Respiratory disease accounts for three of the ten leading causes of death worldwide. Many of these diseases can be treated and diagnosed using a nebulizer. Nebulizers can also be used to safely and efficiently deliver vaccines. Unfortunately, commercially available nebulizers are not designed for use in regions of the world where lung disease is most prevalent: they are electricity-dependent, cost-prohibitive, and not built to be reliable in harsh operating conditions or under frequent use.To overcome these limitations, the Human Powered Nebulizer compressor (HPN) was developed. The HPN does not require electricity; instead airflow is generated manually through a hand-crank or bicycle-style pedal system. A health care worker or other trained individual operates the device while the patient receives treatment.This study demonstrates functional specifications of the HPN in comparison with a standard commercially available electric jet nebulizer compressor, the DeVilbiss Pulmo-Aide 5650D (Pulmo-Aide).Pressure and flow characteristics were measured with a rotameter and pressure transducer, respectively. Volume nebulized by each compressor was determined by mass, and particle size distribution was determined via laser diffraction. The Hudson RCI Micro Mist nebulizer mouthpiece was used with both compressors.The pressure and flow generated by the HPN and Pulmo-Aide were: 15.17 psi and 10.5 L/min; and 14.65 psi and 11.2 L/min, respectively. The volume of liquid delivered by each was equivalent, 1.097 ± 0.107 mL  for the HPN and 1.092 ± 0.116 mL for the Pulmo-Aide. The average particle size was also equivalent, 5.38 ± 0.040 micrometers  and 5.40 ± 0.025 micrometers, respectively.Based on these characteristics, the HPN’s performance is equivalent to a popular commercially available electric nebulizer compressor. The findings presented in this paper, combined with the results of two published clinical studies, suggest that the HPN could serve as an important diagnostic and therapeutic tool in the fight against global respiratory health challenges including: tuberculosis, chronic obstructive pulmonary disease, asthma, and lower respiratory infections. Respiratory disease is a leading cause of death worldwide. According to the World Health Organization, lower respiratory infections (LRIs), chronic obstructive pulmonary disease (COPD), and tuberculosis (TB) are major causes of mortality, ranking 3rd, 4th, and 11th respectively, killing 3.2, 3 and 1 million persons in 2011 [At first glance, these three diseases share only the organ they impact. Etiology, diagnosis, treatment, and prevention strategies for these conditions are diverse in nature and technology. In addition to being diseases of the lung, they do share the populations they impact, namely the poor throughout low and middle-income countries, particularly in regions without access to primary health care. Many facets of poverty augment the incidence and mortality of these conditions. Health care for the poor is confounded by a lack of infrastructure and a dearth of healthcare providers. These factors suggest a need for a simple, appropriate solution, ideally a single technology platform that can address all these diseases.Direct delivery of therapeutics to the lung tissue has long been a successful strategy . InhaledNebulizers have been used widely as well . They haEach of these delivery technologies has advantages and disadvantages. MDIs are small and portable, but their effectiveness has been questioned because of problems in patient inhaler technique and the need for frequent re-training ,16. ThisThe nebulizer, however, could provide a single platform for diagnosing TB, treating COPD and LRIs, and delivering vaccines. Jet nebulizers have several distinct advantages over other aerosolized technologies: improved patient compliance, less patient training, and potentially lower per-treatment costs. Jet nebulizers have the benefit of being less likely to denature the therapeutics they deliver, in contrast to ultrasonic nebulizers ,19.With respect to DPIs and MDIs, nebulizers have the ability to deliver substantial volumes of liquid treatments. The chief drawback of nebulizers is that they are less portable. Ultrasonic and vibrating mesh nebulizers are portable, but they are more expensive, have components that require more frequent replacement, and are not intended for continuous use, such as a clinical setting . In otheA key limitation of jet nebulizers in developing contexts is that they require significant amounts of electric power, on the order of 100 W. Regions where electricity is non-existent or unreliable experience increased incidence of respiratory diseases, for example, those caused by indoor air pollution ,21. UltrThe Human Powered Nebulizer (HPN) was invented to address this problem. The HPN is a manual compressor that works with existing, inexpensive nebulizer mouthpieces. The purpose of this study was to compare the performance of the HPN to an electric nebulizer compressor on key performance measures: volume delivery, pressure and flow characteristics, and delivered particle size distribution. The present study complements two published clinical trials that have demonstrated equivalence between the HPN and an electric nebulizer for the production of sputum samples for TB diagnosis  and for Key to the administration of liquid medication deep into the lungs is the particle size distribution of aerosol particles coming from the nebulizer. A range of 1–5 microns in particle diameter has been suggested as maximizing deposition deep into the lungs . The nebThe basic design of the HPN creates airflow and pressure using pistons, model 042-DXPE  that are driven by human power. In our designs, dual-action pistons were used so that airflow would be generated during the entire piston cycle. The configuration for the airflow system is shown in Figure Each piston has two inlet/outlets. A tee is connected to each inlet/outlet. On one end of the tee is a one-way valve, model 64048  directed inward so that air can flow into the piston. The other end of the tee is connected to a one-way valve directed outward so that air can flow from the piston to the nebulizer mouthpiece. Connections were made with Tygon® tubing, model 5114 K54 . This outlet flow was directed through a flow regulator, model Y1-4 NPT . The outflow from the flow regulator was then delivered to the nebulizer mouthpiece via the tubing supplied by the mouthpiece manufacturer. In order to generate the requisite flow rate using human power with the aforementioned pistons, gearing systems were selected to achieve an effective frequency of piston operation with minimal human exertion.Two HPN designs were studied: a bicycle-based pedal version using one dual-action piston, the functional equivalent of two pistons, and a hand-cranked version using two dual-action pistons, the functional equivalent of four effective pistons. See Figures The bicycle version uses a standard bottom bracket pedal combination, gears and a chain connected to a modified bicycle frame that has been welded so as to secure the pistons in a stationary position. The length of the pedal crank was 18 cm, attached to a 36-tooth gear which drove a 13-tooth gear attached to a modified wheel hub, for a gear ratio of approximately 1:3 – every full turn of the pedal generated 3 piston strokes. A 5 cm plate was attached to the hub, and connected to the piston with a pin. This limited the travel of the piston, i.e., the effective lever arm on the piston, to 10 cm.The hand-cranked version uses a direct gear system, with a 22 cm long handle connected to a two-gear system, models S1VS24-100 F1524 and S1VS24-025 F1516 . The gears were connected to a custom-built crankshaft which then connected to the pistons. The gear ratio in this version was 1:4. For both the bicycle and hand cranked version, the force needed to operate the HPN was approximately 18 N, the equivalent energy expenditure required to pedal a bicycle at approximately 8 miles/hour.In all comparison studies in this work, the HPN was compared to a DeVilbiss Pulmo-Aide 5650D compressor . The nebulizer mouthpiece used was the Hudson RCI Micro Mist . All experiments were conducted between 20 – 24°C at relative humidity between 50 and 60%.Two configurations were used for measuring pressure and flow. In the first configuration, airflow was measured using a variable area rotameter, model MR3000-30 lpm  without the nebulizer mouthpiece in place. The outflow of the rotameter was open to atmospheric pressure. The output of the nebulizer compressors was connected to the rotameter with Tygon tubing. In the second configuration, upstream pressure was measured using a pressure transducer, model PX139-03004 V  with output pressure range between 0 and 30 psi. The pressure transducer output was collected using an A/D converter, model NI USB-6008  and stored on a computer. Pressure was measured both with and without the nebulizer mouthpiece downstream in the airflow circuit. The nebulizer mouthpiece was connected to the nebulizer compressor with a 120 cm length of Tygon tubing. The tubing was cut half the distance between the mouthpiece and the compressor and a plastic tee was inserted. The third branch of the tee was connected to the pressure transducer with a 15 cm piece of Tygon tubing.For these experiments, 5 mL of water was placed in the nebulizer mouthpiece cup and weighed. The nebulizer compressor under test was operated for 5 minutes. The mouthpiece was held stationary, in a vertical position, for the duration of the test. After the operating period, the nebulizer mouthpiece was weighed again and the difference in mass and, thus, volume was recorded.Particle size distribution was measured using the hand-crank HPN design and the DeVilbiss compressor with a Malvern Mastersizer S laser diffraction particle size analyzer . The output of the Micro Mist nebulizer mouthpiece was positioned 2.5 cm from the laser beam of the Mastersizer. The outflow of the mouthpiece was oriented vertically so that the narrowest part of the mist interacted with the laser light. Without the force of a patient’s inspiratory flow, the output of the nebulizer mouthpiece formed a swirling cloud of particles near the output of the mouthpiece of the device. To accurately determine particle size, air from a tank was passed through one end of the mouthpiece at 15 L/min to propagate the mist across the laser path. Particle size was determined with both 2.5 and 5 mL volumes of normal saline in each of the mouthpieces to determine the effect of fill volume on particle distribution. Particle size distribution using either the HPN or the DeVilbiss compressor was recorded. The Mastersizer reports droplet size in volume median (Dv0.5) values: the diameter of the delivered particle at which 50% is smaller than the indicated size. Dv0.5 can be assumed to be equivalent to the mean mass aerodynamic diameter (MMAD) determined by cascade impactor particle sizing if the density of particles is constant across the particle distribution, as is the case in this study. For ease of comparison to other values in the literature, particle size will be reported as MMAD.The volume nebulized during a five minute period for the HPN and Pulmo-Aide was: 1.097 ± 0.107 mL , and 1.092 ± 0.116 mL, respectively. Average pressure sampled over four seconds for the HPN and Pulmo-Aide was: 15.17 ± 0.010 psi (mean ± s.e.m) and 14.65 ± 0.001 psi, respectively. Figure Shown in Table The idea of a nebulizer designed for rural or remote regions is not new. The classic Mexican device for aerosolized vaccine delivery is perhaps the best known . One phyThe goal of the HPN project and of this study was to design a nebulizer compressor that was low cost. The project also aimed to develop a device that conformed to a commonly-used commercially available electric model with typical output characteristics. The hypothesis of the study presented here was that the HPN would perform equivalent to a commercially available electric nebulizer compressor, and the evidence from this study consistently supports that hypothesis. Based on the data presented here, the HPN performs equivalently to the Pulmo-Aide, which was selected for comparison in our study because it is a commonly used, well characterized, compressor model.The small differences in flow and pressure values are well within range of other commercially available nebulizer compressors. Smith et al. presented a performance comparison of 23 different models of jet nebulizer compressors . In thisTo design and build a low-cost nebulizer compressor that provides performance equivalent to the best available devices, but does not require electricity—and would be operated by human effort—levied additional design constraints for performance including operational feedback, user effort, and user perception. Yet performance criteria are not the only considerations relevant to the development and assessment of a device like the HPN; additional design parameters for developing contexts must include considerations of device implementation.Respiratory disease remains a leading cause of death and disability in low and middle income countries. Nebulizers are essential tools in the management and diagnosis of respiratory pathology but their use has been limited to areas with access to electricity. The reported data suggest that the HPN’s performance is equivalent to a popular commercially available electric nebulizer compressor. Consequently, the HPN could serve as an important diagnostic and therapeutic tool in the fight against global respiratory health challenges including: chronic obstructive pulmonary disease, asthma, tuberculosis and lower respiratory infections.The authors declare that they have no competing interests.CJH: conceived of the study, participated in the design of the study, drafted manuscript, performed data collection. MTL: conceived of the study, participated in the design of the study, drafted manuscript, performed data collection. CEZ: participated in the design of the particle sizing studies. WKK: participated in the design of the particle sizing studies. LEO: conceived of the study, participated in the design of the study, drafted manuscript, performed data collection. All authors read and approved the final manuscript.


Notochthamalus scabrosus has revealed two evolutionarily distinct lineages with a joint distribution that suggests an association with one of the two major biogeographic boundaries (~30°S) along the coast of Chile. However, spatial and genomic sampling of this system has been limited until now. We hypothesized that given the strong oceanographic and environmental shifts associated with the other major biogeographic boundary (~42°S) for Chilean coastal invertebrates, the southern mitochondrial lineage would dominate or go to fixation in locations further to the south. We also evaluated nuclear polymorphism data from 130 single nucleotide polymorphisms to evaluate the concordance of the signal from the nuclear genome with that of the mitochondrial sample. Through the application of standard population genetic approaches along with a Lagrangian ocean connectivity model, we describe the codistribution of these lineages through a simultaneous evaluation of coastal lineage frequencies, an approximation of larval behavior, and current‐driven dispersal. Our results show that this pattern could not persist without the two lineages having distinct environmental optima. We suggest that a more thorough integration of larval dynamics, explicit dispersal models, and near‐shore environmental analysis can explain much of the coastal biogeography of Chile.Dispersal and adaptation are the two primary mechanisms that set the range distributions for a population or species. As such, understanding how these mechanisms interact in marine organisms in particular – with capacity for long‐range dispersal and a poor understanding of what selective environments species are responding to – can provide useful insights for the exploration of biogeographic patterns. Previously, the barnacle  Classically, the fact that marine taxa live in an “open” environment with few apparent barriers to dispersal has been presented as a paradox Palumbi : “How doFor example, the physical processes of transport at Point Conception, near Santa Barbara, California, include strong coastal currents and eddies that appear to limit the northward dispersal of marine larvae across this geographic feature  in N. scabrosus, a northern lineage found throughout the domain of the ZL studies (between 18°–40°S) and a southern lineage found only south of 30°S.Previous work in the chthamalid barnacle s Darwin  has shows Darwin  [ZL heres Darwin , with ass Darwin . These bs Darwin , indicatUnderstanding the maintenance of these related distributions entails the integration of larval ecology, physical transport, and the potential for lineages to be adapted to distinct environments across this domain. We have shown previously , to Ushuaia, Argentina (54.1°S), almost the entire species range  could suggest isolation‐by‐distance or as‐yet unrecognized population structure across the larger domain sampled in this study. Each population structure value (k) was explored with five replicate random‐seed analyses with 25,000 steps for statistical burn‐in and 250,000 steps for inference using an admixture model without location as prior. This approach was repeated under a no‐admixture model for contrast. Results were used to establish the most informative value of k using the delta‐k method  was chosen using Ward's clustering method based on BIC summary statistics (the “diffNgroup” selection criterion). Conclusions about population structure were weighted toward the values of k obtained by both analytical approaches. To evaluate the sensitivity of individual assignment to one of k clusters, the DAPC results are used.Genetically divergent clusters can also be identified using discriminant analysis of principal components . The correspondence between mitotype and inferred nuclear genome identity is strongly correlated , AGRIF version  and is a step function of latitude assuming dominance of lineage type, in the respective extremes of the domain. The difference between lineages is Δw that minimizes the mismatch between observation and data. The model is run for two sets of frequencies: the frequency at a location of the northern mitochondrial lineage and the frequency at a location of the individuals inferred to be northern based on SNP data. In the latter case, the mean assignment probability of individuals at that location is counted and used to represent the frequency of northern diversity.The model is run until the distribution of northern and southern lineages reaches a steady state, and a cost function is calculated as the squared difference in relative frequency between the model predictions and observed lineage frequencies. At each latitude, Powell's method  relative to the assumptions based on neutrality and allele frequency. Of these, eight exhibited significantly low Gst values . Of the remaining “high” Gst markers (n = 11), the range of Gst values across all sites was 0.228–0.458.All nuclear SNP data were evaluated for statistical behavior consistent with selection. Outlier analysis using BayeScan identified 19 loci with extraordinary statistical structure  and cytonuclear disequilibrium . In addition, these SNPs were within the top 15% of alleles contributing to the genetic divergence, as assessed during the DAPC analyses.Analysis of cytonuclear disequilibrium indicated 18 SNP loci in significant (corrected for multiple comparisons) allelic disequilibrium with mitotype. Ten markers also exhibited partial genotype‐by‐mitotype disequilibrium. This analysis only included mixed locations from ~40–43°S to identify the markers in statistical disequilibrium with mitotype in a geographic region of potentially active introgression. To conservatively identify loci that have the potential to be associated with distinct environments, the overlap of these two outcomes was considered. Only three SNP markers see Fig.  exhibit k = 2. In STRUCTURE, the assignment probabilities to lineage were highly correlated (r = 0.987) regardless of whether “outlier” loci were included or not. Additionally, the analysis of STRUCTURE results using STRUCTUREHARVESTER  of being assigned to either of the two lineages, indicating very clear genetic structure. Evaluation of larger numbers (k) of groups results in more individuals being assigned with low probability to one of the clusters. Examination of both inferences shows that north of 30°S, individuals are unmistakably assigned to the northern lineage; south of ~45°S, individuals are assigned to the southern lineage.Analysis of SNP data using both STRUCTURE and DAPC indicated a most informative number of populations at P < 2 × 10−16).Between 30–45°S, the populations are composed of individuals assigned to the northern or southern lineage at inversely related proportions across latitude, with some individuals having intermediate assignment probabilities Fig. . These rEvaluation of two‐generation hybrid probabilities using NewHybrids is shown in Figure Gst as high as 0.315 (P < 0.001) between Antofagasta and Añihue (~2250 km). The mean pairwise Gst among sites within the Peruvian region (north of 30°S) is 0.080, with slightly higher mean pairwise differentiation in the transitional region  and Magellanic region . The data overall exhibit a pattern of isolation by distance; at the full scale of the study, the correlation between pairwise Gst and distance (km) is high , but of course includes the gradient in distribution of the two differentiated clades, which is not an indication of this equilibrium model  and southern  lineages appear to also exhibit isolation by distance. Given this understanding, it is important to note that (1) our “outlier” loci likely represent some false positives given the deviation of these data from a standard island model  anyLarval simulations were conducted at multiple release depths; at deeper releases, the mean downstream transport of larvae generally decreased, reducing the fitness differential needed to maintain the observed cline Fig. . Here, wThe fit between the cline generated by the hydrodynamic dispersal model and empirical data is good when the change in lineage fitness occurs between 40–45°S  between the latitudinal change in frequency of genetic lineage in N. scabrosus and the number of biogeographic indicators of transition at each latitude along coastal Chile  and our desire to understand how fitness and asymmetric gene flow interact  information would be necessary to generate such expectations. However, our inference appears to be robust to the inclusion/exclusion of subsets of loci, as well as lineage assignment based on strictly genetic and strictly quantitative models. Additionally, our dispersal fitness model – similar to the modeling approach employed by Ayala et al.  in exploNotochthamalus is influenced by selection in the larval phase, or at or following settlement. Without such information, we can only speculate at the relationship between the true environmental drivers of this transition and the overall biogeography of Chile. Nevertheless, other intraspecific comparisons are relevant. The marine gastropod Acanthina monodon exhibits similar structure associated with the 30° and 42° biogeographic transitions (Sanchez et al. A. monodon does not have pelagic larvae. This region is the only known overlap in range for Humboldt and Magellanic penguins (Baker et al. Still, it is not known whether the distribution of lineages in Acropora cervicornis using ocean modeling data, and also pointed out the importance of additional biological/ontogenetic information for such studies. Other papers, taking similar approaches to that presented here, illuminate the necessity for some form of selection/adaptation to constrain the distribution of diversity (Galindo et al. Notochthamalus along the Chilean coast (Fig. For species with planktotrophic larvae, environmental factors such as sea surface temperature and salinity, both of which transition rapidly near 42°, are likely to be primary factors in separating populations (Fenberg et al. ast Fig. .In fact, the reason these results are of such interest is the complex interaction between site diversity, variation in ocean circulation, and a changing environment, particularly along this coast (Aiken et al. JQ950750–JQ951089, GU125776–GU125954.DNA sequences: GenBank accessions SNPs developed from sequence data in NCBI BioProject PRJNA227359 (Zakas et al. 10.5061/dryad.22bc3, Ewers‐Saucedo et al. (Sampling locations, SNP genotypes, and Structure/Fst analysis outputs uploaded as Dryad doi:o et al. .None declared.


The short-term impact of using different genomic prediction (GP) models in genomic selection has been intensively studied, but their long-term impact is poorly understood. Furthermore, long-term genetic gain of genomic selection is expected to improve by using Jannink’s weighting (JW) method, in which rare favourable marker alleles are upweighted in the selection criterion. In this paper, we extend the JW method by including an additional parameter to decrease the emphasis on rare favourable alleles over the time horizon, with the purpose of further improving the long-term genetic gain. We call this new method dynamic weighting (DW). The paper explores the long-term impact of different GP models with or without weighting methods.Different selection criteria were tested by simulating a population of 500 animals with truncation selection of five males and 50 females. Selection criteria included unweighted and weighted genomic estimated breeding values using the JW or DW methods, for which ridge regression (RR) and Bayesian lasso (BL) were used to estimate marker effects. The impacts of these selection criteria were compared under three genetic architectures, i.e. varying numbers of QTL for the trait and for two time horizons of 15 (TH15) or 40 (TH40) generations.For unweighted GP, BL resulted in up to 21.4% higher long-term genetic gain and 23.5% lower rate of inbreeding under TH40 than RR. For weighted GP, DW resulted in 1.3 to 5.5% higher long-term gain compared to unweighted GP. JW, however, showed a 6.8% lower long-term genetic gain relative to unweighted GP when BL was used to estimate the marker effects. Under TH40, both DW and JW obtained significantly higher genetic gain than unweighted GP. With DW, the long-term genetic gain was increased by up to 30.8% relative to unweighted GP, and also increased by 8% relative to JW, although at the expense of a lower short-term gain.Irrespective of the number of QTL simulated, BL is superior to RR in maintaining genetic variance and therefore results in higher long-term genetic gain. Moreover, DW is a promising method with which high long-term genetic gain can be expected within a fixed time frame.The online version of this article (doi:10.1186/s12711-015-0101-0) contains supplementary material, which is available to authorized users. In GBLUP, the degree of shrinkage is marker-effect independent but frequency dependent: there is less shrinkage towards 0 for markers with intermediate frequencies [A number of alternative approaches have been proposed for genome-based prediction (GP) of genetic values, i.e. genomic estimated breeding values (GEBV), and many studies have focused on improving the prediction accuracy and short-term genetic gain using different approaches -4. Thesequencies ,6. Underquencies . Under tMaximizing the current genetic selection differential results in the maximization of short-term genetic gain. However, repeated use of this selection procedure does not necessarily maximise long-term genetic gain over a longer time horizon, which is the goal of most breeding schemes . SimulatThe studies of Goddard  and JannIn this study, we simulated a long-term breeding program with a time horizon of 15 or 40 generations, in order to test the following four hypotheses: (1) different GP approaches impact long-term genetic gain because of the different shrinkage methods used; to test this, ridge regression (RR) under a Bayesian framework was compared to BL for GP; (2) long-term genetic gain from RR and BL can be enhanced by weighting marker effects as a function of favourable allele frequencies (Jannink’s weighting); (3) an alternative weighting method that accounts for the time horizon of selection (dynamic weighting) can further improve the long-term genetic gain, with small reductions of short-term genetic gain; and (4) a dynamic weighting method is able to increase long-term genetic gain within different time horizons. In parallel, genetic variance, accuracy of selection, inbreeding and loss of favourable alleles over generations were also studied, which helped to interpret the consequences of the different strategies.Different time horizons, 15 generations (TH15) or 40 generations (TH40), were used to test the sensitivity of the assumption on time horizon. Varying numbers of QTL were used, ranging from 25 to 500 per chromosome. Thus, six scenarios were analyzed , where yi is the phenotypic records, μ is the intercept, xij is the marker covariate , and gi for unweighted GP was defined as for animal yi centered at λ is a regularization parameter, and where ment}σe2 . Ridge rribution , λ is a j is:Gianola  has showpj is the frequency of one of the alleles at locus j, βj [where  animals . This shor on βj ,16.χ2 distribution with degrees of freedom (df) equal to 4 and scale equal to 1 was assigned to −4 and 0.6 respectively, following the guidelines in [For RR, a scaled inverse lines in . Marker lines in ,18 and alines in . The Giblines in .βj were initially estimated by RR or BL as described above. Frequencies of the favourable allele were also calculated for all markers. The favourable (unfavourable) allele of each marker was determined by the positive (negative) sign of the estimated marker effect. More specifically, the marker covariates were coded as 0, 1 or 2, as for the estimation of marker effects. The code counts the number of copies of one of the alleles (“1” or “2”) observed at a locus. If the number of allele “1” was counted and the sign of the estimated marker effect was positive, then “1” was taken as the favourable allele. Then, the weight used for each marker in JW was:For weighted GP, the marker effects wJj is the weight for marker j based on [pj is the favourable allele frequency for marker j. Thus, the weight given to each SNP depended on the favourable allele frequency which changes in each generation. The assumption behind this weighting scheme is that selection is performed for a sufficient amount of time to fix all favourable alleles. The expression reflects the total accumulated selection intensity required to move the allele to fixation. The objective is to fix high-frequency favourable alleles of markers almost at the same time as low-frequency favourable alleles.where based on , and pj For DW, in order to allow the weighting to vary according to time horizon, we used the probability density function of the beta distribution:wDj is the weight for marker j based on dynamic weighting, α and b are shape parameters, and B is the beta function. With this function, two aspects are incorporated in DW. First, the initial weighting on markers with a low favourable allele frequency is higher than in JW. In other words, more weight is allocated to favourable alleles with a low frequency compared to JW, to ensure that the rare alleles are maintained. For instance, at G0, if α is set to 0.2, b to 1, and the favourable allele frequency p to 0.05, the weighting given to this marker would be 17.21 times higher than the maker with a p of 0.999. In contrast, with JW, the weighting on that marker would be only 6.17 times higher than the maker with a p of 0.999. Second, the weighting can be adjusted according to the remaining number of generations of selection. For DW, we introduced “current generation” and “total time horizon” into the above probability density function:where α' is a parameter that determines the initial weight assigned to the markers, t is the generation when the weight is assigned to each marker, and N is the generation for which the total long-term genetic gain is to be maximized. According to this function, as α' was set to 0.05 or 0.2 for comparison and to evaluate the importance of putting a higher weight on the rare favourable alleles compared to JW. The weighting as a function of favourable allele frequencies and generations for TH40 is in Figure mentclass2pt{minimwJ(D)j is the weight for marker j based on Jannink’s weighting or dynamic weighting. As in [βj were included in the expression of the selection criterion to reduce the importance of small-effect loci for which the favourable allele could not be determined with any certainty [where g. As in , marker ertainty .0). At G0, the average (±SD) linkage disequilibrium (LD) between neighbouring loci was r2 = 0.27 (±0.32), and the allele frequency distribution followed a U- shaped distribution, with ~30.2% of the loci fixed. Subsequently, the markers and QTL were chosen among all segregating loci according to their minor allele frequencies (MAF). Markers with a MAF greater than 0.05 were picked as the real markers, and a specific number of QTL, depending on the scenario, with a MAF greater than 0.01 were uniformly picked among the potential QTL. As a consequence, 8257 markers that were approximately evenly distributed across the genome were used in the selection procedures.A historical population with a size of 100 males and 100 females for 2000 discrete generations was simulated using QMSim . The sim1. Generations 1 to 25 or 40 were simulated without mutations. The QTL effects were assumed to follow a gamma distribution Γ, following the shape parameter for distribution of QTL effects in pigs [The simulated traits were standardized to have a mean of 0 and a variance equal to the heritability, i.e. 0.1 for animals in G in pigs . The effh2 is the heritability, subscripts i (j) denote QTL i (j), pi (pj) is the frequency of the “1” allele of QTL i (j), and i (j) before being scaled. The additive QTL variance explained all genetic variance. True breeding values (TBV), environmental terms and phenotypic records at each generation were simulated as described in [where ribed in .0 to G1, the population size was increased from 200 to 500, i.e. 50 females that were selected based on the selection criterion in G0 produced 10 offspring. Selection was then continued for 15 or 40 generations. In each generation, the best 5 males and 50 females among 500 candidates were selected based on the selection criterion. Selected individuals were randomly mated and each pair produced 10 offspring with equal sex ratio. For all selection criteria, marker genotypes and phenotypes at Gt (generation t) and Gt-1 were assumed to be known, and the prediction model for GP was updated every generation.From GFor each of the scenarios, summary statistics were based on 100 replicated simulations. It should be noted that for unweighted GP and GP using JW, the simulation of TH15 was nested within TH40, since there were no additional parameters to control the time horizon. This means that the results for TH15 were reported from the data for TH40. In contrast, simulations for TH15 and TH40 were done separately for GP using DW. For each simulation, long-term genetic gains from selection were standardized by the maximal genotypic value possible for the genetic model  as follows:Rs is the long-term genetic gain after the standardization, R0 is the absolute average TBV in G0, Rt is the absolute long-term genetic gain in Gt, which is calculated as the average TBV in Gt minus R0, and Rm is the maximal genotypic value that can be achieved under the current genetic model. Therefore, Rs represents the long-term genetic gain achieved as a proportion of the total genetic gain that can be achieved under the current genetic model, and is expressed on a 0 to 1 scale. Comparisons between criteria in terms of genetic gain were mainly based on Rs. It should be noted that Rm differs among scenarios with different numbers of QTL  given the inbreeding coefficient in Gt and the inbreeding coefficient in the base population  was calculated as et al. [F, and MSD were analyzed using Tukey's HSD (honest significant difference) test, in conjunction with ANOVA (p < 0.05).where eticsPed , using teticsPed  and all ation in . Moreove [et al. . BrieflyRs at G15 or G40 when no weighting is applied. In general, there was no significant difference between RR and BL in Rs at G1, except for the scenario with 100 QTL. But RR resulted in significantly lower Rs at G15 and G40 than BL. For instance, RR provided the following Rs at G15: 43.4, 23.4 and 11.0% of the maximal genetic value with 100, 400 and 2000 QTL. With BL, Rs increased significantly up to 46.1, 25.9 and 12.4% respectively. Similarly, at G40, BL led to 11.6, 19.2 and 22.7% higher Rs than RR. Figure Rs occurred after 8 to 10 generations of selection in all scenarios. In addition to genetic gain, BL also had a ~16.7% lower inbreeding rate at G0 to G15 than RR, irrespective of the number of QTL affecting the trait  to 22.1% (RR_wD0.05), but at a cost of lower initial gain. Similarly, BL_wJ led to an increase in Rs by 11.36% relative to BL, and it was further increased to 16.63% for RR_wD0.2 to 18.64% for RR_wD0.05.When the time horizon was increased to 40 generations, a similar pattern was found, i.e. the initial decrease and later increase in Rs was slightly larger in relative terms. The effect of weighting on rate of inbreeding was not affected by the number of QTL.Tables The weighting of rare alleles also affects the short-term rate of inbreeding Tables  and 4. F10 was used as the short-term level of inbreeding and Rs at G40 was used as the long-term genetic gain. Across 100 replicates for all eight selection criteria, correlations between the short-term inbreeding and Rs were negative and ranged from −0.65 to −0.44. More QTL led to a higher correlation.Given the effect of weighted and unweighted GP on short-term inbreeding and long-term genetic gain, we also examined the correlation between them. The inbreeding coefficient in G25 onwards for selection using RR or BL in all scenarios. This explains why the genetic response to selection from G15 to G40 was smaller than that from G1 to G15 , because genomic selection is mainly advantageous in situations where the accuracy is low, e.g. for traits with low heritability . It is e, becauseThe number of QTL was also varied in our simulations, since it might influence the accuracy of different prediction models. In contrast to prior expectations, the relative superiority of BL over RR was larger when the number of QTL was larger and long-term response was the criterion for comparison. The results showed that number of QTL mainly affected the loss of favourable alleles and the loss of genetic variance, which was greater with RR than with BL. This may be because with more QTL, the selection pressure on each QTL is smaller, and drift therefore becomes relatively more important. The number of QTL did not affect the rate of inbreeding since, here, rate of inbreeding was measured based on pedigree information only. Pedigree inbreeding is only an expectation of the proportion of the genome that is homozygous by identity-by-descent (IBD). Because of variation around this expectation and genetic hitch-hiking due to selection, pedigree inbreeding may not be a good indicator of the true inbreeding . Future et al. [It should be noted that in our study, the assumed genetic model was simplified to contain only additive effects, and genetic variance was expected to decline due to selection and genetic drift. However, Hallander et al.  showed tIt should be noted that the aim of this study was to investigate the main mechanisms that have consequences in long-term selection programs, rather than to provide any concrete guidelines to breeding companies. DW showed a lower accuracy and a lower short-term genetic gain than JW, which may be relevant for practical breeding programs. This applies especially in dairy cattle breeding, for which information on genetic progress of the competitors is easily collected from Interbull reports, which allows comparisons between countries and companies. Given these concerns, it appears that JW and DW methods are more relevant for pig or poultry breeding, since they usually involve closed populations. Also, since pigs and poultry have a shorter generation interval than dairy cattle, long-term selection programs are more relevant. Moreover, another common way of increasing selection limits is to switch the selection rule from truncation selection to optimum contribution selection (OCS). OCS works by optimizing the genetic contribution (i.e. number of matings) of each selection candidate, conditional on EBV and average co-ancestry. By doing so, the genetic gain is expected to be maximized and, at the same time, the rate of inbreeding is restricted. This method has been well studied in dairy cattle, pig and fish breeding and has proven to be promising in terms of long-term genetic gain -37. ThusThis study shows that without weighting methods, BL is superior to RR in maintaining genetic variance and controlling inbreeding, and therefore can result in higher long-term genetic gain, regardless of the number of QTL affecting the trait and length of the planning horizon. With a larger number of QTL, the relative superiority of BL was more pronounced in terms of both absolute and standardized long-term genetic gain, but the difference in rate of inbreeding remained unchanged. Compared to unweighted genomic prediction, both dynamic weighting and Jannink’s weighting can enhance long-term genetic gain and decrease rate of inbreeding with a time horizon of 40 generations. The long-term genetic gain when using dynamic weighting was up to 30.8% greater than that of unweighted genomic prediction, and also up to 8% greater than Jannink’s weighting, although at the expense of a lower short-term genetic gain. With a time horizon of 15 generations, the long-term genetic gain of dynamic weighting can be guaranteed to be at least as high as that of unweighted genomic prediction, whereas Jannink’s weighting cannot. Therefore, dynamic weighting is a promising method that is expected to result in high long-term genetic gain within a fixed time frame.


Studies in the USA report differences in opinion among parents of different ethnic groups toward genetic testing for their child; however, there are no studies that address this issue in the diverse ethnic and immigrant population in Canada.This study aims to determine whether ethnicity and immigration status influences parental interest in clinical genetic testing for a potentially progressive kidney disease.This is a cross-sectional study.Participants were recruited from the Greater Toronto Area, Canada. The study included 320 parents of children ages 1–18 years with nephrotic syndrome enrolled in the Insight into Nephrotic Syndrome: Investigating Genes, Health and Therapeutics (INSIGHT) observational cohort study.Demographic, ethnicity, immigration, and child specific factors as well as interest in genetic testing were collected through self-reported questionnaires administered at baseline study visit.Logistic regression models were used to examine association of ethnicity and immigration status with interest in genetic testing.The majority of parents (85 %) were interested in genetic testing for their child. South Asian and East/Southeast Asian parents had 74 and 76 % lower odds of agreeing to genetic testing when compared to Europeans (odds ratio (OR) 0.26, 95 % confidence interval (CI) 0.10–0.68; OR 0.24, 95 % CI 0.07–0.79, respectively) after controlling for age and sex of child, age and education level of parent, initial steroid resistance, and duration of time in Canada. Immigrants to Canada also had significantly lower odds  of agreeing to genetic testing after similar adjustment. Higher education level was not associated with greater interest in genetic testing .Participants have already agreed to aggregate genetic testing for research purposes as part of enrolment in INSIGHT study.While majority of parents were interested in genetic testing for their child, immigrants, particularly South Asians and East/Southeast Asians, were more likely to decline genetic testing. Genetic counseling needs to be tailored to address specific concerns in these parental groups to maximize informed decision-making in the clinical setting.NCT01605266ClinicalTrials.gov,  Studies in the USA have reported differences in parental attitudes toward genetic testing among different ethnic groups, but this remains unexplored in Canada.Immigrants, particularly South Asians and East/Southeast Asians, have significantly lower rates of agreeing to genetic testing, suggesting specific concerns about genetic testing that need to be addressed when counseling families.Genetic testing has quickly become a clinically applied tool in medicine. It can aid in diagnosis, prevention, and treatment of disease, as well as uncover disease risk in family members. It is especially useful in the early diagnosis of children with progressive diseases so that intervention can begin as soon as possible or medications may be withdrawn that will not alter the clinical course. The use of genetic testing, however, is not universally embraced among parents.Studies in the USA report both ethnic and cultural differences in genetic testing. Reports demonstrate that African Americans were less likely to see the potential benefits of predictive testing for disease risk and were more concerned about potential discrimination resulting from genetic testing compared to European Americans , 2. SimiIn Canada, people of visible minorities are less likely to use hospital or cancer screening services than non-minorities despite the public health-care systems . StudiesNephrotic syndrome is the most commonly diagnosed kidney disease in children with an incidence that is much higher among children of South Asian ancestry in Ontario . The disIn an established cohort study, we asked parents about their interest in testing their child with nephrotic syndrome for a single gene associated with disease response and/or progression of kidney disease. Our objective was to determine whether ethnicity and immigration influences parental decisions toward clinical genetic testing. As genetic discovery advances, genetic testing is becoming more accessible and increasingly recommended in clinical care for nephrotic syndrome and many other diseases. Understanding the concerns and opinions of parents toward genetic testing will allow health professionals to better facilitate clinical decision-making.The data reported are collected from questionnaires completed by parents enrolled in the Insight into Nephrotic Syndrome: Investigating Genes, Health and Therapeutics (INSIGHT) study . INSIGHT is an observational, longitudinal cohort study based in the Greater Toronto Area in Canada . The stuA primary aim of the INSIGHT study is to understand genetic factors associated with disease susceptibility and progression. Participants consent for the INSIGHT study to collect and store samples for future studies on nephrotic syndrome and other kidney-related research. All participants are informed that samples are de-identified and studied in aggregate and as such, families will not be informed of their individual child’s genetic test results. Consent forms in languages other than English are also available if needed. As part of the study, parents complete questionnaires in English with trained research staff and with certified translators (or the child when appropriate) if the participant is not fluent in English. Informed consent is obtained from both parents and children, and the study is approved by the Hospital for Sick Children’s Research Ethics Board.This study is a cross-sectional analysis of data from 320 parents of the 320 children enrolled in INSIGHT that completed the baseline study visit questionnaire.There is a possibility that a specific gene may be associated with frequent relapses of nephrotic syndrome, steroid responsiveness and progression of kidney disease; if your child could be tested for this gene, would you be interested? Using a standardized script, the research coordinators told parents that this was a hypothetical question to assess interest in genetic testing for a single-specific nephrotic syndrome gene and that results of the test could theoretically alter the treatment that their child would receive (steroids or another agent) or be able to identify whether their child was at increased risk of disease progression. Choices included “yes,” “no,” and “uncertain,” and the last two were grouped together for analyses. If parents were interested in genetic testing, they were asked to indicate their reasons for interest in genetic testing and instructed to select one or more options from a list of seven reasons, and parents that were uncertain or not interested were re-contacted and asked to provide their reasoning. In INSIGHT, nine coordinators of different ethnicities implemented the questionnaires.The questionnaires included information on demographics, self-reported ethnicity, immigration history, highest level of education achieved, family income, language spoken at home, and family history of chronic diseases. Parental interest in genetic testing was assessed by the following question in the survey: χ2, t tests, and Fisher’s exact tests by status of interest in genetic testing. Using logistic regression, we determined whether ethnicity or immigration were associated with interest in genetic testing adjusting for demographic, education, or child specific factors. Parent ethnicity and immigration status were then analyzed using multivariable analyses in two parsimonious models adjusting for age and education level of parent, age and sex of child, initial steroid resistance, and duration of time in Canada. Data were checked to ensure covariates had linear association with log odds of genetic testing, and all models were examined for multicollinearity, specification, and goodness of fit to ensure assumptions of the models were met. Statistical analyses were conducted using STATA/SE-14, and a p value <0.05 was considered significant.Descriptive statistics were examined for normality and compared with We screened over 550 children and 70 % of eligible children and families consented to participate in the INSIGHT study (5 % are still undecided and 25 % have refused). Those that refused to participate were mainly of South Asian (45 %), East/Southeast Asian 15 %), or European descent (15 %). There were no differences in age or sex of those who consented compared to that did not consent (data not shown). Table 5 %, or EEighty-five percent of parents were interested in genetic testing for their child. Of the remaining parents, 32 (10 %) were unsure and 17 (5 %) not interested in genetic testing, and these parents tended to be younger and have very young children. These parents were also mainly of South Asian origin, born outside of Canada, recently immigrated, and spoke a language other than English at home.Several factors were found to be significant predictors of parental interest in genetic testing by univariable analyses: European ethnicity, being born in Canada, older age of parent, English spoken at home, and older age of the child Table . Both SoParental ethnicity and immigration status were both found to be the most significant predictors of interest in genetic testing and were highly correlated in this study population  so they were analyzed in two separate models Table . After an = 186) and relationship to child  if available. There were no differences by either income status or by parental sex (data not shown). There was also no difference in medication adherence by genetic testing interest (data not shown).Data analyses were also stratified for family income (n = 271) were also asked for all the reasons influencing their interest in the future genetic testing. Knowledge, benefit to future generations, and benefit to science were the top three reasons selected (Fig. Parents interested in genetic testing n = 27 were alsParental attitudes toward genetic testing in a chronic pediatric disease at risk of progression are significantly associated with ethnicity and immigration. Differences in parental perspectives on genetic testing of a child among ethnic groups are relatively unexplored and yet an important facet in clinical care and will continue to be an issue in Canada given our immigration patterns. Overall, 85 % of parents were interested in genetic testing. Parents that declined genetic testing were primarily immigrants to Canada and predominantly of South Asian and East/Southeast Asian descent, despite higher levels of education beyond high school. There was no concordance between medication adherence and willingness to undergo genetic testing, which suggests that these families have concerns specific to genetic testing rather than overall clinical management. It is important to understand these issues in order to help parents make informed clinical decisions for their child.South Asian or East/Southeast Asian parents were more likely to decline genetic testing when compared to those of European ancestry, and this is independent of age and education level of the parent, age and sex of child, duration of time living in Canada, and disease severity. Reasons for these disparities could include language barriers, mistrust of the health-care system, and cultural barriers. In Canada, aging South Asian immigrants are found to have poorer physical and mental health status and yet are more uncomfortable asking for help, which is attributed in part to cultural beliefs that health problems should be kept in the family and not shared with outsiders . Both SoAmong parents that declined testing, there was a strong need for more information about what genetic testing involved and concerns about what information would be obtained and whether it would help improve their child’s health. This underlines the importance of how genetic testing is framed and what information is gained in parental decision-making processes. In this study, parents were asked about genetic testing in the context of identifying a gene that may alter treatment and management, or uncover an increased risk of disease progression. As genetic testing in this clinical setting is increasingly available and even recommended for nephrotic syndrome, it is important to understand concerns or additional information required to make an informed decision.Previous reports indicate that higher education increases interest in genetic testing. In contrast, we found that higher parent education level was not significantly associated with interest in genetic testing and did not attenuate the findings of ethnic or immigrant groups. Our study population was highly educated, and the lack of association could be due to minimal variability to demonstrate a statistical difference or could reflect that education does not alter understanding of clinical testing. We do not specify in our questionnaires the country in which parents received their education, which is a limitation. It may also be that education level and knowledge about genetic testing is not as closely linked as health-care providers suggest. Relying on education level as an indicator of health literacy may, in fact, distract from understanding parental decision-making processes.Our study has several strengths. The population includes a large number of parents compared to prior studies of childhood chronic diseases, with detailed parental characteristics including demographics, education, ethnicity, and immigration status. It is also the only study to our knowledge that investigates parental attitudes toward genetic testing. Our study does have several limitations. The questionnaire used in the study addressed genetic testing in the context of uncovering a gene that may alter management; however, the questionnaire was not designed to address a number of evolving issues in genetic such as incidental findings from studies of the entire genome. Additionally, the questionnaire did not quantify the interest of parents by gradation but rather yes and no, which may oversimplify the issue, and parent comprehension of the survey question was not assessed. Our study population also includes those that have already agreed to research genetic studies, and even though we recruited a large proportion of our clinic population, it is possible that there would be an even greater reluctance to participate in genetic studies if all families were studied. There were a number of South Asian and East/Southeast Asian families that did not enroll in the study, and thus, our findings are conservative and may underestimate the differences observed between ethnic groups. Further studies exploring parental attitudes in more detail are warranted to understand these complex issues especially as genetic testing becomes more widely available for other childhood diseases.With the knowledge of gene-health relationships expanding rapidly, genetic testing is increasingly available and often recommended in clinical medicine. Health-care professionals must be prepared to address concerns of South Asian and East/Southeast Asian parents, particularly immigrants to Canada, about genetic testing and perhaps identify the personal barriers influencing health-care decisions. Future research should seek to understand these ethnic and immigrant-based apprehensions about genetic testing in order to provide the best parental support in clinical decision-making for their child.


Ocean acidification is predicted to have detrimental effects on many marine organisms and ecological processes. Despite growing evidence for direct impacts on specific species, few studies have simultaneously considered the effects of ocean acidification on individuals (e.g. consequences for energy budgets and resource partitioning) and population level demographic processes. Here we show that ocean acidification increases energetic demands on gastropods resulting in altered energy allocation, i.e. reduced shell size but increased body mass. When scaled up to the population level, long-term exposure to ocean acidification altered population demography, with evidence of a reduction in the proportion of females in the population and genetic signatures of increased variance in reproductive success among individuals. Such increased variance enhances levels of short-term genetic drift which is predicted to inhibit adaptation. Our study indicates that even against a background of high gene flow, ocean acidification is driving individual- and population-level changes that will impact eco-evolutionary trajectories. Ocean acidification represents a deleterious anthropogenic influence that can affect the vital functions of marine organisms23Hexaplex trunculus (L.), a widespread Mediterranean mollusc. Our study made use of CO2 seeps off the coast of Isola Vulcano , which provide a natural gradient of pH and a carbonate chemistry analogue for future oceansH. trunculus has low dispersal capacity , resulting in the potential for population genetic structuring at a fine geographical scale. This makes it an ideal model with which to investigate individual- to population-level responses to prolonged , exposure to elevated pCO2.We investigated the effects of ocean acidification on the gastropod 2 seepspCO2 conditions (7.65 ± 0.01 pHT), the Control site experienced ambient pH conditions (8.00 ± 0.01 pHT) over the long-term, albeit with periods of short-term (hours/days) pH variability (likely associated with wind-driven currentsT), unaffected by the seeps.Three sites along the natural pH gradient were used . All thrEnvironmental factors modulate metabolic activity through alterations in resource demand and/or availability. Should insufficient resources be available, then stress-induced trade-offs between energy demanding processes can occur H. trunculus between two sites (Low pH and Control site) we tested how ocean acidification modulates metabolic activity using oxygen consumption rate . The mean H. trunculus experience increased energetic demand under persistent exposure to ocean acidification, in part this is likely due to higher predicted costs of maintaining calcification and acid–base homeostasisH. trunculus individuals were reciprocally transplanted between Control and Low pH sites, metabolic rates did not significantly differ , with mean Using reciprocal transplants of nditions . This sueatments . These reatments .F2,208 = 3.33, p = 0.034) and thickness  in the acidified conditions were significantly lower , while the sex ratio in the ambient pH sites did not significantly differ from equality . It should be noted that there are increased levels of trace elements and heavy metals at our low pH site . The FIS values suggest that for H. trunculus some aspect of the acidified environment results in greater departures from Hardy-Weinberg equilibrium outcrossing genotype proportions in the form of heterozygote deficits. Such site-specific heterozygote deficits could be generated by inbreeding, natural selection acting on the genetic markers, or spatial/temporal structure within samples known as the Wahlund effectFIS values resulted from significant values at the majority of individual loci, locus-specific selection effects are unlikely. Inbreeding effects within a small population can also be discounted, as the Low pH site sample reported significantly reduced mean individual relatedness (mr) values compared to the Control (p = 0.03) and Reference (p = 0.048) sites .Despite the absence of genetic differentiation between the sites’, the prominent feature of the genetic data was the large, significant per se. Such variance in reproductive success among individuals has been reported for many highly fecund marine invertebrates and is often referred to as sweepstakes recruitmentFor a Wahlund effect to be observed, genetically distinct populations must occur within the geographical scale of the sampling. Due to the high gene flow indicated throughout the sampled area, any heterogeneity in allele frequencies is more likely to be generated by increased variance in reproductive success among individuals, rather than by spatial population structuring Patella vulgataVariance in reproductive success among individuals may be driven by any deterministic and/or stochastic processes influencing fitness, and ocean acidification has been shown to strongly influence recruitment processespCO2 concentrations are driving individual and population level changes that will impact eco-evolutionary trajectories, and highlights the need for deeper understanding of the links between individual effects and (often unknownThe increased variance in reproductive success and consequent genetic drift pulses (within and between cohorts) could, in theory, hinder adaptive evolution of populations in response to ocean acidification22H. trunculus (and subsequent experiments) were carried out at Levante Bay , Vulcano, Italy in May 2013 and May 2014. During the first experimental period, individuals used for the reciprocal transplant were collected and deployed in transplantation cages, with additional individuals collected in order to measure shell length. During the second sampling period individuals were destructively sampled to determine sex, body mass  and shell thickness (outer lip). Genetic samples were collected during both experimental periods to test for temporal stability of any population structuring or demography. Samples were taken non-destructively by removing a tissue sample from the foot, then returning individuals to their respective sites.Collection of H. trunculus, were distributed across four treatments. Individuals from the elevated pCO2 areas were (i) transplanted into control conditions (Control site), or (ii) re-transplanted into the high pCO2 areas (Low pH site), and individuals collected from the Control site were (iii) transplanted into high pCO2 areas, or (iv) re-transplanted into the control conditions. After 14 days exposure, the cages were recovered and transported to a reservoir tank with site-specific ambient pH prior to placement into respirometers for oxygen consumption rate measurements within 30 min of collection.Using an orthogonal design, six cages per treatment (10 × 10 × 10 cm), each containing an individual H. trunculus were placed into a respirometer, and allowed to settle to the experimental conditions for 1 h. Water samples (taken via syringe from the respirometers) were collected in order to measure the partial pressure of oxygen (pO2), by passing the water sample over a pO2 electrode  connected to an oxygen meter  that was calibrated to 100% aerated site-specific seawater. The first water sample was taken following the 1 h settling period, and at the same time, the circulation of seawater from the reservoir to the respirometers was stopped. A second water sample was taken from each respirometer after 1h (maintained above 17 kPa), and the oxygen consumption rate was determined as the change in pO2 between the first and second water samples. This was multiplied by the solubility coefficient for oxygen, adjusted for salinity and temperature2 h−1 mg−1 (wet weight) STPD.Oxygen consumption rate (n = 73–85 per site). A macroscopic maturation scale was employed to determine the sex of H. trunculusn = 24–31 per site). Body mass was determined by dissecting the body tissue from the shell (n = 24–31 per site), and measured as dry weight . Shell thickness (outer lip) was measured in the growing tip along the anterior portion of the shell (n = 18 per site), using a dissection microscope with 10× eyepiece graticule .Shell length was measured using a digital calliper (±0.1 mm) measuring from the apex to the tip of the siphonal canal  by Site. For H. trunculus were developed by construction of a microsatellite-enriched genomic library following methods outlined in refs28DNA was extracted from ethanol preserved tissue samples using a standard CTAB-chloroform/isoamylalcohol method. Novel microsatellite markers specific to n = 48 per site; temporal sample 2: n = 28–30 per site) were genotyped at four microsatellite loci (GenBank KJ765703-KJ765706) by electrophoresis of PCR products on an ABI3500 automated sequencer , with allele sizes determined using GENEMAPPERIndividuals collected at two times from each of the three sites  using FSTAT. FSTAT was used to test for significant differences (1000 permutations) in genetic variability  between groups.Deviations from Hardy-Weinberg equilibrium were evaluated using exact tests in GENEPOPh and π, respectively) and their variances, with differentiation among samples tested by global and pairwise ΦST.MtDNA variation was assessed in ARLEQUINHow to cite this article: Harvey, B. P. et al. Individual and population-level responses to ocean acidification. Sci. Rep.6, 20194; doi: 10.1038/srep20194 (2016).


Eretmochelys imbricata). An improved understanding of the breeding system of this species and how its genetic variation is structured among nesting areas is required before the threats to its survival can be properly evaluated. Here, we genotype 1195 hatchlings and 41 nesting females at 12 microsatellite loci to assess levels of multiple paternity, genetic variation and whether individual levels of homozygosity are associated with reproductive success. Of the 50 clutches analyzed, only 6% have multiple paternity. The distribution of pairwise relatedness among nesting localities (rookeries) was not random with elevated within‐rookery relatedness, and declining relatedness with geographic distance indicating some natal philopatry. Although there was no strong evidence that particular rookeries had lost allelic variation via drift, younger turtles had significantly lower levels of genetic variation than older turtles, suggesting some loss of genetic variation. At present there is no indication that levels of genetic variation are associated with measures of reproductive success such as clutch size, hatching success, and frequency of infertile eggs.The Yucatán Peninsula in Mexico contains some of the largest breeding groups of the globally distributed and critically endangered hawksbill turtle ( Wide‐ranging, migratory species face multiple, often anthropogenic, challenges to their survival because they usually occupy different habitats to feed, rest, and breed CMS . The thrThe circumglobal distribution of most marine turtles means that environmental degradation and loss of habitat is likely to impact some part of their distribution  (Pearse and Avise Eretmochelys imbricata)  Fig. , which ita) Fig. , has beeta) Fig.  with theta) Fig. . Howeverta) Fig.  and the ta) Fig. , and it ta) Fig. .The Yucatán Peninsula in Mexico harbors the largest hawksbill nesting population in the Atlantic and is considered among the most important in the world for the long‐term persistence of this species  in the Yucatan Peninsula with the following objectives: (1) to assess the incidence of multiple paternity; (2) to test whether there are differences in genetic variation among rookeries; and (3) to evaluate whether individual levels of genetic variation are associated with measures of reproductive success.We sampled six rookeries on the Yucatan Peninsula in Mexico: Xicalango‐Victoria and Chenkan in Campeche; Celestún, El Cuyo, and Las Coloradas in Yucatan; and Holbox in Quintana Roo, all of which are inside a Federal Natural Protected Area Fig. .During the 2011 nesting season, tissue samples were collected from the left rear flipper of 41 nesting females using a 3 mm biopsy punch. The tissue was preserved in 70% ethanol and stored at −4°C. Nest location coordinates were taken using a GPS and the nest location was marked with a stake placed nearby. After 55 days incubation, the nests were monitored daily and the hatchings were captured at emergence. Tissue samples were taken from the carapace left marginal scute using a 2 mm biopsy punch, and then preserved in 70% ethanol and stored at −4°C. After releasing the hatchlings, we were able to open the nest chamber of 44 clutches to record the number of shells and hatching live or dead hatchlings; unhatched eggs were also opened to determine the number of undeveloped and partially developed eggs.μL.We extracted DNA using the DNeasy Blood and Tissue DNA extraction kit  from a total of 1195 hatchling samples and 41 nesting female samples; for hatchlings, approximately 25 randomly selected samples were taken from each sampled clutch. DNA concentration was quantified using a Nanodrop 2000c spectrophotometer  and diluted to a standard concentration of 10 ng/Thirteen previously designed polymorphic microsatellites for use in sea turtles were selected for genotyping: Ei8, Cm72, Cc117  following the Invitrogen Taq DNA Polymerase, recombinant (Thermo Fisher Scientific Inc.) basic PCR protocol suggested by Innis et al. . ThermalObserved and expected heterozygosity and the significance of any deviations from Hardy–Weinberg equilibrium were calculated from allele frequency data derived from the parent and one offspring from each of the analyzed clutches using GenAIEx v6.5 , were also excluded and these data were used to estimate the genotyping error rate per locus. For the COLONY analysis the error rate ranged from 0.002 to 0.082. In COLONY, each rookery was analyzed as a single dataset using default parameters in a single medium‐length run and with medium full‐likelihood precision; the mating system for both sexes was considered polygamous, while an outbreeding model was selected because the data do not significantly deviate from Hardy–Weinberg equilibrium.We calculated the probability of detecting multiple paternity for our sample size of 25 offspring per clutch using the software PrDM (Neff and Pitcher r), the average relatedness for the whole data set is zero. We calculated the 95% confidence interval around zero using a permutation approach (999 permutations), and the 95% confidence interval around r were estimated by bootstrapping 999 times.We calculated relatedness using allele frequency data based on the sampled mothers, the reconstructed father genotypes, and one hatchling taken at random from each clutch. The software GenAIEx v6.5 , we used a Wilcoxon test to assess the index values between untagged nesting females, which are considered to be “young” (neophytes), first‐time nesters, and previously tagged nesting females, which are considered to be “older” (remigrant), experienced nesters.We evaluated a total of 50 clutches, including some successive clutches, from 41 different females located at six different rookeries on the Yucatan Peninsula Fig. . A totalUsing COLONY, we detected multiple paternity in 3 (6%) of the 50 clutches analyzed. These clutches with multiple paternity were located at the rookeries: Celestun, El Cuyo, and Holbox. There was no multiple paternity at Xicalango‐Victoria, Las Coloradas and Chenkan Table .The number of sires estimated for the clutches with multiple paternity was two for the clutches from Celestun and El Cuyo, while three sires were detected in the clutch from Holbox Fig. . In all Using the COLONY software, we accepted reconstructed paternal genotypes with the highest probability value , and were ultimately able to reconstruct the genotypes of 45 different males that mated with 41 different nesting females. There were no matching genotypes among all the reconstructed male genotypes. For clutches with multiple paternity, each full‐sibling group was supported by private alleles from 4 to 6 loci. The probability of identity , using all 12 microsatellites was very low (1.2E‐08 to 5.2E‐08). PrDM analysis estimates a high probability of 0.999 of detecting multiple paternity in our clutch sizes of 25 individuals, even when paternal contribution is skew to 90–10%, thus demonstrating that our results on multiple paternity are not likely to be strongly biased by incomplete sampling of clutches.H = 0.77, P = 0.9788), FIS does not significantly deviate from zero (Hardy–Weinberg Equilibrium). HL values vary among rookeries, but combined with the data on allelic richness and FIS, there is little evidence to suggest that higher HL is associated with loss of genetic variation (Table W = 597, P = 0.0252, Fig. Relatedness within each of the six rookeries was significantly greater than zero Fig. . These ron Table . HoweverThere was no evidence that genetic variation was related to differences in clutch size, hatching success, or percentage of infertile eggs, suggesting that levels of genetic diversity are not yet affecting any of these estimators of reproductive success.Genetic variation was similar within each of the six rookeries examined on the Yucatán Peninsula, Mexico. While gene flow is sufficient to prevent significant differences in allelic variation between rookeries, genotypic similarity within rookeries is higher than random, and declines with geographic distance, suggesting some natal philopatry. Although individual rookeries did not vary in genetic variation, our finding that older females have higher genetic diversity than young ones, may indicate loss of genetic variation over time. Nonetheless, we found no indication that losses of genetic variation are at present detrimental, there was no relationship detected between our measures of genetic variation and reproductive success.Microsatellite analysis showed that the incidence of multiple paternity in hawksbill turtles from the Yucatán Peninsula is low. The frequency of multiple paternity can vary between locations as a consequence of factors such as mate availability or inbreeding risk (Bowen and Karl Paternal contribution in the clutches with multiple paternity was mostly dominated by a single sire, which is typical of sea turtles (Birkhead and Hunter FIS values calculated with respect to allele frequencies for each rookery independently, and overall, do not deviate significantly from zero.High within‐rookery relatedness and declining pairwise relatedness with geographic distance indicates that there are different reproductive groups. It has been suggested that male hawksbills, like females, exhibit natal homing and site fidelity to breeding areas (FitzSimmons et al. There may be some loss of genetic variation overtime, genetic diversity indices were higher for neophyte females, indicating that first‐time nesters produce offspring with lower genetic diversity. In the past, hawksbill turtles were abundant on the Yucatan Peninsula Márquez , but in Despite some evidence for loss of genetic variation, we did not find any correlation between homozygosity by loci and clutch size, hatching success or percentage of infertile eggs, suggesting that current levels of genetic diversity are not affecting reproductive success on the Yucatán Peninsula. Despite evidence for some natal philopatry to rookery areas, gene flow among rookeries has been sufficient to prevent significant differences in allele frequencies. Thus, any loss of genetic variation through drift appears to be operating at a scale that at least collectively incorporates each of the rookeries we sampled.None declared.10.5061/dryad.28v1b.Female genotypes, hatchling genotypes and reconstructed male genotypes: DRYAD entry doi: Appendix S1. Sequence of previously designed microsatellite primers used in this work.Click here for additional data file.


This article introduces the identification, prevention, and treatment of hereditary cancer as an important public health concern. Hereditary cancer research and educational outreach activities are used to illustrate how public health functions can help to achieve health benefits of genetic and genomic medicine. First, we evaluate genetic service delivery through triangulating patient and provider survey results which reveal variability among providers in hereditary cancer knowledge and genetic service provision. Second, we describe efforts we have made to assure competency among healthcare providers and to inform, educate and empower patients with regard to the rapidly evolving field of genomics and hereditary cancer. Lastly, key policy-issues raised by our experiences are discussed in the context of how they may help us to more effectively translate future genomic technologies into practice in order to attain population health benefits from genetic and genomic medicine. The National Human Genome Research Institute defines genetics as the study of genes and their role in inheritance . As an eGenetic and genomic medicine involves using genetic or genomic information as part of an individual’s clinical care  . SeveralGenomic medicine, however, is typically less focused on the inheritance of single genes that confer high risks for disease. An example of cancer genomics involves sequencing of tens or hundreds of genes in a tumor from a cancer patient to help in selecting cancer treatments. An important distinction here is that the gene mutations identified in most tumors are not the result of inherited mutations, but occur after conception and are typically only present in the tumor cells. Tumor sequencing is already being incorporated into clinical care at many cancer centers and hospitals across the U.S..The next challenge is going “beyond the bedside” to ensure that genetic and genomic tests are leading to sustained and wide-spread population health benefits while preventing adverse outcomes . We discBRCA1 mutation that confers increased risks for breast and ovarian cancers of up to 70% and 40%, respectively [Targeted therapies and cancer prevention or screening options may be refined based on inherited gene mutations ,5. One oectively ,7,8,9. Tectively ,11.As this real-world experience illustrates, identifying hereditary cancer predisposition is of critical public health importance because it changes cancer risk management options and enables patients and their at-risk family members to benefit from proven cancer prevention or early detection options, which can reduce risks to near that of the general population ,13. MoreEvidence supporting the health benefits of using genetic tests and family health history in clinical practice is reflected by the addition of genomics objectives to Healthy People (HP) 2020 . The firAchieving these HP objectives requires the effective translation of genetics and genomics into healthcare practice through engagement in public health functions at multiple levels, including the patient/family, healthcare providers, and healthcare system  see Fig. In the Ongoing efforts to evaluate genetic service delivery are critical in the context of hereditary cancer given the evolving landscape in which services are provided and the large variety of healthcare providers who offer these services. We have assessed service delivery through surveying Florida healthcare providers who order genetic testing for hereditary breast and ovarian cancer to determine their awareness, knowledge, and practices at two different time points . Overall, survey results were consistent across both time points in revealing significantly higher knowledge and greater awareness of recent changes in genetic testing and policies among those providers with a professional degree in genetics compared to those with little or no formal training in genetics . AdditioAlthough we recognize several limitations associated with self-reported data, the results are consistent with our research findings from surveys of patients who had genetic testing. Specifically, when a provider with a master’s degree in genetic counseling or a fellowship-trained MD in clinical genetics was involved, patients were more likely to recall having their family history taken, reviewing the possibility of uncertain results, and discussing insurance-related issues . TrianguRecognizing the need for educational outreach to practitioners who provide hereditary cancer services in Florida, we created a network of providers through our Inherited Cancer Registry (ICARE) initiative in 2010. Providers are based at centers across Florida and beyond ; and inchttp://inheritedcancer.net/newsletters) [Through our ICARE initiative, we have also established a research registry of high risk patients, to which over 1700 patients have been consented since 2010, including 945 BRCA carriers. Baseline data is collected on participants through a questionnaire, aimed at addressing our own research questions and contributing to the larger research mission through sharing de-identified data with collaborators to answer various clinical questions and perform genetic association studies. Registry participants are provided with clinical and research updates through a mailed bi-yearly ICARE newsletter (available at: letters)  and are Assuring genetic/genomic competency among healthcare providers will be an increasingly important public health function as testing expands because harms have been documented due to lack of access to appropriate genetic testing, inaccurate results interpretation, or failure to tailor recommendations based on the individual’s personal and family medical history ,23,24. TVariability we documented in genetic service delivery raises a key question regarding what constitutes quality in genomic services and who should make decisions about quality. Several organizations have developed professional guidelines for elements to include in a pre-test discussion related to hereditary cancer testing ,26,27,28As we have begun testing for more genes or even the whole exome , it is no longer feasible to present highly detailed information about each gene or all possible test results. Subsequently, even providers with formal genetics training are struggling to identify “best practices” for cancer genetic service delivery in this evolving landscape and there remains an unmet need to define quality genetic service delivery based on patient outcomes research rather than relying on anecdotal experience or expert opinions. Empirically determining what information people actually can and will benefit from in their decision making processes in various contexts will be critical for assuring population health benefits as genetic/genomic medicine expands.Genetic and genomic medicine entail performing appropriate risk assessment, genetic/genomic testing, results interpretation, and patient counseling, all of which are competencies included in accredited Master’s level genetic counseling training programs in North America. Although genetic counselors may be well equipped to help integrate genetic/genomic tests into practice, the majority of clinical testing for hereditary cancer within the U.S. is currently ordered in community settings by providers without a professional degree in genetics; and it is anticipated that this will be the case for other genetic and genomic tests in the future.The Commission on Cancer guideline indicates cancer genetic services may be provided by an informed health care provider with no special certification . HoweverPolicy makers have proposed that health care professionals should, at a minimum, possess the following genomics competencies: (1) a basic understanding of the rationale behind the genomic tests; (2) the ability to identify the limits of his/her genomic expertise; and (3) knowledge regarding where to go for information, resources, and referrals ,30. AddiEvaluating genetic/genomic test results within the context of family history, environmental, and lifestyle factors increases the complexity of prevention interventions and medical care. Recent advances in genetic testing technology have made the option of multi-gene and whole exome testing more financially feasible in clinical practice. Additionally, there are a growing number of genetic testing laboratories offering a variety of hereditary cancer testing options. As such, the increasing complexity of results interpretation that comes with broad-scope testing and the expanding options for hereditary cancer testing highlight the importance of ongoing patient and provider education. Our approach to building a network as part of ICARE is one model by which to discuss challenging cases and educate both providers and patients in the evolving landscape of genetics.i.e., familial and hereditary cancers) and cancer genomics (specific to tumors) will be needed to advance genetic and genomic medicine in the oncology setting.Amidst issues of quality and competency in genetic service delivery, there are also concerns that restricting genetic services to be delivered only by those with specialized training may further reduce utilization of genetic services . This raThis article provides examples of how we have applied a few of the public health functions to the identification and treatment of hereditary cancer to provide insights that may be useful for ensuring successful implementation of other genetic and genomic medicine applications. Although our examples focused on genetic medicine, many of the challenges and questions related to quality and access are applicable to other genomic medicine applications and public health functions are necessary to ensure that genomic technologies lead to population health benefits for all. As genetic/genomic medicine continues to evolve, ongoing evaluation will be needed to monitor dissemination and implementation in various contexts by various providers. Additionally, ongoing educational interventions are needed to assure healthcare providers are prepared and competent to implement genetic/genomic medicine. In conjunction, consideration should be given with regard to policies that that may be needed to define quality of genetic/genomic medicine, promote wide-spread dissemination of evidence-based practices, and assure a competent work force. Ultimately, it will be important to bring various stakeholders together to develop efficient identification and referral systems to facilitate appropriate utilization of genetic and genomic services.