Does habitat stability structure intraspecific genetic diversity? It’s complicated...

Regional phylogeographic studies have long been conducted in the southeastern United States for a variety of species. With some exceptions, many of these studies focus on single species or single clades of organisms, and those considering multiple species tend to focus on deep historical breaks causing differentiation. However, in many species more recent factors may be influencing genetic diversity. To understand the roles of historic and contemporary processes in structuring genetic diversity, we reanalyzed existing genetic data from Southeast of North America using approaches gleaned from phylogeographic and landscape genetic literature that were implemented across species including AMOVAs, PCoAs, Species Distribution Modelling, and tests of isolation by distance, environment, and habitat instability. Genetic variance was significantly partitioned by ecoregions, watersheds, and across phylogeographic breaks in the majority of species. Similarly, genetic variation was significantly associated with some combination of geographic or environmental distance or habitat instability in most species. Patterns of genetic variation were largely idiosyncratic across species. While habitat instability over time is significantly correlated with genetic diversity in some species, it appears generally less important than isolation by geographic or environmental distance. Our results suggest that many factors, both historical and contemporary, impact genetic diversity within a species, and more so, that these patterns aren’t always similar in closely related species. This supports the importance of species- specific factors and cautions against assumptions that closely related species will respond to historical and contemporary forces in similar ways

Does accreditation stimulate change? A study of the impact of the accreditation process on Canadian healthcare organizations

<p>Abstract</p> <p>Background</p> <p>One way to improve quality and safety in healthcare organizations (HCOs) is through accreditation. Accreditation is a rigorous external evaluation process that comprises self-assessment against a given set of standards, an on-site survey followed by a report with or without recommendations, and the award or refusal of accreditation status. This study evaluates how the accreditation process helps introduce organizational changes that enhance the quality and safety of care.</p> <p>Methods</p> <p>We used an embedded multiple case study design to explore organizational characteristics and identify changes linked to the accreditation process. We employed a theoretical framework to analyze various elements and for each case, we interviewed top managers, conducted focus groups with staff directly involved in the accreditation process, and analyzed self-assessment reports, accreditation reports and other case-related documents.</p> <p>Results</p> <p>The context in which accreditation took place, including the organizational context, influenced the type of change dynamics that occurred in HCOs. Furthermore, while accreditation itself was not necessarily the element that initiated change, the accreditation process was a highly effective tool for (i) accelerating integration and stimulating a spirit of cooperation in newly merged HCOs; (ii) helping to introduce continuous quality improvement programs to newly accredited or not-yet-accredited organizations; (iii) creating new leadership for quality improvement initiatives; (iv) increasing social capital by giving staff the opportunity to develop relationships; and (v) fostering links between HCOs and other stakeholders. The study also found that HCOs' motivation to introduce accreditation-related changes dwindled over time.</p> <p>Conclusions</p> <p>We conclude that the accreditation process is an effective leitmotiv for the introduction of change but is nonetheless subject to a learning cycle and a learning curve. Institutions invest greatly to conform to the first accreditation visit and reap the greatest benefits in the next three accreditation cycles (3 to 10 years after initial accreditation). After 10 years, however, institutions begin to find accreditation less challenging. To maximize the benefits of the accreditation process, HCOs and accrediting bodies must seek ways to take full advantage of each stage of the accreditation process over time.</p

Effects of fluoxetine on functional outcomes after acute stroke (FOCUS): a pragmatic, double-blind, randomised, controlled trial

Background Results of small trials indicate that fluoxetine might improve functional outcomes after stroke. The FOCUS trial aimed to provide a precise estimate of these effects. Methods FOCUS was a pragmatic, multicentre, parallel group, double-blind, randomised, placebo-controlled trial done at 103 hospitals in the UK. Patients were eligible if they were aged 18 years or older, had a clinical stroke diagnosis, were enrolled and randomly assigned between 2 days and 15 days after onset, and had focal neurological deficits. Patients were randomly allocated fluoxetine 20 mg or matching placebo orally once daily for 6 months via a web-based system by use of a minimisation algorithm. The primary outcome was functional status, measured with the modified Rankin Scale (mRS), at 6 months. Patients, carers, health-care staff, and the trial team were masked to treatment allocation. Functional status was assessed at 6 months and 12 months after randomisation. Patients were analysed according to their treatment allocation. This trial is registered with the ISRCTN registry, number ISRCTN83290762. Findings Between Sept 10, 2012, and March 31, 2017, 3127 patients were recruited. 1564 patients were allocated fluoxetine and 1563 allocated placebo. mRS data at 6 months were available for 1553 (99·3%) patients in each treatment group. The distribution across mRS categories at 6 months was similar in the fluoxetine and placebo groups (common odds ratio adjusted for minimisation variables 0·951 [95% CI 0·839–1·079]; p=0·439). Patients allocated fluoxetine were less likely than those allocated placebo to develop new depression by 6 months (210 [13·43%] patients vs 269 [17·21%]; difference 3·78% [95% CI 1·26–6·30]; p=0·0033), but they had more bone fractures (45 [2·88%] vs 23 [1·47%]; difference 1·41% [95% CI 0·38–2·43]; p=0·0070). There were no significant differences in any other event at 6 or 12 months. Interpretation Fluoxetine 20 mg given daily for 6 months after acute stroke does not seem to improve functional outcomes. Although the treatment reduced the occurrence of depression, it increased the frequency of bone fractures. These results do not support the routine use of fluoxetine either for the prevention of post-stroke depression or to promote recovery of function. Funding UK Stroke Association and NIHR Health Technology Assessment Programme

Complete mitochondrial genome of the water vole, Microtus richardsoni (Cricetidae, Rodentia)

Water voles (Microtus richardsoni) are sensitive species distributed in the mountains of Canada (Alberta, British Columbia), and the United States of America (Idaho, Montana, Oregon, Utah, Washington, and Wyoming). We assembled the complete circular M. richardsoni mitogenome, which is 16,285 bp in length and encodes 13 protein-coding genes, 22 tRNA genes, and two rRNA genes. We estimated the phylogenetic tree of M. richardsoni and 24 related arvicoline species with two outgroup species: Phodopus roborovskii and Cricetus cricetus

Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses.

When designing phylogeographic investigations researchers can choose to collect many different types of molecular markers, including mitochondrial genes or genomes, SNPs from reduced representation protocols, large sequence capture data sets, and even whole genomes. Given that the statistical power and accuracy of various analyses are expected to differ depending on both the type of marker and the amount of data collected, an exploration of the variance across methodological results as a function of marker type should provide valuable information to researchers. Here we collect mitochondrial Cytochrome b sequences, whole mitochondrial genomes, single nucleotide polymorphisms (SNP)s isolated using a genotype by sequencing (GBS) protocol, sequences from ultraconserved elements, and low-coverage nuclear genomes from the North American water vole (Microtus richardsoni). We estimate genetic distances, population genetic structure, and historical demography using data from each of these datasets and compare the results across markers. As anticipated, the results exhibit differences across marker types, particularly in terms of the resolution offered by different analyses. A cost-benefit analysis indicates that SNPs collected using a GBS protocol are the most cost-effective molecular marker, with inferences that mirror those collected from the whole genome data at a fraction of the cost per sample

CM_144samples_MQ40_BQ20_ref200bpNs_exons+introns_12_C50_DP6_SP13_NA0_noMonomorphicSNPs_notriallelic_tag11_dryad.vcf

Vcf file containing fenotype calls for 144 samples after filtering

cl_cf_co_na_C50_DP6_SP13_merge_144CM.vcf

VCF file containing genotype calls for 144 samples (C. melanopterus) and 4 outgroups as described in the readme file

Data from: Demographic inferences after a range expansion can be biased: the test case of the blacktip reef shark (Carcharhinus melanopterus)

The evolutionary history of species is a dynamic process as they modify, expand and contract their spatial distributions over time. Range expansions (REs) occur through a series of founder events that are followed by migration among neighbouring demes. The process usually results in structured metapopulations and leaves a distinct signature in the genetic variability of species. Explicitly modeling the consequences of complex demographic events such as REs is computationally very intensive. Here we propose an an alternative approach that requires less computational effort than a comprehensive RE model, but that can recover the demography of species undergoing a RE, by combining spatially explicit modelling with simplified but realistic metapopulation models. We examine the demographic and colonization history of Carcharhinus melanopterus, an abundant reef-associated shark, as a test case. We first used a population genomics approach to statistically confirm the occurrence of a RE in C. melanopterus and identify its origin in the Indo-Australian Archipelago. Spatial genetic modelling identified two waves of stepping-stone colonization: an eastward wave moving through the Pacific and a westward one moving through the Indian Ocean. We show that metapopulation models best describe the demographic history of this species and that not accounting for this may lead to incorrectly interpreting the observed genetic variation as signals of widespread population bottlenecks. Our study highlights insights that can be gained about demography by coupling metapopulation models with spatial modeling and underscores the need for cautious interpretation of population genetic data when advancing conservation priorities

Assessing model adequacy for Bayesian Skyline plots using posterior predictive simulation

Bayesian skyline plots (BSPs) are a useful tool for making inferences about demographic history. For example, researchers typically apply BSPs to test hypotheses regarding how climate changes have influenced intraspecific genetic diversity over time. Like any method, BSP has assumptions that may be violated in some empirical systems (e.g., the absence of population genetic structure), and the naïve analysis of data collected from these systems may lead to spurious results. To address these issues, we introduce P2C2M.Skyline, an R package designed to assess model adequacy for BSPs using posterior predictive simulation. P2C2M.Skyline uses a phylogenetic tree and the log file output from Bayesian Skyline analyses to simulate posterior predictive datasets and then compares this null distribution to statistics calculated from the empirical data to check for model violations. P2C2M.Skyline was able to correctly identify model violations when simulated datasets were generated assuming genetic structure, which is a clear violation of BSP model assumptions. Conversely, P2C2M.Skyline showed low rates of false positives when models were simulated under the BSP model. We also evaluate the P2C2M.Skyline performance in empirical systems, where we detected model violations when DNA sequences from multiple populations were lumped together. P2C2M.Skyline represents a user-friendly and computationally efficient resource for researchers aiming to make inferences from BSP