RNA viruses, once considered specific to honey bees, are suspected of spilling over from managed bees into wild pollinators; however, transmission routes are largely unknown. A widely accepted yet untested hypothesis states that flowers serve as bridges in the transmission of viruses between bees. Here, using a series of controlled experiments with captive bee colonies, we examined the role of flowers in bee virus transmission. We first examined if honey bees deposit viruses on flowers and whether bumble bees become infected after visiting contaminated flowers. We then examined whether plant species differ in their propensity to harbor viruses and if bee visitation rates increase the likelihood of virus deposition on flowers. Our experiment demonstrated, for the first time, that honey bees deposit viruses on flowers. However, the two viruses we examined, black queen cell virus (BQCV) and deformed wing virus (DWV), were not equally distributed across plant species, suggesting that differences in floral traits, virus ecology and/or foraging behavior may mediate the likelihood of deposition. Bumble bees did not become infected after visiting flowers previously visited by honey bees suggesting that transmission via flowers may be a rare occurrence and contingent on multiplicative factors and probabilities such as infectivity of virus strain across bee species, immunocompetence, virus virulence, virus load, and the probability a bumble bee will contact a virus particle on a flower. Our study is among the first to experimentally examine the role of flowers in bee virus transmission and uncovers promising avenues for future research. Crithidia bombi, a trypanosome parasite of bumble bees, was transmitted among bumble bees after visiting flowers that were inoculated by hand or previously visited by infected bumble bees [Apicysistis bombi, Nosema spp., and Crithidia bombi were vectored from host bees to flowers and between bee species through shared flowers [Pathogens are among the top threats to bees causing colony losses, population declines, and a growing concern for food security and ecosystem function –4. Althoble bees . More re flowers ,13. ThouVarroa mites, an ectoparasite that vectors RNA viruses [Varroa mites serve as a vector for RNA viruses with high infestations typically resulting to high virus titers.Once thought to be specific to honey bees, RNA viruses have been detected in a number of pollinating arthropod species including beetles, flies, solitary bees, and bumble bees ,9,14. Th viruses ,16. Two  viruses ,18 and b viruses , and bla viruses ; howeverApis mellifera and the Varroa mite [Varroa mite. Additional studies are needed to closely examine the principle directionality of transmission as well as transmission routes of viruses among species.Managed bees including both honey bees and commercial bumble bees have been implicated in the spread of numerous pathogens and parasites –25. Evidroa mite . HoweverDetected in the feces and glandular secretions of worker honey bees as well as in pollen loads carried by bees, RNA viruses are likely left behind on flowers by foraging visitors ,27,28. PTransmission via flowers may be mediated by many factors such as plant traits and/or pollinator behavior. For example, the ability for flowers to serve as conduits for pathogens may be facilitated or constrained by floral traits or morphology ,29. In tHere, we conducted a series of controlled flight cage experiments to test if flowers can act as bridges in virus transmission between bee species. Specifically, we examined if honey bees deposit viruses on flowers and whether bumble bees become infected after visiting contaminated flowers. In addition, we examined whether virus deposition is influenced by plant species and/or plant diversity. By measuring visitation to flowers, we examined whether honey bee visitation rates and/or visit duration increase the likelihood of virus deposition on flowers. To further examine the role of flowers in the transmission of RNA viruses, we tested whether virus transmission from honey bees to bumble bees occurs indirectly through flowers, including chronic exposure to contaminated flowers. We also tested whether virus transmission occurs through direct contact or comingling while foraging on flowers.To test for viral deposition on flowers by honey bees and transmission of viruses between bee species using shared floral resources, we conducted a series of experiments . First, Trifolium pratense (red clover), Trifolium repens (white clover) and Lotus corniculatus (birdsfoot trefoil)  and widely grown in agriculture as nitrogen fixing cover crops and fodder. We grew plants from seed and maintained them in a greenhouse until the start of the experiment. Beginning in mid-May, we broadcast seeds  of T. pratense, T. repens, and L. corniculatus in 8 in. diameter, 6.5 in. deep plastic pots filled with Miracle Grow Potting Mix to achieve ca. 100 seeds per pot. To encourage flowering, we trimmed the T. repens and T. pratense plants once and twice, respectively, and used grow lights to maintain 14 hours of sunlight. To verify that plants were virus-free at the start of the experiment, we haphazardly collected three composite samples of 1.5 grams from each plant species and tested them for DWV and BQCV using RT-qPCR protocols.To focus on floral architecture and reduce variation in other plant traits, we chose three legume species (Family Fabaceae), two of which having similar morphology: trefoil) . The twoad libitum and allowed them to acclimate for up to five days in a growth chamber maintained at 26°C and 52–55% RH. We made new microcolonies every three days to ensure each microcolonies used in the experiment was approximately the same age.To ensure our experimental honey bee colonies were infected with both viruses, we collected 50 bees from each of two five-frame honey bee colonies (University of Vermont research colonies), and tested each composite sample for DWV and BQCV using RT-qPCR. Thus, we knew that these colonies were infected with both viruses. We received seven bumble bee colonies from a commercial supplier (BioBest). To verify these bees were not infected with DWV and BQCV, we pollen-starved 10 bees from each colony for 72 hours and tested each bee using RT-qPCR. Bees were pollen-starved to rid their guts of pollen that may have contained virus particles. All bumble bee colonies tested negative for DWV and BQCV. From the seven colonies, we created microcolonies of 12 adult bees, provided them with 30% sucrose solution We carried out all experiments in three 3 x 3 x 3 m. screened tents with tarp bottoms. Each tent was assigned to one treatment: honey bee tent, control bumble bee tent, or exposed bumble bee tent . We usedOn each day of the experiment, we transported plants from the greenhouse to the plant holding tent and watered them. We counted all inflorescences to ensure a standard range across replicates and treatments and assigned them accordingly. To acclimate the honey bees to their enclosure, the two colonies (consisting of five frames each) were placed in the honey bee tent 24 hours prior to the experiment. To infect the flowering plants, we placed plants within the screened enclosure with the two honey bee colonies and allowed bees to visit the flowers. After the foraging trials, we transferred plants to a holding tent to allow for nectar to be replenished. After 15 hours, we transferred plants visited by honey bees to the exposed bumble bee tent and evenly distributed them among the three hoop houses each containing a single bumble bee microcolony for a total of three replicates per experiment. At the same time, we ran three replicate controls for each experiment in three hoops houses within the control bumble bee tent. Bumble bees in the control tent received clean flowering plants brought directly from the greenhouse. All trials were conducted in the shade to reduce UV exposure to flowers and degradation of viral RNA. On each day of foraging trials, honey bees and bumble bees were allowed to forage on floral arrays for nine and six hours, respectively. For the comingle experiment, where both honey bees and bumble bees were allowed to forage together in the same tent, bees were allowed to forage for seven hours. These foraging times were chosen to maximize the amount of foraging time allowed in a single day to increase the probability of detecting an effect.To measure visitation, we observed bumble bee foragers until 50% of flowers for each replicate were visited. To closely examine how honey bee visitation may influence virus deposition on flowers, we filmed each trial for three hours. We viewed the videos and recorded the total number of honey bee visits to each plant species and computed the visit duration of each foraging honey bee (in seconds) to each inflorescence during the filmed visitation surveys.ad libitum for one week in a growth chamber. If bumble bees were exposed to infective virus during the experiment, the one week ‘incubation’ period allowed for the onset of viral infection. We did not feed bees pollen during this period to clear their guts of pollen that could contain inactive virus particles, resulting in a false positive result during the viral assays. After one week, we collected all bees and stored them in -80°C until RNA extraction and virus assays.For each trial, we allowed microcolonies of 12 bees each to forage on flowers that had or had not been exposed to honey bees. After six hours, we collected all inflorescences and bumble bees. We stored inflorescences at -80°C. We placed the bumble bee microcolonies into new containers and fed 30% sucrose T. repens, T. pratense, and L. corniculatus (“single species” experiment)  . We stanT. repens inflorescences, 6 T. pratense inflorescences, and 15–21 L. corniculatus inflorescences. For both the single plant species and diversity trials, we collected separate samples of each plant species after each replicate for a total of three flower samples per species per trial for each of the exposed and control groups.To test if plant diversity affects virus deposition and/or transmission, we allowed bees to forage on floral arrays containing all three plant species at once (“diversity” experiment) . Each diT. repens (“chronic exposure” experiment) for a total of three replicates (T. repens plants on three consecutive days (six hours each day). We allowed plants to replenish nectar between honey bee and bumble bee foraging bouts as in the other experiments. A new T. repens plant was used each day. After the three exposure events, we collected all bumble bees, transferred them to new containers, provided 30% sucrose ad libitum, and ‘incubated’ them for one week as in the previous experiments and then transferred them at -80°C. We also collected flowers each day of the chronic exposure experiment and stored them at -80°C. Since new plants were used each day, we collected a total of nine exposed flower samples and nine control flower samples.To test if chronic exposure to contaminated flowers is necessary for virus transmission, we repeated the experiment using plicates . Six bumT. repens arrays consisting of 41–47 inflorescences (“comingling” experiment)  . We plac2 and homogenized into 600 ul of RLT buffer (10% β-mercaptoethanol) and Qiagen protocols were used thereafter for each individual bumble bee. For the pre-screening of honey bees, samples of 50 bees were pooled, flash frozen in N2 and homogenized together in an extraction bag with 10 mL of GITC buffer. The resulting homogenate was centrifuged and 100 ul of the lysate was mixed with RLT buffer (10% β-mercaptoethanol) and Qiagen protocols were used thereafter. For both pre-screened and experimental plants, 1.5 g of flower material consisting of entire inflorescences was transferred to an extraction bag  and flash frozen in N2. Plant material was ground to a powder using a ceramic pestle on the outside of the extraction bag for 30 seconds. Three mL of GITC buffer was added to the bag and the pestle again was used on the outside of the bag to mix the homogenate into the buffer for 2 minutes. The resulting homogenate was centrifuged and 200 ul was used in RNA extractions following Qiagen RNeasy mini kit protocols. All RNA quantity and quality were assessed on a Spectrometer .We extracted total RNA following Qiagen RNeasy mini kit protocols. The entire abdomen of each individual bumble bee was dissected and flash frozen on N2) ranging from 0.993–0.999.For bumble bees and honey bees, all RNA extractions were diluted to 20 ng/ul prior to virus assays. RNA recovered from plants was not diluted prior to further analyses. For reverse transcription of RNA and absolute quantification, duplicate reverse transcription quantitative polymerase chain reaction (RT-qPCR) was performed for each sample with SYBR green one-step RT-qPCR kit in 10 ul reactions using 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. Last, the melt-curve was obtained starting at 65-95°C . We used primers specific to the positive strand of the following RNA virus targets: DWV and BQCV, and a housekeeping gene (ACTIN) as a positive control of RNA extraction efficiency . QuantifTo confirm the identity of the viruses, we sequenced virus fragments from bumble bees, honey bees and flowers. qPCR product was cleaned (ExoSAP-IT PCR Product Cleanup) and sequencing was performed using the 3130xl Genetic Analyzer in the University of Vermont Cancer Center Advanced Genome Technologies Core. Sequence data were viewed for quality assessment (FinchTV 1.4) and aligned by eye to genome references using Geneious v 6.0.6 .We refer to virus prevalence on flowers as the percentage of flower samples with virus in each experimental trial. Virus loads are presented as the number of genome copies per flower sample or bee. Visitation rate was calculated as the total number of honey bee visits per hour per plant species. Visit duration was measured as the amount of time honey bee foragers were observed visiting inflorescences (in seconds). Since plants in the chronic exposure trials were experimentally treated the same as plants in the single species trials, we combined these data together in analyses examining virus deposition on plants. Data from the comingle trials were omitted from analyses of virus deposition on plants, as these trials were only conducted to examine transmission via direct contact between bee species and had different experimental conditions that could confound results 10 transformed to achieve normality prior to analyses. For virus load, we conducted linear mixed models (LMM) with identical structures, terms, and random effects as the GLMMs. The interaction of diversity (single species vs. mix of threes species) and plant species was not included in virus load model as the model was rank deficient and unable to compute the interaction term [To examine the effect of plant species, virus species, and their interaction on virus prevalence  on flowers used in single species trials, we used a generalized linear mixed effects model (GLMM) with flower sample as a random effect. In order to examine prevalence of RNA viruses on flowers, the model was structured such that each flower sample was included twice, once for each virus. To examine the interaction effect of plant diversity and plant species on virus prevalence, we conducted a separate GLMM testing the interaction of diversity (single species vs. mix of three species) and plant species with flower sample as a random effect. Since visitation rate and visit duration could additively affect virus deposition to flowers, we conducted a third GLMM including visitation rate and visit duration as fixed effects and included flower sample as a random effect. All GLMM models on virus prevalence were conducted with a binomial distribution (link = “logit”). Virus loads of contaminated flowers were logion term . As no bAll mixed effects models were conducted using the LME4 package using the glmer function for virus prevalence and the lmer function for virus load . Signifi4 and 109 genome copies per bee for DWV and 108 and 106 genome copies per bee for BQCV. All bumble bees were negative for both viruses at the onset of the experiment (n = 70). No bumble bees became infected in any of the experiments  for either the control group (n = 192) or exposed group (n = 220).At the onset of the experiment, all plant species were negative for DWV and BQCV. RNA virus loads in the two honey bee colonies were 1022 = 11.15, p = 0.004), such that DWV and BQCV were not equally distributed across plant species  were negative for both viruses. Of the flowers visited by both honey bees and bumble bees, we detected DWV and BQCV on 24.2% and 21.2%. When single species of plants were offered to infected honey bees, we detected viruses on all three species . However species . Main efpratense . By anal3−105 genome copies  and L. corniculatus (p = 0.005) but did not differ by virus species . The interaction of plant species and virus species was not significant for virus load. Virus loads were different across diversity (single plant species vs. mix of three species) with the highest virus loads occurring on plants in the mix of three species trials . Flowers that received fewer honey bee visits had the highest virus loads . Visit duration did not influence virus loads left behind on flowers by honey bee foragers .Virus loads on flowers ranged from 10e copies . In singAlthough flowers have been implicated as bridges in the spread of bee diseases , the rolL. corniculatus was unique in that BQCV was detected in all samples yet no DWV was detected. In contrast, DWV and BQCV were detected on both Trifolium species during the course of the study. Compared to the Trifolium species, the inflorescences of L. corniculatus are the least similar morphologically and consist of only eight florets (compared to 20–40 in Trifolium species). To visit the nectaries of Trifolium, pollinators access nectaries by probing multiple tubular flowers while crawling about the surface of the inflorescence head. For L. corniculatus, nectaries may be accessed through contact with only the anterior portion of the bee. If a virus is deposited by feces, floral morphology that encourages ‘hovering’ behavior, may reduce the likelihood of viral deposition [Deformed wing virus and BQCV were differentially deposited across the three plant species, indicating that modes of deposition vary for virus species and that deposition may be mediated by floral traits. In our study, virus deposition on position . Likewisposition ,11 or nuposition  are idenposition . InvestiWe found flowers that received longer visits by honey bees were more likely to host viruses. However, flowers with higher visitation rates were less likely to host viruses and also had lower virus loads. These results underline the complexity of this study system and the need to understand how viruses are shed from bees onto flowers during foraging bouts.T. pratense, despite no difference in visit duration for T. pratense between diversity trials (single species vs. mix of three species)  . Our resavonoids , a groupavonoids . HoweverUnder our experimental conditions, bumble bees did not develop an infection after direct contact with honey bees through comingling or indirect contact through shared flowers. These results indicate that transmission of viruses between bee species through flowers is a rare occurrence, with experimental detection contingent on numerous factors. For example, factors such as immunocompetence, virus virulence, virus load, and the probability a bumble bee will contact a virus particle on a flower may all contribute to detection. Though, transmission through flowers may have a low probability, the high prevalence of contaminated flowers and high flower visitation rates exhibited by bees in the wild may be hallmarks of a process that occurs with frequency in nature but is difficult to capture in an experimental setting. We also note that we did not test whether the virus strains in our honey bees were infective to bumble bees. Thus, although we did not demonstrate virus transmission to bumble bees in our experiment, we remain cautious to exclude the possibility under different experimental conditions and with greater sample sizes.Our findings present several promising avenues for future research. We were successful in demonstrating virus deposition to flowers by honey bees under experimental conditions. To test whether our results are relevant in nature, future studies should test field-collected flowers near honey bee apiaries. Since other bee species may also deposit viruses on floral resources, selecting field sites with varying densities of honey bees and measuring floral visitation could shed light on the importance of honey bees versus other bees to virus deposition on flowers. To further understand directionality of transmission, future experiments should test whether infected bumble bees and/or other bee species will also deposit viruses on flowers . In addiS1 Table(PDF)Click here for additional data file.S1 Supplemental InformationVirus and actin amplicons are colored for visualizations: Green = DWV, Blue = IAPV, Red = Actin, Yellow = BQCV. Ten random base pairs (uncolored) flank each target of interest.(PDF)Click here for additional data file.S1 FigLotus corniculatus (birdsfoot trefoil), Trifolium pratense (red clover) and T. repens (white clover). Colors of box plots represent data from the “diversity” experiment, where all plant species were provided at the same time, and “single species” where each plant species were provided individually. Letters above box plots show results of pairwise comparisons for visit duration data. Red lines show the visitation rate (number of honey bee visits/hour) to each plant species for each experiment. Visit duration data were log10 transformed to achieve normality prior to analysis. We examined the effect of plant species on visit duration in an ANOVA using data from the single species experiment trials. We examined pairwise comparisons using Tukey contrasts . In a separate ANOVA using data from the single species and diversity trials, we examined the interaction effect of plant species and experiment (single species vs. diversity) on visit duration.Box plots show median duration of honey bee visits to three plant species: (TIF)Click here for additional data file.


The emergence of porcine epidemic diarrhea (PED) in commercial swine in North America and growing concerns about the potential for the introduction of African swine fever (ASF) from China, the European Union, or other affected regions has put a spotlight on the possible role of contaminated feed and feed ingredients in the introduction and transmission of viral swine pathogens. This paper systematically reviews the scientific literature regarding whether non-animal origin ingredients of commercial swine feed could introduce or transmit viral pathogens of swine into or within the United States. The purpose of this review is to identify, evaluate, and summarize the relevant scientific knowledge, published through March 2018, and to identify information gaps and research needs, thereby making the available evidence more accessible to policy makers, the swine industry, and the scientific community. A total of 26 documents were selected for the final review process, which included experimental studies, case reports, epidemiological investigations, and scientific opinion, among others. The review found that the scientific literature has addressed some critical experimental questions pertaining to transmission of swine viruses via feed and feed ingredients, but the current body of scientific knowledge lacks conclusive evidence of virus contamination of non-animal origin feed ingredients of commercial swine feed, particularly for imported commodities, and further investigation into the epidemiology of virus transmission via feed to swine under field conditions through natural feeding behavior is warranted. Additional studies of how imported ingredients of commercial swine feed are sourced, processed, transported and, thus, contaminated prior to importation into the United States are needed. Moving forward, studies designed to examine the likely source(s) of contamination and subsequent virus mitigation steps in processing and post-processing may be the most fruitful focus of research. Over the past three decades, the swine industry in the United States has experienced several significant disease outbreak events with highly pathogenic viral pathogens, including porcine reproductive and respiratory syndrome virus (PRRSV), porcine circovirus type 2 (PCV2), and, most recently, the swine enteric coronaviruses, including porcine delta coronavirus (PDCoV) and porcine epidemic diarrhea virus (PEDV) –4. TheseDuring the 2013–2014 outbreak of porcine epidemic diarrhea (PED) in North America, contaminated feed and feed ingredients were suspected as a potential introduction and/or transmission route for spread as early cases of PED in Canada were associated with a common feed source containing spray-dried porcine plasma (SDPP) –9. AdditDespite extensive investigative work in the field and the laboratory, the specific mode of introduction of exotic viral pathogens such as PEDV into the United States and, subsequently, into domestic swine premises remains unknown. In order for feed or feed ingredients to be a route of disease introduction into the United States, they must become contaminated with the causative agent; avoid inactivation through (trans-oceanic) transport, feed manufacturing, processing, and distribution; and be ingested at a dose sufficient to cause infection in a susceptible pig.Salmonella are known to be transmitted via swine feed —and the occurrence of emerging swine diseases in new geographic ranges  and/or with increased pathogenicity  suggests that the critical production inputs along with existing biosecurity and mitigating measures that have historically delivered an acceptable level of protection may need to be re-evaluated.In order to better inform policy makers, swine industry stakeholders, and the scientific community, a literature review was conducted on the scientific evidence regarding whether non-animal origin ingredients of commercial swine feed could introduce or transmit viral pathogens of swine into or within the United States. The goal of the literature review is to understand the current scientific knowledge and to identify information gaps. The results may support future scientific research for evaluating the risk of entry of exotic viral pathogens via specific feed ingredients from source countries and mitigation measures to prevent exposure to U.S. swine populations.This literature review aims to answer the following research question:What evidence is available in published scientific literature regarding whether non-animal origin ingredients of commercial swine feed could transmit viral pathogens of swine into or within the United States?The methodology of this literature review follows the framework of a qualitative systematic review . The litA search of the National Library of Medicine/PubMed, National Agricultural Library/PubAg, National Agricultural Library/Navigator  and Google Scholar was conducted to identify published scientific literature pertaining to evidence regarding whether non-animal origin ingredients of commercial swine feed could transmit viral pathogens of swine into or within the United States. Studies published any time through March 2018 were identified.Focus on non-viral pathogensFocus on disease transmission routes other than feed and feed ingredientsAnimal origin feed ingredientsFocus on mitigations/treatment/disinfection of equipment or sanitizing feedNo English translation availableFull text not availableDuplicate publicationSubject matter outside the scope of the review.The study selection process was performed in two stages. In the first stage, an initial screening of search results was performed based on title and abstract. In the second stage, the full text of the preliminary list of studies was evaluated. Additional articles were obtained through manual review of reference citations in the relevant literature. The most common reasons for exclusion, in descending order, were: focus on disease transmission routes other than feed or feed ingredients; focus on mitigations/treatment/disinfection of equipment or sanitizing feed; subject matter outside the scope of the review; and focus on animal origin feed ingredients. The two-stage study selection resulted in retention of 26 included studies. The studies included for the qualitative analysis are reported in The data extraction component is the process by which research reviewers obtain the necessary information about study characteristics, methods, and findings from the included studies. The quality assessment component aims to identify internal and external validity of the selected studies. Standardized data extraction provides consistency in a literature review, thereby reducing potential bias and improving validity and reliability .A fillable, pdf data extraction form template was created for the purpose of this literature review. Twenty-six published articles were included in the data extraction and quality assessment process. Reviewers worked in pairs to perform the data extraction and quality assessment. Each article was reviewed for general information, study characteristics, and outcome results. For the quality assessment portion, the reviewers reported on potential sources of bias, shortfalls in the statistical and analyses methodology, the quality of reporting, and the generalizability of the study to the commercial swine industry in the United States. The data extraction form template is provided in the supplementary information A qualitative, narrative approach was used for the data synthesis and report writing. The information extracted in the data extraction process was summarized into a data synthesis table. This table is provided in The 26 studies included in this literature review were collated into three categories: background information on risk factors for transmission and virus survival on fomites, epidemiology and outbreak investigations, and experimental studies with swine bioassays. Information extracted from these studies may overlap into more than one category and, thus, may be discussed in more than one section. Additionally, the study summaries provided in this section are not meant to be detailed and fully comprehensive but rather are focused on the information pertinent to this literature review, namely, non-animal origin feed ingredients.post-hoc outbreak investigations, and experimental studies of the survival of viruses in contact with fomites. The studies are grouped into two categories: risk factors for virus transmission and virus survival in contact with fomites. The virus scope of these studies includes African swine fever virus (ASFV), porcine high fever disease virus, highly pathogenic PRRSV, pseudorabies virus (PRV), Aujeszky's disease virus, and blue eye disease virus.Numerous investigators have reviewed the epidemiology and impact of swine viral pathogens and analyzed industry expert opinion and outbreak information to identify risk factors for transmission of swine pathogens. Additionally, several studies have looked at the survivability of viruses on various fomites related to swine production and husbandry, including feed and feed ingredients. Methods used by these investigators include expert elicitation, questionnaire-based Three studies examined the epidemiology of specific swine pathogen(s) or outbreak events in various regions of the world –17. The Le et al.  conducteA retrospective case-control study by Fasina et al.  sought tA review by Guinat et al.  summarizBrookes et al.  elicitedThree studies examined virus survivability on various swine-related fomites, including feed and feed ingredients –23. The Schoenbaum et al.  conductePirtle and Beran  conducteMartínez-Gamba et al.  conducteIn summary, most of the reports and studies summarized above were not designed to focus on non-animal origin feed and feed ingredients as a potential vehicle for virus transmission; however, feed and feed ingredients were included in the study design or discussion. Similarly, some findings in this group of studies may not be generalizable to other viruses or virus families or the commercial swine industry in the United States. Given these limitations, several key points are highlighted below.Le et al.  identifiSeveral investigators have examined the persistence of viral activity in the presence of various fomites, including non-animal origin feed ingredients. In experiments in which they spiked fomites with stock virus, they found, in general, that viral activity did not persist for long periods of time under the experimental conditions used. Schoenbaum et al.  found thAmong the knowledge gaps identified in these studies are the need for a comprehensive evaluation of potential transmission pathways involving non-animal origin feed ingredients and swine viruses. The scientific literature regarding the survival times  for various non-animal origin feed ingredient/pathogen combinations as well as determination of infectivity is incomplete and warrants further studies along with documented replication of studies. Furthermore, the likelihood of non-animal origin feed ingredients incurring contamination and documented scenarios in which cross-contamination occurs under field conditions is unknown.In 2013, swine enteric coronaviruses, such as PEDV and PDCoV, emerged as pathogens of significance for the swine industry in the United States and several other countries. Efforts were made to describe the epidemiology of the outbreaks which included a focus on the sources of virus introduction and transmission. Among other things, feed and non-animal origin feed ingredients were suspected as one possible route of virus introduction and spread. Studies reviewed in this section were separated into two major categories: epidemiological reports, reviews, and surveys; and feed and feed ingredient experimental studies. These studies are primarily focused on PEDV and PDCoV; however, other swine pathogens are included such as transmissible gastroenteritis virus (TGEV), PRRSV, and PCV2.Eight epidemiological reports examining the global outbreaks of PED and PDCoV infection were reviewed. The geographic scope of these reports include Europe, Asia, and North America , 24–30. High levels of infectious PEDV are shed in feces, contributing to contamination of various fomites, including vehicles, humans, and feed.The transmission of PEDV via feed has been shown but more data are required to assess its epidemiologic importance.Food waste fed to pigs (swill) can contain PEDV but epidemiologic role of this finding is unknown.In 2014 and 2016, the European Food Safety Authority published two reports pertaining to PED and PDCoV , 30. In In 2016, the European Food Safety Authority published a scientific report of PEDV epidemiology and impact as reported in the scientific literature in 2014 and 2015, together with an analysis of PED cases in the European Union . TransmiAlthough PEDV was first identified in Japan in the 1990s, Japan experienced renewed outbreaks of the disease in 2013. In a retrospective questionnaire-based case-control study, Sasaki et al.  focused In a report by Davies , the autThe author also discussed the risk of feeding animal products to swine and whether or not the risk warrants excluding animal origin products (or other ingredients) from swine diets. The author argues that complete bans on certain ingredients in swine feed may not be the solution. Rather, he suggests that one must take into consideration all contributing disease transmission pathways, the cost-benefits of mitigating risks associated with feed and feed ingredients, and the nutritional needs of commercial swine .In a review by Lowe , the autIn 2014, the United States experienced the emergence of a second novel swine enteric coronavirus, PDCoV. McCluskey et al.  administpost-hoc investigations, epidemiologic surveys, a case-control study, brainstorming, and speculation. They used previously collected epidemiologic data to develop scenarios and identify hypothetical routes of PEDV introduction into the United States and conducted follow-up studies to gather evidence for the most plausible scenarios. The follow-up studies included testing organic soybeans and pet jerky treats imported from China and archived serum samples opportunistically collected from feral swine; all results were negative. The authors did not identify a proven source or route of PEDV introduction into the United States. However, it was suggested that incomplete farm feed/ration records negatively impacted investigators' ability to thoroughly evaluate the potential epidemiologic role of feed or feed ingredients. The authors identified totes used to transport bulk feed or feed ingredients as providing “the simplest explanation” for the investigation findings  for the presence of virus and/or to conduct assays testing the ability of feed to serve as a fomite for virus. The following summarizes the reported findings.Associated with the U.S. outbreak of PED in 2013, an epidemiological investigation was conducted at an affected Ohio swine operation to determine the source of virus introduction . The timA retrospective case study by Greiner  investigTrudeau et al. , 34 condIn summary, the epidemiologic investigations and outbreak studies did not definitively link or exclude transmission of PEDV or PDCoV with non-animal origin feed or feed ingredients. Inconsistent findings impart uncertainty toward feed or feed ingredients as a transmission pathway , 32, 35.Two studies conducted environmental sampling of feed, feed facilities, and feed transport vehicles to determine whether these items contributed to the cause of the outbreaks of PED and PDCoV infection in the United States , 32. ColAmong the knowledge gaps identified in these studies are the identification of critical control points for pathogen contamination of feed and/or non-animal origin feed ingredients and consensus on the feed-based transmission pathways for PEDV and PDCoV. The potential point source(s) of virus contamination of non-animal origin feed or feed ingredients have not been identified nor clearly defined.in vivo biological assays (bioassays) to be conducted. The bioassays were used to assess the biological activity or potency of the pathogen(s) of interest by measuring the magnitude of response such as observed clinical signs consistent with the study disease(s) and/or positive findings to diagnostic testing and necropsy examination. Most studies included in this section of the literature review used swine bioassays to determine the infectivity of the pathogen(s) of interest in feed or feed ingredients subsequent to detection by polymerase chain reaction (PCR) of virus nucleic acid in the matrix (feed or feed ingredients) under examination.The rapid spread of PED in commercial swine in North America in 2013–2014 prompted several non-randomized, experimental studies with ad libitum  feeding , PRRSV, porcine sapelovirus (swine vesicular disease virus surrogate), PCV2, ASFV, and influenza A virus of swine in selected virus-ingredient combinations. Pigs were inoculated by various methods, including orally via syringe, intramuscularly, and intranasally. A positive bioassay was observed for the following virus-ingredient combinations: PRRSV and conventional SBM; PRRSV and DDGS; Senecavirus A and choline; and PCV2 and lysine, choline, and vitamin D .n) included conventional SBM (n = 7), lysine (n = 5), vitamin D (n = 4), choline (n = 4), organic SBM (n = 3), and DDGS (n = 2). The findings suggest that viruses can survive in non-animal origin feed ingredients but survival duration is variable and dependent on virus properties and feed matrix , and bovine herpesvirus-1 (PRV surrogate). The non-animal origin feed ingredients that supported survival of multiple viruses  , 37, 40.Among the knowledge gaps identified in these studies are the identification of vulnerable non-animal origin feed ingredients for viral contamination, ingredient (matrix) characteristics that support or hinder virus survival, and identification of the critical point(s) in the transboundary feed production and distribution continuum where viral contamination of non-animal origin ingredients could occur. There is a lack of field data demonstrating whether, how, and when non-animal origin feed ingredients may become contaminated with swine viruses. Further, although some field epidemiological investigations have associated contaminated (PCR positive) feed with the source of virus introduction on affected farms, to date, experimental studies of virus transmission via feed and feed ingredients have yielded inconsistent data. Additionally, the development of diagnostic assays and sampling techniques capable of detecting small amounts of virus in large volumes of non-animal origin feed ingredients is necessary to allow more accurate estimation of the frequency with which these materials are contaminated with virus, which viruses are present, and, if present, at what concentrations. Subsequent assays to determine the level of virus in the final, processed feed product would be useful to estimate the likelihood that contaminated non-animal origin feed ingredients could serve as a transmission pathway for swine viruses and to what degree feed should be prioritized as a biosecurity risk.The objective of this literature review was to gather and analyze the evidence in published scientific literature regarding whether non-animal origin ingredients of commercial swine feed could introduce and transmit viral pathogens of swine into or within the United States. The goal was to understand the current scientific knowledge and to identify information gaps to better inform policy makers, swine industry stakeholders, and the scientific community. To achieve this, relevant literature was reviewed and findings were qualitatively summarized.The results of the literature review demonstrate that a limited number of studies currently address swine viral pathogen transmission through non-animal origin feed and feed ingredients. Despite the small number of published studies, there is relevant evidence in the literature that contributes to the on-going discussion regarding the potential role of non-animal origin feed ingredients in the transmission of swine pathogens, including:A subset of the studies reviewed provided experimental evidence that swine viruses can survive in non-animal origin feed ingredients under various experimental and laboratory conditions –39, 41. A subset of experimental studies provided evidence that feed contaminated with virus can transmit disease to naïve piglets , 37–41.◦ choline chloride◦ D/L methionine◦ dried distillers grain with solubles◦ lysine HCL◦ soybean meal◦ vitamin D.Further, a subset of experimental studies attempted to identify individual feed ingredients that may be more likely than others to support virus survivability , 39, 41.Extended survival of PEDV was observed in conventional SBM . Similar◦ PEDV-contaminated choline chloride , 39◦ Senecavirus A-contaminated choline chloride ◦ PRRSV-contaminated conventional soybean meal ◦ PRRSV-contaminated dried distillers grain with solubles ◦ PCV2-contaminated choline chloride ◦ PCV2-contaminated lysine HCL ◦ PCV2-contaminated vitamin D A subset of experimental studies concluded that duration of virus survival (and infectivity) is ingredient-dependent. Virus viability as determined in swine bioassay was observed with the following virus-ingredient combinations:Under the laboratory-simulated model conditions, both LA and MCFA were concluded to be effective chemical mitigants against PEDV in individual feed ingredients stored under simulated shipping conditions, suggesting they might be useful for reducing viral load in feed ingredients , 39.n = 4); experimental methods which do not mimic natural feeding behaviors of swine or large-scale commercial swine production; and environmental scenarios which cannot be easily extrapolated to other seasonal variations or geographical regions.Limitations in several studies hindered generalization to real-world commercial swine scenarios. For example, studies were limited by small feed sample volumes  which does not directly equate to the quantities (tonnage) in actual swine production and feed scenarios; small sample sizes (2 replicates) which reduced statistical strength and confidence of findings; low sensitivity of swine bioassays  for swine viruses onto the index farm may differ from the transmission route(s) among housing units within the index farm and between secondary farms. Similarly, the entry route for swine viruses into the United States may differ from the transmission route(s) among domestic swine farms. Thus, if swine viruses contaminate non-animal origin feed ingredients, a multi-modal transmission mechanism is likely to occur. When considering non-animal origin feed ingredients as potential fomites for swine virus transmission, it is important to understand how the primary transmission pathways  interface with one another, in particular, how the production and distribution of feed interacts with other potential or known sources of virus contamination  to contribute to disease transmission both into and within the United States. Similarly, it's important to understand the relative risks of various transmission pathways and where feed ingredients fit in among broadly accepted risk pathways such as movement of infected pigs and fecal contamination of fomites . By understanding the magnitude of the risk of feed ingredients, one can better balance the costs of sourcing “safe” feed ingredients and the nutritional needs of pigs with the costs of applying various mitigation strategies to potentially contaminated feed .Over the past several decades, the U.S. commercial swine industry has improved biosecurity measures on commercial premises to prevent transmission of economically significant viruses such as PCV2, PRRSV, and, most recently, PEDV. Commercial swine operations may use the absence of PRRS on the farm as an indicator of thorough implementation and enforcement of biosecurity measures. In the studies reviewed, Bowman et al.  stated tArguably, the most crucial pieces of missing information are that neither the contamination routes of swine viruses into non-animal origin ingredients of commercial swine feed, leading to virus transmission to swine, nor the pathways of entry of exotic swine viruses into the United States have been definitively identified. A major knowledge gap exists in sources of potential contamination and where feed or feed ingredients may become cross-contaminated. Very little information is available on how non-animal origin feed ingredients are produced and sourced outside the United States and current studies have produced little scientific evidence of whether, how, or when non-animal origin feed ingredients become contaminated with swine viruses in regions outside the United States. The critical point(s) of susceptibility to contamination along the entire feed supply chain, from harvesting of plant-derived feed ingredients in the field to on-farm delivery of feed to swine premises, have not been identified. To compound this issue, reliable and validated assays and sampling techniques capable of detecting small amounts of virus in large volumes (bulk) of non-animal origin feed ingredients are not available. Taking a systematic approach to the entire (transboundary) feed production system, similar to the hazard analysis and critical control points process used in food safety, may help to identify vulnerabilities in the production process, better inform the development and application of mitigation measures to reduce viral contamination risks, and help stakeholders allocate resources toward mitigation measures based on the likelihood of virus contamination.While investigators have addressed some critical questions pertaining to transmission of swine viruses via feed and feed ingredients, the current body of scientific knowledge has yet to provide conclusive evidence of virus contamination of non-animal origin feed ingredients with swine viruses and the epidemiology of virus transmission to swine via feed and feed ingredients under field conditions. If the primary concern lies in the importation of contaminated feed and feed ingredients, then additional research and investigative studies of how ingredients are sourced, processed, and transported prior to importation are needed. However, the lack of validated feed and feed ingredient diagnostic assays and sampling techniques capable of detecting small amounts of virus in large volumes of material limits the ability to determine whether and at what point non-animal origin feed or feed ingredients may become contaminated with viruses and limits the ability to identify critical control points in feed production, distribution, and storage to mitigate risk. Although LA and MCFA were shown to be effective chemical mitigants against PEDV, additional mitigation strategies should continue to be explored, including other chemical treatments, the application of heat or pressure (pelleting) to feed, and holding times for feed or feed ingredients. Moving forward, studies designed to examine the likely source(s) of contamination in the feed supply chain and virus mitigation steps in processing and post-processing may be the most fruitful focus of research.Currently, the role of feed in the transmission of swine diseases is experiencing intense scrutiny and research from U.S. Federal and State government agencies, the swine industry, and the scientific community. The pool of knowledge is rapidly changing; thus, future consideration should be given to conducting an updated literature review to incorporate more recent findings (April 2018 to present).RG, IK, and AM performed the literature searches. RG, KC, IK, DL, and AM reviewed the articles identified via the literature search, determined which articles met the inclusion criteria, and performed the data extraction and synthesis steps. RG, KC, IK, and DL authored the manuscript. All authors reviewed the manuscript, contributed to the design and research purpose statement of this review.The authors declare that the literature review was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The views expressed in this article do not necessarily reflect the official policy of the U.S. Department of Agriculture or the U.S. Government.


Canis dingo), a canid species present on the Australian continent for around 4000 years. The Kelpie breed is split between working and conformation types that have readily recognizable differences in external morphology. We characterize known gene variants relating to external morphology in sequenced representatives of both Kelpie types  and compare the variants present with those in sequenced Australian Dingoes, including 25 canids with locus-constrained data and one with a whole genome sequence. Variants assessed include identified coat color and ear morphology variants. We describe a new variant site in the transcribed region of methionine sulfoxide reductase 3 that may relate to ear phenotype. None of the morphology variants analyzed offer support for co-ancestry of the Kelpie breed with the Australian Dingo.The Kelpie is a breed developed in Australia for use as a livestock herding dog. It has been proposed that the development of the breed included gene flow from the Australian Dingo ( The Kelpie breed is an iconic dog breed developed in Australia in the late 19th century. The Working Kelpie Council of Australia reports that the breed was developed from Scottish Smooth Collie and Farm Collie stock, and was founded upon a small number of key individuals. The breed is renowned for its resilience, working in harsh  conditions in the Australian outback [5,6-dihydroxyindole-2-carboxylic acid oxidase precursor (TYRP1) may result in a brown color [Agouti signaling protein (ASIP) and RNA-Binding Protein  (RALY) loci or a dominant variant at the canine β-defensin 103 (CBD103) locus [TYRP1 are observed to have varying pigment intensity, and the genes underlying this difference in hue are thus far undescribed in dogs with normal coat variation  [The Australian Kelpie (AK) c that hawn color ,4. SolidTYRP1 are colloquially referred to as red in the breed. The tan markings are predicted to be due to alleles at either the ASIP locus (A-locus) or the CBD103 locus (K-locus) [CBD103 [Australian Working Kelpies (AWK) b registeK-locus) ,6. The o [CBD103  is undesginger or cream in the breed), which can be driven by the pheomelanin variant at Melanocortin-1 receptor (MC1R) [y) at ASIP [Melanophilin (MLPH) of black, brown, and ginger, respectively) [Other coat colors that exist in AWKs include yellow (known as r (MC1R) . A red o at ASIP . Blue, fctively) ,10 are oMicropthalmia transcription factor (MITF), which in combination impact the extent of white markings in the dog. The first variant in the region that is expected to impact the extent of white is a short-interspersed nuclear element (SINE) insertion three kilobases upstream of the melanocyte-specific promoter for the gene. The second variant associated with the extent of white is a length polymorphism in the immediate vicinity of the melanocyte-specific first exon [White markings are rarely observed in the breed, and when present, typically result from recent out-crossing with other livestock herding breeds, such as the Border Collie. The white patterning in most dog breeds is controlled by variants in the melanocyte-specific promoter region of rst exon . In geneCanis dingo (Dingo) contributed to its founding. Such ideas were likely fueled by statements attesting this by respected individuals such as geneticist Dr. R. B. Kelley, the author of a widely recognized book used in breeding and training livestock herding dogs first published in 1942 [Throughout the history of the Kelpie breed, speculation has persisted that the Australian wild dog  in 1942 ; more re in 1942 . Others  in 1942 , or who  in 1942 , offer eMethionine sulfoxide reductase 3 (MSRB3) has been suggested as a strong regional candidate gene for the phenotype [The Dingo a has an henotype .MSRB3 that have not been reported in the literature. Both longer variants in the MSRB3 UTR are in near complete linkage disequilibrium, with a potentially functional array SNP that has been strongly associated with prick and drop ears in many breeds. None of the analyzed variants support co-ancestry with the Australian Dingo.Our analysis will determine the mutational basis of commonly observed external morphologies (coat color and ear phenotype) in the two Kelpie breed varieties at loci for which variants have been described. We include a description of two insertion variants in the 3′ untranslated region (UTR) of the gene Genomic DNA was extracted from 12 individual EDTA-stabilized whole blood samples -conformation-type; eight AWKs , and three Kelpies of undocumented type , using the Illustra Nucleon BACC2 kit . DNA was provided to the Ramaciotti Centre  for whole-genome next-generation sequencing. Next-generation sequencing was performed on the Illumina HiSeq 2000 or HiSeq 2500  as 100 base-pair paired end reads on a single lane of the sequencing platform with Tru-seq library preparation (Illumina) [https://www.ncbi.nlm.nih.gov/sra/) [Sequence data for the Labrador retriever LA882 (Accession identifier: ERX425617) and the Dingo (Accession identifier: RKW13760) were obtained from the Sequence Read Archive (SRA) in Genbank (ov/sra/) . The DinASIP, CBD103, and MC1R loci were available for 25 Dingoes in the public domain [Locus-constrained sequencing data for the c domain .Recommendations from the Australian Code for the Care and Use of Animals for Scientific Purposes were strictly adhered to throughout this study. Research was conducted with animal ethics approval, granted by the Animal Ethics Committee at the University of Sydney .Raw reads were aligned as pairs to the CanFam 3.1 reference sequence using the Burrows–Wheeler Alignment-MEM tool (version 0.7.15) with default parameters ,22. Polyhttp://genome.ucsc.edu), using primers described in the relevant article reporting the variant or our own variant calling algorithms to identify the location of the variant. Locus labelling  is based on nomenclature described in [The variants previously identified as coding for the external morphologies used as breed descriptors in the Kelpie breed standards  for ear ribed in , other tribed in .ASIP and RALY) [TYRP1) [CBD103) [MC1R) [MITF) [MLPH that affects dilution of the base coat color [The coat color variants explored were those known to occur at the A-loci (nd RALY) ,8,28, th [TYRP1) , the K-l[CBD103) , the E-l) [MC1R) ,29, and ) [MITF) ,30. The http://genome.ucsc.edu). Manual inspection of sequence alignment throughout the region of MSRB3 was used in conjunction with variant calling  per allele required) from the whole genome sequence, in order to identify a new variant that segregates in strong linkage disequilibrium with the prick versus drop ear phenotype in the sequenced cohort. This variant was compared among the sequenced Kelpies of both varieties; the genome reference ; a publicly available Labrador sequence, representing a validation of the drop ear variant [The SNP variant used to assess ear morphology  was re-m variant ; and a p variant .ASIP, the coding region of MC1R, and the coding region of CBD103 were available in Genbank [Further locus-constrained sequencing data from 25 Dingoes for exon 4 of  Genbank . These w Genbank  and the MC1R that is known to prevent the expression of eumelanin, thus generating a yellow-red coat hue, was observed as a heterozygote in both Kelpie varieties , but only one of 26 sequenced Dingoes had this variant as a heterozygote. The MC1R variant identified as causative for melanistic masking segregated freely in the working Kelpies as g.63694460_C>T  [Observed variants at the major coat loci impacting the Kelpie breed varieties, based on whole genome sequencing data, are shown in  masked) .TYRP1 mutation at CFA11 g.33326685, p.331Q>X  were homozygous for the z et al. ). No furMITF, the prevalent length polymorphism allele observed in both varieties of Kelpie is one that is as yet undescribed [MITF length polymorphism, the variant alleles are encoded in a concise idiosyncratic gapped alignment report (CIGAR) format that is used in the standard sequence alignment map (SAM) format. For example, the canine reference genome allele is termed as 35A, and the variant can be annotated as: “12C9A2G12A”, which corresponds with the sequence “CCCCCCCCCCCCAAAAAAAAA GGAAAAAAAAAAAA” [At escribed ,30. The AAAAAAA” . One dogAAAAAAA” .RALY or ASIP) or the K-locus (CBD103). The dominant black allele  [CBD103. Of the 25 Kelpies previously sequenced, 24 were homozygous for the reference allele (ins/ins) and one was heterozygous [Tan markings were expected to be affected by either the A-loci (rozygous . The whoASIP locus for Ay CFA24:23393510_G (reference is T), CFA24:23393514_G (reference is A), and CFA24:23393552_G (reference is G). These alleles correspond with wild-type at the ASIP exonic locus  [ASIP demonstrates that among 22 Australian dingo sequences derived from geographically dispersed locations, 16 were homozygous for the Ay allele, 6 were heterozygous for wild-type, and one was homozygous for the wild-type variant. The Dingo with whole genome sequence was homozygous for the Ay variant  were homozygous at the 83, R92)  of the f variant . Sequencquencing .MLPH mutation [One sequenced AWK (USCF640) was observed to carry the known mutation , but thiMC1R will be invisible on this coat background); and USCF6348 is likely black with tan points (carrying brown at TYRP1).Five of the Kelpies with whole genome sequencing had no coat color reported in their sample file. From the results of the current analysis, we can predict the colors of three dogs  to be brown with tan points; USCF6343 is likely black with tan points (carrying red/yellow—the melanistic mask from MSRB3 and High Mobility Group AT-Hook 2 (HMGA2) [Erect ears are the most frequently observed ear phenotype in both Kelpie varieties. By sequencing, AK (USCF305), and AWK individuals  are predicted to have erect ears, as they are homozygous for the non-reference allele at the putative locus  . AWK USCMSRB3 is identified in this study (g. 8038433del>ins). At this locus, the Dingo has a 5-base insertion variant (g. 8038433del>insTTTAT). All Kelpies have a 10 bp insertion at the same locus (g. 8038433del>insTTTATTTTAT). The AWK dog (USCF634) that was heterozygous at the intergenic SNP locus had insufficient sequencing coverage at the site of the insertion to exclude the possibility of the dog also being heterozygous at that locus.A new possible functional variant in MC1R while Dingo via ASIP)  has been previously described as being observed in a Scandinavian wolf.There is little or no evidence in the present data to support a history of significant introgression of Dingo into either Kelpie variety. The Dingo and domestic Kelpie populations have different segregation of yellow/ginger coat color (Kelpie via ia ASIP) . The popMSRB_UTR g. 8038433del>insTTTATTTTAT. The Dingo is predicted to have erect ears by both loci (CFA10 g.8085469C>T (T/T), MSRB3_UTR CFA10 g. 8038433del>insTTTAT (ins/ins)), while the Labrador is predicted to have drop ears by both loci (C/C and del/del respectively).Kelpies are predicted to have erect ears (CFA10 g.8085469C>T (T/T)). They also carry a 10-base insertion variant: https://www.ebi.ac.uk/ena/data/search?query=PRJEB28163).Accession identifiers associated with the resource are listed in Despite the commonly held view that the Dingo is an ancestral contributor to the Australian Kelpie ,13,15, tASIP-RALY on chromosome 24) underlie solid color (black/brown/yellow) and saddle or tan-point coat markings. At the ASIP-locus, most wolves would have the wild-type allele, whilst dingoes and many domestic dogs have other variants. Kelpies and Dingoes are strongly diverged at the A-loci (ASIP-RALY on chromosome 24), where in Dingoes the dominant yellow (Ay) haplotype has the highest frequency in conjunction with a variant at the nearby RALY gene, supporting a “saddle” pattern of markings. At these loci, the Kelpie exclusively has a haplotype that supports the non-agouti phenotype, with tan-point markings (at) at the RALY locus and wild-type variants in ASIP. While the saddle pattern from RALY is not readily visible in the Dingo, this is likely affected by the Ay haplotype at ASIP.The A-loci . In the Dingo, yellow coat color is driven by the Ay allele at the ASIP locus and homozygosity for the insertion variant at CBD103 , which enables colors encoded by variants at the A-loci (RALY-ASIP) and E-locus (MC1R) to be observed [MC1R coding region), only one was heterozygous for the MC1R CFA5 g.63694334G>A variant  [Ginger/yellow in the Kelpie is likely caused by the recessive CFA5 g.63694334G>A variant coded by the gene ncy <2%) .CBD103 dominant black (del/-) is perhaps better described as self-color, as it is epistatic to the genotype at ASIP, where the phenotype is black in the presence of homozygosity for the non-agouti allele  at the A-locus [ A-locus . The rep A-locus .CBD103 gene (commonly known as the K-locus) [ASIP, which has been proposed in the past to control black versus black and tan. Both Kelpie varieties actively segregate TYRP1 and MC1R-red, although ginger/cream are disallowed by the Australian National Kennel Council breed standard, which affects the AK variety. Melanistic mask was observed to freely segregate in the AWK. The only observed coding variant at TYRP1 is p.Q331X, and this is the same coding variant for brown coat color for both AK and AWK groups. Differences in pigment intensity or hue in brown kelpies remain unexplained by the loci described thus far. The Dingo RKW13760 was homozygous for the black eumelanin expressing variant at TYRP1.Among Kelpies, the major coat color difference between the two assessed varieties is the presence or absence of tan markings. We show that this variation is controlled by the K-locus) . Both KeMLPH was not assessed thoroughly in this analysis, due to poor sequence quality caused by high local G–C nucleotide content. One dog with low-quality cover (AWK USCF640) had a single sequencing read that is concordant with the dog being heterozygous for the presence of the MLPH splicing variant. Dilute animals are known to be present within the variety.Dilution as coded by MITF defines a spectrum of solid to spotted coat markings in dogs. The allele that is most commonly observed in both Kelpie varieties is yet undescribed in the literature . The absence of the SINE element CFA20 g.21836232_21836427ins>del at the MITF locus would suggest that if white markings were to occur in either Kelpie variety, they would be of modest extent. The allele observed at MITF in the Dingo has been previously described as wild-type 35B (observed in a Scandinavian wolf) [MITF are epistatic with those at the A-locus, to influence the penetrance of white markings as coded by the MITF loci.The length polymorphism in the melanocyte-specific promoter of an wolf) . The seqan wolf) , becauseErect ears are common between the Dingo and both Kelpie varieties. The SNP variant  detectedCBD103 allele in one sequenced Dingo may suggest introgression in that canid, or may represent a natural low frequency variant in that population. In either case, that animal would be expected to have a black coloration. Further investigation of the MC1R sequence for this animal (Alpine5) reveals a likely coding variant near the start codon for the gene, which may result in a gold coloration for this animal (Accession KF586907.1).This study is limited by the genetics observable in modern-day Kelpies. It is possible that attempts at introgression of the Dingo into the Kelpie occurred historically, but that the Dingo genes did not persist in the population at the loci observed. The possible presence of the dominant black C. dingo and 12 dogs designated as Kelpies  failed to support the assertion of significant historical introgression of Dingo genetics that is commonly described in Australian folklore. While the external phenotypes of the animals can be quite similar , explaining their difference in coat patterning.Examination of morphological variants assayed in representative sequenced  similar , particuar (MC1R d, there


With sequencing technologies becoming cheaper and easier to use, more groups are able to obtain whole genome sequences of viruses of public health and scientific importance. Submission of genomic data to NCBI GenBank is a requirement prior to publication and plays a critical role in making scientific data publicly available. GenBank currently has automatic prokaryotic and eukaryotic genome annotation pipelines but has no viral annotation pipeline beyond influenza virus. Annotation and submission of viral genome sequence is a non-trivial task, especially for groups that do not routinely interact with GenBank for data submissions.We present Viral Annotation Pipeline and iDentification (VAPiD), a portable and lightweight command-line tool for annotation and GenBank deposition of viral genomes. VAPiD supports annotation of nearly all unsegmented viral genomes. The pipeline has been validated on human immunodeficiency virus, human parainfluenza virus 1–4, human metapneumovirus, human coronaviruses (229E/OC43/NL63/HKU1/SARS/MERS), human enteroviruses/rhinoviruses, measles virus, mumps virus, Hepatitis A-E Virus, Chikungunya virus, dengue virus, and West Nile virus, as well the human polyomaviruses BK/JC/MCV, human adenoviruses, and human papillomaviruses. The program can handle individual or batch submissions of different viruses to GenBank and correctly annotates multiple viruses, including those that contain ribosomal slippage or RNA editing without prior knowledge of the virus to be annotated. VAPiD is programmed in Python and is compatible with Windows, Linux, and Mac OS systems.https://github.com/rcs333/VAPiD.We have created a portable, lightweight, user-friendly, internet-enabled, open-source, command-line genome annotation and submission package to facilitate virus genome submissions to NCBI GenBank. Instructions for downloading and installing VAPiD can be found at  With sequencing technologies becoming cheaper and more accessible, genomic sequencing is becoming increasingly widespread. Smaller groups are generating more sequencing data than they can analyze alone. In order to extract maximal scientific and public health value out of these data, sharing of assembled consensus genomes and raw sequence data is critical. The democratization of genomics takes a village. This is especially true for infectious diseases, where searchable sequence databases allow for real-time tracking of viral epidemics and solving of foodborne bacteria outbreaks –3. WhileMany foresee a world in which nearly every infectious disease genome is sequenced and archived in a publicly searchable database , 10. StaSurprisingly, other than for influenza virus, NCBI GenBank does not currently have an automatic viral genome annotation pipeline. The incredible diversity of DNA and RNA viruses presents a challenge for development of a universal annotator . ComplexIn order to accept submitted viral genomic data, NCBI GenBank requires 1) viral sequence complete with at least one protein annotation, 2) author/depositor metadata, and 3) viral sequence metadata, such as strain, collection date, collection location, and coverage. While manual annotation of nucleotide sequence can be done for small numbers of viruses, it is extremely time-consuming and labor-intensive. Even after correct annotations have been obtained for all viral sequences, manually integrating author and sample metadata to create files to be submitted is an equally time-consuming effort and not a feasible solution for groups sequencing more than a few viruses.To date, existing viral annotation tools have focused largely on batch submissions of a single virus species. This may be a holdover from when specific PCR-based methods were required to faithfully recover viral whole genome sequence or due to the focus of researchers on a single virus at a time. With the increasing use of metagenomic or shotgun next-generation sequencing and the availability of more and more sequencing capacity, researchers can confidently batch many different RNA or DNA viruses together on a single sequencing run.In order to facilitate viral genome annotation, we have developed a lightweight and user-friendly command-line tool that takes FASTA files of complete or near complete viral genomes as input, automatically annotates them, and outputs the required files for GenBank submission over email. VAPiD handles batch submissions of multiple viruses of different types without prior knowledge of the viral species, correctly annotates RNA editing and ribosomal slippage, performs spellchecking on annotations, handles batch or individual submission of metadata, runs with a simple one-line command, and creates annotated viral sequence files for GenBank submission.https://github.com/rcs333/VAPiD. An installation guide, usage instructions, and test data can also be found at the above webpage. The invocation of VAPiD is shown in Fig. https://submit.ncbi.nlm.nih.gov/genbank/template/submission/). An optional sample metadata file (.csv file) can be provided to VAPiD to expedite the process of incorporating sample metadata. This optional file can also be used to include any of the Source Modifiers supported by NCBI (https://www.ncbi.nlm.nih.gov/Sequin/modifiers.html). If no sample metadata file is provided, VAPiD will prompt the user to input the required sample metadata at runtime. Additionally, users can provide a specified reference from which to annotate all viruses in a run, as well as provide their own BLASTn database or force VAPiD to search NCBI’s NT database over the internet.VAPiD can be downloaded at The VAPiD pipeline is summarized in Fig. In the default case, NCBI’s BLAST+ tools are called from the command line to search against a reference database that is included with the VAPiD installation. This database was generated by downloading all complete viral genomes in NCBI on May 1, 2018. The best result from this search is passed as the reference into the next steps.WWW.qblast function against the online NCBI NT database. The BLASTn output is parsed for the best scoring alignment among the top 15 results that contains “complete genome” in the reference definition line. If no complete genome is found in the top 15 BLASTn results, the top-scoring hit is used as the reference sequence.If the online option for finding the reference is specified, VAPiD finds an appropriate reference sequence for each genome to be annotated by performing an online BLASTn search with a word size of 28 using BioPython’s NCBI If a specific reference is provided, VAPiD simply downloads it directly from NCBI. After the correct reference is downloaded, gene locations are stripped from the reference and a pairwise nucleotide alignment between the reference and the submitted sequence is generated using MAFFT . The relThe diverse array of methods viruses use to encode genes can present problems for any viral genome annotator. Ribosomal slippage allows viruses to produce two proteins from a single mRNA transcript by having the ribosome ‘slip’ one or two nucleotides along the mRNA transcript, thus changing the reading frame. Since ribosomal slippage is well conserved within viral species and complete reference genomes often list exactly where it occurs, custom code was used to strip the correct junction site and include it in the annotation.RNA editing is another process by which viruses can include multiple proteins in a single gene. In RNA editing, the RNA polymerase co-transcriptionally adds one or two nucleotides that are not on the template. These changes are specifically created during viral mRNA transcription and not during viral genome replication. RNA editing presents an annotation issue because the annotated protein sequence does not match the expected translated nucleotide sequence. To correctly annotate genes with RNA editing, VAPiD parses the reference genome viral species, detects the RNA editing locus, and mimics the RNA polymerase. VAPiD adds the correct number of non-templated nucleotides for the viral species and provides an alternative protein translation. This process is hard-coded for human parainfluenza 2–4, Nipah virus, Sendai virus, measles virus, and mumps virus. Although RNA editing occurs in Ebola virus, references for Ebola virus are annotated in the same way as ribosomal slippage, so code written for ribosomal slippage handles Ebola virus annotations.After ribosomal slippage and RNA editing are processed, files required for GenBank submission are generated with the provided author and sample metadata. VAPiD first generates the .fsa file, .tbl file, and optional .cmt file. Submission files for each viral genome are packaged into a separate folder for each sequence. VAPiD then runs tbl2asn on each folder using the provided GenBank submission template file (.sbt). tbl2asn generates error reports and Sequin (.sqn) and GenBank (.gbk) files for manual verification and GenBank submission via email attachment to gb-admin@ncbi.nlm.nih.gov.To illustrate our vision of how VAPiD will be useful to the scientific community we are providing two example use cases.This first example is the task that the authors originally wrote VAPiD for - annotating large numbers of genomes from different viral species, which mirrors the type of data that many clinical and public health laboratories may encounter. To illustrate this, 30 synthetic viral genomes were created by manually mutagenizing sequences downloaded from NCBI GenBank. Only point mutations that did not lead to stop codons were used and each sequence was given about 10–25 changes depending on the viral genome length, equal to roughly one amino acid change per 1000 nucleotides. The species included were Nipah, Sendai, Measles, Mumps, Parainfluenza 1–4, Ebola, Rotavirus segments, MERS, SARS, Coronavirus 229E, West Nile Virus, HTLV, HIV1, Hepatitis A-C, Hepatitis E, Norovirus, Enterovirus, JC virus, and BK polyomavirus. All genomes were put together into a single FASTA file. Metadata  for each of the viral genomes was put together into a single csv file. VAPiD was then executed with the command [python vapid.py example.fasta example.sbt --metadata_loc example_metadata.csv]. After running for 123 seconds the program successfully generated 30 complete and correct NCBI submittable annotation files (*.sqn), which could be immediately emailed to NCBI. When these same sequences were run with the online option it took 280 minutes to complete, most of which was waiting for NCBI to return BLAST results. The above example shows how VAPiD would be ideal for busy groups who produce a diverse array of viral sequence such as public health or clinical testing labs.The second example use case highlights both the cross platform functionality of VAPiD as well as the ability to manually enter NCBI required metadata at run time and use an online BLAST search - reducing the number of required files at runtime to two. For this example, a sample human parainfluenza 3 virus FASTA was created. No accompanying metadata file was created (unlike in the first example). Additionally, the syntax is exactly the same to use VAPiD across all operating systems. The single human parainfluenza 3 virus took approximately 2 min to annotate (including waiting about 30 seconds for NCBI blast results to be returned) on a Windows 10 Virtual machine with a single 2.36 GHz core and 2 Gb of RAM. This example highlights how VAPiD can be used to annotate and submit viruses with only two input files (the author template file only needs to be created once) on almost any Mac, Linux, or Windows computer with a Python installation.https://viral-ngs.readthedocs.io/en/latest/)  and the Broad Institute’s viral-ngs suite  with a single command. VAPiD facilitates input of sample metadata for viral genomic sequence, especially when the user desires to submit only a few sequences of diverse viral species.  VAPiD runs from the command line with two required arguments and one optional sample metadata file, with the option of inputting minimal sample metadata via the command line at the time of annotation. The latest version of VAPiD can be found at Project name: VAPiD.https://github.com/rcs333/VAPiDProject Homepage: Operating System(s): Mac OS X, Linux, Windows 10.Programing Language: Python.Other requirements: Python 2.7.4 or higher, BioPython, tbl2asn, MAFFT, internet connection.License: MIT.Any restrictions to use by non-academics: None.


The aim of this study is to present average annual healthcare costs for Dutch renal replacement therapy (RRT) patients for 7 treatment modalities.Health insurance claims data from 2012–2014 were used. All patients with a 2014 claim for dialysis or kidney transplantation were selected. The RRT related and RRT unrelated average annual healthcare costs were analysed for 5 dialysis modalities , home haemodialysis (HHD), continuous ambulatory peritoneal dialysis (CAPD), automated peritoneal dialysis (APD) and multiple dialysis modalities in a year (Mix group)) and 2 transplant modalities .The total average annual healthcare costs in 2014 ranged from €77,566  for CAPD patients to €105,833  for patients in the Mix group. For all dialysis modalities, the vast majority (72–84%) of costs was RRT related. Patients on haemodialysis ≥4x/week had significantly higher average annual costs compared to those dialyzing 3x/week . Costs for kidney transplant recipients were €85,127  in the year of transplantation and rapidly declined in the first and second year after successful transplantation  and €15,018 ). Transplantation with a deceased donor kidney resulted in higher costs ) in the year of transplantation compared to a living donor kidney transplantation .CAPD patients have the lowest costs compared to other dialysis modalities. Costs in the year of transplantation are 25% lower for patients with kidneys from living vs. deceased donor. After successful transplantation, annual costs decline substantially to a level that is approximately 14–19% of annual dialysis costs. In tpatients . Althougpatients . This imRRT has always served as a classical example of lifesaving treatment with very high per person costs and this essentially has not changed over the past decennia. However, comprehensive cost estimates of RRT in the Netherlands are based on a study from the 1990’s. More reSeveral European studies have recently used health insurance claims to investigate national healthcare expenditures related to RRT –12. DutcThe aim of this study is to provide detailed estimates of the average annual costs per patient for seven RRT modalities. Besides distinguishing between dialysis therapies, we also include transplantation costs by source of kidney donor, living or deceased, and haemodialysis (HD) costs by frequency of dialysis.In the Netherlands healthcare insurance is obligatory; almost all citizens have a healthcare insurance . Vektis From all adults (≥19 years) in the Vektis claims database who had at least one health insurance claim related to RRT we included those patients on chronic RRT and excluded those with incidental use  or unjustified (erroneous) claims. Dialysis patients were selected using health claims in the year 2014 and kidney transplant patients were identified using claims in the period January 1, 2012 to December 31, 2014. We differentiated 7 RRT modalities: (1) in-centre haemodialysis (CHD), (2) home haemodialysis (HHD), (3) continuous ambulatory peritoneal dialysis (CAPD), (4) automated peritoneal dialysis (APD), (5) multiple dialysis modalities within a year (Mix), (6) living kidney donor transplant recipients and (7) deceased kidney donor transplant recipients . After cWe estimated healthcare costs by using registered health claims (reimbursement data). Costs were distinguished according to different healthcare components. First, costs directly related to RRT, based on diagnosis-related group codes (DRG’s), were identified and included all costs of the dialysis procedure , the kidney transplant (including donor expenses) as well as the pre- and post-transplant care. More specifically, RRT related costs include all medications used during dialysis , staff costs, including physician fees, laboratory assessments and other diagnostics as included in RRT clinical guidelines (e.g. chest X-ray). Also, equipment and devices needed, e.g. dialysis machines for home dialysis, is included here. Finally, overhead costs, e.g. for water and energy are included. Second, non-RRT costs were defined as all remaining in- and outpatient DRG costs not directly related to RRT, such as primary care, mental healthcare, medication, medical devices, transportation, healthcare costs incurred abroad and other healthcare costs. These non-RRT costs may incur dialysis related costs as well, e.g. transportation costs to and from the dialysis center, but these costs cannot be attributed with 100% certainty to RRT.Cost data are provided as annual costs, averaged over all patients in a specific modality group. To provide meaningful cost estimates for patients that are not a full year on RRT, e.g. incident and deceased patients, we calculated average 4-week healthcare costs for these patient subgroups.th of July 2019) and converted to the year 2014 according to the Dutch Consumer Price Index  [Descriptive statistics  are presented per treatment modality. The presence of comorbidities was based on medication see . Healthc: 1.010) . All anaOverall, 7,827 persons could reliably be attributed to one of seven RRT modalities in 2014 . Of thesA reliable dialysis frequency pattern could be established for 3412 out of 3604 FYD haemodialysis patients . Only 8%of transplantation are high  and comparable to annual healthcare costs of dialysis patients  1,554 patients received a kidney transplant from a living kidney donor and 1,275 patients obtained a kidney from a deceased person . RRT relOur study using health insurance claims showed high expenses for all dialysis modalities, with annual expenditure ranging between €77,566 for CAPD to €92,616 for CHD and €105,833 for patients of the Mix group. The vast majority of total health care expenses was related to RRT. Patients who dialyzed more frequently had higher overall expenditure because higher RRT related costs were not compensated by lower non-RRT related costs. In the year of kidney transplantation, patients had expenses similar to those on dialysis, but expenses declined steadily in the years post-transplant to €15,018 in the second year for those with a surviving graft after transplantation. Our study found substantial higher expenditure for those who received a kidney from a deceased donor compared to a living donor.The fact that dialysis treatment is expensive confirms findings of both older  and moreExpenses for patients of the Mixed group were remarkably higher in many categories of healthcare use, such as access procedures and medication. In particular, non-RRT related hospital care expenditure in this group was higher than in patients stable on one dialysis modality. This suggests that the switch between dialysis modalities may not only be rooted in therapy failure itself, but also in the occurrence of other diseases that prevent continuation of the initial modality and that are associated with higher non-RRT costs in itself. Indeed, a study from the US  showed iOur study shows a clear cost advantage of transplantation using living donor kidneys compared to deceased donor kidneys, despite additional health expenses for the donor. There was a large difference in dialysis costs, i.e. the dialysis costs were higher for the group who received a kidney from a deceased donor. This is likely related to a substantial proportion of living donor kidney procedures being pre-emptive in the Netherlands. Indeed, 33% of patients receiving a graft from a living donor did not receive dialysis at all during the year of transplantation. Other factors possibly related to lower expenses for those who receive a living donor kidney are better survival , 24 and Annual costs decline fast in the first and second year after transplantation, with medication costs being the highest  component of expenses. These figures include those for non-successful transplantation (n = 105), hence for patients with graft failure who had to return to dialysis and patients who died. Combined with the cost advantages of pre-emptive transplantation as discussed above and the ongoing shortage of deceased donor organs, this stresses the importance of discussing and exploring the possibility of a living donor transplantation in pre-dialysis patients. Recently, the Dutch Parliament accepted a change from opting-in for transplantation after death to an opt-out system, that is expected to increase the number of deceased donor transplantations in the future. Given the small cost differences between pre-emptive transplantation and deceased donor transplantation, relative to the large cost-differences between any transplantation and dialysis, every transplantation is expected to contribute to a decrease in costs of RRT.Following from the source of the data, being insurance claims, we have to face several limitations of our data. First, we have no guarantees that all transplantation related costs of living donors were registered on the ID of the recipient, with the possible consequence of underestimating the costs of living donors. Second, the donor costs of deceased donors are not at all part of the claims data, as these are reimbursed outside the basic health insurance. Moreover, societal costs  and out-of-pocket costs were not part of this study, whereas the limited time frame of two post-transplant years prevents us from predicting cost levels of former transplantation patients in later years. However, as annual costs decline fast after transplantation and are lowest in those without graft failure, there is no reason to expect that the cost difference between dialysis and having a functioning transplant kidney will fade out in later years.One general limitation to studying costs in terms of expenditure is that expenditure is only to be seen as an administrative proxy for real costs, implying that it is unknown whether these costs reflect “true” resource use  needed to provide healthcare to these patients. Another important limitation is that we have not related observed differences in expenditure between modalities to differences in patient characteristics, as we only had limited information on background characteristics of patients. A previous study on dialysis patients shows that age is associated with expenditures where elderly dialysis patients often have lower healthcare costs than younger dialysis patients . This knStrengths of our study include the national coverage (>99% of population) of our data, the inclusion of all RRT modalities, the inclusion of all healthcare use covered by the Health Insurance Act and not only the part that is related to RRT, the good validation of the data with another national database of RRT patients, and data coverage over a three-year period. We used a rigorous approach of classifying patients into 1 of 5 dialysis groups and 2 different transplantation groups, and excluded all patients with erroneous or temporary RRT claims, as well as patients for whom we had diverging information, e.g. with regard to the weekly number of dialysis procedures. For the included patients we have high levels of confidence that expenditure figures can be attributed correctly to the dialysis modality. Furthermore, as a consequence of our assignment of patients to different treatment groups, we were able to show a clear picture of cost differences between stable patients using different dialysis modalities. Because we present cost data also for periods of 4-weeks, we could show that incident and deceased patients have much higher non-RRT related costs than patients who are stable on one dialysis modality.Our data stress the fact that CAPD has a clear cost advantage compared to other home-based therapy and CHD. Starting as many patients as possible on CAPD could reduce the high budget impact of RRT to a certain extent. Approximately 1750 patients start dialysis treatment annually in the Netherlands, of whom 20% start PD (CAPD and APD aggregated) . It is cWe conclude that annual healthcare expenditures of RRT patients are high, while showing relevant differences between dialysis modalities at the same time. Frequent haemodialysis patients have higher RRT related expenditure compared to patients with regular dialysis frequency with similar non-RRT costs. Dialysis patients of the Mix group have the highest annual expenditure, in particular in the RRT unrelated costs. Annual healthcare costs in the year of transplantation are high, but decline fast in the years after transplantation. Living donor kidney transplantation incurs lower costs compared to transplantation with a deceased donor kidney. Therefore, our results indicate that the current practice in the Netherlands, where (pre-emptive) living donor procedures are actively encouraged by nephrologists, is associated with cost advantages in both the short and longer term. At the same time, budget impact of RRT could be diminished to a certain extent when more patients would start treatment with home-based therapies, especially CAPD.S1 File(DOCX)Click here for additional data file.S2 File(DOCX)Click here for additional data file.S3 File(DOCX)Click here for additional data file.S4 File(DOCX)Click here for additional data file.