Background. A history of gestational diabetes is an important predictor of many metabolic disturbances later in life. Method. Life after gestational diabetes Ahvaz Study (LAGAs) is an ongoing population-based cohort study. Up to February 2016, 176 women with gestational diabetes underwent a 75 g oral glucose tolerance test (OGTT) at 6–12 weeks postpartum in Ahvaz (southwestern of Iran). Gestational diabetes was diagnosed according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria and the American Diabetes Association (ADA) criteria applied for diagnosis of postpartum prediabetes and diabetes. Univariate and multivariate regression analysis were done. Results. Overall incidence of early postpartum glucose intolerance was 22.2% , 17.6% prediabetes  and 4.5% diabetes . Independent risk factors for glucose intolerance were FPG ≥ 100 at the time of OGTT , earlier diagnosis of GDM , systolic blood pressure , and insulin or metformin therapy . Conclusion. Results determined a relatively high rate of glucose intolerance at 6–12 weeks after GDM pregnancy. Early postpartum screening of type 2 diabetes is needed particularly in women at high risk of type 2 diabetes. Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance, onset or first recognition during pregnancy . GDM is Gestational diabetes mellitus, as a common metabolic disorder during pregnancy, affects between 1% and 28% of pregnancies  and globPrevalence of gestational diabetes in Iran varies from 1.3% to 18.6% based on Carpenter-Coustan criteria . A RecenA history of gestational diabetes is a strong predictor of many metabolic disturbances, particularly glucose intolerance later in life . In the International guidelines recommend early screening of glucose status for development of prediabetes or diabetes in women with gestational diabetes at 6–12 weeks postpartum using the 75 g 2 h oral glucose tolerance test (OGTT) and thereafter –17. But Potential predicators of future progression of prediabetes and/or diabetes in women with gestational diabetes are prepregnancy body mass index (BMI), higher blood glucose level in pregnancy, particular ethnic groups, earlier diagnosis of GDM, requirement of insulin therapy during pregnancy, and advanced maternal age, with high heterogeneity in reported risk factors , 20, 21.Common universal features of GDM reported in recent decades include a rising trend in incidence of the condition  increasiLife after gestational diabetes Ahvaz Study (LAGAs) is a population-based prospective cohort study to investigate potential short and long-term metabolic outcomes of gestational diabetes in mothers and their offspring. For this reason, the first gestational diabetes clinic in Khuzestan province was established as center of the cohort study on October 2013 in Golestan Hospital, the teaching hospital of Ahvaz Jundishapur University of Medical Sciences. Ahvaz is the capital of Khuzestan province, located in southwestern of Iran with high birth rate, high prevalence of obesity, metabolic syndrome, and type 2 diabetes –26.Pregnant women attending 25 urban public and private centers seeking prenatal care were recruited from March 2015. Single approach for screening, treatment, and management of GDM was applied. Initial screening was done in first trimester of pregnancy by fasting plasma glucose (FPG) test. Women with FPG ≥ 126 mg/dL and those who had pregestational diabetes type 1 or type 2 as defined by American Diabetes Association (ADA) criteria  were exc2, history of diabetes mellitus in first relatives, and history of GDM in previous pregnancies underwent earlier OGTT before 14th week of gestation [75 g OGTT was performed between 24 and 32 weeks of gestation and based on IADPSG criteria, only one abnormal value equal to or greater than the known threshold value was detected as GDM values  . Women westation  and screAll women with gestational diabetes received dietary and exercise counseling, individualized diet or pharmacotherapy (insulin or metformin), and clinical and biochemical reassessment with 2-3 weeks' interval. ADA recommendations were used for goals of treatment .A list of women who were diagnosed as GDM with details of their address and contact information were sent for research team and women referred to Golestan Hospital if they verbally accepted participation in the study. Various methods of communication were used to encourage women to participate and for retention including direct contact by phone, SMS texts via phone line, and other social networks (Whats app and telegram). Messages and reminders were sent to the women themselves and/or to husbands or other relatives who had made their contact number available. Communications were made by Sedigheh Nouhjah who was able to respond to any questions presented by the participants. Clinical evaluation and blood tests were free of charge and a copy of their laboratory reports was submitted to the patients for future reference.Questionnaires related to sociodemographic characteristics of women and their husbands, potential risk factors of GDM, pregnancy outcome for the fetus and mothers, obstetrics and medical history, physical activity, and food habits of participants during 6–12 weeks postpartum were filled by a trained questionnaire. A comprehensive second questionnaire will be used as a follow-up within 2 years of the date of entering the study, based on predicted plane, to identify postpartum problems among mothers or their infants. The questionnaires were completed by an independent and trained researcher at the prenatal care center and postpartum data were collected by a member of the research team in our cohort center. Short forms of delivery were completed during 3–5 days after delivery in 2 main centers for screening of neonatal hypothyroidism.FPG and 75 g 2-hour oral glucose tolerance test were performed at 6–12 weeks after delivery and these tests will be repeated annually for up to two years postpartum. Fasting plasma glucose ≥ 126 mg/dL or 2 hour plasma glucose after a 75 g oral glucose load ≥ 200 mg/dL was defined as diabetes, and prediabetes was diagnosed with fasting plasma glucose between 100 and 125 mg/dL or 2 h post-glucose loading level between 140 and 199 mg/dL according to ADA criteria . DiagnosBlood samples were transported to the laboratory at the Diabetes Research Center, where the research coordinator and two laboratory technicians evaluated blood samples using the standard methods. Prepregnancy weight was recorded using medical and health profile. Weight, height, waist circumference, blood pressure, and hip circumference were measured at each visit during pregnancy and postpartum follow-up. Social Sciences (SPSS version 22). Clinical, biochemical, and sociodemographic characteristics of women who progressed to postpartum glucose intolerance compared with women with normal glucose tolerance using univariate logistic regression analysis. Risk factors with P value less than 0.05 were tested in multivariate backward regression model.Statistical analysis was performed with Statistical Package for theThe study protocol was approved by the Ethics Committee of Ahvaz Jundishapur University of Medical Sciences and all participants signed written informed consent form in addition to the first verbal agreement to taking part in the baseline visit.2 (±4.41 SD). Records showing overweight or obesity were observed in 126/176 (71.6%) of participants based on prepregnancy BMI  aged between 17–45 years underwent a postpartum OGTT at 6–12 weeks after delivery. About half of these participants had high school education. Most of them were housewives (92.4%). The mean prepregnancy BMI was 27.82 kg/mancy BMI . This raDemographic and clinical characteristics associated with postpartum glucose test results are presented in The overall incidence of early postpartum glucose intolerance was 22.2%  inclusive of 17.6% prediabetes  and 4.5% diabetes . Risk factors of persistent hyperglycemia at 6–12 weeks after GDM pregnancy were inclusive of FPG ≥ 100 at the time of OGTT in pregnancy, earlier diagnosis of GDM in pregnancy, systolic blood pressure, and the need for insulin inject or metformin therapy. Results of univariate and multivariate analysis using backward logistic regression are presented in Incidence of glucose intolerance at 6–12 weeks after GDM pregnancy determined in this study was 22.5% (17.5% prediabetes and 4.5% type 2 diabetes).These high estimated rates are consistent with results reported by Tovar et al. . They reIn present study rate of prediabetes was in range with many previous reports  but loweDifferent ethnic groups with different backgrounds including prevalence of diabetes mellitus, obesity, metabolic syndrome, and variation in rate of severe hyperglycemia in pregnancy using different criteria for GDM diagnosis in pregnancy and classification of postpartum glucose intolerance may have caused this wide variation in rates.Multivariate regression test showed that risk factors associated with persistent glucose intolerance 6–12 weeks postpartum were inclusive of earlier diagnosis of GDM, use of insulin or metformin for management of GDM, FPG ≥ 100 at the time of OGTT, and systolic blood pressure. converters) [Various potential risk factors have been determined in other research for prediabetes or diabetes in early postpartum period previously , 38, 39.verters) .Consistent with results of this study, earlier diagnosis of GDM in pregnancy before increasing resistance to insulin between 16 and 26 weeks of gestation , 40 is rIn the present study, pharmacotherapy (use of insulin or metformin) for management of hyperglycemia in pregnancy was strong predictor of progression to abnormal glucose tolerance at 6–12 weeks postpartum . Rate of postpartum glucose intolerance in women who were treated with insulin was 54.4% versus 41.7% in women who had taken metformin while the same rate was 15.4% in diet-only group.β-cell function in women exposed to gestational diabetes. Pellonperä et al. studied women with GDM with two or more abnormal glucose values at 2 h 75 g OGTT, for a period of one year postpartum. This study showed higher incidence of prediabetes in metformin and insulin users  than women treated with diet only . Also, the rate of diabetes was lower in the diet treatment group (P = 0.027) [Need for treatment with insulin or metformin as an indicator of severity of hyperglycemia may reflect impairment in = 0.027) . In addi= 0.027)  showed 9Another risk factor for progression of abnormal glucose tolerance in present study was a higher level of FPG (≥100) at the time of OGTT, during a 24–32 weeks' gestation period .Fasting glucose on OGTT is a common risk factor associated with prediabetes and diabetes after GDM pregnancy , 43, 44.This study determined systolic blood pressure as another related risk factor. Hypertensive disorder in pregnancy  was associated with future diabetes based on the systematic review and meta-analysis reported in Rayanagoudar et al. . Feig etIn the present study there was no association of maternal age at pregnancy, maternal education and occupation, parity, and family history of diabetes with development of glucose intolerance in the early postpartum period. Some previous studies have shown an association of maternal age, parity, and a family history of diabetes with glucose intolerance, but reports are inconsistent , 39, 52.No significant association was determined between total weight gain during pregnancy, BMI, and obesity before pregnancy and postpartum glucose intolerance at 6–12 weeks postpartum. Women with higher blood glucose levels, who had a high chance of early postpartum progression to abnormal glucose intolerance, usually received a strict diet program that controlled their weight gain during pregnancy . Body maIn present study 56.8% of women with gestational diabetes underwent cesarean delivery. High rate of cesarean delivery (48%) in Iranian population is reported by Azami-Aghdash et al. . Mean biMoreover, based on our results, rate of preterm delivery was 8%. This rate in general population reported 9.2% (95% CI: 7.6–10.7) by Vakilian et al. , based oPreterm delivery was associated with higher risk of progression to postpartum glucose intolerance using univariate analysis but was not determined as a risk factor when adjusted in the multivariate model. Rayanagoudar et al. showed preterm delivery increases risk of diabetes in women with GDM  . Our resThere were two main limitations in this study. Despite using different methods of communication, the rate of postpartum return for glucose testing and follow-up was low. This may be a source of bias. Participants in this study were compared in terms of sociodemographic and clinical characteristics and those who did not return for follow-up. There were no significant differences between the two groups. A similar problem has been reported in several previous studies , 19. AnoThe strength of this study was that it involved husbands of patients at follow-up in order to decrease the chance of attrition bias. In addition, using a combination of different methods for recall and by sending reminders, this study benefited from its use of social media. To the best our knowledge, this study is the first population-based prospective cohort study in this area to follow postpartum metabolic outcome of gestational diabetes in mothers and their offspring that included several variables.Gestational diabetes is a risk factor for postpartum progression to glucose intolerance. Short-term postpartum follow-up of women with GDM showed a relatively high rate of glucose intolerance among women in this population. This finding highlighted the need for early postpartum screening and implementation of an intervention program to prevent type 2 diabetes, particularly in women whose GDM was diagnosed during the earlier weeks of gestation, mothers with higher fasting glucose level at the time of OGTT, higher blood pressure in pregnancy, and patients who required pharmacotherapy for management of hyperglycemia.


A decline in burned area along with warmer, wetter climates drove WPE, although this has been mitigated in areas with high population growth rates, and high and low extremes of herbivory, specifically browsers. These results confirm global greening trends, thereby bringing into question widely held theories about declining terrestrial carbon balances and desert expansion. Importantly, while global drivers such as climate and CO2 may enhance the risk of WPE, managing fire and herbivory at the local scale provides tools to mitigate continental WPE.While global deforestation induced by human land use has been quantified, the drivers and extent of simultaneous woody plant encroachment (WPE) into open areas are only regionally known. WPE has important consequences for ecosystem functioning, global carbon balances and human economies. Here we report, using high-resolution satellite imagery, that woody vegetation cover over sub-Saharan Africa increased by 8% over the past three decades and that a diversity of drivers, other than CO Woody plant encroachment has important implications for habitat conservation and global carbon budgets, but its drivers require quantification. Here, Venter et al. report that encroachment is predominantly driven by human activities, changing weather conditions, fire, and herbivory. A less well-known, yet equally important global trend is gradual woody plant encroachment (WPE), occurring in non-forest biomes3. In Africa, WPE has been identified as a concern for rangeland management since the early 20th century, and has the potential to reduce rangeland carrying capacities of wild and domestic grazers through the displacement of herbaceous forage by trees and shrubs. On the other hand, WPE may significantly contribute to forage for wild and domestic browsers, household fuel-wood provision, and may lead to increased carbon sequestration, with consequences for global carbon budgets and climate change4. In order to manage the effects of WPE on these diverse local and global ecosystem services, we need to understand what is driving it.Continental-scale changes in woody plant cover have been mapped for forests >5 m in height26 and associated climatic changes, coupled with changing fire and herbivore management regimes, have been proposed as dominant drivers8. While homogenous global CO2 enrichment may enhance tree growth9, the trends in WPE are spatially variable, suggesting other local- or regional-scale drivers. For example, increases in rainfall have been shown to correlate with WPE, while the influences of trends in temperature are less clear10. Agriculturally induced transformation of Africa’s unique set of functional herbivore guilds11, and the alteration of fire regimes12 may shift systems into tree-dominated states at the local scale. However, quantifying these drivers at continental scales has been limited by the paucity of local-scale studies3 or continental analyses relying on low-resolution remotely sensed data10. The lack of spatially explicit measures of the magnitude and scale of WPE has made it difficult to draw generalised conclusions about its causes, and to identify the potential for the use of local drivers  as management tools to mitigate the putative effects of global (i.e. climatic) drivers on WPE.The drivers of WPE are poorly understood compared to those of deforestation where human-induced clearing is dominant. Rising atmospheric CO2 as a global driver and other local- or regional-scale drivers that have received less attention  predominate. Altering fire and herbivory management regimes thus has the potential to mitigate WPE.We mapped change in woody plant cover excluding closed forest  at 30 m resolution for Africa over the past three decades. We considered a suite of potential drivers to explain this change, including CO2 (55%) of non-forest biomes  significant decrease in woody plant cover, confirming local-scale studies indicating increases in WPE over the last century3. Woody cover loss was prevalent in parts of the Sahel, East Africa and much of Madagascar, but WPE dominated the central-interior of Africa. Countries exhibiting a mean fractional increase >30% were Cameroon, Central African Republic, South Sudan, and Uganda  and woody cover change.The widespread trend in WPE correlates with a significant rise in atmospheric COall Fig. , but alsall Fig. . To avoi1 are not limited to the forest biome. Low population growth rates had a negligible effect on curbing WPE, potentially due to a covariance with human-induced landscape fragmentation and the subsequent reduction in fire spread12. Local disturbances by fire and herbivory are known to maintain open savannas in areas that could climatically support closed-canopy forest15. Our analysis confirms that local disturbance patterns can have continental consequences for WPE and are of equal importance to edaphic and climatic variables in explaining the spatial variation in woody cover change  or by inhibiting shrub and tree growth rates and thereby increasing vulnerability to fire25. Indeed, we found that areas with high browser densities experienced lower encroachment rates  estimates of net primary productivity in semi-arid areas38. The present dataset of decadal woody cover change might aid in more accurately quantifying the extent to which WPE contributes to the global carbon sink, potentially offsetting the carbon losses from deforestation. Despite the potential benefits to the global carbon budget, the local-scale disadvantages (e.g. reduced grazing capacity) and their effects on rural livelihoods has motivated substantial governmental investment into clearing alien and native invasive woody plants (e.g. ca.100 million US$ per annum in South Africa)39. Initial indications from our models suggest that WPE management interventions will be most needed in areas that are expected to increase in temperature and rainfall under future climate change scenarios. More importantly, manipulating local disturbance patterns has the potential to override climatic effects and significantly mitigate WPE. Management interventions may include increasing fire using heterogenous management regimes40, or through rewilding savannas with historical herbivory pressures21, and diversifying herbivore functional guilds by incorporating more browsers18. Thus, while global drivers such as climate and CO2 may enhance the risk of WPE, the realisation of WPE is largely dependent on management decisions.The widespread continental increase in woody plants shown here corroborates global trends of increasing leaf area index2, equivalent to 22.8 billion Landsat pixels. Woody plant cover was defined as fractional woody cover of 30 × 30 m squares, defined by the Landsat pixel grid. The dynamics of tree cover change have been comprehensively explored using remote sensing techniques for forest biomes1. Given that the potential for WPE to occur in areas already saturated with tree cover is negligible and that our aim was to investigate WPE and its drivers, we excluded the forest biome from our analysis. Pixels with >40% cover by trees of >5 m in height were considered as closed forest42 and excluded using data from the Global Land Cover Facility43. Tree cover may be unable to fully distinguish forests from densely wooded savannas44; however, these ecotonal boundary areas are relatively small compared to the total area occupied by true non-forest biomes. Thus, the erroneous masking of densely wooded savannas was expected to have little effect on the continent-wide analysis. Forestry areas were defined as pixels that have both lost and gained woody cover between 2000 and 2015 using global forest cover change data derived from Hansen et al. 20131 and were excluded from our analysis. Urban surfaces, water, wetland, cropland, and natural-cropland mosaics were also excluded from the analysis using the MODIS landcover product45. This combined pixel mask  from the USGS Earth Resources Observation and Science archive47 were analysed to identify change in fractional woody cover. We analysed 6 epochs of Landsat data between 1986 and 2016  and the mean reflectance values for observations between selected percentiles . Similar time-series metrics have been successfully used in forest cover mapping using Landsat data54. To further assist in differentiating between woody and herbaceous cover, which have different phenological metrics55, we derived the variance and range in vegetation indices over time for each epoch.The remote sensing analysis was performed using the Google Earth Engine cloud computing platform for earth observation and data analysisr Africa 986–2016 56. Training data were derived from image interpretation methods using very high spatial resolution images derived from Google Earth. We generated 4000 randomly scattered 30 × 30 m sampling quadrats, aligning with the Landsat pixel grid, within the unmasked areas for the given Landsat epoch collection. We manually classified the fractional woody plant cover of each sampling quadrat by identifying woody plant canopies using texture, colour and canopy shadows as identification cues  regression model to predict fractional woody plant cover for each 5-year epoch , the model assumptions were checked and satisfied, thus data were not transformed prior to fitting the model. Nevertheless, the analysis of drivers of woody cover change was performed on both untransformed and logit-transformed woody cover data, and both yielded similar results. Estimates of data quality were calculated for each pixel based on the number of available Landsat timepoints for the linear regression, and the total number of pixels used to derive time-series metrics 63 for comparison with GLDAS. Annual counts of extreme rainfall events, defined as any 5-day rainfall amount that exceeded the 95th percentile of all measurements for that gird cell64, were calculated. Rainfall variability was calculated as the standard deviation across both yearly and 5-hourly time series. The extent to which rainfall is evenly distributed though the year was calculated as the precipitation concentration index65 using data from the CHIRPS dataset. For each variable, we calculated the long-term average and the slope of the linear trend over time. WorldClim rainfall and temperature min, max, mean values for the driest, wettest, warmest and coldest quarters, and seasonality were also included66.High temporal resolution climatic data were obtained from the Global Land Data Assimilation System (GLDAS) produced by NASA at 0.25° every 3 h between 1986 and 20162 concentration data at 2 × 2.5° resolution were obtained from Atmospheric Infrared Sounder between 2010 and 201767. The means and trends were calculated per grid cell, but after consideration were not included in the modelling procedure for the following reasons: the data were collected at lower spatial resolution than all other explanatory variables; they were collected for the mid-troposphere and thus the relevance to ambient ground-level CO2 was questionable; and, unlike other bio-climatic variables, the range in the means (2 ppm) and temporal trends in CO2 (0.35 ppm yr−1) concentrations were very small  to induce significant changes in woody plant growth34. An attempt was also made to include the long-term CO2 trend in the model, however, because this is spatially homogenous it had very low explanatory power and was thus excluded.Mid-troposphere daily CO68. These included depth to bedrock (R horizon); bulk density (kg m3); cation exchange capacity (cmol kg−1); clay and sand content (% gravimetric); soil organic carbon content (g kg−1) and pH (in H2O). The data for six soil depths were aggregated by depth-weighted averaging . Digital elevation at 30 m resolution from the Shuttle Radar Topography Mission69 was used to calculate a terrain ruggedness index70, which measures the sum change in elevation between a pixel and its eight neighbouring pixels.Edaphic data were derived from the ‘SoilsGrid 1 km’ global dataset71 at quarter degree resolution. These included modelled grazer, browser, mixed feeder and total herbivore densities using the FOA livestock data19 and indigenous wildlife census data from reserves across Africa. To obtain a change layer for herbivore density, we constructed a BRT model (see methods in following section) to hind- and fore-cast herbivore densities. The FAO reference year used in the dataset was 2005, thus the 2001–2006 epoch was used as the starting point for hind- and fore-casting. The model was able to explain 72% of the total deviance in herbivore density. Explanatory variables included population density, normalised difference vegetation index, longitude, latitude, temperature, and rainfall which contributed 25, 24, 22, 21, 5, and 3% to the explanatory power of the model, respectively. The slope of the linear trend in modelled herbivore density was calculated for each 0.5° square. Despite the uncertainty in deriving herbivory trends, we found that its removal/addition in woody cover change models did not unduly influence model explanatory power. Removing change in herbivory from the model presented in Fig. Herbivory data were supplied by Archibald and Hempson72 were used to derive the annual average and annual trend in mean annual burned area, fire frequency, and burn date per 0.5 × 0.5° square between 2000 and 2017. Due to technical problems on the MODIS satellite experienced during 200173, we decided to exclude burned area for 2001 in our analysis. To derive trends in fire data that are representative of the study period (1986–2016), we followed the same approach as with herbivory and hind-cast fire data using a BRT model. The model, trained on the mean fire data between 2000 and 2017, was able to explain 70% of total deviance. For further validation, a separate model, trained on 2006–2011 mean data, was used to predict burned area for 2001–2006 and 2011–2016 mean data. The adjusted R2 of the linear regression between observed and predicted burned area for 2001–2006 and 2011–2016 was 0.66 and 0.72, respectively, thus corroborating the predictive capability of the model used for hindcasting. Explanatory variables included in the model were latitude, normalised difference vegetation index, population density, longitude, rainfall, and temperature, which contributed 24, 22, 17, 15, 14, and 8% to the explanatory power of the model, respectively. The equivalent analyses were conducted on fire intensity data from the Fire Information for Resource Management System dataset74. All fires that fell within the data mask  burned area monthly product at 500 m resolution.051 burnwww.wdpa.org)75. Quarter degree squares were classified into vegetation type76, ecoregion and biome77 based on the centroid of each grid cell. The average and trend in African population density between 2000 and 2015 at 1 km resolution was obtained from the Gridded Population of the World, Version 4 (GPWv4) dataset78.We determined the proportion of each 0.5° square covered by protected areas using data from Protected Planet  and called these drivers, and those without a temporal component (e.g. average precipitation) and called these facilitators of WPE. Prior to fitting the models, we identified a limited set of strongly collinear variable groups with an Data that support the findings of this study are available from the corresponding author upon request. The woody cover change raster is available at full resolution online via Google Earth Engine upon request.Supplementary InformationPeer Review File


All the meals were video recorded, and oral processing behaviours were derived through behavioural coding. Eating behaviours showed good to excellent consistency across the meals  and participants who ate faster took larger bites  and consistently consumed more energy, independent of meal palatability, sex, body composition and reported appetite . Importantly, eating faster at one meal predicted faster eating and increased energy intake at subsequent meals . Faster eating is relatively consistent within individuals and is predictive of faster eating and increased energy intake at subsequent similar meals consumed in a laboratory context, independent of individual differences in body composition.Faster eating has been identified as a risk factor for obesity and the current study tested whether eating rate is consistent within an individual and linked to energy intake across multiple meals. Measures of  Fast eating has been identified as a risk factor for increased energy intake , obesityIf faster eating is a risk factor for overweight, one prediction is that faster eating should be relatively consistent within an individual and linked to increased energy intake across multiple meals. In support of this, several early studies have characterised individuals based on the extent to which eating rate decelerated towards the end of a meal and reported good test–retest reliability for measures of within-meal eating microstructure, using both video recordings of bite and chewing behaviours ,22 and UDetermine the consistency of eating behaviours  within individuals.Describe the relationship between eating rate, oral processing behaviours, and energy intake across multiple meals.Test whether eating rate at one meal can be used to predict eating rate and energy intake at subsequent meals.The current research draws on data collected across four studies conducted recently in the Clinical Nutrition Research Centre (CNRC) to assess individual consistency in eating rate, oral processing behaviours, and food intake across multiple laboratory-based meals. In all of the studies, participants attended four identical test days to consume four similar meals ad libitum and have their eating behaviours recorded. Specifically, the research aimed to:Understanding whether eating behaviours measured at single eating occasion are likely to reflect eating behaviours at subsequent meals, within the context of the laboratory, has implications for a better understanding of the proposed relationship between oral processing behaviours, energy intake, and weight status.Participants were 146 male and female volunteers taking part in one of four studies running at the Clinical Nutrition Research Centre (CNRC) between July 2015 and September 2016. Study-specific methods are reported in detail elsewhere ,28,29. EThe rice-based test meals presented in Eating rate and oral processing of the test meals were determined by coding video recordings of participants during consumption, using previously established methods and described fully in recent papers ,31. A coAll behavioural coding was completed by trained researchers. Validation coding was conducted for a minimum of 10% of the total coded videos and had to show at least 80% agreement between all coders for the data to be accepted for analysis.Data were collected across four studies investigating the effect of food/beverage structure and energy density on satiation and satiety responses (rated appetite and subsequent intake). Participants believed they were taking part in studies investigating the effects of “food on mood”, and no participants took part in more than one of the studies.All participants completed a questionnaire assessing their health and dietary habits. Basic anthropometry was collected during screening (Studies 1–3) or upon study completion (Study 4). Each study required participants to consume four test meals ad libitum, either for lunch (Studies 1–3) or breakfast (Study 4) on four non-consecutive days with at least three days between each session. All participants fasted from 11 pm the evening before a study day.hunger, fullness, and desire to eat were presented on 100-point visual analogue scales (VAS) alongside distractor “mood” ratings of happy, stressed, alert, energetic, and clearheaded. The VAS question was “How <rating> do you feel right now”, anchored from Not at all <rating> (0) to Extremely <rating> (100). All ratings were presented in a randomised order and completed on the computer.All ad libitum test meals were served in individual air-conditioned booths at the CNRC and followed the same procedure across all studies. Each booth was fitted with a computer  and a webcam  mounted above eye level on the wall facing the subject. Participants were informed of the video recording during the consent process, but were unaware that the recording was used to assess oral processing behaviours. Participants were unable to see themselves on the video display, and the video was started as they were seated. Participants began the session by completing pre-meal appetite ratings disguised as “Mood Questions”. To do this, ratings of The test meals were served immediately after completion of the first set of appetite ratings, and participants were prompted to taste the food and rate its pleasantness using the same VAS format. Participants were then instructed “now you may eat as much or as little of the <test meal> as you like to feel comfortably full.” Participants were allocated 20 min to eat, and those who finished the portion within this time were provided with another immediately. The test meal was removed as soon as the participant indicated to the researcher that they were finished, at which point participants completed a set of post-meal appetite ratings. The total weight of food consumed was calculated by measuring the weight of the serving plate/bowl (i) empty before serving; (ii) full after serving; and (iii) at the end of the meal. All measurements were taken on a Sartorius balance accurate to 0.001 g.Intra-class correlation coefficients (ICCs) with 95% confidence intervals (CIs) were used to determine the consistency of Eating Rate (g/min), Oral Processing Behaviours , and Energy Intake  within individuals across the four test meals . Two-way random error were assumed, and an ICC value of <0.5 indicates poor consistency, 0.50–0.75 indicates moderate consistency, 0.75–0.9 indicates good consistency, and >0.90 excellent consistency .β) and unstandardized (b) betas are presented with bootstrapped 95% CIs and p-values.Multiple regression analyses were used to test the relationship between eating rate, energy intake and oral processing characteristics across the four meals. Preliminary analyses revealed a main effect of the Study on the relationship between eating rate and energy intake, due to the differences in texture and energy density in the study foods, so for clarity these data are reported separately for each of the four studies. These analyses controlled for meal pleasantness (a significant independent predictor of energy intake) and included “Eating Behaviour × Meal” interaction terms, which tested whether the relationships were consistent across different test days within the studies. Additional analyses were conducted to further control for other individual differences linked to eating rate and/or energy intake across the meals within this sample: BMI, % Fat Mass, Age, pre-meal appetite , sex (for Study 4 only) and reported restrained eating. For all analyses, standardised  could be used to predict eating behaviours at the other meals . All analyses were conducted in IBM SPSS Statistics version 23.F ≥ 7.42, p < 0.001). This means, for example, that individuals who ate at a faster rate had a larger bite size or consumed more did so consistently across the four meals within each study.The ICCs are reported in β = 0.28, b = 5.26 , p = 0.022), Study 2 , Study 3  and Study 4 . The strength of the relationship between eating rate and intake was consistent across all four meals in Studies 1 to 3 , but not in Study 4 when the meals varied in texture and energy density (see p < 0.001) and Meal 4 (p = 0.001), where the two higher energy porridges  were consumed, but was marginally similar to the relationship seen in Meal 3, when the thicker lower energy porridge was consumed (p = 0.056). After controlling for individual characteristics , the relationships between eating rate and intake remained significant across all of the studies and meals .sity see D. Specifβ ≥ 0.39, b ≥ 1.72, p < 0.001). Having a shorter oral exposure time per bite was independently associated with faster eating in Studies 2–4 , and marginally in Study 1 . Fewer chews per gram of food consumed predicted faster eating in Study 1  and 3 , but not Study 2  and 4 . Increased energy intake was also predicted by larger bite size across all studies  and shorter oral exposure per bite in Studies 3 and 4 , but not Studies 1 and 2 . Fewer chews per gram did not predict energy intake across any of the studies . All relationships were consistent across meals and remained after controlling for additional individual characteristics .Across all studies and meals, faster eating was characterised by participants taking larger bites  consistent within individuals from meal to meal; (ii) repeatedly associated with increased energy intake; and (iii) predicted faster eating and increased energy intake at other meals. This was independent of the study, test day, and individual differences in meal pleasantness, appetite, body composition, and reported eating style.A number of studies have now linked a faster rate of eating to increased energy intake within a single meal , and meaThough rate of eating appears to be a consistent eating behaviour within individuals, food texture is also an important determinant of oral processing, impacting eating rate and bolus formation, independent of the person consuming the food. For instance, harder, thicker, and chewier foods require more chewing, spend more time in the mouth, and are consumed at a slower rate than softer, less chewy foods ,34. The Understanding how individual differences in eating rate interact with features of the foods a person consumes to influence “real-world” energy intake is key to unpacking the link between the reported faster eating and higher BMI and obesity risk noted previously in observational studies ,10,11,12


Capripoxvirus in the family Poxviridae, are severely afflicting small ruminants’ production systems in Africa and Asia. In endemic areas, SPP and GTP are controlled using vaccination with live attenuated vaccines derived from SPPV, GTPV or Lumpy skin disease virus (LSDV).Sheeppox (SPP) and goatpox (GTP) caused by sheeppox virus (SPPV) and goatpox virus (GTPV), respectively of the genus Sometimes outbreaks occur following vaccination. In order to successfully control the spread of the virus, it is essential to identify whether the animals were infected by the field strain and the vaccine did not provide sufficient protection. Alternatively, in some cases the vaccine strain may cause adverse reactions in vaccinated animals or in rare occasions, re-gain virulence. Thus, diagnostic tools for differentiation of virulent strains from attenuated vaccine strains of the virus are needed.The aim of this study was to identify an appropriate diagnostic target region in the capripoxvirus genome by comparing the genomic sequences of SPPV field isolates with those of the most widely used SPP vaccine strains.A unique 84 base pair nucleotide deletion located between the DNA ligase gene and the VARV B22R homologue gene was found only in SPPV vaccines derived from the Romanian and Yugoslavian RM/65 strains and absent in SPPV field isolates originated from various geographical locations of Asia and Africa.In addition, we developed and evaluated a conventional PCR assay, exploiting the targeted intergenic region to differentiate SPPV vaccine virus from field isolates. The assay produced an amplicon size of 218 bp for the vaccine strains, while the SPPV field isolates resulted in a 302 bp PCR fragment. The assay showed good sensitivity and specificity, and the results were in full agreement with the sequencing data of the PCR amplicons.The developed assay is an improvement of currently existing diagnostic tools and, when combined with a capripox virus species-specific assay, will enhance SPP and GTP diagnosis and surveillance and facilitate epidemiological investigations in countries using live attenuated SPP vaccines. In addition, for laboratories with limited resources, the assay provides a simple and cost-effective alternative for sequencing.The online version of this article (10.1186/s12985-018-0969-8) contains supplementary material, which is available to authorized users. Capripoxvirus of the family Poxviridae [Sheeppox (SPP) and goatpox (GTP) are caused by sheeppox virus (SPPV) and goatpox virus (GTPV) of the genus xviridae . In endexviridae . They arxviridae .The main mode of virus transmission is the direct contact between diseased and non-infected animals, but indirect transmission may also occur . ClinicaSPP and GTP are endemic in many African, Middle Eastern and Asian countries and recurrent epidemics have occurred in Greece and Bulgaria in 2013–2014  and in GIn endemic regions, control of the disease is through effective immunization using killed or live attenuated vaccines derived from SPPV, GTPV or Lumpy skin disease virus (LSDV). In general, live attenuated vaccines are the better choice as compared to inactivated vaccines, as they confer long-lasting immunity. For instance, the Yugoslavian RM65, the Romanian Fanar and KSGP0240 strains, the most commonly used vaccines strains against SPPV, are reported to provide high levels of protection . The YugThe KSGP 0240 is widely used in several endemic regions in Africa. Nevertheless, KSGP0240 has been shown, by sequencing, to be a LSDV, thus, it can be differentiated from virulent isolates of SPPV using available capripoxvirus genotyping methods .However, when using live attenuated vaccines, the epidemiological investigation of outbreaks can become quite challenging. When outbreaks occur following vaccination, it is essential to identify whether the animals were infected by the field strain because the vaccine did not provide sufficient protection. Alternatively, in some cases the vaccine strain may cause adverse reactions in vaccinated animals or, in rare occasions, re-gain the virulence as suggested by Lee and co-workers for herpesvirus vaccine .Unfortunately, the current live attenuated capripox (CaP) vaccines do not offer the possibility to differentiate vaccinated animals from infected ones. This creates a need to identify a suitable genomic target and develop molecular tools that would enable the differentiation of SPPV field isolates from vaccine strains to rule out the involvement of SPP vaccines during a CaP outbreak in a vaccinated herd. Such a tool will facilitate the management and control of CaP infections in small ruminants.The present study describes the use of a suitable diagnostic target of the SPPV genome to develop an assay that can discriminate SPP vaccines derived from the Romanian and the Yugoslavian RM/65 strains from SPPV field isolates, to facilitate the diagnosis and surveillance of capripox virus (CaPV) infections in small ruminants.The information related to the field isolates and vaccine strains of SPPV as well as other CaPVs used in this study are presented in Table The target region was selected based on the alignment of the full genomes of three SPPVs, Sheeppox virus 10,700–99 AY077832), Sheeppox virus A (AY077833) and Sheeppox virus NISKHI, (AY077834), retrieved from GenBank, and the unpublished genome of the Romanian vaccine strain used in Morocco. PCR primers, flanking a unique nucleotide deletion in the Romanian vaccine strain, were designed using Primer3Plus online tool. The target was an intergenic region located between the DNA ligase gene and the VARV B22R homologue gene of CaPVs corresponding to position 121,500–122,799 of SPPV A (AY077833). The primers , 1× PCR buffer, and 2 μl template DNA. The cycling conditions were as follow: 95 °C for 4 min followed by 35 cycles of 95 °C for 30 s, 58 °C for 30 s, and 72 °C for 30 s and a final extension at 72 °C for 2 min. PCR products were cheeked by electrophoresis on a 2% agarose gel for 1 h at 100 V.The PCR amplicons of SPPV Denizli and SPPV Morocco vaccine (Romanian vaccine strain) were selected to prepare positive control plasmids, representing the field isolates and vaccine strains respectively. For plasmid preparation, each amplicon was purified and ligated into pGEM-T Easy Vector Systems (Promega). The ligated products were used to transform DH5α competent cells (Invitrogen). Plasmids containing the inserts were purified from the positive bacteria clones using the PureYield Plasmid Midiprep System (Promega) following the manufacturer’s instructions. The purified plasmids were sequenced to confirm the presence of the correct target region and quantified using the Quant-iTPicoGreen dsDNA Assay Kit (Invitrogen) on a NanoDrop 3300 fluorospectrometer. The concentration of the plasmids was determined following the steps described by Lamien et al., (2011) and the plasmids were kept at − 20 °C until analysis.7 to 100 copies/reaction, then follow by 80, 60, 40, 20, 10 and 1 copies/reaction dilutions, of plasmids containing the corresponding target of SPPV Denizli and SPPV Morocco vaccine. The lowest number of viral genome copies that could be detected by the assay was recorded.The analytical sensitivity of the method was assessed by amplifying 10-fold serial dilutions, from10Mycoplasma capricolum ssp. capripneumonia (Mccp), Bovine herpes virus (BOHV), Bovine popular stomatitis virus (BPSV) and cDNA derived from peste des petits ruminants (PPR) virus  and sequenced commercially by LGC Genomics (Germany). The sequence data were edited and the fragments assembled using Vector NTI 11.5 software (Invitrogen). Multiple sequence alignments were performed using the CLUSTALW algorithm implemented in BioEdit 7.5 software package to compare SPPV field isolates and vaccine strains. All sequences were deposited in GenBank under accession number MG764242 to MG764286.Primers were designed to amplify a region between the DNA ligase gene and the VARV B22R homologue gene of SPPV. The region was first selected based on the sequence alignment of three SPPV publicly available full genome sequences and a draft genome sequence of the SPP Morocco vaccine derived from the Romanian vaccine strain. The SPP vaccine had an 84 bp nucleotide deletion as compared to SPPV field isolates Fig. . The iniThe optimal assay parameters are presented in Methods. The optimised assay was further evaluated by testing 46 CaPV isolates or clinical samples including 12 field isolates of SPPV, 5 SPP vaccines, 13 field isolates of GTPV and 15 field isolates of LSDV and 1 LSDV vaccine (Table Mycoplasma capricolum ssp. capripneumonia (Mccp), Bovine herpes virus (BOHV), Bovine popular stomatitis virus (BPSV) and cDNA from peste des petits ruminant virus. No amplification was observed  presented a 34-nucleotide insertion as most LSDV of this study.In this study, we identified a suitable target in CaPV genome and developed a PCR method to discriminate SPP vaccine strains from SPPV field isolates as well as from other CaPVs.By aligning the full genome sequences of SPPV field isolates with the unpublished full genome of SPPV Morocco vaccine, a Romanian strain, we identified a region of 84 bp nucleotide deletion in the vaccine strains. Primers were designed to amplify this intergenic region located between the DNA ligase gene and the VARV B22R homologue gene of CaPV. The sequencing of this region in SPPV vaccine strains and SPPV field isolates available for this study, showed this deletion to be unique to the SPP vaccines derived from the Romanian and the Yugoslavian RM/65 strains produced in Algeria, Egypt, Morocco and Senegal. However, the sequence of the NISKHI vaccine, whose full genome has been previously published  did not Interestingly, Romanian and Yugoslavian RM/65 SPPV vaccines produced amplicons of shorter lengths, as compared to field isolates of SPPV and other CaPVs, and thus could be easily discriminated from them. The assay was found to be very specific and sensitive, and the accuracy and reliability was confirmed by sequencing the corresponding amplicons of SPP vaccine strains and SPPV, GTPV and LSDV field isolates available for this study.The high sensitivity of this assay for SPPV vaccine strain, as compared to the field isolates, is likely due to the shortest amplicon size in the vaccine strains. No amplification was detected for any non-CaPV samples by the assay. However, the assay could not differentiate SPPV field isolates from LSDVs and GTPVs. Although an insertion of 34–36 nucleotides was observed in all LSDVs, making them longer than GTPVs and SPPV field isolates, it was not possible to resolve these differences on the agarose gel. Owing to the availability of species-specific PCR –13 for CThe availability of an easy-to-use molecular method is needed for the identification of SPPV, to rule out the involvement of SPP vaccines following a CaP outbreak in previously vaccinated flock of small ruminants. In Middle Eastern and Asian countries, small ruminants are protected from CaPV infections using various SPPV, GTPV or LSDV derived vaccines, however, SPP vaccines derived from Romanian and the Yugoslavian RM/65 strains are predominant . In AfriThe molecular assay described herein is a reliable and rapid method that can easily be implemented for the differentiation of SPP vaccine derived from the Romanian or the Yugoslavian RM/65 strains from virulent SPPV field isolates. The method is applicable as a routine tool for outbreak investigations and disease surveillance in both SPP and GTP enzootic and disease-free countries. It is expected that its adoption by veterinary laboratories in CaPV affected countries, will help facilitate the control and management of CaP disease in small ruminants.Additional file 1:Table S1. Non-capripoxvirus samples tested for specificity study. (DOCX 16 kb)Additional file 2:Figure S1. Gel picture of PCR products for the remaining capripoxvirus samples. These sample were tested in this study, but not presented in Fig. Additional file 3:4, 103, 100, 80, 60, 40, 20, 10, 1 and 0) for SPPV vaccine (A) and SPPV field isolates (B) were tested in parallel reactions and run on agarose gel. (PDF 77 kb)Figure S2. Determination of the limits of detection of the PCR assay. Defined amount for the plasmid genotype standard ; 6 (BPSV); 7–8 (Mccp); 9 ; 10 (BOHV-1); 11 (BOHV-2). (PDF 45 kb)


Prunus sibirica L.), a temperate deciduous species distributed in this arid belt, using two chloroplast DNA (cpDNA) sequences, seven chloroplast microsatellite loci (cpSSRs), and 31 nuclear microsatellite loci (nSSRs), to study its phylogeography. Chloroplast data showed the complete fixation of two different genetic groups: the eastern and western groups. Genetic differentiation between the two groups was significant . This pronounced phylogeographic break was also indicated by nSSR data, but there were disparities regarding individual populations. An asymmetric gene flow via pollen and seeds likely resulted in discordance between the present-day geography of nuclear and chloroplast lineages. There was a distinct boundary between the two large groups, which were fixed for two of the most ancestral chlorotypes. Two populations with the highest chloroplast genetic diversity were located in the Yanshan Mountains and Jinzhou, considered to be the glacial refugia. The split of chloroplasts between the eastern and western groups was estimated to have occurred ~0.1795 Ma, whereas nuclear divergence occurred approximately 13,260 years ago. Linear regression analysis showed that climatic factors  had a significant correlation with mean ancestry value (P < 0.05) indicated that they were potential factors for the formation of the two groups. In addition, this boundary was a contact zone between two groups from different refugia.There is evidence that a band of dry climate separated plants in East Asia into distinct northern and southern groups. However, few studies have focused on the arid belt in this region, especially with regard to plants. We analyzed genetic variation in 22 populations of Siberian apricot ( Phylogeographic studies have been used to investigate the effects of past climatic changes on the genetic structure of plant species, and allow inferences to be made about species evolution. The distribution ranges of plants and the genetic diversity within and among present-day populations of such organisms in the Northern Hemisphere have been affected deeply by climatic changes over the last 2 million years Hewitt, . It has Instead of a physical barrier , an east-west arid belt which was between 35 and 45°N, has been thought to act as a climate barrier between the two regions . Northern China (including north and northeast China) is covered with diverse plant biomes that range from tropical to cold forests and taiga , covering the whole range of East Asia, to study the role of the climate barrier in diversification. Both nuclear and chloroplast data showed that the Yanshan Mountains contained a dividing line, separating the northeast and southwest lineages. Similar results have been described in other species, such as, walnut  is one of them. This temperate, deciduous, and wind-pollinated species is distributed widely across the mountainous areas of north and northeast China. It can also be found in eastern Siberia and Mongolia  than for nuclear DNA Ennos, . Indeed,In this study, we re-ran the STRUCTURE analysis using nSSR data we obtained, and used a set of chloroplast simple sequence repeats (cpSSRs) and cpDNA sequences to analyze Siberian apricot populations in China. The major aims of this study were to address the following questions: (1) How did nuclear DNA and cpDNA lineages of Siberian apricot distribute? (2) Does the Siberian apricot show any concordance between the geographical distribution of cpDNA and nuclear DNA lineages? (3) Did refugia exist in the Siberian apricot distribution regions? (4) What is the potential factor(s) of the formation of different lineages?In total, 672 Siberian apricot individuals were collected from 22 populations covering the entire range of the natural distribution in China  for 1 min, and 72°C for 1 min, followed by 8 cycles of 94°C for 30 s, 53°C for 40 s, and 72°C for 45 s, with a final synthesis step at 72°C for 10 min. The products were separated with an ABI 3730XL DNA Analyzer using GeneScan-500LIZ as an internal marker . The fragments were sized using the Gene-Marker 1.75 software .We selected 19 cpSSR markers after an initial screening from 40 candidate cpSSR markers . Amplification was carried out under the following conditions: 94°C for 5 min, followed by 35 cycles of 94°C for 1 min, Tm for 1 min, a 2-min extension at 72°C, and a final synthesis step at 72°C for 10 min. PCR products were purified using a TIANquick Midi Purification Kit following the manufacturer's protocol (Tiangen). Purified PCR products were sequenced directly in both directions using the PCR primers on an ABI 3730XL DNA Analyzer (Applied Biosystems).Using universal primers, we conducted an initial screening for sequence variability of various chloroplast markers against 15 samples. The cpSSR haplotypes of the 15 samples were different from each other based on the result of completed cpSSR analysis. The intergenic spacers (IGSs) of the following pairs of genes were amplified using previously published primers: T, average within-population diversity HS, and two differentiation measures  were estimated for haplotypes and compared via a test with 1,000 permutations using Permut 2.0 software , the effective number of haplotypes (Ne), the number of private haplotypes (Np), Nei's haplotype diversity (H), and the unbiased haplotype diversity (He) Nei, . Total gatpB-rbcL and trnQ-rps16 sequences were combined into a complete sequence. Multiple alignments were performed with the ClustalX program  were estimated with the same parameters as cpSSR analysis. All populations were grouped by performing spatial analysis of molecular variance (SAMOVA) using the SAMOVA software (ver. 1.0)  for the “best” grouping of populations. Then, the observed genetic variation among and within the populations and groups was characterized by an analysis of molecular variance (AMOVA) using ARLEQUIN (ver. 3.5) software  reported for the angiosperm species 1–8.24 × 10−9 s s−1 y−1 to estimate the timescale of divergence  steps. A uniform prior probability distribution was used to accommodate the uncertainty of the prior knowledge. We compared the outcomes of all five clock models with the Yule speciation process by using the TRACER program (ver. 1.6)  software were implemented to estimate phylogenetic relationships and divergence times between cpDNA haplotypes  software  program was used to simplify the comparison of clustering results from the STRUCTURE programs across all 20 repetitions of K and to determine the most likely number of clusters.In this study, we used the correlated allele frequencies model and the admixture model .An approximate Bayesian computation (ABC) approach was used to infer the recent colonization history of the Siberian apricot. The STRUCTURE analysis revealed two clusters that corresponded to the western group (WG) and northeastern group (EG). To determine which among several scenarios of the history of divergence of populations from these regions was the most probable, we used the ABC procedure in DIYABC (ver. 2.0.4) software  was significantly smaller than NST .Seven perfect chloroplast microsatellite loci were used to assay 222 Siberian apricot individuals, resulting in 18 different alleles. In total, 15 unique cpSSR haplotypes were produced by combinations of the 18 different alleles. Details of the haplotype frequency and population genetic diversity are provided in Supplementary Tables atpB-rbcL and trnQ-rps16) was 1,400 base pairs in length. Six nucleotide substitutions and five indels were found in the combined fragment which revealed eight cpDNA haplotypes  was not significant higher than GST (0.862). Five populations were polymorphic while the remaining 17 were fixed for a single haplotype ; ; ; (P13); (P17); and (P22). Meanwhile, AMOVA of the six groups revealed that 91.70% of the variance was distributed among groups  were divided into two clades, one associated with the EG and the other with the WG , based on chloroplast variation across all populations, was much smaller than the total genetic diversity, HT (0.809). A permutation test showed that NST (0.871) was significantly higher than GST .In combination, the mixed cpDNA sequences identified 21 chlorotypes , , and . SAMOVA of chloroplast data variation separated all populations into two large groups and one small one. The two large groups had a distinct boundary, which was the longitude lines of P16 , and the second largest ΔK was at K = 2 (ΔK = 9.30). However, the absolute values of ΔK were very small  showed an upward trend until 0 Figure . The vall Figure . The CLUK Figure . The bigmWGEG →  was 344.75, and that of 4 NmEGWG →  was 322.86. Linear regression analysis showed that the annual precipitation had a significant correlation with mean ancestry value (P = 0.00103 < 0.01) whereas annual mean temperature had a significant correlation with mean ancestry value at P = 0.05 level . The genetic diversity of cpDNA (HT = 0.652) showed a relatively lower level of genetic diversity than those in other deciduous tree species, such as, Prunus spinosa  than that of 170 plant species  was significantly higher than that of GST (0.758) using mixed cpDNA sequence data, indicating the presence of a phylogeographic structure. The grouping of populations produced by SAMOVA of mix-sequences variations strikingly similar to that of STRUCTURE, based on nSSRs  during the LGM  originated from a single glacial refugium, which was located in the Changbai Mountains  were likely the refugia for the WG and EG, respectively. Moreover, an isolated microrefugium (P22), near the Changbai Mountains, was suggested within the EG. Overall, apart from geographic barriers, our findings highlight the importance of climate in the present-day distribution of temperate deciduous trees in northern China.KY000823-KY000832.All cpDNA sequences were deposited in GenBank under the accession numbers ZW, RW, and XP planned and designed the research. ZW, ZZ, JT, and SS performed experiments and analyzed data, and ZW, YZ, and XP wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Developing an effective HIV vaccine is the overriding priority for HIV prevention research. Enrolling and maintaining cohorts of men into HIV vaccine efficacy trials is a necessary prerequisite for the development and licensure of a safe and efficacious vaccine.One hundred-fifty consenting HIV-negative men were enrolled into a pilot 1:1 randomised controlled trial of immediate vaccination with a three-dose hepatitis B vaccine compared to deferred vaccination (at 12 months) to investigate feasibility and acceptability of a future HIV vaccine trial in this population. Adverse events, changes in risk behaviour, acceptability of trial procedures and motivations for participation in future trials were assessed.P = 0.338). Acceptability of trial procedures and services was very high overall. However, only 65% of the deferred group strongly liked being randomised compared to 90% in the immediate group (P = 0.001). Informed consent processes were viewed favourably by 92% of the delayed and 82% of the immediate group (P = 0.080). Good quality health services, especially if provided by a male nurse, were rated highly. Even though almost all participants had some concern about the safety of a future HIV vaccine (98%), the majority were willing to participate in a future trial. Future trial participation would be motivated mainly by the potential for accessing an effective vaccine (81%) and altruism (75%), rather than by reimbursement incentives (2%).Men were a median 25 years old (inter-quartile range = 23–29), 53% were employed, 90% secondary school educated and 67% uncircumcised. Of the 900 scheduled study visits, 90% were completed in the immediate vaccination arm (405/450) and 88% (396/450) in the delayed arm  contains supplementary material, which is available to authorized users. In 2015, there were 37 million people estimated to be living with HIV globally; 26 million in sub-Saharan Africa (SSA), of which 10 million were men . An effeConducting large phase III HIV prevention trials is challenging, however, and relatively little is known about men’s participation in HIV prevention research . Most HICurrent evidence for HIV vaccine acceptability and trial feasibility comes largely from studies focussing on women , 17, peoRecent experiences of suboptimal adherence to potentially efficacious interventions in HIV prevention trials have provided a timely reminder about the importance of including end-user perspectives in the design and delivery of prevention products , 27. We From August to September 2011, participants were recruited from primary health care clinics in Johannesburg Region F, male-oriented venues in the community and referrals from enrolled participants. The following clinics were involved: Esselen, Jeppe Joubert Park, Malvern, Marshalls Town, Mayfair, Rosettenville and Yeoville clinics, and the Hillbrow Community Health Centre. Men were considered eligible for enrolment if older than 18 years, sexually active (had sex in past 3 months), HIV negative, negative for hepatitis B core antigen and hepatitis B surface antigen , and if they had no clinical evidence of chronic hepatitis B infection. Men with a history of bleeding disorders, hypersensitivity to the hepatitis B vaccine or its ingredients, and those with evidence of acute infection or a fever >37.8 °C were excluded. Those excluded for medical conditions were referred to local health care facilities for further management and care.Eligible participants who demonstrated adequate understanding of trial procedures through a comprehension checklist were enrolled after providing written informed consent for study participation and for long-term storage of biological specimens. Informed consent procedures included a thorough explanation of randomisation concepts, study visit schedules and encouragement of participants to discuss any concerns about the study. A pre-vaccination assessment, including physical and genital examination, was performed for evidence of sexually transmitted infections (STIs).Sequentially numbered envelopes containing study allocation were pre-prepared by an independent statistician based on simple randomisation using a random number list. Envelopes were assigned consecutively and opened in the presence of the participant. Participants were randomised 1:1 to receive immediate vaccination (IV) or deferred vaccination (DV). The hepatitis B vaccine ENGERIX-B or equivalent generic from the GSK Biologicals was administered in three doses during the study in the IV group . Participants in the DV group were offered vaccination at the month 12 visit, again given in three doses. In accordance with manufacturer’s instructions, 1-mL adult dose was provided, that contains 20 mcg of hepatitis B surface antigen adsorbed on 0.5 mg aluminium as aluminium hydroxide. The adult formulation contained sodium chloride (9 mg/mL) and phosphate buffers . Vaccination was deferred to the next visit in those that had evidence of an acute febrile illness.The hepatitis B vaccine was selected as it shares some features with a potential HIV vaccine: the infective agent in both cases is a virus that causes chronic infection and shares transmission modes, and the hepatitis B’ vaccine’s multi-dose regimen is likely analogous to that of a future HIV vaccine. Deferring vaccination, rather than administering a placebo vaccine, for example, enabled us to compare the hypothetical perspectives and adverse events between the groups. Relative rates of adverse events in the two groups may provide useful information on the expected rates of vaccine site soreness or swelling in future HIV vaccine trials, for example. Lastly, providing a vaccine after study completion may actually occur in HIV vaccine trials, where participants in a placebo arm may be invited to receive the HIV vaccine if it were shown to be effective.TM), followed by Unigold RecombigenTM. Discordant results were confirmed using Vironostika HIV-1 ELISA testing. Blood samples at baseline were also tested for syphilis  and HSV-2 . Urine samples were tested for N. gonorrhoeae, C. trachomatis and T. vaginalis using a multiplex PCR .Following randomisation, participants were seen at monthly intervals for the first 3 months of follow-up, and then quarterly until month 12. A structured interviewer-administered questionnaire was administered at baseline and every 3 months thereafter. At screening for study enrolment and each quarterly visit, participants were also counselled and tested for HIV using Determine HIV-1/2 rapid tests . Those testing positive for HIV during the trial were retained in the study, and referred to local HIV treatment facilities for further care.At month 12, to assess acceptability of participation in the current trial and in future HIV vaccine trials, we collected data on participants’ perspectives on several aspects of the study procedures (10 items) and clinical services they had received (10 items). In these measures, participants were asked to rate how they felt about the procedure or service on a scale of 0–5 (with 0 being those least liked and 5 being most liked).P < 0.1) and model fit assessed using goodness of fit tests. The variables study group (DV and IV) and age were forced into the model. In a separate univariate analysis, we also explored whether any of the 20 acceptability items were associated with retention. In this exploratory analysis we defined retention as having attended all four visits .The primary outcomes were the proportion of men screened who fulfilled all eligibility criteria and accepted enrolment; the number of expected visits actually attended; and the proportion successfully retained in the trial at 12 months. We also calculated the ratio of screened-to-enrolled men and used Generalised Estimating Equations to identify factors associated with retention. Model selection was carried out beginning with the set of significant univariate predictors  at quarterly visits. HIV incidence and the point prevalence of STI episodes were estimated in the overall cohort. Differences between categorical variables were examined using the chi-square test or Fisher’s exact test when the expected values in any of the cells was below five . Wilcoxon = 75) or deferred (n = 75) vaccination (screen-to-enrol ratio = 1.89). The main reasons for non-enrolment were positive hepatitis B serology or HIV infection .In total, 284 men were screened and 150 then randomised to receive immediate  of the expected visits were completed , and in those who had lived in Johannesburg for over a year, compared to briefer periods .In the IV group, no participants refused vaccination post-enrolment, but 5% missed dose 2 (4/75) and 8% dose 3 (6/75). Two had vaccinations deferred until the next visit, one with a contra-indication (flu) and one who missed the scheduled visit. Dose completion in the IV group was more frequent in men reporting consistent than inconsistent condom use in the 3 months prior to baseline  of participants in the DV group returned for hepatitis B vaccination. Reasons given for non-acceptance included unwillingness to be vaccinated (6) and current receipt of TB treatment (1). No differences were noted in the sociodemographic characteristics or acceptability measures between those in the DV group who were or were not vaccinated.p ≤ 0.001; Table Overall, 61 AEs were reported. All AEs were non severe (Grade 1) and no allergic reactions related to vaccination were reported. More AE were reported by the IV than DV study arm  were observed over the 1598.3 person-months of follow up . No incident cases of hepatitis occurred during the trial. All five infections occurred in the first 6 months of follow-up.P = 0.061). At study end, participants rated the validity of their responses to self-reported questions, scoring themselves relatively high with condom use (IV 60 [88%] vs. DV 56 [85%]), number of partners (IV 65 [96%] vs. DV 58 [88%]) and sexual behaviour in general (IV 67 [89%] vs. DV 65 [98%]).In both study groups, men reported a higher coital frequency and lower condom use at baseline than at all subsequent visits Table . CompareP = 0.001). By contrast, 92% of the DV group held favourable views on the informed consent processes, compared to 82% of the IV group (P = 0.080). The collection of blood and genital specimens were viewed relatively unfavourably by both groups.Of the study procedures assessed, more than 90% of participants rated questionnaire completion, repeated HIV testing and receipt of reimbursements as a 4 or 5 out of 5 (Table P = 0.075). Other highly preferred aspects of the clinical services in both groups (>90% participants scored item as 4 or 5) were: clean clinic environment, clinic staff attitudes, free treatment and condoms, and counselling and health information, and the hepatitis B vaccine itself. Only 79% of the IV and 83% of the DV group scored travel time favourably (P = 0.560).In terms of the clinical services and visits, in both groups, being examined by a male nurse was viewed as more acceptable than a female one. All men in the IV group liked being examined by a male nurse, while these views were not universal among men in the DV group . The main motivations for participation were potential HIV protection (81%), to help find a vaccine that works (75%), and to help others (68%). Interestingly, only 2% reported that reimbursements for study visits would motivate participation. Free HIV testing and treatment, and knowing someone with HIV were also not regarded as incentives for participation. No variations by study group were observed in these views. Almost all viewed side effects as a major concern for future trial participation (98%).WTP in a future HIV vaccine trial was high in both groups . Few viewed ease of access , side effects , cost , number of doses  and duration that the vaccine was on the market  as important factors influencing whether they would accept an HIV vaccine known to be effective. Again, findings were similar between the two study arms.This study indicates that it is feasible to recruit and retain a population of high-risk heterosexual men in an HIV vaccine trial in Johannesburg, South Africa. Recruitment was relatively efficient, with a screen-to-enrol ratio under two. Compared to non-eligible men, however, those enrolled in the study had lower risk behaviours and consequently are likely to have fewer incident HIV infections. This phenomenon raises the sample size required for demonstrating efficacy of an intervention . Follow-In both study arms, the levels of WTP in an HIV trial were among the highest recorded among men in similar studies to date. In a review of 16 preparedness studies , willingUse of a surrogate vaccine and randomisation into immediate and deferred vaccine groups provided useful insights. Most especially, we were able to evaluate the relative acceptability of the different components of a future vaccine trial. The levels of discontent about the informed consent procedures in the IV arm suggest that participants require more information during consent relating to the vaccine and study procedures. Consent also needs to focus on ensuring participants comprehend the concepts of randomisation and unknown efficacy to avoid therapeutic misconception and potential increases in risk behaviours.Also, in this study, as in others , 25, parEven though men in the IV group experienced higher rates of adverse events than those allocated to DV, cohort retention was similar between study arms. While these events were all minor, this finding seemingly contrasts with that of a systematic review of qualitative studies on participation in HIV vaccine trials . That reA potential concern for all randomised blinded placebo controlled trials of HIV preventive technologies is the possibility that participants believe themselves to be protected against HIV, despite the vaccine’s unknown efficacy and the possibility that they were randomised to the placebo arm , 18. In Overall, we contend that the use of randomisation, an actual vaccine and an untreated control group extends to knowledge beyond previous hypothetical vaccine studies. However, though the study findings might help optimise the design of future HIV vaccine trials, recruitment and retention rates in this study may not necessarily reflect those of a future trial. Firstly, the hepatitis B vaccine is of proven efficacy and hepatitis B differs from HIV in many important ways. Moreover, self report of WTP does not necessarily translate into participation in an HIV vaccine trial , 22, 24.Despite its limitations, the study was able to demonstrate a high degree of WTP in future trials, as shown by the actual retention rates and views expressed on the issue. Recruitment of men into vaccine trials that address the concerns raised here is therefore likely to be feasible and acceptable in this setting. While access to vaccines was an important motivation for enrolment in a future trial, quality health services were viewed as equally important, especially those provided by a male health worker. Moreover, the differences noted between study groups in sexual behaviour shows that changes in sexual behaviours might be anticipated in a vaccine trial in this population. Lastly, use of a surrogate vaccine, unlike previous studies based on hypothetical acceptability , 24, 40,Additional file 1: Table S1.Factors associated with participant retention; a generalised estimating equations analysis. (DOCX 28 kb)Additional file 2: Table S2.Association between perspectives on acceptability collected at 12 months and attendance at all four study visits. (DOCX 29 kb)


Coregonus clupeaformis representing a continuum in the early stage of ecological speciation. We sequenced the 16s rRNA gene V3-V4 regions of the intestinal microbiota present in a total of 108 wild sympatric dwarf and normal whitefish as well as the water bacterial community from five lakes to (i) test for differences between the whitefish intestinal microbiota and the water bacterial community and (ii) test for parallelism in the intestinal microbiota of dwarf and normal whitefish.It is well established that symbionts have considerable impact on their host, yet the investigation of the possible role of the holobiont in the host’s speciation process is still in its infancy. In this study, we compared the intestinal microbiota among five sympatric pairs of dwarf (limnetic) and normal (benthic) lake whitefish The water bacterial community was distinct from the intestinal microbiota, indicating that intestinal microbiota did not reflect the environment, but rather the intrinsic properties of the host microbiota. Our results revealed a strong influence of the host  on the intestinal microbiota with pronounced conservation of the core intestinal microbiota (mean ~ 44% of shared genera). However, no clear evidence for parallelism was observed, whereby non-parallel differences between dwarf and normal whitefish were observed in three of the lakes while similar taxonomic composition was observed for the two other species pairs.This absence of parallelism across dwarf vs. normal whitefish microbiota highlighted the complexity of the holobiont and suggests that the direction of selection could be different between the host and its microbiota.The online version of this article (10.1186/s40168-018-0427-2) contains supplementary material, which is available to authorized users. Therefoal cells –12. The al cells –15, whical cells .The concept of holobiont offers a new angle for the study of adaptive divergence ultimately leading to speciation. For instance, the role of microbiota on pre-zygotic isolation has recently been documented . MoreoveThe intestinal microbiota could be particularly prone to playing a key role in the process of population divergence and speciation given its broad array of functional impacts on its host . The invWhile there are now a plethora of studies that have documented the positive influence of holobionts on hosts, including humans, relatively few studies have focused on fish microbiota in the wild even though they represent around 50% of the total vertebrate diversity , 38. To Coregonus clupeaformis) comprises sympatric species pairs referred to as dwarf and normal whitefish that are found in five lakes of the St. John River drainage in the province of Québec, Canada, and in Maine, USA. A relatively recent period of post-glacial adaptive radiation occurred approximately 12,000 years before present (YBP), leading to parallel phenotypic and ecological divergence in different lakes of the dwarf whitefish derived from the ancestral normal whitefish [Lake whitefish  were sampled with gill nets from Cliff Lake, Indian Pond, and Webster Lake in Maine, USA, in June 2013, and from East and Témiscouata lakes in Québec, Canada, during summer 2013, from May to July  of each specific primer, 21 μl of sterile nuclease-free water, and 2 μl of water bacterial DNA (around 5 ng/μL). The PCR program consisted of an initial denaturation step at 98 °C for 30 s, followed by 30 cycles, with 1 cycle at 98 °C for 10 s (denaturation), 56 °C for 30 s  and 72 °C for 45 s (extension), and a final extension of 72 °C for 5 min. Negative and positive controls were included for all PCRs. All the PCR results, including the negative controls, were purified using the AMPure bead calibration method. The purified samples were quantified using a fluorometric kit , pooled in equimolar amounts, and sequenced paired-end using Illumina MiSeq Bakt_341F-long and Bakt_805R-long at the Plateforme d’Analyses Génomiques . To prevent focusing, template building, and phasing problems due to the sequencing of low-diversity libraries such as 16S rRNA amplicons, 50% PhiX genome was spiked in the pooled library.Raw forward and reverse reads were quality trimmed, assembled into contigs for each sample, and classified using Mothur v.1.36.0 , 64. Convegan package [vegan package in R to test the species effects, the lake effects, and their interaction. The METASTATS software with standard parameters was also used (p ≤ 0.05 and number of permutations = 1000) to detect differential abundance of bacteria at the genus level between dwarf and normal whitefish [P values and Bonferroni corrections were calculated for Spearman’s correlations for each sample. Then, the different networks were visualized using Cytoscape version 3.2.1, a software for visualizing networks [A matrix containing the number of bacterial sequences was constructed for each genus in each fish sample from the two Mothur taxonomy files (stability.an.shared and stability.an.cons.taxonomy). Therefore, OTUs  with the same taxonomy were merged. This genus-merged matrix was used to perform the taxonomic composition analysis at the phylum and genus level, the principal coordinate analyses (PCoA), the permutational analysis of variance (PERMANOVA), the Metastats analysis, and the network analysis. Moreover, to determine if there was a significant difference at the alpha diversity level between species within and among lakes, we used a generalized linear model (GLM) with a Gaussian family followed by an ANOVA. In order to build the PCoAs, a Jaccard distance matrix was made from the genus-merged matrix after Hellinger transformation using the  package  in R  and 36 bacterial water samples , Actinobacteria (33.5%), Bacteroidetes (10.6%), Verrucomicrobia (4.4%), OD1 (2.0), and Firmicutes (1.9%). The five most abundant phyla of dwarf intestinal microbiota were Proteobacteria (40.6%), Firmicutes (17.8%), Actinobacteria (6.1%), OD1 (5.5%), and Bacteroidetes (3.4%), whereas the five most abundant phyla of normal microbiota were Proteobacteria (39.0%), Firmicutes (20.1%), Fusobacteria (4.1%), Actinobacteria (4.1%), and Tenericutes (2.5%). Thus, the phylum Proteobacteria dominated all sample types, but other phyla differed between the fish microbiota and water bacterial communities. Moreover, even if Proteobacteria, Firmicutes, and Actinobacteria were present in similar abundances between dwarf and normal microbiota, the phyla OD1 and Bacteroidetes were more present in dwarf whitefish and the phyla Fusobacteria and Firmicutes were more present in the normal whitefish.Highly different communities at the genus level were observed with weighted UniFrac and PERMANOVA tests between the water bacterial community and whitefish microbiota within each lake and among the lakes Table . MoreoveFST = 0.28) whereas those from Témiscouata Lake are the least differentiated (FST = 0.01). Thus, if there was some association between the extent of genetic divergence and the difference in microbiota, dwarf and normal whitefish from Cliff should have the most differentiated intestinal microbiota and Témiscouata should have the least differentiated ones. This was not the case as species specific microbiota was observed in the latter lake, whereas no significant difference was found in both Indian and Webster lakes where genetic differentiation between dwarf and normal whitefish is more pronounced (FST Indian = 0.06 and FST Webster = 0.11).There was a significant difference between the dwarf and the normal whitefish microbiota at the genus level across all lake populations combined Table . When trThe weighted UniFrac, which took into account the bacterial abundance rather than simply the presence or absence of taxa in the samples, were significant in all lake populations Table . TherefoBased on the network analysis, the five networks corresponding to each lake gave results that were similar to those obtained with the PCoA analysis, further supporting the observation that the dwarf-normal difference in microbiota varies according to the lake Fig. . AlthougPutative microbiota functions were predicted using PICRUSt by assignment of the predicted metagenome Fig. . The genThere was no difference between the dwarf and the normal whitefish in terms of bacterial diversity. Thus, the inverse Simpson index was not significant either between species within lakes or between lakes Table . SimilarOD1, Methylobacterium, and Clostridium. Additionally, all dwarf whitefish populations shared Flavobacterium, TM7, and Pseudomonas, whereas all normal whitefish populations shared Aeromonas. Within a given lake, more genera were shared between dwarf and normal whitefish, their number varying between four and 11 depending on the lake  test for differences in whitefish intestinal microbiota and water bacterial community from the same lake, (ii) test for differences in intestinal microbiota between dwarf and normal whitefish from the same lake, and (iii) test for the occurrence of parallelism in those patterns. Below, we discuss the main results obtained for each of these objectives, as well as their relevance in the context of ecological speciation.In order to improve the laboratory protocol and avoid bacterial contamination, meticulous care was taken by working in sterile conditions, performing blank extractions, using positive and negative PCR controls, and sequencing negative PCR controls. These controls revealed very few sequences in negative PCR controls  and their environment [Gasterosteus aculeatus) tends to be more similar to food-associated bacteria rather than water-associated bacteria [The whitefish intestinal microbiota was not reflective of the whitefish environment within each lake tested. Therefore, host physiology, immunity, and genetic background may play a role in determining the internal intestinal microbiota , 47, 81.ironment . Howeverironment , 82 or vironment . Howeverbacteria . AlthougProteobacteria is reported to be the most abundant phylum [Firmicutes, Bacteroidetes, Actinobacteria, Acidobacteria, Chlamydiae, Fusobacteria, Planctomycetes, Spirochaetes, TM7, Verrucomicrobia, and Tenericutes has been reported in many freshwater fishes [OD1, which was present at a relatively low frequency in both dwarf and normal whitefish, has usually been reported in freshwater samples but not freshwater fish, further supporting the acquisition of part of whitefish microbiota from the environment [In this study, only the bacteria that formed a stable and specific association with the whitefish were analyzed. In fact, only the intestinal adherent microbiota of whitefish was selected, allowing for an indirect investigation of the host effect. In freshwater fishes, the dominant t phylum . Also, tr fishes , 84, 85.ironment , 87.Colossoma macropomum) that reported 121 and 525 genera, respectively [Danio rerio) intestinal microbiota study, where the number of OTUs decreased during zebrafish development until reaching an equilibrium at fish maturity [Globally, we observed a total of 421 different genera in the intestinal mucosa from 108 fish. This is comparable to the level of diversity reported in other recent studies that analyzed 30 intestinal contents of five wild African cichlid fish species (tribe Perissodini) and 72 feces of the wild Amazonian fish tambaqui , suggesting that the host had an effect on bacterial diversity [Interestingly, our data revealed no difference in diversity between intestinal microbiota of dwarf and normal whitefish found in sympatry within a given lake. This is in contrast with our previous study on kidney tissues where normal whitefish harbored a higher diversity than dwarf whitefish in all five lakes studied . We had iversity . Thus, tiversity , 49. TheDanio rerio) [Sequencing the microbial world has revealed an overwhelming intestinal microbiota impact on the host and has allowed documenting the core intestinal microbial communities in mammalian and teleost fish , 91–93. o rerio) . Here, oo rerio) , 47. TheParallelism is the evolution of similar traits in independent populations . In the All in all, we found no clear evidence of parallelism in the intestinal microbiota across the five dwarf and normal whitefish species pairs. Instead, our results suggested that the main source of variation in whitefish microbiota was the lake of origin. As mentioned above, an important proportion of the intestinal microbiota could be attributed to the colonization by bacteria from the water. However, each lake studied had a distinct water bacterial community . Although the whitefish host could modulate the intestinal microbiota, the lake bacterial variation could positively or negatively influence the intestinal microbiota of whitefish species. Cliff, Webster, and Indian lakes harbor the most genetically divergent species pairs, whereas East and Témiscouata species pairs are the least differentiated , 74. TheNeotoma lepida) enables its host to feed on creosote toxic compounds, suggesting a fitness advantage by limiting resource competition [Nasonia vitripennis and Nasonia giraulti) to create F2 hybrid larvae raised with their symbionts  and without the symbionts (germ free). The F2 lethality was clearly more important with symbionts  than without symbionts (germ free). Moreover, this lethality was not seen in pure larvae of both species reared with symbionts. Symbionts can also increase the host phenotype plasticity [Acyrthosiphon pisum) to acquire a new phenotype: the digestive capability of alfalfa (Medicago sativum) [Most of adherent bacteria living on the intestinal mucosa are not randomly acquired from the environment , but arepetition . Symbionpetition , 17. In petition . Second,petition . These aasticity . For exasativum) . This neIn summary, we analyzed the intestinal microbiota in the context of population divergence and speciation in the natural environments. We selected the whitefish mucosa; only the bacteria which formed a stable and specific association with the whitefish were analyzed. To our knowledge, this is the very first study which sequenced the intestinal adherent microbiota in natural fish host populations. Our main goal was to test for the occurrence of parallelism in the microbiota of dwarf and normal whitefish that evolved in parallel across different environments. However, no clear evidence for parallelism was observed at the bacterial level. We found distinct microbiota between the dwarf and the normal species in three of the five lake populations suggesting more selective pressure from the environment. This absence of parallelism across dwarf vs. normal whitefish microbiota highlighted the complexity of the holobiont and suggests that the direction of selection could be different between the host and its microbiota. Furthermore, the comparison of the adherent microbiota with the water bacterial environment and whitefish kidney bacterial community  providedAdditional file 1:Table S1. Steps used to reduce sequencing and PCR errors. (XLSX 9 kb)Additional file 2:Table S2. Bacterial taxa found in the PCR negative control. (XLSX 19 kb)Additional file 3:Table S3. Bacterial species specific to a single whitefish species within lake obtained with Metastats and BLAST. (XLSX 17 kb)