The effectiveness of flower strips and hedgerows on pest control,pollination services and crop yield: a quantitative synthesis

Floral plantings are promoted to foster ecological intensification of agriculture through provisioning of ecosystem services. However, a comprehensive assessment of the effectiveness of different floral plantings, their characteristics and consequences for crop yield is lacking. Here we quantified the impacts of flower strips and hedgerows on pest control (18 studies) and pollination services (17 studies) in adjacent crops in North America, Europe and New Zealand. Flower strips, but not hedgerows, enhanced pest control services in adjacent fields by 16% on average. However, effects on crop pollination and yield were more variable. Our synthesis identifies several important drivers of variability in effectiveness of plantings: pollination services declined exponentially with distance from plantings, and perennial and older flower strips with higher flowering plant diversity enhanced pollination more effectively. These findings provide promising pathways to optimise floral plantings to more effectively contribute to ecosystem service delivery and ecological intensification of agriculture in the future.     

Sampling strategy optimization to increase statistical power in landscape genomics: A simulation‐based approach

An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. Implementation of this approach requires the sampling phase to consider the complexity of environmental settings and the burden of logistical constraints. These important aspects are often underestimated in the literature dedicated to sampling strategies. In this study, we computed simulated genomic data sets to run against actual environmental data in order to trial landscape genomics experiments under distinct sampling strategies. These strategies differed by design approach (to enhance environmental and/or geographical representativeness at study sites), number of sampling locations and sample sizes. We then evaluated how these elements affected statistical performances (power and false discoveries) under two antithetical demographic scenarios. Our results highlight the importance of selecting an appropriate sample size, which should be modified based on the demographic characteristics of the studied population. For species with limited dispersal, sample sizes above 200 units are generally sufficient to detect most adaptive signals, while in random mating populations this threshold should be increased to 400 units. Furthermore, we describe a design approach that maximizes both environmental and geographical representativeness of sampling sites and show how it systematically outperforms random or regular sampling schemes. Finally, we show that although having more sampling locations (between 40 and 50 sites) increase statistical power and reduce false discovery rate, similar results can be achieved with a moderate number of sites (20 sites). Overall, this study provides valuable guidelines for optimizing sampling strategies for landscape genomics experiments.     

Canadian polar bear population structure using genome‐wide markers

Predicting the consequences of environmental changes, including human‐mediated climate change on species, requires that we quantify range‐wide patterns of genetic diversity and identify the ecological, environmental, and historical factors that have contributed to it. Here, we generate baseline data on polar bear population structure across most Canadian subpopulations (n = 358) using 13,488 genome‐wide single nucleotide polymorphisms (SNPs) identified with double‐digest restriction site‐associated DNA sequencing (ddRAD). Our ddRAD dataset showed three genetic clusters in the sampled Canadian range, congruent with previous studies based on microsatellites across the same regions; however, due to a lack of sampling in Norwegian Bay, we were unable to confirm the existence of a unique cluster in that subpopulation. These data on the genetic structure of polar bears using SNPs provide a detailed baseline against which future shifts in population structure can be assessed, and opportunities to develop new noninvasive tools for monitoring polar bears across their range.     

Benchmarking and optimization of a high-throughput sequencing based method for transgene sequence variant analysis in biotherapeutic cell line development

In recent years, High-Throughput Sequencing (HTS) based methods to detect mutations in biotherapeutic transgene products have become a key quality step deployed during the development of manufacturing cell line clones. Previously we reported on a higher throughput, rapid mutation detection method based on amplicon sequencing (targeting transgene RNA) and detailed its implementation to facilitate cell line clone selection. By gaining experience with our assay in a diverse set of cell line development programs, we improved the computational analysis as well as experimental protocols. Here we report on these improvements as well as on a comprehensive benchmarking of our assay. We evaluated assay performance by mixing amplicon samples of a verified mutated antibody clone with a non-mutated antibody clone to generate spike-in mutations from ∼60% down to ∼0.3% frequencies. We subsequently tested the effect of 16 different sample and HTS library preparation protocols on the assay's ability to quantify mutations and on the occurrence of false-positive background error mutations (artifacts). Our evaluation confirmed assay robustness, established a high confidence limit of detection of ∼0.6%, and identified protocols that reduce error levels thereby significantly reducing a source of false positives that bottlenecked the identification of low-level true mutations.     

Association of FcRn Heavy Chain Encoding Gene (FCGRT) Polymorphisms with IgG Content in Bovine Colostrum

In this study, we evaluated haplotypes of the bovine FCGRT (encoding the FcRn heavy chain) and their relationship to the IgG concentration in bovine colostrum. Four single nucleotide polymorphism (SNP), classified into five haplotypes, were identified in a total of 49 Holstein-Frisians cows. Haplotype 5 was found to be significantly associated with a high IgG level ([OR] = 9.90, 95%CI = 1.11–88.34, p = 0.016) and haplotype 2 exhibited a similar trend ([OR] = 2.89, 95%CI = 1.17–7.11, p = 0.019).     

Nighttime Sugar Starvation Orchestrates Gibberellin Biosynthesis and Plant Growth in Arabidopsis

A plant’s eventual size depends on the integration of its genetic program with environmental cues, which vary on a daily basis. Both efficient carbon metabolism and the plant hormone gibberellin are required to guarantee optimal plant growth. Yet, little is known about the interplay between carbon metabolism and gibberellins that modulates plant growth. Here, we show that sugar starvation in Arabidopsis thaliana arising from inefficient starch metabolism at night strongly reduces the expression of ent-kaurene synthase, a key regulatory enzyme for gibberellin synthesis, the following day. Our results demonstrate that plants integrate the efficiency of photosynthesis over a period of days, which is transduced into a daily rate of gibberellin biosynthesis. This enables a plant to grow to a size that is compatible with its environment.     

Pre-Eclampsia Increases the Risk of Postpartum Haemorrhage: A Nationwide Cohort Study in The Netherlands

Background

Postpartum haemorrhage is a leading cause of maternal morbidity and mortality worldwide. Identifying risk indicators for postpartum haemorrhage is crucial to predict this life threatening condition. Another major contributor to maternal morbidity and mortality is pre-eclampsia. Previous studies show conflicting results in the association between pre-eclampsia and postpartum haemorrhage. The primary objective of this study was to investigate the association between pre-eclampsia and postpartum haemorrhage. Our secondary objective was to identify other risk indicators for postpartum haemorrhage in the Netherlands.

Methods

A nationwide cohort was used, containing prospectively collected data of women giving birth after 19 completed weeks of gestation from January 2000 until January 2008 (n =  1 457 576). Data were extracted from the Netherlands Perinatal Registry, covering 96% of all deliveries in the Netherlands. The main outcome measure, postpartum haemorrhage, was defined as blood loss of ≥1000 ml in the 24 hours following delivery. The association between pre-eclampsia and postpartum haemorrhage was investigated with uni- and multivariable logistic regression analyses.

Results

Overall prevalence of postpartum haemorrhage was 4.3% and of pre-eclampsia 2.2%. From the 31 560 women with pre-eclampsia 2 347 (7.4%) developed postpartum haemorrhage, compared to 60 517 (4.2%) from the 1 426 016 women without pre-eclampsia (odds ratio 1.81; 95% CI 1.74 to 1.89). Risk of postpartum haemorrhage in women with pre-eclampsia remained increased after adjusting for confounders (adjusted odds ratio 1.53; 95% CI 1.46 to 1.60).

Conclusion

Women with pre-eclampsia have a 1.53 fold increased risk for postpartum haemorrhage. Clinicians should be aware of this and use this knowledge in the management of pre-eclampsia and the third stage of labour in order to reach the fifth Millenium Developmental Goal of reducing maternal mortality ratios with 75% by 2015.