The global loss of biodiversity continues at an alarming rate. Genomic approaches have been suggested as a promising tool for conservation practice, and we discuss how scaling-up to genome-wide inference can benefit traditional conservation genetic approaches and provide qualitatively novel insights. Yet, the generation of genomic data and subsequent analyses and interpretations are still challenging and largely confined to academic research in ecology and 20evolution. This generates a gap between basic research and applicable solutions for conservation managers faced with multifaceted problems. Before the real-world conservation potential of genomic research can be realized, we suggest that current infrastructures need to be modified, methods must mature, analytical pipelines need to be developed, and successful case studies must be disseminated to practitioners. 3 Conservation biology and genomicsLike most of the life sciences, conservation biology is being confronted with the challenge of how to integrate the collection and analysis of large-scale genomic data into its toolbox. Conservation biologists pull from a wide array of disciplines in an effort to preserve biodiversity and ecosystem services [1]. Genetic data have helped in this regard by 30 detecting, for example, population substructure, measuring genetic connectivity, and identifying potential risks associated with demographic change and inbreeding [2]. Traditionally, conservation genetics (see Glossary) has relied on a handful of molecular markers ranging from a few allozymes to dozens of microsatellites [3]. But for close to a decade [4], genomics -broadly defined high-throughput sampling of nucleic acids [5] -has been touted as an important advancement to the field, a panacea of sorts for the unresolved conservation problems typically addressed 35 with genetic data [6,7]. This transition has led to much promise, but also hyperbole, where concrete empirical examples of genomic data having a conservation impact remain rare.Under the premise that assisting conservation of the world's biota is its ultimate purpose, the emerging field of conservation genomics must openly and pragmatically discuss its potential contribution towards this goal. While there 40are prominent examples where genetic approaches have made inroads influencing conservation efforts (e.g., Florida panther augmentation [8,9]) and wildlife enforcement (i.e., detecting illegal harvest [10]), it is not immediately clear that the conservation community and society more broadly have embraced genomics as a useful tool for conservation.Maintaining genetic diversity has largely been an afterthought when it comes to national biodiversity policies [11,12], and attempts to identify areas that might prove to be essential for conserving biological diversity rarely mention 45 genomics (e.g. [13,14]). An obvious reason for this disconnect is that many of the pressing conservation issues (e.g., [15,16]) simply do not need genomics, but instead need political will.The traditional use of gene...

BackgroundMicrosatellite markers are widely used for estimating genetic diversity within and differentiation among populations. However, it has rarely been tested whether such estimates are useful proxies for genome-wide patterns of variation and differentiation. Here, we compared microsatellite variation with genome-wide single nucleotide polymorphisms (SNPs) to assess and quantify potential marker-specific biases and derive recommendations for future studies. Overall, we genotyped 180 Arabidopsis halleri individuals from nine populations using 20 microsatellite markers. Twelve of these markers were originally developed for Arabidopsis thaliana (cross-species markers) and eight for A. halleri (species-specific markers). We further characterized 2 million SNPs across the genome with a pooled whole-genome re-sequencing approach (Pool-Seq).ResultsOur analyses revealed that estimates of genetic diversity and differentiation derived from cross-species and species-specific microsatellites differed substantially and that expected microsatellite heterozygosity (SSR-H e) was not significantly correlated with genome-wide SNP diversity estimates (SNP-H e and θ Watterson) in A. halleri. Instead, microsatellite allelic richness (A r) was a better proxy for genome-wide SNP diversity. Estimates of genetic differentiation among populations (F ST) based on both marker types were correlated, but microsatellite-based estimates were significantly larger than those from SNPs. Possible causes include the limited number of microsatellite markers used, marker ascertainment bias, as well as the high variance in microsatellite-derived estimates. In contrast, genome-wide SNP data provided unbiased estimates of genetic diversity independent of whether genome- or only exome-wide SNPs were used. Further, we inferred that a few thousand random SNPs are sufficient to reliably estimate genome-wide diversity and to distinguish among populations differing in genetic variation.ConclusionsWe recommend that future analyses of genetic diversity within and differentiation among populations use randomly selected high-throughput sequencing-based SNP data to draw conclusions on genome-wide diversity patterns. In species comparable to A. halleri, a few thousand SNPs are sufficient to achieve this goal.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3459-7) contains supplementary material, which is available to authorized users.

Objective To examine the effect of optimising drug treatment on drug related hospital admissions in older adults with multimorbidity and polypharmacy admitted to hospital. Design Cluster randomised controlled trial. Setting 110 clusters of inpatient wards within university based hospitals in four European countries (Switzerland, Netherlands, Belgium, and Republic of Ireland) defined by attending hospital doctors. Participants 2008 older adults (≥70 years) with multimorbidity (≥3 chronic conditions) and polypharmacy (≥5 drugs used long term). Intervention Clinical staff clusters were randomised to usual care or a structured pharmacotherapy optimisation intervention performed at the individual level jointly by a doctor and a pharmacist, with the support of a clinical decision software system deploying the screening tool of older person’s prescriptions and screening tool to alert to the right treatment (STOPP/START) criteria to identify potentially inappropriate prescribing. Main outcome measure Primary outcome was first drug related hospital admission within 12 months. Results 2008 older adults (median nine drugs) were randomised and enrolled in 54 intervention clusters (963 participants) and 56 control clusters (1045 participants) receiving usual care. In the intervention arm, 86.1% of participants (n=789) had inappropriate prescribing, with a mean of 2.75 (SD 2.24) STOPP/START recommendations for each participant. 62.2% (n=491) had ≥1 recommendation successfully implemented at two months, predominantly discontinuation of potentially inappropriate drugs. In the intervention group, 211 participants (21.9%) experienced a first drug related hospital admission compared with 234 (22.4%) in the control group. In the intention-to-treat analysis censored for death as competing event (n=375, 18.7%), the hazard ratio for first drug related hospital admission was 0.95 (95% confidence interval 0.77 to 1.17). In the per protocol analysis, the hazard ratio for a drug related hospital admission was 0.91 (0.69 to 1.19). The hazard ratio for first fall was 0.96 (0.79 to 1.15; 237 v 263 first falls) and for death was 0.90 (0.71 to 1.13; 172 v 203 deaths). Conclusions Inappropriate prescribing was common in older adults with multimorbidity and polypharmacy admitted to hospital and was reduced through an intervention to optimise pharmacotherapy, but without effect on drug related hospital admissions. Additional efforts are needed to identify pharmacotherapy optimisation interventions that reduce inappropriate prescribing and improve patient outcomes. Trial registration ClinicalTrials.gov NCT02986425 .

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SummaryThe evolution of crop-related weeds may be constrained by recurrent gene flow from the crop. However, flowering time variation within weedy populations may open the way for weed adaptation by allowing some weeds to escape from this constraint. We investigated this link between phenology, gene flow and adaptation in weedy sunflower populations that have recently emerged in Europe from crop-wild hybridization.We studied jointly flowering phenology and genetic diversity for 15 microsatellite loci in six cultivated sunflower (Helianthus annuus) fields infested by weedy sunflower populations.The flowering overlap of cultivated and weedy sunflowers varied between and within populations: some weedy individuals were found to be completely isolated from the crop, the frequency of these plants being higher in populations from highly infested fields. Within weedy populations, we detected a pattern of isolation-by-time: the genetic divergence between individuals was positively correlated with their divergence in flowering period. In addition, earlier weeds, which flowered synchronously with the crop, were genetically more similar than lateflowering weeds to the cultivated varieties.Overall, our results suggest that crop-to-weed gene flow occurred, but was limited by divergent phenologies. We discuss the roles of weed adaptation and population history in the generation of this partial reproductive isolation.