, requiring expensive equipment and a team of trained operatives. These approaches also pose a risk to fish and non-target organisms. In contrast, Pritchard Traps provide a cost-effective passive, low risk survey method requiring minimal training and only one operative. Pritchard traps, therefore, show particular promise for benthic fish surveying and monitoring

Molecular footprints of the Holocene retreat of dwarf birch in Britain

© 2014 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited

A complex pattern of post‐divergence expansion, contraction, introgression and asynchronous responses to Pleistocene climate changes in two Dipelta sister species from western China

The well-known vicariance and dispersal models dominate in understanding the allopatric pattern for related species and presume the simultaneous occurrence of speciation and biogeographic events. However, the formation of allopatry may postdate the species divergence. We examined this hypothesis using DNA sequence data from 3 chloroplast fragments and 5 nuclear loci of Dipelta floribunda and D. yunnanensis, two shrub species with the circum Sichuan Basin distribution, combining the climatic niche modeling approach. The best-fit model supported by the approximate Bayesian computation (ABC) analysis indicated that, D. floribunda and D. yunnanensis diverged during the mid-Pleistocene period, consistent with the largest glacial period in the Qinghai-Tibet Plateau (QTP). The historically inter-specific gene flow was identified but seemed to have ceased after the last interglacial period (LIG), when the range of D. floribunda moved northward from the south of the Sichuan Basin. Further, populations of D. floribunda had expanded obviously in the north of the Sichuan Basin after the last glacial maximum (LGM). Relatively, the range of D. yunnanensis expanded before the LGM, reduced during the post-LGM especially in the north of the Sichuan Basin, reflecting the asynchronous responses of related species to the contemporary climate changes. Our results suggested that complex topography should be considered in understanding the distributional patterns even for closely related species and their demographic responses

Influence of hyperhomocysteinemia on the cellular redox state - Impact on homocysteine-induced endothelial dysfunction

Hyperhomocysteinemia is an independent risk factor for the development of atherosclerosis. An increasing body of evidence has implicated oxidative stress as being contributory to homocysteines deleterious effects on the vasculature. Elevated levels of homocysteine may lead to increased generation of superoxide by a biochemical mechanism involving nitric oxide synthase, and, to a lesser extent, by an increase in the chemical oxidation of homocysteine and other aminothiols in the circulation. The resultant increase in superoxide levels is further amplified by homocysteinedependent alterations in the function of cellular antioxidant enzymes such as cellular glutathione peroxidase or extracellular superoxide dismutase. One direct clinical consequence of elevated vascular superoxide levels is the inactivation of the vasorelaxant messenger nitric oxide, leading to endothelial dysfunction. Scavenging of superoxide anion by either superoxide dismutase or 4,5-dihydroxybenzene 1,3-disulfonate (Tiron) reverses endothelial dysfunction in hyperhomocysteinemic animal models and in isolated aortic rings incubated with homocysteine. Similarly, homocysteineinduced endothelial dysfunction is also reversed by increasing the concentration of the endogenous antioxidant glutathione or overexpressing cellular glutathione peroxidase in animal models of mild hyperhomocysteinemia. Taken together, these findings strongly suggest that the adverse vascular effects of homocysteine are at least partly mediated by oxidative inactivation of nitric oxide

A two-year participatory intervention project with owners to reduce lameness and limb abnormalities in working horses in Jaipur, India

Participatory methods are increasingly used in international human development, but scientific evaluation of their efficacy versus a control group is rare. Working horses support families in impoverished communities. Lameness and limb abnormalities are highly prevalent in these animals and a cause for welfare concern. We aimed to stimulate and evaluate improvements in lameness and limb abnormalities in horses whose owners took part in a 2-year participatory intervention project to reduce lameness (PI) versus a control group (C) in Jaipur, India.In total, 439 owners of 862 horses participated in the study. PI group owners from 21 communities were encouraged to meet regularly to discuss management and work practices influencing lameness and poor welfare and to track their own progress in improving these. Lameness examinations (41 parameters) were conducted at the start of the study (Baseline), and after 1 year and 2 years. Results were compared with control horses from a further 21 communities outside the intervention. Of the 149 horses assessed on all three occasions, PI horses showed significantly (P<0.05) greater improvement than C horses in 20 parameters, most notably overall lameness score, measures of sole pain and range of movement on limb flexion. Control horses showed slight but significantly greater improvements in four parameters, including frog quality in fore and hindlimbs.This participatory intervention succeeded in improving lameness and some limb abnormalities in working horses, by encouraging changes in management and work practices which were feasible within owners’ socioeconomic and environmental constraints. Demonstration of the potentially sustainable improvements achieved here should encourage further development of participatory intervention approaches to benefit humans and animals in other contexts

Efficient Utilization of Rare Variants for Detection of Disease-Related Genomic Regions

When testing association between rare variants and diseases, an efficient analytical approach involves considering a set of variants in a genomic region as the unit of analysis. One factor complicating this approach is that the vast majority of rare variants in practical applications are believed to represent background neutral variation. As a result, analyzing a single set with all variants may not represent a powerful approach. Here, we propose two alternative strategies. In the first, we analyze the subsets of rare variants exhaustively. In the second, we categorize variants selectively into two subsets: one in which variants are overrepresented in cases, and the other in which variants are overrepresented in controls. When the proportion of neutral variants is moderate to large we show, by simulations, that the both proposed strategies improve the statistical power over methods analyzing a single set with total variants. When applied to a real sequencing association study, the proposed methods consistently produce smaller p-values than their competitors. When applied to another real sequencing dataset to study the difference of rare allele distributions between ethnic populations, the proposed methods detect the overrepresentation of variants between the CHB (Chinese Han in Beijing) and YRI (Yoruba people of Ibadan) populations with small p-values. Additional analyses suggest that there is no difference between the CHB and CHD (Chinese Han in Denver) datasets, as expected. Finally, when applied to the CHB and JPT (Japanese people in Tokyo) populations, existing methods fail to detect any difference, while it is detected by the proposed methods in several regions

Comparison of Population-Based Association Study Methods Correcting for Population Stratification

Population stratification can cause spurious associations in population–based association studies. Several statistical methods have been proposed to reduce the impact of population stratification on population–based association studies. We simulated a set of stratified populations based on the real haplotype data from the HapMap ENCODE project, and compared the relative power, type I error rates, accuracy and positive prediction value of four prevailing population–based association study methods: traditional case-control tests, structured association (SA), genomic control (GC) and principal components analysis (PCA) under various population stratification levels. Additionally, we evaluated the effects of sample sizes and frequencies of disease susceptible allele on the performance of the four analytical methods in the presence of population stratification. We found that the performance of PCA was very stable under various scenarios. Our comparison results suggest that SA and PCA have comparable performance, if sufficient ancestral informative markers are used in SA analysis. GC appeared to be strongly conservative in significantly stratified populations. It may be better to apply GC in the stratified populations with low stratification level. Our study intends to provide a practical guideline for researchers to select proper study methods and make appropriate inference of the results in population-based association studies

Discovery of Rare Variants via Sequencing: Implications for the Design of Complex Trait Association Studies

There is strong evidence that rare variants are involved in complex disease etiology. The first step in implicating rare variants in disease etiology is their identification through sequencing in both randomly ascertained samples (e.g., the 1,000 Genomes Project) and samples ascertained according to disease status. We investigated to what extent rare variants will be observed across the genome and in candidate genes in randomly ascertained samples, the magnitude of variant enrichment in diseased individuals, and biases that can occur due to how variants are discovered. Although sequencing cases can enrich for casual variants, when a gene or genes are not involved in disease etiology, limiting variant discovery to cases can lead to association studies with dramatically inflated false positive rates

Presymptomatic risk assessment for chronic non-communicable diseases

The prevalence of common chronic non-communicable diseases (CNCDs) far overshadows the prevalence of both monogenic and infectious diseases combined. All CNCDs, also called complex genetic diseases, have a heritable genetic component that can be used for pre-symptomatic risk assessment. Common single nucleotide polymorphisms (SNPs) that tag risk haplotypes across the genome currently account for a non-trivial portion of the germ-line genetic risk and we will likely continue to identify the remaining missing heritability in the form of rare variants, copy number variants and epigenetic modifications. Here, we describe a novel measure for calculating the lifetime risk of a disease, called the genetic composite index (GCI), and demonstrate its predictive value as a clinical classifier. The GCI only considers summary statistics of the effects of genetic variation and hence does not require the results of large-scale studies simultaneously assessing multiple risk factors. Combining GCI scores with environmental risk information provides an additional tool for clinical decision-making. The GCI can be populated with heritable risk information of any type, and thus represents a framework for CNCD pre-symptomatic risk assessment that can be populated as additional risk information is identified through next-generation technologies.Comment: Plos ONE paper. Previous version was withdrawn to be updated by the journal's pdf versio

A Covering Method for Detecting Genetic Associations between Rare Variants and Common Phenotypes

Genome wide association (GWA) studies, which test for association between common genetic markers and a disease phenotype, have shown varying degrees of success. While many factors could potentially confound GWA studies, we focus on the possibility that multiple, rare variants (RVs) may act in concert to influence disease etiology. Here, we describe an algorithm for RV analysis, RARECOVER. The algorithm combines a disparate collection of RVs with low effect and modest penetrance. Further, it does not require the rare variants be adjacent in location. Extensive simulations over a range of assumed penetrance and population attributable risk (PAR) values illustrate the power of our approach over other published methods, including the collapsing and weighted-collapsing strategies. To showcase the method, we apply RARECOVER to re-sequencing data from a cohort of 289 individuals at the extremes of Body Mass Index distribution (NCT00263042). Individual samples were re-sequenced at two genes, FAAH and MGLL, known to be involved in endocannabinoid metabolism (187Kbp for 148 obese and 150 controls). The RARECOVER analysis identifies exactly one significantly associated region in each gene, each about 5 Kbp in the upstream regulatory regions. The data suggests that the RVs help disrupt the expression of the two genes, leading to lowered metabolism of the corresponding cannabinoids. Overall, our results point to the power of including RVs in measuring genetic associations.National Science Foundation (U.S.) (grant (IIS-0810905)National Institutes of Health (U.S.) (U19 AG023122-05)National Institutes of Health (U.S.) (R01 MH078151-03)Louis & Harold Price FoundationNational Institutes of Health (U.S.) (N01 MH22005)National Institutes of Health (U.S.) (U01-DA024417-01)National Institutes of Health (U.S.) (P50 MH081755-01)National Institutes of Health (U.S.) (R01 AG030474-02)National Institutes of Health (U.S.) (N01 MH022005)National Institutes of Health (U.S.) (R01 HL089655-02)National Institutes of Health (U.S.) (R01 MH080134-03)National Institutes of Health (U.S.) (U54 CA143906-01)National Institutes of Health (U.S.) (UL1 RR025774-03)Scripps Genomic Medicine ProgramNational Human Genome Research Institute (U.S.) (Grant Number T32 HG002295