Well-advised priority setting in prevention and treatment of injuries relies on detailed insight into costs of injury. This study aimed to provide a detailed overview of medical and productivity costs due to injury up to two years post-injury and compare these costs across subgroups for injury severity and age.A prospective longitudinal cohort study followed all adult (≥18 years) injury patients admitted to a hospital in Noord-Brabant, the Netherlands. Patients filled out questionnaires 1 week, 1, 3, 6, 12 and 24 months after trauma, including items on health care consumption from the medical consumption questionnaire (iMCQ) and productivity loss from the productivity cost questionnaire (PCQ). Furthermore, injury severity was defined by Injury Severity Score (ISS). Data on diagnostics was retrieved from hospital registries. We calculated medical costs, consisting of in-hospital costs and post-hospital medical costs, and productivity costs due to injury up to two years post-injury.Approximately 50% (N = 4883) of registered patients provided informed consent, and 3785 filled out at least one questionnaire. In total, the average costs per patient were €12,190. In-hospital costs, post-hospital medical costs and productivity costs contributed €4810, €5110 and €5830, respectively. Total costs per patient increased with injury severity, from €7030 in ISS1-3 to €23,750 in ISS16+ and were lowest for age category 18-24y (€7980), highest for age category 85 years and over , and fluctuated over age groups in between.Both medical costs and productivity costs generally increased with injury severity. Furthermore, productivity costs were found to be a large component of total costs of injury in ISS1-8 and are therefore a potentially interesting area with regard to reducing costs. Injury is a leading cause of death and disability across the world, and therefore a major public health problem , 2. FurtPrevious research on costs of injury is scarce, and has mainly focussed on specific injury types rather than injury severity. Some examples of specific injury types that have been studied are traumatic brain injury , 5, handThis study aimed to provide a detailed overview of the in-hospital and post-hospital health care costs and productivity costs due to injury up to two years after presentation at the emergency department (ED), and to provide an overview of differences in health care and productivity costs after injury for subgroups based on injury severity and age. The data that were used in this study consist of highly detailed registries of both injury severity and medical care used after hospital discharge. The highly detailed registries, including diagnostic costs during hospital stay (such as costs of a CT-scan), contribute to the uniqueness of this study, as costs can be displayed on a more detailed level than has been done in previous research.Data on injury severity and health care consumption was acquired from the Brabant Injury Outcome Surveillance (BIOS) study . The BIOIf participants did not complete the first questionnaire, they were not excluded from the BIOS study but were still invited at the subsequent time points. In case a participant was incapable of filling out a questionnaire due to for example severe injuries or dementia, a proxy informant filled out the questionnaire. Data on diagnostics during hospital stay were retrieved from the hospital registries. In our study, participants from the BIOS study were included if they filled out at least one questionnaire. Participants who were registered at the ED, but failed to fill out at least one questionnaire were considered non-responders.Demographic information of the patients, such as age and gender, were registered at hospital admission. Furthermore, injury severity was defined by the Injury Severity Score (ISS) . The ISSHealth care use was reported by patients in the follow-up surveys at 1, 3, 6, 12 and 24 months after trauma. Each of these surveys included the Medical Consumption Questionnaire (iMCQ) . The iMCTotal health care use per respondent was determined per period in between surveys. More specifically, all respondents of the survey at one month were included in the health care use of period one, all respondents at three months were included for the health care use between one and three months after hospital discharge, etcetera. A distinction was made between respondents with different entry moments to the follow-up (e.g. start follow-up at 1 month or start at 3 months). Since not all respondents filled out every question in the survey, the mean costs per health care item are based on the respondents that did answer the corresponding questions. Therefore, total costs cannot be based on the average costs per cost component, as the cost components comprise different groups of respondents within the included population.Unit costs of all health care activities that were undertaken (diagnostics excepted) were retrieved from a cost-reference manual and are presented in Apart from medical costs, also productivity costs were included in the analyses. Productivity loss at work was reported by respondents with the iMTA productivity cost questionnaire (PCQ) . RespondResponders and non-responders were compared to see whether responders were different from non-responders. Distribution of age, gender, ISS and length of hospital stay were compared using a chi-squared test for categorical variables, Mann-Whitney U test and independent sample T-test for continuous variables. P-values<0.05 were considered to indicate statistical significance. Subgroups of different injury severities, sex and age were compared to see whether these differed in costs. Age was divided in 18-24y, 25-44y, 45-64y, 65-74y, 75-84y and 85y+, and ISS was divided in categories ISS1-3, ISS4-8, ISS9-15 and ISS≥16+. Furthermore, an interaction term for age and injury severity was tested for statistical significance using linear regression with age, injury severity and the interaction term as explanatory variables for dependent variables: in-hospital costs (model 1), post-hospital costs (model 2), productivity costs (model 3) and total costs (model 4). All analyses were conducted in SPSS V.24 .A total of 4883 patients participated in the BIOS study (response rate 50.0%), and 3785 patients (77.5%) filled out at least one follow-up questionnaire on health care use and return to work and were included in the analyses . ApproxiThe total in-hospital costs were on average €4810 per patient and were mainly driven by the costs of stay at a ward   followed by the costs of staying in an institution (€1140). In total, 5.9% of the patients stayed at a nursing home for on average 37 days, 4.6% stayed at a care home for on average 41 days and 6.4% stayed in a rehabilitation center for on average 41 days. The median costs and interquartile range show that costs of stay/day treatment in an institution and homecare in most subgroups are skewed, and the mean costs are driven by only a small group of respondents with extremely high costs. Post-hospital medical costs were on average €7190 for the group of elderly (65y+). Among this group of elderly homecare contributed most (68.6%) to the post-hospital medical costs. Furthermore, we found that costs of stay in an institution and homecare increased with age, whereas costs of day treatment fluctuated with age.Approximately one third  of the respondents within the working age range  indicated not to be in paid employment before sustaining injury, of which 88% was aged 45-67y. Within the group that was in paid employment before sustaining injury, 82.7% (n = 1022) indicated to have missed workdays due to injury, with a mean duration of 13.6 work weeks. Mean productivity costs (€5830) were higher than in-hospital costs and post-hospital costs for the working population (18-67y). Productivity costs were almost twice as high for males compared to females . A larger percentage of males than females was in paid employment before injury , and mean number of hours work missed was higher for males than for females . Furthermore, productivity costs were higher for the younger working population (25–44 years) than for the older working population (45–67 years), with a mean of €7830 versus €5330 per person. Once returned to work, respondents in the working age (18–67 years) rated their productivity as 6 out of 10 . The mean number of days at work with reduced productivity was 35 days .In total, the average costs per patient were €12,190. No pattern was found in the total costs per person over age groups, as mean total costs were lowest for age 18-24y (€7980) and for age 65-74y (€8960). Due to the inclusion of productivity costs, and the absence of productivity costs after the age of 67, there is no clear pattern in total costs. Highest total costs per person were found for age 85 years and over, with a mean of €15,580. Mean in-hospital costs per person increased with increasing injury severity, from €2890 for ISS 1–3 to €11,590 for ISS≥16. This difference in in-hospital costs was mainly driven by differences between ICU costs, which were almost 100 times higher for the ISS≥16 respondents (ISS 1–3: €30 vs. ISS≥16: €2290), and costs for stay at a ward, which were more than 5 times higher (ISS 1–3: €1490 vs. ISS≥16: €7510). Post-hospital medical costs also increased with increasing injury severity up to ISS 9–15, but were lower in ISS≥16 than in ISS 9–15. Costs of homecare were an exception, with second lowest costs for ISS≥16 (€1990), and highest costs for respondents with ISS 9–15 (€4750). As homecare is more common for elderly people, it should be noted that only 18% of respondents in ISS≥16 was aged 75+ years, whereas in ISS 9–15 this proportion was 49%. Furthermore, 67% of participants in ISS 9–15 suffered from hip fracture, and homecare is likely to be provided after a hip fracture. The main driver of post-hospital medical costs was homecare for ISS 1–15, and costs of stay in an institution for ISS≥16. Productivity costs were again highest for the most severely injured (ISS≥16: €8640), and lowest for the minor injuries (ISS 1–3: €3910). In ISS≥16 74% of the respondents was in the working age range (18-67y). The mean total costs of injury, including both medical and productivity costs, increased with injury severity, but fluctuated over age groups within the ISS categories . Even thThis study described the medical costs and productivity costs after trauma in a large multicentre prospective injury cohort study with varying injury severity. Mean total costs per person of injury, including both medical and productivity costs, increased with injury severity, but varied across age groups. However, mean medical costs per person increased with age. The difference in patterns across age groups for total costs and medical costs can be explained by the absence of productivity costs in age groups of 67+ year, and high productivity costs in younger age groups. Furthermore, an interaction term of age and injury severity was found to be significant for in-hospital costs, which might affect the pattern of medical costs. In-hospital costs were also found to increase with injury severity, mainly driven by costs of stay at a ward. Furthermore, in-hospital costs were the smallest cost component for injury severity categories 1–3 and 9–15; however, for ISS≥16 it was the largest cost component. Post-hospital medical costs increased with injury severity up to ISS 9–15, and were mainly driven by costs of homecare. ISS≥16 was an exception, where post-hospital medical costs were lower than in ISS 9–15 and were not driven by costs of homecare, which can be explained by the small percentage of elderly in this injury severity category (18% vs. 49% in ISS9-15). Productivity costs were increasing with injury severity, except for ISS 9–15, due to the large proportion of elderly (67y+) in this group that have no productivity costs. In ISS 1–3 and ISS 4–8 productivity costs comprised a large part of total costs of injury. Productivity costs were highest in all ISS categories for age group 24–44, except for ISS 9–15. After return to work, productivity level was just over half, meaning that productivity costs are actually even higher.All costs were reported as mean values, with the median and interquartile range available as well. The median and interquartile range show that costs of ICU stay, stay in an institution, day treatment and homecare are skewed, meaning that outliers affect the mean costs. This can be seen in mean costs for ICU, as the IQR is zero for the total population, while subgroup ISS≥16 has an IQR ranging from 0 to €3639. Furthermore, mean costs of homecare were affected by some outliers in the elderly population.Costs of injury have been studied before, but not with a specific injury severity classification in combination with a detailed level of costs. The findings of the studies by Polinder et al. and Meerding et al. , 8 were Another study by Polinder et al.  pointed This study had several strengths and limitations. A major strength of our study was that the in-hospital, post-hospital medical costs and productivity costs were calculated with a high level of detail. The in-hospital costs included costs of diagnostics, which is unique for a study of injury costs in a general injury population. Furthermore, because ISS of the respondents was available, we could calculate each of the cost components by injury severity level, which has not been studied before.A limitation of our study was that the rate of respondents that completed follow-up up to 24 months post-injury was relatively low. A possible cause of the low response rate was the length of the survey, which included measurement instruments on health status, psychological consequences, health care consumption, work absenteeism and work presenteeism. Patients with a rapid recovery are likely to have been lost to follow-up sooner, as questions on health status, psychological consequences, health care consumption and work might seem irrelevant to them when recovery took place shortly after their injury. This could have resulted in a participation bias of the sample that filled out more questionnaires and therefore an overestimation of the actual mean costs. This affects both internal validity of our findings and generalizability of the results to the Dutch injury population. In addition, it was found that demographics of responders and non-responders differed with respect to a number of characteristics, which supports also the expectation of non-response bias.A second limitation of this study was that several assumptions had to be made to calculate the costs of injury. As not all respondents filled out the questionnaires completely, the number of respondents that was included in the cost calculations of different items varied. Even though it is a limitation that the group of respondents is not the same for each cost item, the inclusion of all available responses enables the use of all available information. Another assumption that should be taken into account is the duration between different surveys. It is likely that responses one month after injury (informing on the previous month), 3 months after injury (informing on the previous 2 months) and 6 months after injury (informing on the previous 3 months) are more accurate than responses 12 months after injury (informing on the previous 6 months) and 24 months after injury (informing on the previous 12 months), considering recall bias. Furthermore, to enable total cost calculations, zero-values had to be imputed for missing values, which may have led to an underestimation of total cost.A third limitation of the study was the inability to control for the deviation between injury related health care and health care that was not related to the injury. Costs of homecare in particular were found to be high in ISS1-3, indicating that reported homecare is not only injury related. Even though respondents were asked to report only injury related care activities, the results indicate that also homecare related to, for example, comorbidities was reported. Therefore, the costs of homecare and post-hospital medical costs are most likely an overestimation of injury related costs, especially in the older age groups.A final limitation of our study was that for the calculation of productivity costs the average wage per hour was used independently of education level. General average wage for male and female was available only, with no subdivision for education level. As the percentage of respondents with a low education level in our study (52.4%) was much higher than the percentage for the Dutch working population (28.6%) , this maThe findings of this study showed that productivity costs were high. With a long duration of work absence, and on average just over half the productivity level at work on return, an intervention dedicated to improve return to work and productivity level after injury might reduce the total costs of injury. Furthermore, it was shown that costs of injury are increasing with severity, but fluctuated over age groups. With the group of 85y+ having the highest costs of injury, this is a relevant group for injury prevention, as injuries in this age group often result from falls and programs directed to prevent falls are available.In conclusion, medical costs of injury were increasing with injury severity. The main contributor to in-hospital costs are the costs of stay at a ward, and for post-hospital costs the costs of homecare, except for ISS≥16. Productivity costs comprised a large part of the total costs of injury for the working age population (18-67y) in all severity categories, indicating that these costs should be included in the analyses of injury costs as well, and should be a main focus point of interventions aiming to reduce costs of injury. Total medical costs were found to be highest for the oldest age group (85y+), indicating that among this age group injury prevention is especially important.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


Primula is controlled by the S locus. The S locus genes, which control anther position, pistil length and pollen size in pin and thrum flowers, have not yet been characterized. We have integrated S‐linked genes, marker sequences and mutant phenotypes to create a map of the P. vulgaris S locus region that will facilitate the identification of key S locus genes. We have generated, sequenced and annotated BAC sequences spanning the S locus, and identified its chromosomal location.Heteromorphic flower development in in situ hybridization.We have employed a combination of classical genetics and three‐point crosses with molecular genetic analysis of recombinants to generate the map. We have characterized this region by Illumina sequencing and bioinformatic analysis, together with chromosome P. vulgaris S locus flanked by phenotypic and DNA sequence markers. BAC contigs encompass a 1.5‐Mb genomic region with 1 Mb of sequence containing 82 S‐linked genes anchored to overlapping BACs. The S locus is located close to the centromere of the largest metacentric chromosome pair.We present an integrated genetic and physical map across the Primula and enable evolutionary analyses of the S locus.These data will facilitate the identification of the genes that orchestrate heterostyly in  S locus     , red stigma (g), red leaf back (l) and double (x)  analysis . Hose in Hose  according to the manufacturer's instructions, and Southern analysis was performed as described previously , microscopy and imaging were performed as described previously  was added to each slide (40 μl) before hybridization to limit the hybridization of repetitive probe sequences. After hybridization, the most stringent wash in 0.05 × saline sodium citrate (SSC) at 43°C corresponded to a hybridization stringency of 78% (high‐stringency hybridization), and in 1 × SSC at 42°C to low‐stringency hybridization.BACs were labelled with biotin‐dUTP or digoxigenin‐dUTP and detected with fluorescein or Alexa‐594 conjugates. et al., http://www.tgac.ac.uk/tgac-browser/. Contig assembly and annotation details are given in Supporting Information Methods S1. All sequences have been deposited at the National Center for Biotechnology Information (NCBI) under Bioproject number PRJEB7311. BAC contigs and annotations are available at http://browser.tgac.ac.uk/primula_vulgaris_slocus/.BAC library construction and screening have been described previously  and 2.9‐kb (P2) bands; a 3.0‐kb band (T) represents the thrum allele. A P1P1 homozygote, a P1P2 heterozygote and a P2P2 homozygote with respect to PvSLL1 are shown. The two thrum plants have genotypes P1T and P2T  and > 12‐kb (P2) bands; a 4.0‐kb band represents the thrum allele (T)  is common to pin and thrum alleles of PvGlo. A 6.3‐kb band, also found in pins and thrums, derives from both P1 and P2 alleles, and is designated P1 + P2. The plant in lane 1 lacks the 4.2‐kb P2 allele, but shows a stronger signal for the 6.3‐kb band compared with other plants, and is a P1P1 homozygote. The pin plants in lanes 2 and 3 are labelled as P2P? as it is not possible to determine whether the 6.3‐kb band derives from the P1 or P2 allele. Thrum plants have a thrum‐specific 11.5‐kb band. We assigned P1 and P2 to the different pin alleles of PvSLL1, PvSLL2 and PvGlo before genetic analysis to determine their recombination relationships to the S locus and each other.Figure S‐linked markers with a larger number of F2P. vulgaris cv Blue Jeans’ progeny. Between 144 and 193 plants were used in each assay, as shown in Table S locus and PvSLL1, PvSLP1 or PvGlo in any of the F2 progeny tested. However, we did observe two recombination events between the S locus and PvSLL2. The progeny numbers are small, but enabled us to determine minimum map distances based on the absence of recombination  and eight from recombination between Oakleaf and the S locus (O–S), are shown in Fig. PvSLL1 allele in coupling with the s allele is represented by a 3.0‐kb RFLP  also show that recombination of Hose in Hose does not affect PvSLL1. The two pin plants (plants 1 and 7) are homozygous for the 3.0‐kb pin allele of PvSLL1, and the thrum plant (plant 4) is heterozygous for the pin and thrum alleles of PvSLL1. PvSLL1 cannot therefore be outside Hose in Hose with respect to the S locus. Interestingly, plant 6 reveals a 2.5‐kb PvSLL1 allele in addition to the 3.0‐kb pin allele. This band either represents a deletion or a point mutation that affects the RFLP, or a recombination event between the S locus and PvSLL1 that affects the size of the RFLP. If this band represents a recombination event, this places PvSLL1 between the S locus and Hose in Hose. Subsequent analysis of the BAC contig spanning the S locus confirmed this location (see later).Eighteen of the 25 PvSLL2 is represented in this population by two alleles, a < 15‐kb band in coupling to the s allele, and a 5.0‐kb band in coupling with the S allele  showed recombination between either PvSLL1 and S or PvSLL2 and S. Only 28 plants showing recombination between Oakleaf and S were identified in 2075 progeny; of these, only one had recombined for PvSLL2. Based on these data, we assign a map distance between PvSLL2 and the S locus of 0.05 cM. Similarly, if the 2.5‐kb PvSLL1 RFLP in plant 6   defined the location of PvSLP1 on the map  and BAC81I19 (green))  for chromosome in situ hybridization on metaphase chromosomes. The 22 chromosomes were visualized with DAPI , is shown in Fig. PvGlo side of the S locus . These data  and BAC13A4 (green), which map to either side of the P. vulgaris BAC libraries and their screening using four S locus‐linked probes, PvSLL1 and PvSLL2 . We have not been able to join contig 3 . Group‐B: overlapping DNA sequence anchored to BACs from Contig S‐right yielded 58 contigs covering 888 kb. Group‐C: unanchored sequence contigs from pool 1 BACs comprised 56 contigs covering 325 kb. Group‐D: unanchored sequence contigs from pool 2 comprised 99 contigs covering 178 kb. In total, 1.5 Mb of sequence flanking the S locus was assembled; 1 Mb is anchored to specific BACs . It was not possible to generate a contiguous assembly across the entire region, and this is reflected by the assembly gaps in Group‐A  and Group‐B , and the unanchored contigs in Group‐C and Group‐D. The 17 contigs in Group‐A (Contig S‐left) and 58 contigs in Group‐B (Contig S‐right) were ordered relative to the BAC tiling path ; contigs residing between BAC‐ends could not be oriented or ordered relative to each other. Although it is not possible to assign an unambiguous order for all intervening contigs from specific BACs, a high level order of these contigs is shown in Table S1. Contigs containing BAC‐ends are highlighted in bold. The order of intervening contigs remains to be confirmed.The sequencing of 10 individual BACs from across the contig assemblies enabled us to assemble sequence contigs associated with the BAC contigs. We also sequenced two pools of BACs. Five BACs sequenced individually were also included in the pools . Pool 1 contained 19 BACs from contigs 1 and 2 . The number of predicted genes and gene fragments in each of the four BAC sequence groups is summarized in Table S2; 266 potential genes or gene fragments were identified. Of these sequences, 119 identified known proteins in BlastX searches; the remaining 147 predicted gene fragments gave no database similarities. We searched the Arabidopsis TAIR10 database and, after removal of duplicates caused by gene models on the same contig matching the same Arabidopsis gene, or the same Arabidopsis locus matching gene predictions on neighbouring contigs, we found 82 related Arabidopsis genes.We undertook Contig S‐left and Contig S‐right are presented in Table S2. Confirmation of gene order on internal BAC contigs remains to be confirmed. Within these contigs, we identified PvSLL1 on S_locus_groupB_ctg13 and PvGlo on S_locus_groupB_ctg58; we also located PvSLP1 to S_locus_groupB_ctg36. These data confirm the order of S‐linked markers on BAC contig assemblies , as summarized in Fig. Our previous studies defined ces Fig.  by RFLP cus Fig. . The RAPP. viscose and P. hortensis, De Winton & Haldane  has identified at least 82 new S locus‐linked genes (Table S2); a further 500 kb of S‐linked sequences remain to be anchored, and this will be facilitated with a more complete Primula genome assembly. Although we cannot yet predict the size of the gap between the two contigs, our data suggest that PvSLL2 and PvGlo are at least 1.5 Mb apart. PvGlo is at least 888 kb from the S locus , and Hose in Hose (PvGlo) is between 0.39 and 1.53 cM from the S locus; this suggests a relationship of 1 cM to 580–2277 kb.The assembly of over 1 Mb of sequence anchored to BACs surrounding the S locus genes or whether these reside within the gap between contigs. PvSLL2 is located within a contig flanked by 66.6 and 27.1 kb on either side (Table S1). None of the predicted genes in this contig are obvious candidates for Oakleaf ; ongoing annotation of the P. vulgaris genome and transcript‐driven gene model definition will resolve the number of genes. We have not found sequences corresponding to those identified in F. esculentum and L. grandiflorum in our gene annotations (Table S2), and this possibly reflects the polyphyletic origins for floral heteromorphy.It remains to be seen whether the assembled BAC contigs include the key Primula has a long history as a model for studies on floral heteromorphy, built on Darwin's landmark studies  should be directed to the Fig. S1  Map of the S locus showing assembly of the BAC contig flanking the regions.Methods S1  Bioinformatic supplemental methods.Click here for additional data file.Table S1  Sequence contig assemblies derived from S locus‐associated BAC sequencingTable S2  Annotation of sequence contig assemblies derived from S locus‐associated BACsClick here for additional data file.


One of the major causes of liver-related mortality and morbidity is Hepatitis C Virus (HCV) infection. It is also one of the reasons behinds of chronic liver disease and related complications such as cirrhosis and hepatocellular carcinoma. This autoimmune liver disease imposes a high economic burden on individuals and the society. This study aimed to estimate burden of HCV in Iran.Overall, 200 patients with HCV infection, referred to hospitals in three cities of Tehran, Karaj and Tabriz, Iran during year 2015, were randomly enrolled. To estimate the total burden of hepatitis, direct and indirect costs, costs of DALYs and social welfare were calculated.Economic burden of HCV infection was obtained 26242.8 purchasing power parity (PPP$). Intangible costs of HCV was calculated 207421.6 PPP$.Total direct costs of HCV for each patient are more than household consumption expenditure. Therefore, it is a reasonable policy to control and increase insurance coverage of HCV patients in order to decrease their costs. One of the major causes of liver-related mortality and morbidity is Hepatitis C Virus (HCV) infection. It is also one of the reasons behinds of chronic liver disease and related complications such as cirrhosis and hepatocellular carcinoma , 2. OverTransmission of this blood-borne pathogen will occur due to the exposure to the contaminated body fluids and blood , 8. DespSeveral methods have been proposed to quantify population-level burden of disease. The disability-adjusted life years (DALYs) is one way to measure population health which is being increasingly used in comparing and analyzing the burden due to diseases . It is aThe average diagnosis and treatment costs of hepatitis C were studied. One course of treatment and six months after that with standard protocol plus Ribavirin and Peg-interferon plus Ribavirin have costs of exceeds 3,850 and 16,494 purchasing power parity dollars (PPP$) respectively . HepatitWe aimed to estimate the population-level burden of HCV infection by calculating the disability-adjusted life years, direct and indirect costs and social welfare.Our study was descriptive, analytical, applied and retrospective. To do this study, 200 patients with HCV infection, who referred to hospitals in three cities of Tehran, Karaj and Tabriz, Iran during year 2015, were randomly selected.Written informed consent was obtained from each participant. The study was approved by Ethics Committee of Shahid Beheshti University of Medical Sciences, Tehran, Iran.Public library system and questionnaire were used for data collections. Questionnaire which contains information about demographic and patient’s history, quality of life, work productivity and activity impairment was prepared. Content validity of the questionnaire was examined with reference to the gastroenterologists’ and pharmacoeconomists’ comments and opinions. They were asked to evaluate relevance, completeness, scoring and clarity of each question. The Cronbach’s Alpha Coefficient for each question was determined to test the reliability of the questionnaire. Cronbach’s Alpha Coefficient more than 0.75 was approved level to each question. Correlation of each question with other questions was higher than medium level and there was no negative correlation (an inverse relationship) between questions.After questionnaire preparation, a review of the literature was undertaken to recognize the latest treatments available for patients with HCV, in Iran. In order to calculate total economic burden of hepatitis C, the algebraic sum of direct medical costs, direct non-medical costs and indirect costs was obtained. Costs of DALYs and costs of economic welfare index were also calculated as intangible costs. These items were collected as following:For direct medical and non-medical costs and indirect costs’ calculations, diagnostic and laboratory tests, physician visits and drug treatments were considered as direct medical costs and transportation, meals and telephone conversation were considered as direct non-medical costs. Common therapeutic protocol in HCV infection including direct-acting antivirals (DAAs) was used . We alsohttp://irmna.com/). The prices of medication were retrieved from drug list of Food and Drug Organization of Iran (http://www.fda.gov.ir/en/).The unit costs of these items (diagnostic and laboratory tests and physician visits) were calculated  using Murray methodology . The yeai is the income of individual and n is number of individuals. Finally, total economic burden of hepatitis C was obtained by the algebraic sum of direct medical costs, direct non-medical costs and indirect costs. Costs of DALYs and costs of economic welfare index were also calculated as intangible costs.Where W is social welfare, YThe study was done on 200 patients with HCV infection in Iran. The demographic characteristics of the mentioned patients have been shown in In We have also evaluated HCV patients in terms of underlying diseases. Liver disease and dementia disease were the most prevalent underlying diseases with frequency of 120 (60 %) and 62 (31%) respectively. Education and occupational status of HCV patients have been displayed in For estimation of direct medical and non-medical costs of HCV infection, we calculated costs of laboratory and diagnostic tests, physician visits and drug treatments as direct medical costs and transportation, meals and telephone conversation as direct non-medical costs.Common laboratory and diagnostic tests and their costs have been shown in Associated costs for treatment have been presented in Average indirect costs, ratio of direct to indirect costs and total costs of HCV infection were estimated in DALYs are formed from years of life lost (LLY) because of premature death and years lived with disability (YLD) consist of nonfatal injuries and disease. In order to calculate the years of life lost (YLL) because of premature mortality, 150 patients passed away because of HCV were randomly selected and their age at death was determined. YLL was obtained 0.87 yr based on the differences between life expectancy and the average age at death in HCV patients.Another dimension of the DALY is the time period in years lived in states of poor health or disability due to each disease (YLD). The disability is measured in length in years and in severity. The disability severity weights have been appointed by WHO for each disabling condition on a scale from one to zero. The mentioned scale, patients’ physical conditions, and experts’ opinions determine the weights. HCV patients’ physical conditions and reasons for their disability were evaluated. Reasons of patients’ disability were determined as insomnia, physical weakness, nervousness, depression, anxiety, joint and muscle pains, loss of appetite, inability to climb stairs, inability to flex knee, inability to walk more than 2 km and breathing problems. Average of severity weight for patients with HCV was obtained 0.34. HCV patients lived 15 yr in health states less than ideal health (with disability). YLD was calculated as follow:YLL and YLD were obtained about 0.8 and 3.74 yr respectively. Finally, DALYs formed from two components was obtained 4.6 yr. Costs of DALYs were gained from GDP per capita by means of YLL and YLD estimation. In A cardinal social welfare function is a function that takes as input numeric representations of individual utilities and returns as output a numeric representation of the collective welfare. Costs of social welfare were 135553.1 PPP$.Finally, economic burden of HCV infection was gained by sum of direct costs and indirect costs. It was obtained 8025.3 $ equal to 26242.8 PPP$. Intangible costs of HCV were sum of costs of DALYs and costs of social welfare. It was calculated 63431.7 $ equal to 207421.6 PPP$.HCV is one of the most common causes of morbidity, mortality and liver transplantation in the future. It also imposes a high socioeconomic burden on patients and the society , 18. Thehttps://data.worldbank.org/), total direct costs of HCV population was equal to 4.8% of it. Since the household consumption expenditure per capita in 2015 was about 9962 PPP$ based on our results, total direct costs of HCV for each patient are more than the household consumption expenditure per capita. Therefore, for the HCV patient, household’s income is not enough to cover the costs of it. Another point is about indirect costs of HCV. It will impose 613,560,000 PPP$ on community and health care systems which is due to loss of productivity and can damage the economics of the society. Most of direct costs of HCV were spent on drug treatments. Therefore, it is a reasonable policy of our healthcare systems to increase insurance coverage of HCV drugs in order to decrease costs imposed on HCV patients.Some portions of direct medical costs of HCV will be decreased due to insurance coverage. According to the insurance coverage percentages, different behavior of the insurance organizations in Iran, share of paid by patients and portion of services covered by insurance, we estimate that up to 40% of direct medical costs will be paid by insurance and the remaining will be deducted from the household consumption expenditure. Therefore, about 4,393,356,000 PPP$ will be imposed on HCV patients population in Iran. As the total health costs in Iran in 2015 was 90,799,249,123 PPP$  have been completely observed by the authors.


Lycium chinense Miller) showing chlorosis symptoms and its complete genome sequence was determined. The viral genome consists of a positive-sense single-stranded RNA of 10,100 ribonucleotides and contains six open reading frames (ORFs). Electron microscopy showed that the viral genome is packaged as a filamentous particle with an average length of approximately 850 nm. Phylogenetic analysis and amino acid similarity analysis of the encoded ORFs revealed that this new virus could be classified in an intermediate position between the families Benyviridae and Virgaviridae. The GBCV 200-kDa replicase (ORF1) is more similar to benyvirus replicases than to virgavirus replicases, while its 17-kDa coat protein  is more closely related with virgavirus CPs than benyvirus CPs. ORF3 was predicted to produce a C-terminally extended protein from ORF2 via frameshifting. While ORF4 (45-kDa), ORF5 (44-kDa), and ORF6 (16-kDa) have no apparent sequence homology with other known viruses, ORF5 is predicted to encode a movement protein (MP) that is phylogenetically related to the furovirus MP and ORF6 was experimentally proven to encode a viral suppressor of RNA silencing. These unusual characteristics suggest that GBCV may represent an evolutionary link between the families Benyviridae and Virgaviridae and indicate the existence of a novel, unidentified virus group.An unusual novel plant virus provisionally named goji berry chlorosis virus (GBCV) was isolated from goji berry plants ( Tobacco mosaic virus (TMV) in 1898, over 1470 species of plant viruses are now recognized by the International Committee for Taxonomy of Viruses (ICTV) . Therefore, we suggest that this contig is the genome sequence of a novel plant virus and the name goji berry chlorosis virus (GBCV) is proposed. The full-length genome sequence of GBCV was deposited in GenBank under the accession number MH791331.A total of 43,584,935 raw reads obtained after RNA-Seq were (184 nt) . The ORF3)T(X3)NS/T(X22)GDD (where X is any residue) at amino acid positions 1584–1619 [ORF1 (replicase) of GBCV contains three conserved domains : a viral(X3)NS/TXGDD  CP , and with the pea early-browning virus  CP . Amino acid sequence alignment revealed the GBCV CP contains some conserved motifs, such as DDA and FE, which were identified from amino acid positions 77–79 and 147–148, respectively  CP , with the tobacco rattle virus  and a stem-loop structure near the ORF2/ORF3 overlap region , which has a similar genetic organization with GBCV [ORF3 was detected in nt 5990–7102 and its N-terminus overlapped ORF2 in frame -1 . ORF3 hap region . The preith GBCV . FurtherORF4 and ORF5 were calculated to encode 45-kDa and 44-kDa proteins, respectively . BLASTn Benyviridae, Virgaviridae, Alphaflexiviridae, and Betaflexiviridae , whereas ORF4 has no phylogenetic relationship with other viral MPs, suggesting that ORF5 may encode a viral MP. Further experimental investigations are required for functional analyses of the ORF5 translation product.Plant viruses encode MPs for viral cell-to-cell and long-distance trafficking . As desciviridae . The treN. benthamiana transgenic line expressing GFP (line 16c). The tomato bushy stunt virus (TBSV) P19, which is a well-characterized viral silencing suppressor, was used as a positive control. At 3 dpi, GFP expression was observed under UV light. Suppression of GFP silencing was observed in the leaves infiltrated with agrobacteria expressing ORF6, but not in plants infiltrated with agrobacteria expressing either ORF4 or ORF5   . This phPlatypuvirus in the family Alphaflexiviridae might represent an evolutionary link between alphaflexiviruses and tombus-like viruses. Similarly, GBCV contains a chimeric genetic composition between benyviruses and virgaviruses , isolated from goji berry plants showing chlorosis symptoms. Based on determination of the complete genome sequence of GBCV, its genome organization, putative proteome characteristics, and taxonomic position were analyzed. The principal biological significance of the discovery of GBCV is in the intermediate position that this virus occupies between two different virus families, the S1 File(TXT)Click here for additional data file.


Fabavirus, Luteovirus) a fact that challenges our perspective of plant viruses in general. Finally, applied methodologies, including the use of different molecules as templates, as well as advantages and disadvantages and future directions of HTS in fruit tree virology are discussed.Perennial crops, such as fruit trees, are infected by many viruses, which are transmitted through vegetative propagation and grafting of infected plant material. Some of these pathogens cause severe crop losses and often reduce the productive life of the orchards. Detection and characterization of these agents in fruit trees is challenging, however, during the last years, the wide application of high-throughput sequencing (HTS) technologies has significantly facilitated this task. In this review, we present recent advances in the discovery, detection, and characterization of fruit tree viruses and virus-like agents accomplished by HTS approaches. A high number of new viruses have been described in the last 5 years, some of them exhibiting novel genomic features that have led to the proposal of the creation of new genera, and the revision of the current virus taxonomy status. Interestingly, several of the newly identified viruses belong to virus genera previously unknown to infect fruit tree species (e.g.,  Prunus species [Fruit trees host a wide range of viral pathogens, mainly as a result of their vegetative mode of propagation and perennial nature . Notably species . Some of species . The ide species ,6,7,8,9.Malus platycarpa, Malus micromalus, Malus pumila “Virginia Crab” or “Spy227”, for apple and pear virus pathogens [Prunus persica GF305, Prunus tomentosa, Prunus serrulata “Kwanzan” or “Shirofugen” [Several biological, serological, and molecular assays have been applied, either alone or in combination, for the detection of fruit tree viruses. Biological assays, also known as biological indexing, were, in the past, an essential tool for the evaluation of the health status of individual plants and for the detection and/or characterization of a particular virus. In the case of fruit tree viruses, bioassays took advantage of the increased susceptibility of some fruit tree genotypes to viral infection, resulting in pronounced and easily identifiable symptoms expression. A number of fruit tree genotypes have been used for this purpose, e.g., athogens ,11; and rofugen” ,13,14, frofugen” ,15, althPlum pox virus, PPV). In addition, a high intra-species genetic diversity of fruit tree viruses may result, not only in variable symptomatology [Effectiveness of bioassays vary considerably and can be hampered by several factors. Firstly, there is a need for controlled greenhouse facilities for plant maintenance, due to the vector-mediated transmission of several viruses, thus limiting a large scale and easy-to-use evaluation. Although symptoms on woody indicators could appear a few weeks post-inoculation, they may take from several months to years in the case of some viruses  and certification schemes, the labor- and time-consuming biological indexing, with problematic reliability and subjective evaluation, has less practical application in virus diagnosis.Serological methods, ELISA (enzyme-linked immunosorbent assay) and its modifications, although limited in sensitivity, enable cheap and fast parallel diagnosis of many samples, using either polyclonal, monoclonal, or recombinant antibodies ,20,21. HPrune dwarf virus (PDV) [Apple chlorotic leaf spot virus (ACLSV) [Generally, detection of viral pathogens by genome amplification techniques  is more sensitive than ELISA, while offering the possibility of multiple detection ,23,24,25us (PDV)  and Appl (ACLSV) , highligSuch problems can be overcome by the use of modern next generation sequencing (NGS) or high-throughput sequencing (HTS) technologies, which, theoretically, can produce sequence data of every putative viral agent present in a sample without the need of any former knowledge about their genome . This faHTS technologies were introduced in 2005 with the commercialization of FLX Genome Sequencer from 454 Life Sciences using real-time sequencing-by-synthesis pyrosequencing technology . The 454Nowadays, Illumina offers nine different sequencers  that can+) is released as a byproduct. Thus, the technology is based on the real time detection of hydrogen ion (H+) concentration, representing a change in the pH due to the ion release when a nucleotide is incorporated into a DNA strand. The principal components of the Ion Torrent sequencers are the sequencing chips. These microprocessor chips incorporate extremely dense arrays of millions of micromachined wells coupled to a proprietary ion sensor. Each well is able to hold a single DNA molecule from the DNA library. Currently, Ion Torrent commercializes three different sequencers that can hold different types of chips , which added a revolutionary semiconductor sequencing technology. Ion Torrent™ Technology directly translates chemical output into digital information on a semiconductor chip. The technology exploits the biochemical process that takes place when the polymerase incorporates a nucleotide into the growing DNA strand when a hydrogen ion  sequencing (Pacific Biosciences) where no amplification step for sample preparation is required, are in development. Pacific Biosciences offers two different sequencers that can generate from 500,000 to 10 million reads, with an average length of 1000 nucleotides . RecentlSample preparation for HTS usually includes a set of common steps, regardless of the HTS platform: Nucleic acid extraction, fragmentation, and/or size-selection; enrichment of RNA viral sequences; preparation of libraries; and bioinformatic analysis. Although these procedures require significant manipulation, time, and skills on genomic library preparation, currently, there are commercially available automated systems able to produce sequence-ready nucleic acids libraries. Platform manufacturers and third-party companies provide specific kits simplifying and standardizing the construction of libraries that, in addition, can be prepared for multiplexing if necessary. Optimal results are obtained using highly pure starting nucleic acids preparation. Contamination, inhibitors, or impurities in the starting material can produce false negative results and artifacts. Although nucleic acid purification, even from woody plants, is a routine task in many laboratories, the preparation of high quality nucleic acids for HTS is not trivial. Different types of targets have been used for fruit tree virus detection, as follows. (a) Virus-derived small interfering RNAs RNA silencing constitutes a major antiviral mechanism in plants, where hosts enzymes called dicers cut the viral RNA into small interfering RNAs (siRNAs) 21–24 nt long. These molecules can be isolated from the infected plants, subjected to HTS, and used to reconstruct viral genomes. Virus-derived siRNAs have been used to detect known and unknown plant viruses in fruit trees by HTS ,40,41,42(b) Double-stranded RNA Apricot vein clearing associated virus (AVCaV) [Prunus virus T (PrVT) [dsRNA has been exploited to detect fruit tree viruses by HTS, and also in the study of diseases of unknown etiology ,48,49,50 (AVCaV) , Prunus T (PrVT) , a new lT (PrVT) .(c) Total DNA or RNATotal DNA-sequencing has been scarcely used in the detection of viruses from woody plants. It has been successfully applied in citrus to identify a new DNA virus  using gePrunus species [Total RNA-sequencing has been used to detect and characterize viruses in several woody crops, such as grapevine ,54,55,56 species ,49. Alth(d) Virion-associated nucleic acids purified from virus-like particlesVirion-associated nucleic acids (VANA) are used to enrich viral nucleic acids by purifying viral particles from the plant material , howeverhttps://blast.ncbi.nlm.nih.gov/Blast.cgi). De novo assembly has limitations, especially when faced with the recovery of several viral variants or virus strains of the same virus species in a single plant sample. This occurs particularly when siRNAs are used as template for HTS, due to the low length of reads that can produce false positive results or incorrect assembly. In that case, a strategy that uses longer reads  can help solve the problem, as stringent assembly parameters facilitates the recovery of each of the isolates that infect the sample. Subsequently, different nucleotide sequences among variants, such as single nucleotide polymorphism (SNP) or insertions and deletions (indels), can be analyzed by PCR amplification and restriction fragment length polymorphism (RFLP) analysis. The increasing number of available host genomes allows for the bioinformatic depletion of host genomes that, along with the deduplication of reads, can facilitate the analysis at high sequencing depth. There is a continuous development of suitable pipelines for plant virus discovery and detection, in the attempt to reconcile computing needs with the pace of the improvements and development of new HTS platforms. The first automatic pipeline for the identification of viruses in RNA-sequenced samples, VirusFinder, was developed by Wang et al. [The bioinformatic analysis of the HTS data can be performed with biologist-friendly commercially available packages or with open platforms. Quality control, sequence assembly, contig annotation, and identification of variations between samples are required steps for the analysis of data. Quality control depends on the technology and the standard parameters whose thresholds are usually provided by the manufacturer. The assembly of reads to recover a viral genome can rely on two different approaches: (i) De novo assembly, where the viral genomes are partially or fully reconstructed by annotation of the generated contigs, or (ii) reads mapping against a reference sequence. For low titer fruit tree viruses, a combination of both approaches might be required, along with higher sequencing depth. Annotation of contigs is performed using BLASTn, BLASTx, BLASTp, and tBLASTx .HTS is now entering in the routine detection of plant viruses, either in cases of unknown etiology or in quarantine analysis of plant material trades. Facilitated by the decrease of costs, HTS is going to become the method of choice for virus discovery and identification in fruit trees. Scientific discussions are now dealing with the challenges of the technique and with the definition of laboratory standards for its application  CitrusCitrus yellow vein clearing virus, CYVCV) was discovered by siRNA analysis in Turkish accessions, and it was related to, but sufficiently divergent from the Indian citrus ringspot virus in the genus Mandarivirus. In the latter disease, a new viral DNA sequence was associated with the symptoms through siRNAs and total DNA sequencing. This new, highly divergent monopartite geminivirus was named Citrus chlorotic dwarf associated virus (CCDaV).The list of citrus virus-like diseases with unknown etiology was updated since 2012, with two publications on citrus yellow vein clearing of lemon trees  and citrEnamovirus genus. In order to identify the causal agent of citrus vein enation disease, Vives et al.  examinedOrchid fleck virus, and attributed it to the proposed and still unassigned genus Dichoravirus. From Citrus leprosis symptomatic leaves from Colombia, Roy et al. [Citrus leprosis virus atypical strain , plus Citrus tristeza virus (CTV) and citrus viroid sequences. This new virus produced symptoms typical of CiLV, but was not detected with either serological or PCR-based assays targeting the previously described cytoplasmic virus. Finally, the same group detected in Florida, on Carrizo citrange analyzed for citrus decline disease/citrus blight, three different endogenous pararetroviruses, significantly matching the Petunia vein clearing virus genome [A series of studies on citrus leprosis-associated viruses was described by Roy and co-authors. This disease, present in South and Central America and transmitted by mites, is caused by two differently shaped and taxonomically allocated viruses. Roy et al. ,64 descry et al.  produceds genome ; while, s genome .Citrus sudden death-associated virus (CSDaV), and an effort to further clarify the virome linked to disease expression was done by Matsumura et al. [A siRNAs library was prepared in Italy from orange trees affected by concave gum, a severe citrus disease reported more than 80 years ago and still with an unknown etiology. Navarro et al.  identifia et al. . The seq(b) Stone fruitsPrunus for de novo discovery and detection of viruses started from the INRA–Bordeaux team in 2013. Candresse et al. [Little cherry virus-1 (LChV1), suggested that LChV1 could be responsible for the SSD syndrome.A pioneering work on HTS application to e et al.  analyzedBetaflexiviridae. The identified viral species showed sequence homology with the sole member of the genus Tepovirus, Potato virus T (PVT). The name Prunus virus T was proposed for this new virus, which has 1% prevalence in the screening of a large Prunus collection.From a cherry tree collected in Italy, and a plum tree collected in Azerbaijan, both with mixed-infections and no symptoms, Marais et al.  reconstrPrunus viruses were detected, while sequencing of dsRNA allowed the identification of a novel virus showing the highest nucleotide identity (ca. 40%) with Citrus leaf blotch virus (CLBV). The borderline phylogenetic allocation of this virus, namely Apricot vein clearing associated virus (AVCaV), between citri- and vitiviruses (presence of four distinct encoded proteins) led to a proposal for a new genus in Betaflexiviridae. Indeed, a further report from Marais et al. [Caucasus prunus virus, CPrV). The authors suggested that AVCaV and CPrV, having close genetic and structural similarity, could be integrated in the newly created genus Prunevirus. Anyway, while Elbeaino et al. [Subsequently, during a field survey in apricot orchards, vein clearing and mottling symptoms were observed by Elbeaino et al.  on youngs et al.  identifio et al.  identifiAsian prunus virus 1, 2, and 3 . A relevant phylogenetic assessment was that APV2 should be considered as a distinct viral species in the genus Foveavirus, while taxonomies of APV1 and APV3 were not yet defined. In the most recent report from this group [Prunus mume) showing diffuse chlorotic spots on leaves. Lenz et al. [Luteoviridae reported to naturally infect woody plants. After this discovery, sequence homologies to ChALV were identified by Wu et al. [Rosaceae-associated luteoviruses  was therefore conceived and proposed. Additional work was presented on the full genome sequencing of the Asian prunus viruses. Marais et al.  reconstris group , the newz et al. , in Czecu et al.  in the UP. persica trees; the same marafivirus and luteovirus were found in symptomless nectarine and peach selections, which tested negative by indexing or free from known viruses by serological and molecular tests. In the attempts to clarify the complex association and genomic relationship of several virus-like diseases and the related agents in cherry, Villamor et al. [Cherry green ring mottle virus, and Cherry necrotic rusty mottle virus) and determined new sequences from isolates of Cherry twisted leaf-associated virus (CTLaV) and Cherry rusty mottle-associated virus (CRMaV). Finally, the segregation of these viral sequences into four clades corresponding to distinct virus species was assessed. The establishment of a new genus (Robigovirus), gathering these viruses, was then suggested within the family Betaflexiviridae.A sequencing project performed in California  on dsRNAr et al.  did a coPrunus virus F (PrVF), and it was found associated in the sample along with other common Prunus-infecting viruses. Villamor et al.  revealedPrunus viruses were also identified during recent HTS screening and surveys in Asia. He et al. [Fabavirus species, CVF, was identified by Koloniuk et al. [More new e et al.  sequencek et al.  infectinMarafivirus, with a closer relationship (56–61% amino acid identity) with Nectarine virus M (NeVM), recently reported to infect nectarine. Similarly, Jo et al. [Tymoviridae, having a very close similarity to PeVD.Igori and co-workers described the complete sequence of a highly divergent South Korean isolate of a ChALV from peach . Later oo et al.  describi(c) Pome fruitsApple stem grooving virus (ASGV), Apple stem pitting virus (ASPV), Apple green crinkle associated virus (AGCaV), and Apricot latent virus (ApLV). HTS analysis of an siRNA library allowed for the discovery of an isolate of AGCaV in field-grown quince plants showing symptoms of fruit deformation and bud failure [HTS analysis was applied to study the occurrence of symptoms of small leaves and growth retardation in field-grown apple trees in Korea . The stu failure . In a suApple mosaic virus (ApMV), led to the discovery of a novel ilarvirus, closely correlated with ApMV, which was named Apple necrotic mosaic virus (ApNMV) [An apple geminivirus was discovered in apple by sequencing an siRNA library . The vir (ApNMV) .Bunyavirales. The authors suggest a taxon as a new genus under the Phenuiviridae family. Finally, Apple-associated luteovirus (AaLV) is a new species in the genus Luteovirus discovered by HTS sequencing of a library of rRNA-depleted total RNAs [A couple of publications deal with the study of Apple rubbery wood disease by HTS analysis. While Jakovljevic et al.  failed ital RNAs . AaLV wa(d) Examples of High-Throughput Sequencing based virus discovery on minor fruit trees A short survey on the literature regarding the minor fruit tree species can be presented to further support the wide potential of HTS discovery when applied to some “neglected” virus-like plant disorders. Ito et al.  detectedMulberry mosaic dwarf associated virus) in a Chinese accession affected by mosaic and dwarfing symptoms. This virus has a small monopartite circular DNA genome (2.95 kb) containing ORFs (open reading frames) in both polarity strands, resembling CCDaV, a divergent geminivirus recently identified in citrus  has been characterized as the etiological agent of a disease observed on a mulberry tree in Lebanon by Chiumenti et al. [In mulberry, a library from siRNAs allowed Ma et al.  to idente et al. ). The Mui et al. . An siRNActinidia spp.) in China, and provided the first complete genome sequence of an ASGV isolate (ASGV-Ac) infecting a kiwi fruit plant. This sequence is phylogenetically distant to ASGV isolates from all other hosts by sharing about 80% genome sequence identity, and likely represents a novel variant. Zheng et al. [Emaravirus. A final report from New Zealand [Actinidia chinensis (a seedling in home garden), its genome contains four open reading frames, and is most closely related to CPrV (56% nt identity), a member of the genus Prunevirus in Betaflexiviridae. Plants were affected by vein chlorosis and mottling, but were found to be co-infected with Actinidia virus A and/or Actinidia virus 1, although ASbLV was also detected in asymptomatic vines as a single infection.Wang et al.  sequenceg et al.  characte Zealand  describeThe increasing use of HTS techniques for a rapid and sensitive detection of the virome in particular plant material  is essentially devoted to have a complete picture of the systemic agents (for what is known in that host). This application is generally intended as “targeted”, when generic or even specific primers are able to amplify all the variability in a particular target sequence and compare, simultaneously, up to several hundreds of samples in a single run. Alternatively, the unbiased, or “untargeted”, sequencing of many samples can also aim to describe the fine-tuning of nucleotide variability in the quasi-species frame. A by-product of this analysis is the refinement of conventional molecular diagnostic tools through the additional genome variability information gained.Citrus dwarfing viroid. Analyzed siRNAs showed the pathogen regions associated with increased silencing and an altered plant hormone regulatory pattern. The same group developed and evaluated e-probes to be applied on citrus massive sequencing for rapid, simultaneous identification of 11 recognized viruses and viroids [At least two applications for a massive genotyping and virus characterization through HTS can be reported. The first one is the screening for dominant strains or isolates in endemic areas where cross-protection against dangerous pathogens is performed. In Brazil or South Africa, mild CTV strains are used to control the emergence of severe strains. In these cases, accurate monitoring of newly emergent strains, that can occur by introduction or recombination, can be used for timely containment actions. A second application is an eco-genomic survey in certain crops or for certain virus groups, that is, run necessarily as a pilot study in geographic areas   to check viroids . This e-In the frame of CTV research, Yokomi et al.  sequenceOther records of variability of citrus viruses were done in Japan , where fPlum bark necrosis stem pitting-associated virus (PBNSPaV) or Cherry virus A (CVA), as well as on newly identified fabaviruses. Studies on ilarviruses in Australian stone fruits focused on genetic variability of a number of isolates obtained by generic amplicon sequencing [On the side of stone fruit, more attention was paid to date to some less characterized viruses such as LChV1, quencing . Prunus samples of unclear or unknown etiology [More specifically, several variants of PBNSPaV were retrieved from a project of sequencing four etiology , while aetiology . Recentletiology , apricotetiology , and sweetiology . Full geetiology  and Hungetiology , and froetiology . In a wietiology  found twetiology  in 39 stUsing sequencing of dsRNA on PCR positive samples Špak et al.  obtainedIlarvirus species in Australia interestingly applied a strategy of sequencing of double-indexed amplicons. In a first study [Prunus necrotic ringspot virus (PNRSV) was investigated on 53 PNRSV-infected trees in conserved gene regions of each of PNRSV RNA1, RNA2, and RNA3. Some plant samples had sequence variants occurring in multiple PNRSV phylo-groups, and a nucleotide identity of 97% was determined as demarcation threshold for each of the PNRSV phylo-groups, each one composed by distinct clades of polymorphic variants. A second study [Prunus trees from a wide survey in stone fruit orchards. Mixed-infections of ilarviruses were detected, and also two different RNA2 sequence variants most likely belonging to unknown ilarviruses, from which no other genomic RNAs were identified. In a survey of 127 Prunus tree samples collected from five states in Australia, Kinoti et al. [Three publications from a project on st study , the varnd study  addressei et al.  found ApFurthermore, by using HTS, Koloniuk et al.  describeFinally, in HTS research of virus variability in apple, Visser et al.  analyzedThe application of HTS technologies has several advantages over the classical serological, molecular, and biological approaches both for disease diagnosis and for specific virus detection in fruit trees. Among the most important advantages of HTS is that a priori knowledge on the viral pathogens infecting a plant sample is not required. This means that there is no need to know the sequence of a targeted virus species, as in PCR, in order to design primers for its molecular detection or, like ELISA, to have antibodies available for serological detection. The classical detection assays, with the exception of biological indexing, are highly specific and cannot identify unknown viruses that might be involved in the etiology of a plant disease. The use of HTS reduces the time needed, and facilitates the necessary procedures in order to identify the etiological agent of a disease, since the method provides the identification of the plant sample’s virome, often unveiling the presence of novel viral pathogens ,111,112.de novo assembly, in combination to sequence depths which can reach up to a few thousand reads per site, can reveal the presence of variants in very low frequencies, as well as defective RNAs or mixed-infections of closely related strains/isolates [As far as virus detection is concerned, the application of deep sequencing approaches alleviates the problem of false negatives due to high genetic variability or low titer, which are frequently encountered in viruses infecting fruit trees ,114. Morisolates ,40,49. IIn woody perennial crops, mixed virus infection is the most common feature, so unravelling diseases of unknown etiology is complicated by the simultaneous presence of different viruses , and the presence/absence of a novel key virus should be further confirmed by conventional detection in wider surveys. Symptoms can be linked to peculiar, severe isolates of a virus species, thus the recovery of specific sequences maybe not enough for causality association. In the citrus sudden death disease , a speciDespite the advances in the field of HTS technology and the ability to sequence several samples simultaneously as a pool of extracted nucleic acid, testing the large number of samples necessary to study the incidence or molecular epidemiology of a plant virus species is still costly. In addition, there are no established thresholds of reads numbers to identify the presence of a virus species in a sample, which needs to assess the sanitary status of a sample. The detection of a low number of reads from a viral genome could indicate either the presence of a virus in low titer, or the contamination of the sample during handling. Therefore, the additional application of species-specific molecular/serological techniques is still needed in order to confirm such findings. Another drawback of high-throughput technologies is the impact of the selected template on the kind of viral pathogens detected. This template-dependency might be observed for DNA viruses which are excluded from the analysis of dsRNA-based libraries and, likewise, after poly(A) enrichment, where viruses lacking a poly(A) tail are not detected. On the other hand, VANA has been reported to successfully detect both RNA and DNA viruses ,120 but Finally, it should be highlighted that diagnostic interpretation of the bioinformatic analysis of HTS data is of paramount importance compared to interpretation of the results of classical detection assays. Whichever the template used for the analysis, it is highly probable that a multitude of different viruses will be found in a sample. Perennial host trees accumulate viruses over the years and those might, or might not, play a role on the development of a disease. The presence of a virus in a diseased sample is not proof of the induction of the observed symptomatology and caution should be even taken when naming a new virus, as the inclusion of the disease in the virus name could predispose the research on this virus, and might have implications on the movement of propagative material across borders. Characterization of a newly identified virus and its role in disease etiology would probably require the use of infectious complementary DNA clones or other biological techniques, enabling establishment of a single agent infection of a plant .HTS analysis is undoubtedly a technological breakthrough that has yet to offer a lot in plant virology. However, advances in the field of fruit-tree virology using HTS have to mitigate the weaknesses of the other assays, mainly those related to pathogen diagnosis and the identification of the sanitary status of the trees. Those two aspects of research are directly involved in the production of virus-tested high-quality propagative material, and the prevention of trading of diseased plants which are the main ways of containment for serious fruit tree viral diseases. The perennial life cycle of tree crops places virus infections into a different perspective than those of the annual herbaceous plants. In the latter, the diseases and viral loads might change each year, and annual fluctuations are observed even in areas where specific viruses are endemic. In fruit trees, however, viruses accumulate over the years, giving rise to mixed-infections, which become the normal status of a tree. Moreover, the initial sanitary status of each plant from the nursery might play a major role on the development of a disease through the interactions of the viruses present. Therefore, it will be highly important to further improve current HTS technologies and subsequent bioinformatic analysis procedures, so that they can be efficiently applied in the fields of certification of fruit tree propagation material and phytosanitary control.HTS will eventually lead to the identification of the majority, if not every, virus and viroid present in each host species, updating their virome data. This extensive database, of different isolates from the viruses infecting trees, will be able to optimize the existing detection assays by addressing one of the major shortcomings for the traditional methodologies, which is the high sequence variability present in fruit tree-infecting viruses. The optimization of the existing primers based on sequences from different isolates, and the variants of these isolates present in a sample, will minimize false-negative results, thus leading to more accurate diagnostic assays. Moreover, the assessment of the new viruses identified will provide a thorough list of pathogens posing potential threats, and quarantine lists can be updated.HTS has proven a valuable tool in the identification of genotype mixtures in the form of virus variants, and different isolates inside a single plant. With the aid of this technology, the study of interactions between different viruses or virus genotypes will be facilitated, unveiling mechanisms of pathogenesis and disease development. Importantly, the method could be used for the study of plant–virus–vector interactions through transcriptomic analyses or studies of resistance mechanisms, such as RNA silencing, acting against viruses in different fruit tree species, which in the end, could lead to the development of novel control tools.


Orthomyxoviridae family. This infectious disease has serious impacts on public health systems and results in considerable mortality and economic costs throughout the world. Based on several experimental studies, massive host immune reaction is associated with the disease severity of influenza. Programmed cell death is typically induced during virus infection as a consequence of host immune reaction to limit virus spread by eliminating niches for virus propagation without causing inflammation. However, in some viral infectious diseases, such as influenza, in the process of immune reaction, aberrant induction of programmed cell death disturbs the maintenance of organ function. Current reports show that there are different types of programmed cell death that vary in terms of molecular mechanisms and/or associations with inflammation. In addition, these novel types of programmed cell death are associated with pathogenesis rather than suppressing virus propagation in the disease course. Here, we review our current understanding of mechanisms of programmed cell death in the pathogenesis of influenza.Influenza is a respiratory disease induced by infection by the influenza virus, which is a member of  The other intracellular PRRs including retinoic acid-inducible gene-I (RIG-I) like molecules, Z-DNA-binding protein 1(ZBP1)/DNA-dependent activator of IFN-regulatory factors (DAI), nucleotide-binding oligomerization domain (NOD)-like molecules, or absent in melanoma 2 (AIM2)-like molecules should recognize the injected and/or de novo vRNP in cytozol to activate intracellular signals promoting several cytokine gene inductions . Among cApoptosis is the most common form of PCD. When cells induce apoptosis, they shrink their cellular shapes and involve their intracellular components  into their cytoplasm to prevent unwanted immune responses.The intracellular mechanism of apoptosis induction is molecularly defined . Most apDuring virus infection, activation of initiator caspases is triggered by several cytokines. These cytokines are called death ligands, which are type-II transmembrane proteins that include tumor necrosis factor (TNF), Fas ligand (FasL) or TNF-related apoptosis-inducing ligand (TRAIL). In the naïve state, death ligands present as homophilic trimers, whereas the specific receptors  present as monomers on cell surfaces. The trimeric complex of death ligands engages monomeric DRs to induce aggregation of the receptors and adaptor proteins that bind to cytoplasmic tail of the receptors. Among the adaptor proteins, Fas-associated protein with death domain (FADD) recruits pro-caspase-8 to its cytoplasmic tail and induces homophilic activation of caspase-8. Activated caspase-8 cleaves and activates its downstream caspases such as effector caspase-3. Caspase-8 also cleaves pro-apoptotic B-cell lymphoma 2 (Bcl2) family proteins, such as BH3 interacting domain death agonist protein (Bid). The cleaved and activated Bid mediates mitochondrial damage and the loss of mitochondrial membrane potential to release cytochrome-c to the cytosol from the interior of mitochondria. The released cytochrome-c binds to apoptotic protease activating factor 1 (Apaf1), an adaptor protein, to form “Apoptosome”, a protein complex that induces auto activation of initiator caspase-9. The activated caspase-9 also cleaves and activates caspase-3 to amplify the apoptotic signal cycle.During influenza A virus infection, functional defects on FasL, a specific ligand of Fas receptor, protect mice. However, deficiency of the FasL gene has almost no effect on virus propagation in mouse lung during lethal influenza virus infection ,32. DuriInduction of TRAIL expression is also linked to influenza pathogenicity. In contrast to FasL, the role of TRAIL is more complex in protecting the host during influenza virus infection. Functional defects in the TRAIL gene in mice cause reduced survival rate during mild influenza virus infection . HoweverNecrosis is often considered as an accidental and unregulated cellular event. However, increasing reports indicate that the phenomenon is also induced by the programmed mechanism in response to several external stimulations such as virus infection. This programmed necrosis is called necroptosis. Necroptosis is an alternative cell death program and is histologically distinguished from apoptosis. When cells induce necroptosis, the cell body bursts and immediately releases intracellular components  that can trigger inflammatory reaction mediated by the innate immune system. The molecular mechanisms that induce necroptosis and their differences compared with those of apoptosis are currently discussed ,40.The induction of necroptosis depends on the formation of necrosomes that consist of at least three kinases: receptor interacting kinase (RIPK)-1 and -3 and mixed lineage kinase domain-like (MLKL) . The intNecroptosis is triggered by several pro-apoptotic stimuli including the death ligands, toll-like receptor agonists or genotoxic stress when caspase activity is blocked . TherefoThe role of necroptosis in host protection against the influenza virus infection is highly controversial. ZBP1/DAI deficiency protects mice during lethal influenza virus infection, although the virus titer is higher in ZBP1/DAI deficient than in wild-type mice . AnotherBased on studies using mice with defects of other necroptosis-related molecules, RIPK3 deficiency leads a high mortality rate in mice infected with influenza virus ,45,46. RTaken together, these studies suggest the importance of necroptosis in regulating influenza virus-mediated cell death in in vitro experiments. DAI-mediated necroptosis also has a crucial role in suppressing virus propagation in vivo.Pyroptosis is a type of cell death that is associated with production of pro-inflammatory cytokines including IL-1β and IL-18 ,48. The Podospora anserina (HET-E) and telomerase-associated protein (TP1) (NACHT), leucine-rich repeats (LRR) and PYD domains-containing protein 3 (NLRP3)) and PRR-adaptor protein to take place. The activated caspase-1 cleaves and converts pro-IL-1β and pro-IL-18 into their mature forms.In cells infected with intracellular microbial pathogens, several microbial components are recognized by cytosolic PRRs, which conserve a caspase activation and recruitment domain (CARD) or a pyrin domain (PYD), such as NOD-like receptor proteins (NLRPs), absent in melanoma (AIM) and pyrin. The CARD-containing PRRs (NLRP1 and NLRC4) directly recruit pro-caspase-1 to their CARDs for aggregation and form inflammasomes to activate caspase-1. Recruitment of apoptosis-associated speck-like protein containing CARD (ASC) is required for formation of inflammasome of PYD-containing PRRs , MHC class II transcription activator (CIITA), incompatibility locus protein from Caspase 1 deficiency reduces the survival rate of mice during non-lethal challenge with influenza virus , whereasActivation of caspase-1 in the hematopoietic but not the stromal compartment recruits several inflammatory leukocytes to the lung during virus infection. These include macrophages, dendritic cells, natural killer cells, neutrophils, and lymphocytes. Recruitment of the cells contributes to the induction of host antiviral immunity  as well In this review, we discuss the molecular mechanisms of the three main types of PCD, and their association with the pathogenicity of the seasonal influenza virus infection in mammals . As descTo control influenza, the first choice for prevention is immunization with influenza vaccines, which induce virus-specific antibodies and cellular responses to eliminate the viruses. These responses depend on antigenicity of the virus, which reduces the effectiveness of this strategy for completely preventing the spread of the virus. This is because the viruses can easily change their antigenicity in response to host antigenic pressures. The genetic diversity of the virus is derived from its RNA-dependent RNA polymerase, which lacks a proofreading system, which DNA polymerase has. This characteristic of the influenza virus (referred to as “antigenic shift”) accumulates point mutations on their genomic sequences and facilitates their escape from host immunological reactions, which consist of antiviral protein-specific antibodies and cytotoxic T lymphocytes. The influenza virus also has another characteristic, which leads its escape from host immune reactions. The viral segment can easily transmit among the different subtypes when they co-infect within the same cell (referred to as “antigenic drift”). This phenomenon can result in rapid and frequent change of the virus serotype .Currently, for therapeutic treatment, several anti-influenza virus reagents such as amantadine have been developed and are used clinically. These reagents are antagonists that selectively block the catalytic pocket of viral proteins, and their specificity depends on the structure of the targeted viral protein . Therefo


Lassa virus is a highly pathogenic arenavirus that causes severe hemorrhagic fever in humans. Currently, there are no efficacious vaccines or treatments available to combat this pathogen. An important component of any vaccine candidate against Lassa virus will likely include the highly glycosylated glycoprotein complex presented on the virion surface. Here, we determine the composition of the Lassa virus glycome, revealing that the virus presents an abundance of glycans that are not biosynthetically processed to full maturity. Such underprocessed glycans form spatially distinct clusters, which shield the proteinous surface of the Lassa virus glycoprotein spike from the humoral immune response. These data are integral for the development of humoral-based vaccines that mimic the mature Lassa virion. N-linked glycosylation on the GPC. Here, using a virus-like−particle system that presents Lassa virus GPC in a native-like context, we determine the composite population of each of the N-linked glycosylation sites presented on the trimeric GPC spike. Our analysis reveals the presence of underprocessed oligomannose-type glycans, which form punctuated clusters that obscure the proteinous surface of both the GP1 attachment and GP2 fusion glycoprotein subunits of the Lassa virus GPC. These oligomannose clusters are seemingly derived as a result of sterically reduced accessibility to glycan processing enzymes, and limited amino acid diversification around these sites supports their role protecting against the humoral immune response. Combined, our data provide a structure-based blueprint for understanding how glycans render the glycoprotein spikes of Lassa virus and other Old World arenaviruses immunologically resistant targets.Lassa virus is an Old World arenavirus endemic to West Africa that causes severe hemorrhagic fever. Vaccine development has focused on the envelope glycoprotein complex (GPC) that extends from the virion envelope. The often inadequate antibody immune response elicited by both vaccine and natural infection has been, in part, attributed to the abundance of  Lassa virus (LASV), an arenavirus endemic to rodent populations in West Africa, causes severe hemorrhagic fever upon transmission to humans, with an estimated 300,000 infections and several thousand deaths each year . To date39The arenaviral GPC is encoded by the S segment of the single-stranded, bisegmented RNA genome. Following expression of a single polyprotein precursor, the GPC is proteolytically processed by the host cell subtilase SKI-1/S1P  and disp15192225N-linked glycosylation sites (PNGs) found on each SSP−GP1−GP2 protomer accounts for nearly 30% of the total mass of the LASV GPC  system , 14, we N-linked glycosylation sequons on both the GP1 and GP2 subcomponents of the GPC  analysis. Cleavage of the released glycan pool with endoglycosidase H (Endo H) revealed an abundance (49%) of oligomannose-type glycans  B. Consis5–9GlcNAc2 species that form following processing by endoplasmic reticulum (ER)-resident α-glucosidases I and II   isomer . We observed two Man7GlcNAc2 isomers, with the seventh mannose located on either the six-antenna (D3) or three-antenna (D1) arm . These isomers have also been observed in HIV-1 (gp120) and Semliki Forest virus E1 and E2 glycoproteins  . Consistocessing , MS/MS oproteins , 42; it GP1, Asn89GP1, Asn99GP1, Asn365GP2, and Asn373GP2) were predominantly of the oligomannose type. The level of mannosylation varies widely across these sites, where the glycans at Asn79GP1 and Asn365GP2 present a dominant population of Man9GlcNAc2 and Asn89GP1, Asn99GP1, and Asn373GP2 exhibit less restrictive processing and display Man6GlcNAc2 and Man7GlcNAc2.It has been previously shown that oligomannose-type glycans displayed on the LASV GPC mediate host cell attachment to DC-SIGN presented on monocyte-derived dendritic cells . We sougN-linked glycosylation sites  composition observed in this region is likely due to the high spatial density of N-linked glycans, which limit the accessibility of glycan processing enzymes to these sites. The existence of such a high mannose cluster has precedence and is reminiscent of the “mannose patches” observed on the glycan shield of the HIV-1 envelope glycoprotein .Using the crystal structure of the trimeric LASV GP1−GP2 ectodomain [Protein Data Bank (PDB) ID code 5VK2 ], we deton sites B. This aoprotein –45. Furtoprotein , 29. Theoprotein , 15, 30,N-linked glycosylation to obstruct immunodominant receptor-binding sites has been observed for other highly glycosylated viruses, such as the CD4 binding site on the envelope spike of HIV-1 , at the membrane-distal apex of the trimer B. Intereof HIV-1  and the of HIV-1 .SI Appendix, Fig. S3). Consistent with a recent dN/dS analysis on LASV GPC  and Old World (GP1−GP2 interfaces) GPCs  GPCs , 51, 52.N-linked glycan biosynthesis processing pathway . Oligomannose-type glycans were also observed at sites outside of this cluster, albeit at lower levels. The presence of oligomannose at multiple locations across the GPC is suggestive of a promiscuous model of DC-SIGN usage, where numerous N-linked glycans may contribute as attachment factors for LASV entry.We present a structure-based model for rationalizing glycan-mediated shielding of LASV GPC from the humoral host response, revealing a cluster of underprocessed glycans that spans both the GP1 and GP2 subunits of the trimeric spike complex . While tThe existence of a large population of oligomannose-type structures on LASV GPC has important consequences in the development and production of recombinant vaccine candidates. On recombinant glycoproteins, oligomannose-type glycans are considered to impart elevated clearance rates and may influence immunogenicity , 58. In This study also reveals that amino acid diversification occurs primarily at glycan-devoid regions on the LASV GPC , providiN-linked glycosylation on the LASV surface, we suggest that the compositional and structural data presented here will be integral for the creation of a humoral immunity-based vaccine capable of mimicking the mature LASV virion.Continued emergence and high pathogenicity render LASV an important human pathogen and underscore the necessity for reagents capable of preventing and treating infection. Given the prominence of g for 30 min). VLPs were pelleted through 10 mL of 20% sucrose cushion by ultracentrifugation . The pellets were resuspended in SPG buffer at pH 8 for 12 h at 4 °C.MDCK-II cells stably expressing LASV GPC  were cultured in DMEM supplemented with 10% FCS for 96 h. The medium was replaced with DMEM with 2% FCS for VLP expression, as previously described . After 9Proteins from LASV VLPs were analyzed by Western blotting, as previously described . MonocloA 3-µL aliquot of purified VLP samples was applied on a plasma-cleaned grid coated with holey carbon . The grids were floated on a drop of 200-µL PBS buffer to remove sucrose and were blotted for 3 s followed by plunge-freezing into a mixture of liquid ethane (37%) and propane (63%) using a plunger device . Micrographs were collected at liquid nitrogen temperature using a 300-kV transmission electron microscope  equipped with a CCD camera  at a calibrated magnification of 75,000×, resulting in a final pixel size of 2 Å/pixel.N-linked glycans were fluorescently labeled with procainamide. A 100-µL aliquot of labeling mixture  was added to the sample and incubated at 65 °C for 4 h. Labeled glycans were purified using Spe-ed Amide 2 columns (Applied Separations), as previously described  on a Waters Acquity H-Class UPLC instrument as performed in ref. escribed .N-linked glycans were performed on a Synapt G2Si instrument (Waters) as previously described . ProteoExtract Glycopeptide Enrichment Kit (Merck Millipore) was used to enrich glycopeptides for LC-ESI MS. For site-specific analysis of LASV GPC glycosylation, enriched glycopeptides were analyzed on an Orbitrap Fusion Tribrid mass spectrometer (Thermo Fisher Scientific) coupled to an EASY-Spray nano-LC system (Thermo Fisher Scientific). MS data were acquired with XCalibur 4.0 (Thermo Fisher Scientific). Glycopeptides were fragmented using both higher-energy collisional dissociation and energy transfer dissociation. Data analysis and glycopeptide identification were performed using Byonic and Byologic software (Protein Metrics).SI Appendix, Supplementary Method.Publicly available sequences encoding the GPC spike were downloaded from GenBank and manually aligned. The sequence alignment comprised 217 sequences, spanning 1,473 bp of GPC region. A maximum likelihood phylogeny was inferred using randomized axelerated maximum likelihood (RAxML), where the model parameters included general time reversible model with rate categories (GTRCAT) substitutional model and rapid bootstrap analysis with 100 bootstrap samples . The resN-linked glycan presentation on LASV GPC were created using the trimeric crystal structure , comple in Coot .Supplementary File


Bombus spp.) has been linked to an increased prevalence of pathogens caused by spillover from managed bees. Although poorly understood, RNA viruses are suspected of moving from managed honeybees (Apis mellifera) into wild bumblebees through shared floral resources. We examined if RNA viruses spillover from managed honeybees, the extent to which viruses are replicating within bumblebees, and the role of flowers in transmission. Prevalence and active infections of deformed wing virus (DWV) were higher in bumblebees collected near apiaries and when neighboring honeybees had high infection levels. We found no DWV in bumblebees where honeybee foragers and honeybee apiaries were absent. The prevalence of black queen cell virus (BQCV) was also higher in bumblebees collected near apiaries. Furthermore, we detected viruses on 19% of flowers, all of which were collected within apiaries. Our results corroborate the hypothesis that viruses are spilling over from managed honeybees to wild bumblebees and that flowers may be an important route for transmission.The decline of many bumblebee species ( Many infectious diseases are caused by generalist pathogens that infect multiple host species . For patApis mellifera), the importance of native pollinators has risen to global attention [Given recent declines in managed honeybees  of RNA viruses and whether the viruses were actively replicating in two bumblebee species. We then examined if virus prevalence, load, and active infection in bumblebees correlated with the presence of managed honeybee colonies and their virus loads. We also investigated transmission through shared floral resources by testing flowers collected from our field sites and examining how bee abundance, honeybee colony presence, and landscape level floral density influenced patterns of virus prevalence.th- August 26th 2015. Within a given week of sampling, we went to both apiary and non-apiary sites to ensure that site type was not confounded by time. At each site, we collected up to 15 bumblebees of each target species: Bombus vagans and B. bimaculatus  in GITC buffer  over liqActin) as a positive control of RNA extraction efficiency in bees (Actin), with correlation coefficients (R2) ranging from 0.993–0.999. We tested a total of 15 composite honeybee samples and 342 bumblebee workers consisting of 180 B. vagans and 162 B. bimaculatus. We tested 33 composite flower samples of which 13 were collected from sites with apiaries and 20 were collected from sites without apiaries.For reverse transcription of RNA and absolute quantification of each virus in bees and plants, we performed duplicate reverse transcription quantitative polymerase chain reactions (RT-qPCR) for each diluted sample using SYBR green one-step RT-qPCR kit in 10 ul reactions. We used the following thermal cycling program: 10 min at 50°C (RT) followed by 1 min at 95°C, and 40 amplification cycles of 95°C for 15 s, 60°C for 60s and derived melt-curves using the following program: 65–95°C . We used primers specific to the following RNA virus targets: deformed wing virus (DWV), black queen cell virus (BQCV) and Israeli acute paralysis virus (IAPV), and a housekeeping gene  and sequencing was performed using the 3130xl Genetic Analyzer in the University of Vermont Cancer Center Advanced Genome Technologies Core. Sequence data were viewed (FinchTV 1.4) and aligned by eye to genome references using Geneious v 6.0.6 .7) or ‘low’ (<107) honeybee virus loads based on the clear bimodal distribution of the logarithmic value of the virus genome copies/bee at for each site , and R v 0.99.903 (R Core Team 2016). We selected six ten-fold dilutions for each target  and used a regression analysis to derive a standard curve for quantification.We performed all analyses in R v 0.99.903 (R Core Team 2016). To analyze bumblebee virus load data, we first log transformed all virus loads to improve normality. To investigate whether honeybee apiary presence, floral density, or bumblebee species affected the prevalence, load, or replication of RNA viruses in bumblebees (DWV and BQCV were tested in separate models), we used separate general linear mixed models (GLMMs)  with virus prevalence, virus load, and presence of the viral negative strand as our response variables. To test whether honeybee abundance influenced the prevalence, load, or replication of RNA viruses in bumblebees, we used the same model structure, conducting separate GLMMs and substituting honeybee abundance for honeybee apiary presence. Virus load in bumblebees was analyzed using a Gaussian distribution and the presence of virus as a binomial distribution. In each model we used the fixed effects of apiary absent/present, site level floral density, and bumblebee species with site, latitude and longitude as random effects.7 genome copies; low: < 107 genome copies) or honeybee abundance. We used honeybee viral load, honeybee abundance, and floral density as fixed effects and site as a random effect.Site average honeybee virus loads were bimodally distributed . TherefoTo investigate whether honeybee or bumblebee abundance affects virus deposition on plants, we used a GLMM with binomial distribution with honeybee abundance, bumblebee abundance and virus  as fixed effects and site as a random effect. To examine if the presence of apiaries and bumblebee species affected the prevalence of replicating viruses, separate chi-square tests for independence were conducted for each virus. To calculate the significance of each fixed effect for all models, we created a reduced model by removing the effect, and compared each reduced model to our full model using a likelihood ratio test. All full models tested against a random null model to ensure that full models explained more variance than a random model.6 to 109 for BQCV and 104 to 1010 for DWV. Honeybee DWV loads followed a bimodal distribution (7 genome copies) or “high” (> 107 genome copies) virus loads. The prevalence of BQCV was significantly higher in B. bimaculatus (86.3%) compared to B. vagans (65.9%)  but DWV prevalence was similar in both bumble bee species    . Bumbleb< 0.016) . In site< 0.016) . Virus lχ12 = 8.068,P = 0.018)  but not DWV .The prevalence of DWV in bumblebees was significantly higher in sites with high honeybee DWV loads compared to bumblebees collected from sites where DWV load in honeybees was low (= 0.018) . Virus lB. bimaculatus (26.2%) compared to B. vagans (8.6%) . DWV was actively replicating in 7.4% of B. bimaculatus and 5.2% of B. vagans . Replicating DWV was more prevalent in bumblebees collected near honeybee apiaries . However, this was not the case for BQCV infections   .3−105 (BQCV) and 102−106 (DWV) genome copies per gram of flower material. All positive samples came from flowers collected from sites with honeybee apiaries and included the following plant species: , , , . Of the samples collected in apiaries, 26.7% were positive for DWV, 20% were positive for BQCV and one was positive for both viruses. Honeybee abundance but not bumblebee abundance was greater in sites where we detected viruses on plants  and replicating DWV  in bumble bees. However, floral density was not correlated with BQCV prevalence, BQCV load, replicating BQCV, or DWV load . ,45. ApisS1 Fig7 genome copies) or low (< 107 genome copies) viral loads.Distribution follows a bimodal distribution with sites either have high (> 10(DOCX)Click here for additional data file.S2 FigApis) or bumblebee (Bombus). Bar groupings represents site type: apiary absent or apiary present within 1 km from site. Bee abundance was measured as the number of bees within 5 m of either side of a 100 m transect over a 10-minute period.Bars and points are color coded by bee species: honeybee ((DOCX)Click here for additional data file.S1 TableBombus bimaculatus and B. vagans) and honeybees (Apis mellifera).Site IDs were assigned for each collection site. Location is provided with latitude and longitude. Sites either had a commercial apiary present (Y) or no apiary nearby (N). Total sampling sizes are given for each of two bumblebee species ((DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table2. Bee species was either Bombus bimaculatus or B. vagans. Asterisks represent significance.Table shows chi squared value, degrees of freedom (Df) and p-value. Honeybee abundance was calculated as the number of honeybees observed within 5 m of either side of a 100 m transect over a 10-minute period. Floral density was calculated as the number of inflorescences per m(DOCX)Click here for additional data file.S4 Table7 genome copies) and “low” if below 15 (<107 genome copies). Bee abundance was measured as the number of honeybees observed per m2. Floral density was calculated as the number of inflorescences per m2. Table shows chi squared value, degrees of freedom (Df) and p-value. Asterisks represent significance.Prevalence in bumblebees is the percentage of bumblebees with DWV detected. Honeybee virus loads were calculated as the number of virus genome copies per bee and log transformed. Virus loads in honeybees were considered “high” if above 15 (>10(DOCX)Click here for additional data file.S1 DataVirus and actin amplicons are colored for visualizations: Green = DWV, Blue = IAPV, Red = Actin, Yellow = IAPV. Ten random base pairs (uncolored) flank each target of interest.(DOCX)Click here for additional data file.S1 Appendix(DOCX)Click here for additional data file.