A. thaliana populations over 5 successive plantings whose timing was determined by the natural progression of the plant’s life cycle and disentangle the environmental and genetic factors that drive plant ecological performance at a given locality. We show that, at the temperate latitude where the experiment was conducted, a given genotype can experience winter-, spring- or summer-annual life cycles across successive seasons. Lifetime fitness across these seasons varied strongly, with a fall planting yielding 36-fold higher fitness compared to a spring planting. In addition, the actual life-stage at which plant overwinter oscillated across years, depending on the timing of the end of the summer season. We observed a rare but severe fitness differential coinciding with inadequate early flowering in one of the five planting. Substrate variation played a comparatively minor role, but also contributed to modulate the magnitude of fitness differentials between genotypes. Finally, reciprocal introgressions on chromosome 4 demonstrated that the fitness effect of a specific chromosomal region is strongly contingent on micro-geographic and seasonal fluctuations. Our study contributes to emphasize the extent to which the fitness impact of phenotypic traits and the genes that encode them in the genome can fluctuate. Experiments aiming at dissecting the molecular basis of local adaptation must apprehend the complexity introduced by temporal fluctuations because they massively affect the expression of phenotype and fitness differences.Understanding the genetics of lifetime fitness is crucial to understand a species’ ecological preferences and ultimately predict its ability to cope with novel environmental conditions. Yet, there is a dearth of information regarding the impact of the ecological variance experienced by natural populations on expressed phenotypic and fitness differences. Here, we follow the natural dynamics of experimental  There is overwhelming evidence that local selection pressures have shaped the genetic composition and ecological performance of natural populations –3. But iArabidopsis thaliana, a plant species that stands as a model for the dissection of the molecular underpinnings of local adaptation [Here we document seasonal variation in expressed plant life cycles and measurements of fitness in aptation . In thisaptation –15. Pattaptation –20. Reciaptation ,22 and captation . While taptation –26. Thisaptation . In mostaptation ,27,28. YTo answer these questions, we designed an experiment that dissects how environmental factors affect fitness profiles in natural populations at temperate latitude. We report the monitoring of lifetime fitness in experimental populations over 5 natural successions of plant cycles in conditions differing in soil substrate and water availability. We monitored 4 genotypes, including two genomic backgrounds, one of local and one of Southern origin (Col-0 and C24), and the reciprocal chromosome 4 (Chr 4)-introgressions of several polymorphisms previously reported to associate with differential fitness in various locations . We expeArabidopsis thaliana is an annual weed growing across a broad geographic range [ic range . The fruic range . We furtic range . Seeds wic range . Of thosic range .NIL due to limitation in personnel (48 pots). The timing of the different plantings is given in In this study, we monitored germination, flowering time and fitness of the 2 wild type genotypes, Col-0 and C24 and their reciprocal Chr4 introgressions in the field over five consecutive generations that followed a quasi-natural population establishment dynamics. Fifty field-collected seeds of the two NILs and their wild-type parents were placed in 12 replicate pots , for each of the two soil compositions and 4 genotypes. Seeds were taken from a pool of 500 seeds collected from 5 plants per pot in the previous planting. There were two exceptions to this scheme: planting 1 was started with 200 seeds and conducted in only four replicates (32 pots), and planting 5 was performed with only Col-0 and Col3, Einheitserde Werkverband, Sinntal-Jossa) or a soil mixture enriched in sand (a 1:3 mixture of the turf described above and sand). Pots thus dried faster in the sand mixture compared to turf. Pots were randomized and placed on a large plastic cover that prevented germination from the soil below (The field was located in the middle of a flat grass meadow and fenced with iron nets to prevent grazing by rabbits. No vegetation protected it from sun or wind. We filled large flat pots (30cmx40cmx12cm) with two soil types: Arabidopsis turf soil  and mi06 (5’-ATCTCCCCACTCCCCAATTTT-3’), which generate a length polymorphism at AT4G24415 within the chromosome 4 introgression [For all plantings, seedlings other than gression . We deteThe field study was conducted on the experimental land area of the Max Planck Institute for Plant Breeding Research . This field study did not require specific permission because it did not include transgenic plant material and did not involve endangered or protected species.For the first planting, early, intermediate and late germinants were observed but the exact germination date was not scored. Germination time was scored for plantings 2–5, flowering time (date of the first open flower) was scored for all five plantings. Silique number was counted for a sample of 3–8 randomly chosen plants in each population. In total, fitness was scored for 96, 401, 583, 301 and 691 plants in plantings 1 to 5, respectively . In addition, in plantings 2, 3 and 4, the number of seeds was determined for three siliques in each of 3 randomly chosen plants per population. For fruit number flowering time and germination time, an average was computed for each population (e.g. each pot). The average fruit number per pot was taken as an estimate of lifetime fitness. Variation in average seed number per silique did not change the conclusions based on fruit number (not shown). When plants in a pot failed to germinate or survive until reproduction, lifetime fitness was set to zero. To account for variation in germination rates, we included plant density as a covariate in the analyses (see below). Raw phenotypic and fitness data is shown in drop1. To control for the non-Gaussian error distribution, we used a negative binomial distribution of error (implemented in R Package MASS) and tuned its free parameter to adjust the residual deviance to the degrees of freedom of the model. This adjustment was performed at each step of the procedure, until the minimum model was determined. The resulting “minimal” model included the four main factors and the significant interaction terms. Interpreting the effect of a single experimental factor is not straightforward in the presence of interactions between factors, especially when the 4-way interaction is significant. We thus broke down the factors and conducted separate ad-hoc GLM for each genomic background or for subsets of plantings. The fold-change attributed to experimental factor was calculated by taking the exponential of the log estimates given by the model . This measure corresponds to the odds ratio associated with the factor. The proportion of variance explained by each factor or interaction term, was calculated as the ratio of the deviance calculated for a given factor against the total deviance. To compute the fitness fold-change attributed to the chromosome 4 introgression within each combination of experimental factor , we ran a separate GLM analysis with introgression as a factor nested within a factor called “setting”, which combined soil condition, planting and genomic background in 16 levels. Fitness fold-change attributed to variation in the chromosome 4 region was calculated as described above.All statistical analyses and figures were performed in R. A generalized linear model (GLM) was used to establish the minimal model explaining phenotypic or fitness variation. For this, we followed the procedure described in . A firstPhoto-Thermal Units (PTU) for each planting, following Brachi et al. 2010 [The product of day length (h) by mean temperature (°C) was calculated for each day and summed for the time windows covering date of sowing to average germination (or flowering) date to compute the cumulated al. 2010 .A. thaliana populations over five naturally consecutive plantings by counting the average number of siliques produced per pot (We monitored average silique (fruit) production in experimental  per pot . Climati per pot .p = 1.03e-11, The average number of siliques (fruits) produced in each population was significantly affected by the number of germinants (or survivors) in each replicate population, i.e plant density  is believed to have an important impact on final fitness ,34. Yet,We observed in the 3 overwintering seasons a greater spread in the timing of life-history transition. Planting 1 was started in early December and no germination occurred before spring. Although the precise germination date was not scored for the first planting, we observed that germination was staggered across 1 month. This observation was repeated for planting 5, where germination occurred after 2–3 months . For botIn this study, we designed a field experiment to quantify the fitness outcome of climate, substrate and genotypic variation on phenotypic and fitness variation in the natural setting of successive seasons. Our results reveal that environmental variance experienced over successive growth seasons at a given locality of temperate latitude with permissive summer season, is not buffered by phenotypic plasticity. Genotypic differences in phenotype and fitness fluctuate in magnitude across soil conditions and seasons. Seasonal fluctuations experienced at temperate latitude markedly alter expressed life cycles, which can display winter-, spring- or summer-annual cycles.A. thaliana genotypes in the field has already been reported in several studies [A. thaliana completes two cycles per year while the third one is suspended during winter, either at the rosette (planting 3) or at the seed stage (planting 5). Our experiment shows that a given genotype may manifest diverse life cycles in the course of successive seasons, confirming theoretical predictions based on a combination of hydrothermal and photothermal models of germination and flowering decisions[The performance of various  studies ,21,23,27decisions–34. The decisions.We further observed that life time fruit production also varied by up to 36-fold across successive seasons. This is likely to be due to the dramatic environmental differences to which genotypes are exposed throughout the successive seasons. Indeed, level of fluctuation for a winter annual cycle replicated over 5 distinct years reported up to 7-fold fitness fluctuations . BecauseBased on previous laboratory studies, we expected that the two backgrounds would display markedly different life histories in the field. The genotype C24 was reported to flower 11 days after Col-0 in long day conditions but is a relatively early genotype under short day conditions because of a weak FLC allele . In addiLife history transitions such as germination and flowering time are known to be dependent on the environment ,35,39–41A. thaliana clade of genotypes originating from natural stands in Germany [A. thaliana genotypes originating from Southern latitudes, which is the case for C24, perform comparatively well at intermediate temperate latitudes [A. thaliana stands, can magnify or mask differences observed between Col-0 and the Southern genomic background C24 Click here for additional data file.S2 FigA. The effect of plant density in the pot was only strong in planting 2, 3 and 5. For 3 and 5, Co-0 was the only genomic background that survived. B. For planting 2, the C24 background did not perform well, so that density was too low to reveal an impact of competition on total life time fitness.(TIFF)Click here for additional data file.S3 FigPlantings 2 and 4 had similar germination and flowering time. By contrast, generation 3 showed spread flowering time and generation 5 rather spread germination (spring germination), suggesting that the buffering of germination and flowering differed across planting (and across genotypes). Note that the Chr4 introgression did not impact these differences. In generation 1, the date of germination was not scored, but three cohorts were observed, reflecting a spread of germination over March/April, whereas flowering time occurred within 1–2 weeks.(TIFF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.


Obesity and chronic kidney disease (CKD) are major global health problems. There are very little data concerning the prevalence and its associated factors of obesity in non-dialyzed patients who have different stages of CKD. Therefore, in this study, we examined the prevalence of obesity and its associated factors according to the stages of CKD. We used nationwide representative data from the Korean National Health and Nutrition Examination Survey, which was conducted over a 7-year period from 2008 to 2014 by the Korea Centers for Disease Control and Prevention. The results indicated that: (1) general obesity and abdominal obesity were more prevalent in patients with CKD compared to those without CKD; (2) the prevalence of general obesity and abdominal obesity was highest in stage 2 CKD; (3) stages 3a and 3b were the factors associated with general obesity, and stage 3a was significantly associated with abdominal obesity; (4) the association between general obesity/abdominal obesity and CKD disappeared in people with advanced stage 4/5 CKD; and (5) the presence of comorbidities contributed to the development of both general obesity and abdominal obesity. The findings of this study might support the idea that weight loss is a good potential intervention for the prevention of disease progression in moderate CKD (stage 3), but not severe CKD (stage 4/5). Obesity is a worldwide health threat. Socio-economic burden and the prevalence of obesity worldwide has increased substantially over the last 3 decades . ObesityThe present study is a secondary data analysis of the Korean National Health and Nutrition Examination Survey (KNHANES) which was performed over a 7-year period from 2008 to 2014 by the Korea Centers for Disease Control and Prevention (KCDC). The KNHANES is an ongoing, nationwide, population-based, cross-sectional, multistage, stratified, and clustered probability sampling survey with the aim of minimizing sampling bias and ensuring that the sample represents the South Korean population . The surIn the present study, we included adults aged ≥ 19 years and excluded: (1) those who were pregnant or lactating, (2) those who had missing data for body mass index (BMI) or waist circumference (WC), and (3) those who had missing data for estimated glomerular filtration rate (eGFR). A total of 58,307 individuals were screened, and 37,002 people were included in the study according to the inclusion and exclusion criteria. General obesity was defined as BMI ≥ 25 kg/m2 based on the cut-off value for Asians . Abdominhttp://knhanes.cdc.go.kr/). These data are open to the public after completing a designated registration process for access [The KNHANES survey is reviewed and approved by the Institutional Review Board of the Korea Centers for Disease Control and Prevention on an annual basis . Each study participant provided written informed consent before the survey. Data were downloaded from the official website of the KNHANES (Body mass index (BMI) was calculated as weight in kg divided by height in m2. General obesity was defined as BMI ≥ 25 kg/m2 based on the cut-off value for Asians . AbdominSerum creatinine level was measured using the kinetic Jaffe method with an ADVIA 1650 Analyzer  and/or a Hitachi Automatic Analyzer 7600  in 2008–2012 and the rate-blanked and compensated Jaffe method with a COBAS 8000 C70  in 2013–2014. Blood samples were obtained after an overnight fast [The eGFR was calculated using the Modification of Diet in Renal Disease Study equation . ChronicSociodemographic characteristics of the participants included age, sex, educational level, residential area, household income quartiles and employment status. Health behaviors included alcohol drinking and smoking habits, and mental health included perceived health status assessed by self-reported questionnaires.Alcohol drinking was defined as the consumption of more than seven glasses of alcoholic drinks per occasion, more than two times per week. Current smoking was defined as both currently smoking and having smoked ≥ 100 cigarettes in a participant’s lifetime. Regular exercise was defined as exercising at a moderate level of intensity (≥ 30 min per session) more than five times per week or a rigorous level of intensity (≥ 20 min per session) more than three times per week. Perceived health status was defined as the level of overall health  perceived by the person. Health-related quality of life (HRQoL) was measured using the EuroQoL, which uses both a health-status descriptive system (EQ-5D) and a visual analogue scale (EQ-VAS) ranging from 0 to 100: 0 signifies the worst HRQoL while 100 indicates the best HRQoL . HyperteData were analyzed using SAS version 9.4 . A p-value < 0.05 was considered statistically significant. All data are presented as means ± standard error (SE) for continuous variables or as proportions (±SE) for categorical variables. Analysis of variance and chi-square tests were performed to evaluate the differences in continuous and categorical variables between the groups. The prevalence of general obesity and abdominal obesity according to eGFR was analyzed as a proportion (±SE). Sociodemographic and clinical characteristics, including mental health and comorbidities, were also examined according to eGFR.Hierarchical multiple logistic regression analyses were conducted to explore the associations between general obesity, eGFR and all outcomes of interest. The same approach was followed to explore the associations between abdominal obesity, eGFR, and these outcomes. In the analyses, Model 1 was unadjusted, and Model 2 was adjusted for the variables in Model 1 and sociodemographic factors . Model 3 was adjusted for the variables in Model 2 and health-related characteristics , and Model 4 was adjusted for the variables in Model 3 and comorbidities . Finally, Model 5 was adjusted for the variables in Model 4, SBP, DBP, and laboratory measurements . The EuroQoL (VAS) was assessed only in 2010–2012, and ferritin was measured only in 2008–2012. Therefore, these factors were omitted from the adjustments. The results were reported using adjusted odd ratios (ORs) and their 95% confidence intervals (CIs). A 95% CI that did not span 1.0 was considered statistically significant.The prevalence rates of general obesity and abdominal obesity in the study participants were 32.5% and 24%, respectively . The prep < .001). The serum levels of total and LDL cholesterols were highest in stage 2 CKD patients (p < .001). Current smoking and alcohol drinking are more common in patients with CKD stage 1 and 2 among the CKD group.It is thought that obese people are more likely to develop CKD and ESKD because of hemodynamic and histopathological changes in the kidney in the setting of obesity , 19, 20.The findings of the present study can be summarized as follows: (1) general obesity and abdominal obesity were more prevalent in CKD groups compared to the non-CKD group; (2) the prevalence of general obesity and abdominal obesity was highest in stage 2 CKD; (3) stages 3a/3b CKD were the significant factors associated with general obesity, and stage 3a CKD was significantly associated with abdominal obesity; and (4) the presence of various comorbidities was an independent contributor to the development of both general obesity and abdominal obesity.ghrelin or leptin, could be different according to the CKD stage, as both ghrelin and leptin are metabolized in the kidney, leading to a skewed indication of positive energy balance in patients with early CKD [Our study showed that people with CKD stages 3a and 3b were more likely to have general obesity and people with CKD stages 3a were more likely to have abdominal obesity. It has been suggested that WC, not BMI, might be a better indicator of obesity-related health risk . Adiposiarly CKD , 24. At The present study also found a relatively lower prevalence of general obesity and abdominal obesity in CKD stage 4/5 than other CKD stages , and theViewed in combination, these previous findings and those of the current study may suggest that obesity is strongly associated with the development and progression of CKD at an early stage but confer a benefit in advanced CKD. In other words, obesity might be a double-edged sword for CKD patients. Thus, a therapeutic approach to overweight and obesity in patients with advanced CKD should be approached carefully.Regarding the factors associated with general obesity /abdominal obesity other than CKD Tables  and 5, iOf note, we have used the Korean definition in this study to define general and abdominal obesity . A recenThe findings of the present study have a few important clinical implications. First, these findings are congruent with those of previous studies in that they revealed a significant association between general obesity/abdominal obesity and CKD. Second, we further observed that the association between general obesity/abdominal obesity and CKD disappears when CKD reaches an advanced stage (stage 4/5). This means that weight loss might be a sign of poor clinical outcomes in patients with severe CKD. Third, CKD itself could be a contributing factor to obesity in moderate CKD (stage 3). Given the role of obesity in the progression of CKD, patients with moderate CKD can enter a vicious cycle if they have both CKD and obesity. In conclusion, the findings of this study clearly support the idea that weight loss is a good potential intervention for the prevention of progression in moderate CKD (stage 3), but not severe CKD (stage 4/5).The main strength of this study is that it was done in a large number of individuals using nationwide and representative survey data. Also the ethnic homogeneity of study participants can be another strength since it enabled us to reduce the potential confounding effects of different races and ethnicities to address the relationship between obesity and CKD. However, this ethnic homogeneity of study participant could be viewed as limitation since further studies will be needed in populations with different ethnic backgrounds before generalization of our study findings. Furthermore, as mentioned earlier, the cross-sectional design of the KNHANES precluded the identification of a causal relationship, and this represents another limitation of the present study. Due to the nature of cross-sectional studies, patients with acute kidney injury could have been accidentally included in this study given that a single measurement of eGFR might not represent CKD accurately.In conclusion, there is increased prevalence of obesity in patients with CKD in South Korea except for severe CKD patients. Stages 3 CKD seems to be an independent factor for obesity as well. The findings of this study clearly support the idea that weight loss might be a good potential intervention for the prevention of disease progression in moderate CKD (stage 3), but not severe CKD (stage 4/5).


Objective: It is generally difficult to achieve symmetry in implant-only breast reconstruction with ptosis, and it remains unclear what quantitative criterion may be applied in cases of breast ptosis regarding the application of this modality. Our study aimed to suggest a criterion for obtaining good aesthetic outcomes and a symmetrical inframammary fold that is well-fitting for the brassiere in implant-only breast reconstruction after simple mastectomy. Methods: We classified into 3 groups 50 consecutive patients who underwent implant-only breast reconstruction that created an inframammary fold using a modified internal method after simple mastectomy. The classification was based on the rostrocaudal distance along the chest wall between the lowest point of the breast the and the inframammary fold on the contralateral side . Thereafter, we compared this distance on the reconstructed side , Dc−Dr, and projection of the implant  between the groups and investigated the correlation between Dr and lower (Pi < 5.0 cm) and higher Pi (Pi ≥ 5.0 cm). Results: Dr was similar to Dc in groups 1 and 2 ; however, Dr was significantly lesser than Dc in group 3 . In addition, we found significant positive correlations between Dr and lower Pi and between Dr and higher Pi. Conclusions: A Dc below 10 mm may be a good indication for implant-only breast reconstruction. Furthermore, the modality may be applied where Dc is 7 mm or less in cases with lower Pi and where Dc is 13 mm or less in cases with higher Pi. Implant-based breast reconstruction techniques are widely used because they are less invasive. To achieve good aesthetic outcomes, the shape and position of the reconstructed breast should be symmetrical. In addition, considering a proper fitting for the brassiere, the inframammary fold (IMF) should be as symmetrical as possible. However, in implant-only breast reconstruction with ptosis, it is generally difficult to achieve such symmetry.To achieve symmetry of both breasts in severe ptosis, revision surgery of the contralateral breast or reconstruction with autologous tissue is needed. Therefore, it is important to evaluate the degree of ptosis before deciding on the method of breast reconstruction. Regnault'sOur study aimed to evaluate degree of breast ptosis based on the rostrocaudal distance between the IMF to the lowest point of the breast and suggest a useful and practical criterion for obtaining good aesthetic good outcomes and a symmetrical IMF for satisfactory brassiere fitting in the reconstructed breast with respect to implant-only breast reconstruction after simple mastectomy. Furthermore, it seemed necessary not only to predict the need for a contralateral side operation preoperatively but also to suggest conversion to autologous reconstruction when unsatisfactory outcomes are expected.2; period of measurement, range = 6 to 12 (mean 9.5) months postoperatively; follow-up period, range = 8 to 36 (mean 20.9) months postoperatively; and breast implant weight, range = 90 to 620 (mean 342.7) g.We prospectively investigated 50 consecutive patients who underwent unilateral, 2-stage, implant-only breast reconstruction after simple mastectomy between April 2014 and August 2016. We used an anatomical and textured silicone breast implant  for the procedures. Patients who received radiation therapy were excluded. The following characteristics were noted in the patient cohort: age, range = 18 to 71 (mean 48) years; body mass index, range = 15.5 to 27.3 (mean 21.3) kg/mIn the first stage, a tissue expander  was covered completely with well-vascularized tissue composed of the pectoralis major muscle, serratus anterior fascia , and rectus abdominis fascia, using the musculofascial pocket method. For expanding the skin at the lower pole mainly, the TE was placed at the lower border, 2 fingers below the IMF at the contralateral side. We performed an overexpansion with the TE, particularly in cases of breast ptosis. The extent of tissue expansion was determined by the quality of skin and weight of the breast implant. The rate of expansion  ranged from 1.1 to 2.4 (mean = 1.4).In the second stage , the TE was replaced with the breast implant. Breast implant insertion was performed using previous incisions. After cutting the capsule and removing caudal soft tissue, including the superficial fascia, the IMF was created using a modified internal method by Nava et alFor 6 months after breast implant insertion, patients fixed both breasts with a controlling brassiere. All reconstruction procedures and measurements were performed by the first author.We measured the rostrocaudal distance along the chest wall in the anterior view between the lowest point of the breast and the IMF on the reconstructed side (Dr) and also measured this distance on the contralateral side (Dc), after more than 6 months post–breast implant insertion . If the t test was used to compare continuous variables between Dr in lower Pi and Dr in higher Pi. For all statistical tests, a P value less than .05 was considered statistically significant.Data were analyzed using the Statistical Package for the Social Sciences for Windows, version 23 . Holm's test was used to compare the means of continuous variables  between the 3 groups. Simple linear regression was used to define the linear relationship between Dr and lower Pi and between Dr and higher Pi. Student's The protocol for this study was approved by the institutional review board. All patients provided written informed consent before publication of this article. Our study was conducted in accordance with the Declaration of Helsinki.None of the patients experienced TE or breast implant failure due to infection or extrusion, necrosis of the skin envelope, and definite postoperative capsule contracture . Dc−Dr was significantly longer in group 3 than in group 1 and in group 3 than in group 2 . No significant difference was noted in Dc−Dr between group 1 and group 2 (P = .18). Pi was significantly longer in group 2 than in group 1, in group 3 than in group 1, and in group 3 than in group 2   .R = 0.47, P < .05) and between Dr and higher Pi   . The difP < .05) .This prospective study aimed to investigate the classification of patients who underwent unilateral, 2-stage, implant-only breast reconstruction using a modified internal method by Nava et al,2,3,6-In breast reconstruction with ptosis, it is necessary to achieve a symmetrical IMF with sufficient depth and acceptable aesthetics in order to achieve a good shape and position, as well as a comfortable fit for the brassiere. The skin envelope decreases postoperatively compared with preoperatively after simple mastectomy. Furthermore, the shape of the breast implant is different from the shape of the ptotic breast in the sagittal plane ; therefo5,Larger implant volume was a significant predictor of better IMF outcomes according to photogenic assessment, and increased breast projection with implants has some corrective effects on ptosis of the reconstructed breast.5The gap between Dc and Dr may be acceptable until a length of 5 to 6 mm considering the allowance of minimal asymmetry for brassiere fitting and therefore the application of implant-only breast reconstruction should be for cases where Dc is 7 mm or less  for the lower Pi group (Pi <5.0 cm) and where Dc is 13 mm or less  for the higher Pi group (Pi ≥ 5.0 cm).The skin envelope tends to constrict according to the shape of the breast implant. Therefore, even if overexpansion of the skin envelope is performed and an IMF is created with firm fixation, it is difficult to achieve a symmetrical IMF in implant-only breast reconstruction with moderate ptosis using a breast implant with a low projection, because the difference in the application of the procedure between cases in the lower and higher Pi groups becomes apparent.The rostrocaudal distance along the chest wall between the lowest point of the breast and the IMF is a useful criterion for the application of implant-only breast reconstruction after simple mastectomy. Furthermore, patients may be informed, with better evidence than before, of the need to reshape the contralateral breast and the desirability of reconstruction using autologous tissue to achieve symmetry of both breasts.Our study could have included a control group using other techniques of IMF creation, other mastectomy methods , different silicone breast implant types , and/or receiving radiotherapy. However, breast reconstruction after simple mastectomy using the anatomical silicone breast implant is the most popular modality; thus, our study seems relevant.We classified patients who underwent implant-only breast reconstruction after simple mastectomy into 3 groups based on Dc and compared the Dr, Dc−Dr, and Pi between these groups. Moreover, we determined the correlation between Dr and lower Pi and between Dr and higher Pi. Classification into group 1 or 2 (0 ≤ Dc <10 mm) may be a good indication for implant-only breast reconstruction. In addition, on the basis of Dc, we showed the application of this reconstruction technique in patients with lower Pi and higher Pi. We believe that Dc with reference to Pi is a simple, practical, and useful criterion for the application of implant-only breast reconstruction after simple mastectomy.


The global pandemic of obesity has led to an increased risk for prediabetes and type-2 diabetes (T2D). The aims of the current project are: (1) to evaluate the effect of a 22-week family based intervention program, including supervised exercise, on insulin resistance syndrome (IRS) risk in children with a high risk of developing T2D and (2) to identify the profile of microRNA in circulating exosomes and in peripheral blood mononuclear cells in children with a high risk of developing T2D and its response to a multidisciplinary intervention program including exercise.N = 42) or intervention (N = 42) groups. The control group will receive a family based lifestyle education and psycho-educational program (2 days/month), while the intervention group will attend the same lifestyle education and psycho-educational program plus the exercise program . The following measurements will be evaluated at baseline prior to randomization and after the intervention: fasting insulin, glucose and hemoglobin A1c; body composition ; ectopic fat (magnetic resonance imaging); microRNA expression in circulating exosomes and in peripheral blood mononuclear cells ; cardiorespiratory fitness (cardiopulmonary exercise testing); dietary habits and physical activity (accelerometry).A total of 84 children, aged 8–12 years, with a high risk of T2D will be included and randomly assigned to control  contains supplementary material, which is available to authorized users. Type-2 diabetes (T2D) is an important cause of premature death and disability as well as a costly disease affecting more than 415 million people worldwide . The lifAs a consequence of the high rates of obesity and diabetes risk, health and scientific organizations demand urgent early preventive actions for increasing life expectancy and quality of life of overweight/obese children at a high risk of T2D , 6, 7. TIn adults, lifestyle intervention programs based on diet and physical activity level modifications have proven to be effective in decreasing the rate of the progression from glucose intolerance or prediabetes to T2D . HoweverThere is substantial evidence indicating that lifestyle behaviors associated to obesity and T2D are established in childhood and are difficult to modify into adulthood . The adoFamily based lifestyle modification interventions  seem to be the most efficacious treatment format for childhood obesity . In addiExercise is a critical component for T2D prevention and management. Likewise, regular physical activity improves insulin sensitivity in diabetic or prediabetic children . PreviouObesity, insulin resistance and T2D are caused by a combination of genetic, epigenetic and environmental factors such as diet and exercise. During the last few years, a growing number of studies demonstrate that small, non-coding, ribonucleic acid (RNA) molecules that function as regulators of gene expression, microRNAs (miRNAs), may be involved in the pathogenesis of obesity, diabetes and related metabolic disorders , 35. SevTherefore, the primary aims of the PREDIKID (Prevention of Diabetes in Kids) study are: (1) to evaluate the effect of a 22-week, family based, multidisciplinary intervention program including exercise on IRS in children with a high risk of developing T2D and (2) to identify the profile of microRNA in circulating exosomes and in peripheral blood mononuclear cells in children with a high risk of developing T2D and its response to a family based multidisciplinary intervention program including exercise.The PREvention of DIabetes in KIDs (PREDIKID) study is a randomized clinical trial (RCT)  . Children aged between 8 and 12 years, meeting the international criteria for classification of T2D risk , and havA pre-screening appointment will be scheduled with the investigation team to assess eligibility, family needs and commitment. Parents will provide the child’s and family health history and detailed contact information. After completion of the informed consent process, children will undergo anthropometric screening , complete physical examination and blood sampling, and will be selected for inclusion in the study if they meet the inclusion criteria Table . Every cd) of 0.7 for insulin resistance  . These effect size estimates are based on previous studies performed in overweight children with similar age range and a with intervention programs including supervised exercise [Insulin resistance is the primary outcome of this study. We expect that pre-post intervention differences in our design consisting in two experimental groups, control and exercise group, will have a size effect  for 90 min . The design of the programs has been published elsewhere [The family based healthy lifestyle education program will be conducted by experienced nutritionists. The aim of the program will be in promoting changes in lifestyle behaviors strongly associated to obesity and T2D risk: promoting healthy dietary habits , increasing regular physical activity levels, reducing time spent in sedentary behaviors and promoting sleep hygiene and adequate sleep duration.The aims of the psycho-educational program will be to provide parental skills to optimize the family environment in order to make positive changes in their lifestyles and to learn assertive communication skills. The program will also provide skills to children for managing the emotions and feelings that they are experiencing and to improve their self-esteem and psychological wellbeing.The exercise group will do exercise 3 days/week, 90 min per session, over a 22-week period. The program will be open to the families 5 days per week to choose a total of 3 days/week. Sessions will be designed and supervised by exercise specialists. The design of the exercise program has been published elsewhere . BrieflyThe success of the intervention is strongly dependent on enjoyment and active participation. In order to motivate children’s active participation, the staff will use several strategies to celebrate success achieving the proposed objectives in both the healthy lifestyle education and the exercise programs: celebrate and recognize their efforts, reward with smiley emoticons, etc. Children who complete the program successfully will be rewarded with a certificate of completion. The attendance to the lifestyle education and psycho-education programs and of the exercise program will be recorded. Children will be marked as absent when: (1) the child does not attend the exercise session or does not participate in the proposed activities and (2) the child and at least one parent/caregiver do not attend one session of the healthy lifestyle education and psycho-educational programs.IRS and the risk of T2D is characterized by excess adiposity, low levels of insulin sensitivity, dyslipidemia and hypertension. In the current project, the primary outcome is insulin resistance. Secondary outcome variables include total, abdominal and visceral adiposity, ectopic fat (hepatic and pancreatic fat), cardiorespiratory fitness, cardiovascular disease risk factors and inflammation markers, hepatokines and adipokines (Table HOMA has been shown to be the more reliable method to assess insulin resistance in children . The comBody mass (SECA 760), height (SECA 220) and waist circumference (SECA 200) will be measured following standard protocols at least twice until consistent measures are obtained and, thereafter, Body Mass Index (BMI) and waist to height ratio will be calculated. Systolic and diastolic blood pressure measurements will be performed following the recommendations for children  using anIn children, the role of total, abdominal and visceral fat accumulation in the development of IRS, and ultimately T2D, is well established. One recent report observed that every additional 1% of adiposity at 8–10 years decreased insulin sensitivity by 2.9% 2 years later . Total aExcess adiposity is associated with an accumulation of fat in multiple organs and tissues. Fat accumulation in the liver and pancreas promotes a pro-inflammatory state that may increase the risk of insulin resistance and T2D. Likewise, ectopic fat accumulation seems to be an important predictor of the onset of T2D in adolescents . Insulin2max, ml/kg/min) from the 20-m shuttle run test scores and (2) direct cardiopulmonary exercise progressive incremental treadmill test using the modified American College of Sports Medicine protocol with respiratory gas analysis to exhaustion [Cardiorespiratory fitness is an independent predictor of T2D in adults . In youthaustion .Early changes of atherosclerosis can be detected assessing carotid intima-media thickness (cIMT). In adolescents with T2D, Shah et al. reported that every 1% increase in hemoglobin A1c (HbA1c) or each year increase of the duration of the disease was associated with 30% higher cIMT . In chilThe obesity-associated chronic inflammatory process participates in the onset of T2D, although the underlying mechanisms are not well understood , 62. SevWe will assess all these lifestyle behaviors both at the beginning and the end of the intervention. Children will wear an accelerometer on the non-dominant wrist  for seven consecutive days for 24 h to record physical activity intensity levels and patterns, as well as sleeping habits and participants will also complete a diary log. Sedentary behaviors, such as watching TV, playing computer games, playing video games or phone games and surfing the Internet, will be self-reported by the children using validated questionnaires . DietaryRecently, miRNAs have emerged as key regulators of gene expression. T2D is associated with changes in the level of several miRNAs in pancreatic β-cells as well as in tissues such as liver, skeletal muscle or adipose tissue , 68. MorExosomes will be obtained from 1 ml of plasma using the Total Exosome Isolation Kit (Thermo Fisher Scientific) following manufacturer’s protocols. RNA molecules will be isolated from white blood cells (buffy coat) and exosomal fractions using Qiagen miRNeasy kit  according to the manufacturer’s instructions. Once isolated, RNA will be quantified using a fluorimetric method.Species of miRNA present on samples of individual subjects, before and after the intervention program, will be analyzed using RNA-seq methodology on Illumina’s MiSeq Next Generation Sequencing system. This workflow allows one to fully characterize the miRNA profile present in the samples analyzed (exosomes and white blood cells) and to quantify the expression levels of different miRNA species. In this sense, effects of the intervention program on the miRNA profile and on expression level of specific species can be inferred. Briefly, Illumina’s TruSeq Small RNA Sample preparation kit will be used to generate sequencing libraries, from 1 μg of total RNA isolated from previous samples (either exosomes or white blood cells). Only 145 to 160 bp libraries will be selected for sequencing, as they include miRNA species (22–30 bp plus adapters). Sequencing reactions will be performed on Illumina’s MiSeq Reagent Kit V3, which supports to multiplex up to 10 samples on a single run, and single reads of 50 nt in length. Analysis of results, FASTQ files generation and sequence alignment will be performed using specific software packages .At baseline, the pediatrician will evaluate Tanner staging by direct-examination breast palpation in girls and testicular measurement by orchidometer in boys.Information about socioeconomic status, demographic characteristics and family medical history of obesity, diabetes, dyslipidemia and hypertension will be collected. Socioeconomic status will be evaluated using The Family Affluence Scale  and pareAll adverse effects or health problems attributable to the testing or exercise sessions will be recorded.Participants’ data will be identified only by a study number (starting with 001) and only the principal investigator and study coordinator will have access to identifiers that can link the data to the individual participant. Participants who drop out will be noted and their reasons documented. Data will be entered and stored on a standalone computer into excel and SPSS data files, and the information will be password protected. We will assure the quality of data entry by random checking of the data entered. Study data is only accessible by the researchers involved in the trial, and only the principal investigator and investigators in the project will have access to the data for analysis. The investigators will monitor that the informed consent process is conducted appropriately and that informed consent was obtained prior to proceeding with any study procedures. Only participants who meet study eligibility criteria will be enrolled. Data will be kept for 10 years after the research is completed and all data (electronic and hard copy) will be destroyed after the storage period. There is no data monitoring committee due to the characteristics of the current study.t test or the Mann-Whitney U test, as appropriate. Differences in categorical variables at baseline between the two groups will be explored by chi-squared tests. Repeated-measured analysis of variance will be used to assess the effect of exercise (time (pre-post 22-weeks’ intervention) × group interactions) on the primary (insulin resistance) and secondary study  outcomes and the intention-to-treat principle will be applied. For sensitivity analyses, we will analyze the effect of the adherence to the program on the results of the intervention.All outcome variables will be checked for normality and results will be expressed as mean and standard deviation (SD) or median and ranges. Multiple regression analyses will be performed to examine the potential independent predictors of T2D risk. At baseline, differences in continuous variables between groups (control group vs. exercise group) will be analyzed by Student’s The principal investigator will inform the parents about their child’s health before and after the intervention program. The main results of the trial will be communicated to the health care professionals (pediatricians) in Vitoria-Gasteiz and other relevant groups , as well as to the public. Scientific articles will be also written.The worldwide obesity pandemic and the increasing prevalence of T2D at younger ages are important public health issues with both individual and social costs. Likewise, research focusing on the prevention of T2D in pre-adolescent children is a high priority for public health. Scientific associations emphasize the need for evidence-based adiposity and IRS control treatments that may reduce T2D risk in children at a high risk .The primary aim of the PREDIKID project is to test the effect of a multidisciplinary program including supervised exercise in the reduction of IRS in pre-adolescents at a high risk to develop T2D that could serve as preventive model of T2D in childhood. The families participating in the study will receive an educational program including lifestyle, psychological and emotional aspects that the scientific literature implicates in the development and progression of obesity and T2D risk in childhood. Moreover, the exercise intervention of the PREDIKID study will obtain objective data about the effect of high intensity exercise on metabolic variables closely associated to T2D risk in children, such as insulin resistance, HbA1c, ectopic fat, total, abdominal and visceral adiposity, cIMT, cardiorespiratory fitness, adipokines, hepatokines and cytokines, blood pressure or lipid profile. We will examine clinical outcomes intimately associated with T2D using innovative technology and reference methods. Likewise, the PREDIKID project will help to better understand the relationship between hepatic and pancreatic fat and IRS and risk of T2D in children. In addition, the current study may offer relevant clinical information about the efficacy of a family based multidisciplinary intervention program that includes exercise on reducing ectopic fat, IRS and cardiovascular disease risk factors in children at a high risk of T2D.The pathophysiology of childhood obesity and associated comorbidities, such as T2D, is not well established. To date it is not clear why some children develop IRS and T2D, while others show the metabolically healthy phenotype . BiomarkThe recruitment started on March 2017, and is expected to finish in September 2018.


AP3S2, ELP5, SVIP, IRS1, FADS2, WFS1, RBM6, HORMAD1, PYROXD2), which are enriched in tissues  and biological processes and canonical pathways  that are important for the pathogenesis of type 2 diabetes and obesity. Our discovery-based approach also identifies enrichment for eQTL SNP-gene interactions in tissues that are not classically associated with diabetes or obesity. We propose that the combinatorial action of active obesity and diabetes spatial eQTL SNPs on their gene pairs within different tissues reduces the ability of these tissues to contribute to the maintenance of a healthy energy metabolism.The mechanisms that underlie the association between obesity and type 2 diabetes are not fully understood. Here, we investigated the role of the 3D genome organization in the pathogeneses of obesity and type-2 diabetes. We interpreted the combined and differential impacts of 196 diabetes and 390 obesity associated single nucleotide polymorphisms (SNPs) by integrating data on the genes with which they physically interact (as captured by Hi-C) and the functional  outcomes associated with these interactions. We identified 861 spatially regulated genes (e.g.,  HMGA1 on chromosome 6 and the transcription of the INSR gene on chromosome 19.Genome-wide association studies (GWAS) have been instrumental in identifying numerous genetic risk loci for type 2 diabetes and obesity  capture regions of the genome that are physically associated and able to be covalently connected by a cross-linking agent  identified in GWAS typically use the nearest gene model. However, clinical risk for polygenic disorders is the sum result of the gene-environment interactions. These interactions occur within the context of a regulatory network that is “tuned” by the combined action of regulatory sites that spatially cluster. These sites are subject to genetic variation, which may alter these spatial clusters and thereby disrupt the functioning of target genes. As such, it is imperative that previously identified intergenic GWAS variants are tested for spatial interactions. Crucially, this approach has the potential to elucidate the regulatory network that describes the disease-associated SNPs which enhance or reduce the expected co-occurrence and severity of both obesity and type 2 diabetes.Here we integrate information on spatial organization and functional  data to identify the overlap between regulatory pathways that contribute to type 2 diabetes, obesity, and comorbid obesity plus type 2 diabetes phenotypes. We demonstrate that loci marked by diabetes—and obesity-related SNPs are involved in regulatory interactions in a tissue—and disease-specific manner.https://github.com/alcamerone/codes3d).Our aim was to identify SNPs where the genetic variant correlates with the expression level of the spatially associated partner gene , JAZF1 ) and NPC1 [i.e., rs1805081 and rs1808579 (r2 = 0.7) Table Due to the restrictions on Hi-C data resolution, SNPs that were in strong linkage and located on the same restriction enzyme fragment were not separable using CoDeS3D. For example, r2, 0.78) and rs1108842 , are located in loci that regulate genes  within a 300 kb genomic region on chromosome 3 . However, they are located on different MboI restriction fragments , rs1470579—CCDC14 (Chr 3), and rs1470579—SND1 (Chr 7).SNPs within the ARAP1 and BRD7 were affected by globally significant SNPs  that had previously been associated with both obesity and type 2 diabetes.Comorbidity can be explained by direct effects on the same genes or epistatic effects acting through pathways. Notably, only sixteen common genes , skeletal muscle (p < 1.57 × 10−2), and pancreas . Notably, there was no enrichment for eQTL SNP-gene pairs involving genes for lipid metabolism within the liver.The disease and tissue specificity of the spatial eQTL SNP-gene pairs can be further classified according to the metabolic function(s) that the interacting gene is involved in  Hi-C data captured from eight non-synchronized immortalized human cell lines . This finding reinforces the high discovery potential of integrating diverse sets of partially orthogonal data. This is particularly pertinent for polygenic type 2 diabetes and obesity where the metabolic dysbiosis is associated with a fundamental breakdown in the ability of the body to maintain and regulate a stable equilibrium for energy metabolism. The increased numbers of obesity eQTLs may reflect the fact that obesity can result from perturbations to a greater number of pathways, or at more points within these pathways, than diabetes. However, the absolute number of eQTL SNP-gene pairs that are influencing gene regulation in a particular tissue is not necessarily a direct measure of the significance of the changes for either diabetes or obesity.The tissue specificity of the regulatory effects we identified is consistent with current observations of the dynamic changes that occur within the local and global landscapes of genome organization in different cell types (Dixon et al., a priori assumption of tissue relevance. This was necessary because the GTEx database is a growing resource that does not currently include all the tissues that are classically considered “relevant” to the pathogenesis of Type 2 diabetes or obesity. The utility of our discovery-based approach is reinforced by studies on Huntington's disease that have identified pre-pathology changes in tissues, which were not previously associated with the pathogenesis or progression of Huntington's disease (Carroll et al., We undertook a discovery approach that makes no Our results provide novel insights into the separate roles of different adipose repositories in the development of the metabolic syndrome (Lee et al., In conclusion, we propose that the identity and number of obesity and diabetes spatial eQTL SNP-gene pairs that are active within different tissues reduces the ability of these tissues to contribute to the maintenance of a healthy energy metabolism Figure . EnvironCE wrote CoDeS3D. TF ran analyses, contributed to the software, interpreted data and co-wrote the manuscript. JI participated in discussions and commented on the manuscript, WS contributed to data interpretation and commented on the manuscript, JO directed the study, contributed to data interpretation and co-wrote the manuscript. JO is guarantor for this article.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.


Streptococcus pyogenes strains of different emm types in two pools, each containing 50 strains. We used four variant calling tools  and one emm1 strain, SF370, as a reference genome. In total 63719 SNPs and 164 INDELs were identified in the two pools concordantly by at least two of the tools. Majority of the variants (93.4%) from six individually sequenced strains used in the pools could be identified from the two pools and 72.3% and 97.4% of the variants in the pools could be mined from the analysis of the 44 complete Str. pyogenes genomes and 3407 sequence runs deposited in the European Nucleotide Archive respectively. We conclude that DNA sequencing of pooled samples of large numbers of bacterial strains is a robust, rapid and cost-efficient way to discover sequence variation.Knowledge of the genomic variation among different strains of a pathogenic microbial species can help in selecting optimal candidates for diagnostic assays and vaccine development. Pooled sequencing (Pool-seq) is a cost effective approach for population level genetic studies that require large numbers of samples such as various strains of a microbe. To test the use of Pool-seq in identifying variation, we pooled DNA of 100  Streptococcus pyogenes  are among the increasingly sequenced genomes; currently 45 complete GAS sequences have been recorded in the Genomes OnLine Database35Next generation sequencing (NGS) technologies have enabled progress in many biological research areas such as whole genome studies of various organismsThe cost of NGS technologies dropping significantly over the past decade has contributed to the growth in the availability of sequenced genomes. Nonetheless, population level studies of large sample sets are still cost prohibitive in many situations. Pooled sequencing (Pool-seq), in which only a single library containing a mixture of DNA from all the samples is sequenced, is one approach to reduce costs and speed up identification of sequence variation without significant loss of information8Pool-seq has been successfully used in various areas of research such as Genome Wide Association Studies (GWAS)8emm 1 type strain, SF370. The emm1 (serotype M1) type is one of the well-known GAS emm types that is mostly isolated from both human invasive infections and pharyngitis in high-income countriesWe assessed Pool-seq for identifying polymorphisms in 100 GAS strains relative to one of the publicly available complete genomes, the The aligned average depth for the two pools were ~18000x and 20000x. Compared to the individually sequenced publicly available ENA data, the two pools of the study had a much higher depth of coverage per strain (~400X vs ~186X) . The higNext, we analyzed sequencing depth in each 100 bp stretch of the GAS genome. Certain regions of the genome were not covered by reads (approx. 0.23% of the GAS genome) while there were other areas with a high number of reads in both our pools and the ENA data . One of Various studies demonstrated the efficiency of Pool-seq for variant identification and allele frequency estimation at a much lower expected depth of coverage than that of the average depth in our study  the number of identified variants  but sincNext, we studied the effect of duplicate removal on the variant calling since in whole genome re-sequencing studies, especially during variant calling, it is a common practice to remove both PCR and optical duplicates. Duplicate removal has also been recommended and applied in Pool-seq studies7Spy_2009 and Spy_0430) for PCR and Sanger sequencing. Out of the 100 strains used for pooling, Spy_2009 gene was amplified with PCR from 86% and the strains missing the gene were of emm types 6 and 12. However, only 30/86 strains gave an amplicon of the exact expected length (1250 bp) as judged by agarose gel electrophoresis. In the case of Spy_0430, PCR of only the emm1, emm78 and emm119 strains gave an amplicon. Therefore, the results indicate that some emm type strains in our pools lack these genes while some other strains exhibit high variability even in terms of the size of the gene.The SNPs and INDELs identified spread uniformly across the reference genome except in some areas that exhibited very high and low variations . Almost To determine the effect in our results of choosing a particular reference genome, besides the SF370 updated genome (accession id AE004092), we also used 19 of the 45 complete genomes as a reference to analyze variants in one of the pools. The number of SNPs and INDELS from this analysis ranged from 62680 to 72133 and 1271 to 1551 respectively . This coThe 44 complete genomes that were publicly available in September 7, 2016 were aligned to the selected reference genome. In total, 84312 SNPs and 3159 INDELs were discovered in all these genomes altogether see . These vTo compare the variants identified from Pool-seq data to a larger dataset than the completed genomes available, we used GAS sequence data from the European Nucleotide Archive (ENA). We aligned to the reference genome initially 3513 paired end Illumina sequencing runs that had varying degrees of sequence quality (mapping percentage that ranged from 1% to 100%). We removed 106 of the runs that had mapping percentage of less than 1.5*IQR (<83.93% mapping percentage) from the variant analysis resulting in 3407 runs that had an average mapping and proper pair percentages of 93.3 and 91.0 respectively . In thisTo investigate whether certain regions were more variable in either the pools, the 44 genomes, or the ENA data, we divided the entire genome of the reference strain into 10 kb regions and calculated the proportion of variants in such regions . As analIn this report, we show that the Pool-seq strategy was successfully used in identifying variants in a large number of GAS strains. Furthermore, we show that data from large published datasets, such as the European Nucleotide Archive (ENA), can be used to identify variations in a wide range of GAS strains. Although all the data in this study pertains to GAS, it is likely that a similar approach could be utilized with other microbes too. Therefore, the results may have a significant impact on identification of variants in genes and proteins of various pathogenic microbes allowing rational selection of optimal, i.e. least variable, targets for diagnostic tests and vaccines. Additionally, the results can help in understanding genomic variation in GAS and lead to novel epidemiological tools based on next generation sequencing.Understanding genomic variations that exist among bacterial strains might help delineate the distinctive nature of strains that, for instance, result in outbreaks of epidemic infections. Currently, such comparative studies are prevailing because of the growing availability of whole genome sequences of numerous bacterial strains. In GAS, various strains of both invasive and non-invasive nature have been whole genome sequenced. However, whole genome sequencing of individual strains may not be feasible due to time and money constraints and it is important to assess the robustness of Pool-seq as a potential alternative to sequencing strains individually. We have demonstrated that Pool-seq is a robust, rapid and cost-efficient alternative for genome-wide polymorphism surveys given high enough sequencing depth, suitable minimum read count, and the right choice of variant calling methods.In Pool-seq, the precision of variant detection increases with the increase in depth of coverage and decreases with the minimum number of reads required for allele calling25The analysis with the random subset of reads showed that Pool-seq could be useful in variant discovery even at ~20x depth of coverage per strain than the average aligned depth that we reached (~400x per strain). In planning a Pool-seq approach, it is, however, necessary to be aware of an increase in the false negative rate by an increase in the required minimum proportion of reads. For example, the false negative rate can be up to ~63% at a minimum count threshold of 50%. We note that we used only a few individually sequenced strains for verifying the efficiency of Pool-seq and as a result the false negative rate could be higher for some strains due to differential representation in the pool. Further, because we had variant information for only six of the 50 strains in a pool, we cannot report the false positive rate from our study.et al. used SAMtools for variant detection and removed PCR duplicates which resulted in identification of only 598 of the 1304 (45.9%) dbSNPs variantset al. observed for their Restriction site-Associated DNA (RAD) data that without duplicate removal the “effective pool size” substantially decreased, leading them to conclude that PCR duplicates considerably contribute to the overall experimental erroret al.In our comparison of variant calling tools, using SAMtools with duplicate removal resulted in the identification of the least number of variants within each of the six individual strains. Some Pool-seq studies have used SAMtools and/or removed duplicates11Results from the analysis of the public data were used to confirm the efficiency of our pooling strategy by validating the variants we identified from the pools. For instance, we correctly identified low variability within the 23S rRNA region that is highly conserved among different strains of GAS. Similarly, we also found the prophage regions of the reference strain to have the lowest depth of coverage in our pools and the same was seen in the public ENA data. In our analysis of the public data, we also found that only a small portion of the variants identified from the ENA dataset was discovered in our two pools and the 44 complete genomes. This shows that the strains in our pools and the complete genomes represent only a small and geographically limited selection of strains. Therefore, if the Pool-seq strategy is used in identifying diagnostic or vaccine targets it is essential to select strains from as wide geographical area as possible.In this study, we have examined issues such as the expected depth of coverage, representation of samples in a pool, frequency of alleles and variant calling methods that are central to a Pool-seq genome wide polymorphism detection study. We have demonstrated that Pool-seq can be an efficient and cost-effective alternative in polymorphism discovery for large samples of organisms, especially if a high quality reference genome is already publicly available.emm types isolated in wide geographical area in Finland within years 1995–2012.The 100 GAS strains used in the two pools are listed in the 2. DNA was isolated using UltraClean Microbial DNA Isolation Kit (MoBio) according to manufacturer’s instructions except for the following modifications: in the beginning 300 μl MicroBead solution and 6 μl mutanolysin (1 mg/ml) was mixed in a tube followed by addition of a 10 μl loopful of bacteria scraped from the culture plate. After incubation for 60 min at +37 °C, the solution was transferred to a MicroBead tube, and 2 μl of RNAse A (1 mg/ml) was added. From there, the manufacturer’s instructions were followed until at step 18, 35 μl of solution MD5 was added followed by 2 min incubation. Before pooling, the quality and the integrity of the DNA was checked using Nanodrop equipment (Thermo Scientific) and agarose gel electrophoresis. From each GAS strain 400 ng of DNA was used in one of the pools of 50 strains . Adapter and primer contaminants discovered by FastQC were trimmed using Trimmomatic (version 0.33)2, and DNA was extracted from bacterial colonies with MagAttract HMW DNA Kit (Qiagen). DNA extraction was done as the manufacturer indicates, but adding 6 μl mutanolysin (1 mg/ml) with lysozyme to improve DNA yield. Library was constructed with Illumina Nextera XT DNA Kit for sequencing and the library was sequenced with Illumina MiSeq 150 bp paired-end sequencing at Turku Centre of Biotechnology, Finland.Six strains were cultivated overnight on sheep blood agar at 35 °C under 5% COReads from the ENA dataset and the six individual strains were quality checked using FastQC (version 0.11.2). Trimmomatic (version 0.33) was used to trim low quality reads and contaminants. Bwa mem (version 0.7.10), using default parameters, was used to align the quality filtered reads to the reference genome. Duplicates were marked using Picard (version 1.122). SAMtools (version 1.1) was used to call variants from reads having a mapping quality of at least 20.The variants among the 45 complete genomes (including the used reference genome) were identified by using C-Sibelia (version 3.0.5)The variants from the two pools were concatenated and merged using bcftoolsFisher’s exact test was used to compare the proportion of the variants from the pools, the ENA dataset and the 44 complete genomes. The p-values obtained were adjusted using the Bonferroni multiple test correction and a significance cut off value of 0.05 was used. The Welch Anova test was performed to compare the means of the proportions.Polymerase chain reaction and Sanger sequencing were used to confirm variant calling results. Two out of the 20 most variable genes were selected as the target genes and all samples from both the pools (50 samples in each pool) were investigated by PCR. DNA amplification was performed using GoTaq G2 Hot Start polymerase  as the manufacturer indicates. The following primer pairs were used to amplify the investigated genes, respectively: 5′-TTTGATGAGGCAGCACATCT-3′ and 5′-TTTCAAAAGAAGGCATAGCAGT-3′; 5′-TAATGAGAGGAGTAAACTAGAAC-3′ and 5′-AGCCAAGAATTCACCAACCA-3′. Primers were designed to bind outside the gene region by using Primer3 softwareHow to cite this article: Weldatsadik, R. G. et al. Sequence analysis of pooled bacterial samples enables identification of strain variation in group A streptococcus. Sci. Rep.7, 45771; doi: 10.1038/srep45771 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.