Innate antiviral immune responses are driven by virus-induced changes in host gene expression. While much research on antiviral effectors has focused on virus-inducible mRNAs, recent genome-wide analyses have identified hundreds of novel target sites for virus-inducible transcription factors and RNA polymerase. These sites are beyond the known antiviral gene repertoire and their contribution to innate immune responses is largely unknown. In this study, RNA-sequencing of mock-infected and Sendai virus-infected cells was performed to characterize the virus-inducible transcriptome and identify novel virus-inducible RNAs (nviRNAs). Virus-inducible transcription was observed throughout the genome resulting in expression of 1755 previously RefSeq-annotated RNAs and 1545 nviRNAs. The previously-annotated RNAs primarily consist of protein-coding mRNAs, including several well-known antiviral mRNAs that had low sequence conservation but were highly virus-inducible. The previously-unannotated nviRNAs were mostly noncoding RNAs with poor sequence conservation. Independent analyses of nviRNAs based on infection with Sendai virus, influenza virus, and herpes simplex virus 1, or direct stimulation with IFNα revealed a range of expression patterns in various human cell lines. These phylogenetic and expression analyses suggest that many of the nviRNAs share the high inducibility and low sequence conservation characteristic of well-known primary antiviral effectors and may represent dynamically evolving antiviral factors. Induction of the immune response depends on recognition of viral components by host pattern recognition receptors. Though RNA- and DNA-genome viruses are detected by distinct pattern recognition receptors4, the cellular response to most virus infections culminates in the activation of master transcription factors IRF3 and NF-κB.Virus infection of human cells initiates host cell signaling cascades that result in widespread changes in gene expression. Collectively, these changes produce robust antiviral responses that form the basis of innate and adaptive immunity5, including several types of interferon (IFN), antiviral cytokines that are secreted from the infected cells6. Type I IFN includes the single IFNβ, as well as a number IFNα subtypes that all bind to a common IFNα/β receptor6; Type II IFN includes the single IFNγ that binds to the distinct IFNγ receptor6; Type III IFN includes IFNλ members, also known as IL-28 and IL-29, that bind to a distinct IFNλ receptor7. These receptors activate downstream JAK-STAT signaling9 and the expression of hundreds of effectors, known as interferon stimulated genes (ISGs)12.The most widely studied virus-induced RNAs encode effector proteins that mediate virus interference and signal amplification17. Noncoding RNAs are also increasingly being linked to the cellular response to viruses. For example, BISPR is an IFNα-induced long noncoding RNA (lncRNA) that regulates the expression of tetherin, a cellular antiviral factor that blocks viral release19. NEAT1 is a virus-induced lncRNA that regulates the expression of antiviral genes such as IL-820. In the case of lncRNA-ACOD1, expression promotes rather than interferes with virus replication by regulating cellular metabolism21. These examples underscore the importance of deep sequencing approaches to characterize the extent of noncoding RNA transcription following virus infections.The rise in genome-wide sequencing studies has revealed many previously unrecognized RNA species including noncoding RNAs with diverse roles in cellular processes such as gene expression, post-transcriptional regulation, translation, cell cycle regulation, and immune responses22. Many of these binding sites were novel virus-inducible sites in intergenic and intronic regions of the genome, suggesting the existence of novel virus-inducible RNAs22. The identification of these novel binding sites along with the recent increase in identification of individual novel RNAs with functions related to regulation of virus infection motivated genome-wide examination of virus-inducible RNAs. In this study, novel RNA-encoding loci were identified throughout the genome, but unlike most annotated RNAs, they were primarily expressed from intergenic regions. Analysis of newly-identified virus-induced RNAs, referred to here as nviRNAs22, reveals that they can be induced by RNA and DNA-genome viruses as well as by direct stimulation with the type I IFN, IFNα, in both general and cell-specific fashion. These findings expand the extent of virus-induced transcription and suggest that both coding and noncoding RNA expression are hallmarks of the cellular response to virus infections.Our previous study in human cells showed that early responses to RNA-genome virus infections initiate genome-wide binding of IRF3 and NF-κB to diverse loci to recruit and activate RNA polymerase II, assemble transcriptional machinery, and induce transcription22. Mock-infected cells and cells infected with 5 plaque forming units (pfu) of Sendai virus per cell for 6 hours were subjected to paired-end RNA sequencing. Approximately 200 million reads of 100 bp read length were obtained for each sample. On an average, 90% of total reads mapped to the human reference genome (GRCh37/hg19).To fully appreciate the extent of virus-induced RNA transcription, human Namalwa B cells were infected with Sendai virus, an RNA virus that is a potent inducer of antiviral signalingEnrichment of RNAs in mock-infected or virus-infected samples was analysed with the DESeq2 program, resulting in the identification of 6210 RNAs that were differentially expressed after virus infection at a false discovery rate (FDR) of 5% and fold change of at least 1.5. Among these RNAs 3300 were induced by virus infection, while 2910 were suppressed. The expression changes of representative groups of these RNAs were confirmed in independent samples by RT-qPCR using primers specific for virus-induced previously-annotated genes Fig.  and prevThe magnitude of differential expression was much less for the suppressed RNAs compared to the RNAs induced by virus infection. The expression of the most suppressed RNA, C10orf71, was suppressed only 50-fold by virus infection while the most induced RNA, IL29, was induced almost 20,000-fold. More than 480 of the virus-induced RNAs are induced by more than 50-fold after virus infection. Due to this discrepancy in range of expression change, further emphasis was placed on analysing the virus-induced RNAs.23. The most highly induced of these annotated RNAs , type III IFNs7 , chemokines24 (CXCL10 and CXCL11), the antiviral mediator, OASL25, and the antiviral E3 ligase, HERC527. In addition, 115 of the 389 previously identified type I ISGs compiled in a recent study28 were found to be induced by at least 1.5 fold.Of the 3300 virus-induced RNAs, 1755 have an existing RefSeq annotation30, a functional annotation tool that determines statistically significant gene enrichment in biological processes from a given gene list. The previously-annotated virus-induced RNAs mapped to 1608 DAVID gene IDs and were significantly enriched in more than 400 Gene Ontology (GO) biological processes and 40 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.To further characterize these induced RNAs, cellular pathways induced by virus infection were identified using DAVID Bioinformatics ResourcesAs expected, the top 10 most enriched GO processes describe cellular functions that enable the cell to respond to virus infection, including type I IFN and cytokine signaling Fig. . The topTo better understand the extent of biological processes that are induced after virus infection, clustering analysis was carried out on all enriched GO biological process terms. The enriched GO biological processes formed 27 clusters with an enrichment score above 3, indicating that a majority of the processes within the cluster were statistically significant (Supplementary Table 22.Among the 3300 virus-induced RNAs there were 1755 previously RefSeq-annotated RNAs and 1545 novel virus-inducible RNAs (nviRNAs) that were not previously RefSeq-annotated. The previously-annotated RNAs and the identified nviRNAs were found to be widely distributed among all the chromosomes Fig. , but the31. Analysis of previously characterized RNAs has shown that known noncoding RNAs generally score below 50 while protein-coding genes score above 5033.To compare the protein coding potential of the virus-induced RNAs, a PhyloCSF score was calculated for each RNA. PhyloCSF is a method that uses a multi-species sequence alignment to calculate a score reflecting the likelihood that an open reading frame (ORF) encodes a proteinThere were 10 previously-annotated RNAs and 20 nviRNAs that did not have an ORF and were excluded from this analysis. The remaining 3270 RNAs were analysed and plotted in Fig. Though the nviRNAs are mostly noncoding RNAs, they may nevertheless have important functions in the antiviral system. Sequence conservation among vertebrates is frequently used to determine functional capacity of RNAs. However, many immune genes have undergone positive, diversifying selection and are therefore poorly conserved. Lower sequence conservation in virus-inducible genes may be indicative of an important antiviral role.34. To determine average sequence conservation across vertebrates, the mean PhastCons score for each RNA was calculated. Overall, the previously-annotated RNAs had much higher sequence conservation than the nviRNAs  or influenza A virus (10 hours) or directly treated with IFNα (6 hours). THP-1 cells were also infected with 5 pfu/cell of HSV-1 (10 hours). In 2fTGH cells, transfection of the synthetic dsRNA, poly(I:C), an IFN activator that can robustly induce the expression of IFNs and ISGs, was included as a stimulus. The known virus-induced genes IFNβlls Fig.  and THP-lls Fig.  by variolls Fig.  and THP-lls Fig. . In 2fTGlls Fig. . Expresslls Fig. , with HSlls Fig.  and THP-lls Fig.  by 10 hoThe expression level and induction of each nviRNA varied greatly depending on the inducing stimulus, likely due to differences in the activation kinetics or intensity of each stimulus. Of the 12 nviRNAs expressed in both 2fTGH cells and THP-1 cells, 10 nviRNAs were also expressed in the epithelial HeLa and A549 cells Tables . The expIn this study, RNA-sequencing of Namalwa cells mock-infected or infected with Sendai virus identified 1755 previously RefSeq-annotated RNAs and 1545 novel virus-inducible RNAs (nviRNAs). Analysis of these virus-inducible RNAs revealed insights into the previously unrecognized depth and breadth of the virus-inducible transcriptome, and identified nviRNAs as possible targets of positive selection in the cellular response to viruses.22. Based on the RNA polymerase II binding sites, 1450 nviRNAs were predicted to be expressed22. Using the same cell line and virus for infection, 501 of these predicted nviRNAs were partially matched to RNAs identified in RNA-sequencing analysis. Factors that may contribute to this apparent disparity include timing, abundance and methodology. Furthermore, most of these RNAs were excluded from further analysis due to their low expression levels. Nevertheless, since many noncoding RNAs have low expression levels37, the subset of functional nviRNAs may extend past the 1545 nviRNAs analysed in this study.This study was motivated in part by the identification of novel virus-inducible binding sites for the antiviral transcription factors IRF3 and NF-κB, and RNA polymerase IIThough both previously-annotated RNAs and nviRNAs were distributed similarly across the chromosomes Fig. , there wThe protein coding potential and functionality of the virus-inducible RNAs was assessed using PhyloCSF and PhastCons respectively. A majority of the previously RefSeq-annotated RNAs were identified as protein coding mRNAs, while very few of the nviRNAs were found likely to encode a protein Fig. . The mea39. Virus evolution to overcome host antiviral immunity creates a potent selective force for diversification of key antiviral effectors. The cyclical virus-host interplay has resulted in immune genes being among the more recently evolved and more diversified genes in the human genome40. The poor sequence conservation of the highly induced nviRNAs may indicate that they are previously unidentified antiviral factors that evolved under positive selection.While most genes have undergone negative selection to be conserved through evolution, many immune genes have been positively selected for diversityIn further support of this concept of nviRNA functionality, expression of a subset of nviRNAs was analysed and found to be induced, albeit variably, by different RNA and DNA viruses, and antiviral stimulation with poly(I:C) and IFNα. Differences in both expression and temporal regulation were observed among the nviRNAs tested due to specific virus or treatment, as well as in the cellular host cell line. It is reasonable to speculate that at least some of the nviRNAs, particularly the 10 expressed in 5 different cell lines tested Fig. , could rThis study focused on identifying nviRNAs with potential functions in the cellular response to viruses; however, it is worthwhile to also examine potential novel antiviral factors among the previously RefSeq-annotated RNAs. Many of these RNAs encode known antiviral genes that are enriched in critical antiviral biological processes, but not all of the annotated RNAs have been assigned an antiviral function. Of the 1755 previously-annotated virus-induced RNAs, 328 were not assigned to any GO biological process, indicating that they are poorly characterized functionally. Additionally, there are many RNAs that despite being assigned a GO biological process, were not previously identified as virus-inducible RNAs. Combining these previously-annotated, virus-inducible RNAs with the nviRNAs identifies a large pool of potential antiviral responders that could have untapped value as antiviral diagnostic or therapeutic tools.Namalwa B cells (ATCC CRL-1432) and THP-1 cells (ATCC TIB-202) were cultured in RPMI 1640 Medium . HeLa cells (ATCC CCL-2), A549 cells (ATCC CCL-185) and 2fTGH cells (ECACC 12021508) were cultured in Dulbeco’s Modified Eagle Medium . For all cell lines medium was supplemented with 10% Cosmic calf serum  and 1% Penicillin-Streptomycin . Sendai virus (Cantell strain) was grown in embryonated chicken eggs, and titers were determined on Vero cells. The A/Udorn/72 strain of influenza virus  was propagated and titer was determined on MDCK cells. HSV-1 (F strain)  was propagated and titer was determined on Vero cells. Cells were infected at a multiplicity of infection (MOI) of 5 for indicated times. Virus infections were performed in serum-free medium (SFM), with 1% bovine serum albumin (BSA) supplemented for influenza virus. At 1 hour post-infection, the inoculation medium was replaced with medium containing 2% serum for the remainder of the infection. For poly(I:C) transfection, 2.5 μg/mL of low and high molecular weight poly(I:C) (Invivogen) was transfected for 6 hours using the Lipofectamine 2000  transfection reagent. For direct treatment with IFNα, cells were treated with 1000 U/mL recombinant IFNα (Roche).Total RNA was extracted using the TRIzol Reagent  and treated with DNAse I . The RNA quantity was obtained using NanoDrop 2000 (Thermo Fisher Scientific). For RNA used in RNA sequencing, the integrity was examined by the Bioanalyser 2100 system (Agilent Technologies) to obtain RNA Integrity Number (RIN) of over 9.41 using TopHat42 (2.0.10). The mapped reads for each sample were independently assembled into annotated and novel transcripts using the Cufflinks43 (2.1.1) suite of programs.Duplicate samples of mock-infected and Sendai virus-infected cells for 6 hours were used to prepare RNA libraries for sequencing on Illumina HiSeq2000 platform (Illumina) to generate 100 bp paired-end sequencing reads. Raw data was filtered to remove adapter sequences and low-quality reads. The remaining rRNA reads were removed by mapping to known human rRNA sequences. The clean, high-quality data was mapped to the human reference genome (GRCh37.p10/hg19)44 (0.6.0) for each sample and analysed by the DESeq245 (1.2.10) program. Significance was calculated using the Wald test and a Benjamini-Hochberg False Discovery Rate cut-off of 5% was used to assess statistically significantly differential expression. The lowest quartile of RNAs based on expression were excluded from further analysis. RefSeq genomic feature distribution information for coding exons, introns, 3′ and 5′ untranslated regions (UTRs), promoters (−1kb), and transcription termination sites (+1 kb) was downloaded from the UCSC genome browser (http://genome.ucsc.edu/)23 and analysed using the BEDtools program46. The online functional annotation tool, DAVID30 (6.8), was used to conduct gene enrichment analysis. A list of gene symbols corresponding to differentially expressed RNAs was mapped to DAVID gene IDs to determine which Gene Ontology biological processes and KEGG pathways were enriched. A Benjamini-Hochberg False Discovery Rate cut-off of 5% was used to assess statistical significance. Clustering analysis of enriched GO biological processes was done using DAVID’s heuristic fuzzy multiple-linkage partitioning method47. An enrichment score cut-off of 3 was used to determine significance. Base-by-base PhastCons34 conservation score across 100 vertebrates were downloaded from the UCSC Genome Browser. For each RNA a mean score was calculated if there was a score available for at least 80% of the bases in the sequence. The PhyloCSF31 software was locally installed and used to determine the coding potential of the longest start-to-stop open reading frame in each RNA. The multiple-species alignments needed for this analysis were prepared on Galaxy web platform at usegalaxy.org48.To determine differential expression between mock-infected and Sendai virus-infected samples, read counts for each RNA were generated by HTSeq−∆CT method or fold change over mock by the 2−∆∆CT method49. Primers are listed in Supplementary Table Purified total RNA was random primed and reverse transcribed using SuperScript III Reverse Transcriptase . Gene expression was measured by quantitative real-time PCR (qPCR) and normalized to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) to determine relative abundance by the 2Supplementary FiguresSupplementary Tables


Chordopoxvirinae. Future research is needed to determine whether this virus could affect human health.Northern pygmy mice from 2 localities in East Central Texas, USA, had proliferative epidermal lesions on the tail and feet. Electron microscopy of lesion tissue revealed poxvirus. Phylogenetic analyses indicated the virus differed 35% from its closest relatives, the  Chordopoxvirinae is a diverse subfamily of viruses within Poxviridae. These geographically widespread viruses infect birds, reptiles, and mammals, and many are zoonotic (Baiomys taylori) found at 2 localities in east central Texas, USA, and further characterize the virus through genetic analysis.B. taylori mouse (mouse 1) at the Attwater Prairie Chicken National Wildlife Refuge in Colorado County, Texas. The mouse had large (4–8-mm diameter) proliferative lesions on the hind feet and tail (B. taylori mouse (mouse 2) with mild 1–2-mm proliferative lesions on the left hind foot and tail. Both animals were euthanized in accordance with Texas Parks and Wildlife Department scientific collections permit (SPR-0512-917) and Texas A&M University Institutional Animal Care and Use Committee’s animal use protocol (2015-0088). These 2 B. taylori specimens are housed at Biodiversity Research and Teaching Collections .In August 2014, we captured a severely affected adult male and tail , panel AWe subjected mouse 1 to a full necropsy and found the mouse to be in good body condition. Extending from the skin of the dorsal aspect of the left hind foot, plantar aspect of the right hind foot, and the dorsal tail were several firm, pedunculated, irregular masses 0.4–0.8 cm in diameter , panel A<50 μm in diameter. The dermis and stratum basale were infiltrated by lymphocytes, plasma cells, and macrophages and a large number of viable and degenerate neutrophils. We examined sections of the spleen, liver, lungs, heart, kidneys, and intestines and identified no substantial lesions. A viral etiology was suspected, so formalin-fixed paraffin-embedded sections of the mass were processed for transmission electron microscopy. Ultra-thin sections were examined with a Morgagni 268 transmission electron microscope  at an accelerating voltage of 80 kV. Cytoplasmic inclusions contained granular, electron-dense material and numerous brick-shaped virions with dense cores and inner and outer membrane shell consistent with poxvirus , we converted the gene sequences into amino acid sequences for the purpose of alignment to those of 49 other chordopoxviruses (Chordopoxvirinae) and 2 entomopoxviruses (Entomopxvirinae), which were used as outgroup taxa. We then concatenated the gene sequences  and conducted partitioned phylogenetic analyses using Bayesian approaches in MrBayes version 3.2.2 (http://mrbayes.sourceforge.net/download.php). The phylogenetic position of this virus revealed it to be a divergent member of the Chordopoxvirinae , the genetic data strongly suggest this poxvirus does not belong to any recognized genus as of March 2018. We propose the tentative species name Brazospox virus in reference to the proximity of both field sites to the Brazos River.The poxvirus sequenced from a online  Table. A>17 individual rodents of 3 species . The combined distributional range of these 3 host species includes >20 US states and a large portion of Mexico (The epidermal lesions produced by the virus are unique among previously described poxviruses of wild rodents, being proliferative rather than ulcerative in nature, and lacking systemic involvement (Novel poxviruses identified in wildlife populations might be useful for the identification of threats to human and animal health. The description of these new viruses contributes to the study of viral diversity and pathogenesis. Propagation of the Brazospox virus in cell culture for use in infection studies, coupled with expanded field surveillance, examination of museum specimens, and full genome analysis could yield additional clues to the origin, pathogenesis, and potential host range of this novel poxvirus.Taxon information and genetic distances of poxviruses used in phylogenetic analysis of novel Brazospox virus isolate.


Traditionally, cost-benefit analyses (CBAs) focus on the direct costs of animal disease, including animal mortality, morbidity, and associated response costs. However, such approaches often fail to capture the wider, dynamic market impacts that could arise. The duration of these market dislocations could last well after an initial disease outbreak. More generally, current approaches also muddle definitions of indirect costs, confusing debate on the scope of the totalities of disease-induced economic impacts. The aim of this work was to clarify definitions of indirect costs in the context of animal diseases and to apply this definition to a time series methodological framework to estimate the indirect costs of animal disease control strategies, using a foot and mouth disease (FMD) outbreak in Scotland as a case study. Time series analysis is an econometric method for analyzing statistical relationships between data series over time, thus allowing insights into how market dynamics may change following a disease outbreak. First an epidemiological model simulated FMD disease dynamics based on alternative control strategies. Output from the epidemiological model was used to quantify direct costs and applied in a multivariate vector error correction model to quantify the indirect costs of alternative vaccine stock strategies as a result of FMD. Indirect costs were defined as the economic losses incurred in markets after disease freedom is declared. As such, our definition of indirect costs captures the knock-on price and quantity effects in six agricultural markets after a disease outbreak. Our results suggest that controlling a FMD epidemic with vaccination is less costly in direct and indirect costs relative to a no vaccination  strategy, when considering large FMD outbreaks in Scotland. Our research clarifies and provides a framework for estimating indirect costs, which is applicable to both exotic and endemic diseases. Standard accounting CBAs only capture activities in isolation, ignore linkages across sectors, and do not consider price effects. However, our framework not only delineates when indirect costs start, but also captures the wider knock-on price effects between sectors, which are often omitted from CBAs but are necessary to support decision-making in animal disease prevention and control strategies. Animal diseases represent threats to the environment, animal welfare, public health, and the economy. Livestock diseases contribute to losses via increased mortality, reduced productivity, control costs, loss in trade, decreased market value, and food insecurity . The ecoThe economic costs of animal disease can be categorized as either direct or indirect losses.Over the last decade, the direct cost of zoonotic diseases has been estimated at more than $20 billion and indirect losses at over $200 billion to affected economies as a whole . This hiAt the same time, even where indirect costs are considered in the analysis, the definitions of direct and indirect costs of animal disease outbreaks vary in the literature  in markets as a result of changes in prices and quantities for producers and/or consumers, which can also be described as revenue foregone, after disease freedom. Using disease status as a marker, our definition of indirect costs objectively differentiates when direct costs end and indirect costs begin to avoid double counting.A country's animal disease status changes over time. For this reason, we assume direct costs are the sum of losses from the first confirmation of a notifiable disease outbreak until disease freedom is declared . AccordiA range of models are available for assessing the economic cost of livestock diseases . Based oAn alternative and complementary approach to PE and CGE modeling is times series analysis. Time series modeling  is an ecThe culling of animals for disease control reduces their supply, disrupting domestic meat production. Economic theory assumes that the slaughter of animals will lead to a supply shortage affecting producers and consumers by increasing the prices consumers pay for commodities . During The overall aim of this work was to outline the steps necessary to estimate indirect costs, i.e., the economic losses incurred in markets after disease freedom is declared using a time series model. We apply this in the context of a modeled Foot and Mouth Disease (FMD) in Scotland. FMD is considered one of the most economically significant livestock diseases globally due to its impact on production, as a barrier to international trade and high control/stamping out costs . While tWhile FMD is likely to affect international trade and tourism, the data to support such analysis are not available at an appropriate resolution. Hence, our paper focusses on the domestic supply side evaluating indirect costs incurred by producers after a disease outbreak is over as an illustration of the method. The distribution of indirect costs was compared to direct costs on alternative FMD control strategies in Scotland. We assess the potential impact of vaccine stock scenarios on indirect costs on decision outcomes in a future outbreak and so the suitability of time series for contribution to decision support. Vaccine capacity is important , 38 and Our indirect cost methodology was demonstrated in the context of a FMD outbreak in Scotland. The indirect cost modeling framework  for estiFMD is a highly contagious viral disease affecting ruminants, including cows, sheep and pigs. Globally, FMD is estimated to cost endemic countries between $6.5 and $21 billion annually, due to visible production losses and vaccination costs in endemic countries . In addiAnimal health and welfare is a devolved issue in the UK, meaning the Scottish Parliament and Scottish Government have responsibility for the health and welfare of animals in Scotland. FMD is a notifiable disease and control mechanisms include movement bans and restrictions of the marketing of milk and meat products during an outbreak. The principal control method to eradicate FMD, as required under EU and national law, is the slaughter of affected animals  to prevent any further spread of the virus. Vaccination is also an important tool in controlling FMD during an outbreak. However, preventative vaccination is banned under EU law, but the Scottish Government considers emergency vaccination a disease control strategy during an outbreak . The pren = 156 observations) were gathered from various sources for this study  data were not available at an appropriate monthly resolution to determine the indirect cost after disease freedom is declared. Consumer demand was assumed not to be affected because FMD is not a zoonosis and there was not sufficient model power to include retail market data series.A time series model was used to quantify the indirect costs, i.e., the economic losses incurred in markets after disease freedom is declared, in domestic commodity markets associated with an FMD outbreak in Scotland. The steps for selecting the most appropriate time series model are presented in Descriptive statistics and plotting were used to summarize and visualize the characteristics and patterns in the data series, including the presence of seasonal variation. Seasonal adjustments were performed by estimating and removing seasonality from the data to understand underlying trends and movement in the data over time, masked by seasonal variation –57. DataFollowing the methodological framework , data seStationarity is an underlying statistical property of data required for time series analysis. A stationary process is such that the mean, variation, and autocorrelation in the structure of the data do not change over time. A trend in the mean due to the presence of a unit root or deterministic trends are causes that violate the underlying assumption of stationarity.t, is integrated of order 0, or at the level, if Yt ~ I(0) is stationary. Yt is integrated of order 1, denoted by I test tobehavior .I(1)) and a linear combination of these series are integrated of order 0 ). If cointegration is present, this suggests there is an equilibrium relationship in the long-run, although the series may diverge from that equilibrium in the short-run. Johansen's trace test (I(1) time series are cointegrated. The Johannsen's trace test was used because it is robust to skewness and excess kurtosis. In the case that cointegration is present a vector error correction model is selected, which models both short and long-run relationships jointly in multiple data series. In cases where no cointegration is detected alternative models, such as autoregressive and autoregressive distributed lag models, are appropriate . As a rICs, of alternative vaccination strategies, S, and six domestic commodity markets , i, were estimated. The indirect costs are associated with price and quantity changes, i.e., change in revenue or revenue foregone, in each market, i, as a result of a supply shock of animals culled, j, after disease freedom is declared:The indirect costs, i denotes commodity markets for beef, pork, lamb, chicken, milk, and feed wheat, and j represents cattle, pig and sheep culled. Pi and Qi are the price and quantity in the ith commodity market, respectively. t denotes the period before the outbreak and d is the period after disease freedom is declared until the supply shock dissipates. To quantify the total indirect costs across the six markets, the change in revenue is summed across the commodity markets for animals culled for alternative scenarios, S.where ElPi, j is the IRF elasticity of price of the ith market, Pi, with respect to the jth species culled, and the ElQi, j is the IRF elasticity of quantity of the ith market, Qi, with respect to jth species culled. The IRF elasticities, estimated from the time series model, capture proportional changes in the levels of price and quantity changes as a result of animals culled. Finally, the total economic cost is the sum of indirect and direct costs.where The objective of this paper was to demonstrate a method for estimating the indirect costs, i.e., the economic losses incurred in markets after disease freedom is declared, under alternative disease control strategies using time series analysis.I(1)), except QSheep  which is stationary at the level, i.e., I(0), at the 5% level of significance. While a VECM requires all variables to be stationary at I(1), in systems with three or more series a VECM is appropriate providing at least two of the variables are stationary at I(1)  . Therefor = 0) against the alternative that there is at least one cointegrating relationship .The next step was to test for cointegrating relationships between the variables. The Trace statistics  tests thThe trace statistic  indicateI(1) and cointegration. Long-run relationships were estimated using maximum likelihood for a VECM(1) with 12 endogenous data series , one lag , two cointegrating relationships , and a constant deterministic regressor as shown in Allan et al.  was estimated to evaluate short-run dynamics. The correlation of the variance covariance matrix suggests there is little correlation between the coefficients . In whicThe magnitude of indirect, direct, and total costs conducive to large outbreaks is presented in The distribution of indirect costs, i.e., the economic losses incurred in markets after disease freedom is declared, in the baseline and alternative vaccine stock scenarios is presented in Our study confirms controlling an FMD epidemic using vaccination costs less, on average, than under a no vaccination strategy . In our Economic cost frameworks that classify costs as either direct or indirect are often subjective and there lacks a consistent framework to evaluate them, making it difficult to assess the costs of alternative animal disease relative to one another. An economic cost framework should “(1) Be consistent with economic principles; (2) Be derived from and consistent with veterinary control measures; and (3) Include an explicit definition of the economic perspective and the stakeholders included” . Our fraThis paper presents a framework that outlines the necessary steps to estimate indirect costs, i.e., the economic losses incurred in markets after disease freedom is declared, using time series analysis. Using agricultural commodity data, time series models can capture market dynamics and the knock-on price and quantity effects between markets, which are often omitted from traditional farm account-based CBAs and other methods. PE and CGE models have been used to explore the indirect costs of animal disease outbreaks. A drawback of these models is that that they are sometimes based on strong assumptions in the absence of good data, e.g., elasticities, defining the demand and supply relationships in multiple sectors to anticipate the likely economic impact of a supply shock. Often elasticities are taken from the literature or assumed unless estimations are developed directly for the model. By contrast, our econometric approach estimates elasticities directly from data to capture production and price dynamics and equilibrium levels, without the need for relying on the literature or making key assumptions and as such can complement PE or CGE models.PE models can examine a single sector or multiple markets capturing changes in production and prices. An advantage of CGEs over time series models is that they can represent an entire economy. However, a drawback to CGEs is the use of more complex modeling techniques and results that can be difficult to interpret . Our timFMD is not a zoonotic disease i.e., it has no human health or food safety risk. For this reason, the retail response of consumer demand was not considered. However, the FMD outbreak of 2001 had psychological impacts on members of the rural community . IndirecData availability can also restrict the scope of indirect costs estimated when considering time series modeling. UK market data are available but often such data are not disaggregated into UK administrations, such that regionalization cannot be accurately considered. For this reason, access to publically available data at a disaggregation required, i.e., monthly observations for Scotland, at the farmgate can be problematic. Where possible we have used Scottish-specific data in our model, otherwise UK-level farmgate price and quantity data were adjusted to reflect a regionalisation for Scotland. Likewise, net export trade data were only available quarterly for the UK-level, however such an aggregation did not allow for sufficient variation in the data. Hence, indirect costs do not capture the impact of animal disease outbreak on trade flows. If a country affected by a disease outbreak is a large exporter of livestock, a shock in the domestic market will have knock-on effects into international markets, and consequently international prices if there is an export ban .If animal health is considered a public good , better The Scottish Government's animal health and welfare strategy is to prioritize limited resources and to consider cost sharing responsibilities for preventing and controlling disease. Therefore, indirect costs are a concern for policy makers to understand the cost of alternative prevention and control strategies in context of one another given the allocation of limited resources. Governments need to appropriately balance the costs of disease control between industry and the tax payer, ensuring financial support for farmers and value for money for taxpayers. During the 2001 UK FMD outbreak, farmers were compensated £1.4 billion for the slaughter of animals and disposal and clean-up costs. In addition, the epidemic costed £1.3 billion to eradicate and other public sector costs amounted to £0.3 billion. The private sector was not compensated but also experienced losses; agriculture, food supply chain and supporting services lost £0.6 billion, while the outbreak costed tourism and supporting industries between £4.5–5.4 billion . The morThe indirect cost methodology presented in this study is applicable not only to FMD but also other exotic animal diseases. Furthermore, the method is particularly pertinent in light of Brexit, which can be thought of as a “shock” that may alter the UK's livestock disease risk and disrupt markets. It will be important to evaluate the knock-on-indirect effects of alternative Brexit scenarios that are likely to arise from changes to trade rules and access to pharmaceuticals. New trading arrangements may affect the import and export of livestock products and also the movement of animals which may alter the UK's disease risk and interrupt the supply chain. In the context of changing trade relationships with global trading partners under Brexit, understanding indirect costs will become even more important. The UK is a net importer of agri-food production from the EU, which could have implications for EU farming and food sectors . The antIn conclusion, this paper has presented a framework for defining and estimating the indirect costs, i.e., the economic losses incurred in markets after disease freedom is declared, of an animal disease outbreak. The time series model identified was a VECM, a useful tool for capturing knock-on market dynamics following a disease freedom/outbreak. Overall, in terms of indirect costs it is more beneficial to vaccinate compared to a “cull only” FMD control strategy. Our findings suggest indirect costs vary with the size of the initial vaccine stock and are less variable when vaccination is used instead of culling. The estimation of indirect costs contributes to the overall economic assessment of the costs of an animal disease outbreak, which is often overlooked but is necessary in support of decision-making. In future, constraints on data and analytical frameworks that otherwise limit the estimation of indirect costs should be addressed. The framework presented can be applied to other animal disease scenarios to more consistently evaluate indirect costs. It is important that indirect costs are not overlooked because their estimation is necessary for a more complete picture of the costs of animal disease outbreaks across case studies to better prioritize limited resources and inform cost sharing. Our indirect cost modeling framework can be adapted to model how changes in the political economy, such as Brexit, might impact the cost of animal disease outbreaks in the future.AS developed the initial concept with GG, Dr. Habtu Weldegebriel, and TP, with further refinement from AB and KR. AB gathered data, developed the indirect cost model with KR and JE and carried out the modeling. AB drafted the paper, and KR, JE, AS, TP, and GG also contributed to the manuscript. GG and AS secured funding and led the project. All authors gave final approval for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor is currently editing and co-organizing a Research Topic with one of the authors GG, and confirms the absence of any other collaboration.


The mechanism of anomalous ice crystallization during rewarming is still unclear. The objective of this study is to observe the ice grains that form in Sephadex® beads and to comprehend their frozen state with a focus on the ice crystallization during rewarming. Sephadex® beads containing 50 wt % water were prepared and used for the measurements. The observation of the ice grains was carried out by using synchrotron radiation-sourced X-ray CT (computed tomography). XRD (X-ray diffraction) analysis was also conducted to investigate the frozen state. As a result, ice grains that were larger than ~1 μm were hardly observed after the slow cooling of Sephadex® beads, except in the G25 beads. However, at the occurrence of ice crystallization during rewarming, ice grains that were larger than 10 μm appeared in the G25 beads. Using XRD, it was found that small incomplete ice crystals were formed in G25 beads and the presence of glassy water was indicated in the gel. In conclusion, the size and distribution of ice grains that formed in Sephadex® beads were different depending on the density of the crosslinks.Water in Sephadex Biological systems often take a gelled state. Understanding the frozen state of gels  is of practical importance for the implementation of cryopreservation. Water in gels is compartmentalized by the polymer network ,2, and t® (crosslinked dextran) gels has been investigated mainly by DSC  [® G25 gel, the water remains partially unfrozen during cooling and the ice crystallizes during the subsequent warming (rewarming), as indicated by DSC. A conceivable scheme of ice crystallization during rewarming is described as follows. Some part of the water in the gel is trapped by the polymer network at the time of freezing initiation when it is cooled, followed by a change in the polymer network that turns it into a glassy state. The glassy water crystallizes during the rewarming, caused by the partial melting of the ice that was previously separated [® gels with crosslinks of both higher and lower densities than that of G25, an anomalous freezing behavior during rewarming was not observed, and the larger ice crystals were considered to have formed, which was also indicated by the two-dimensional XRD study [In this connection, the freezing behavior of Sephadexrimetry) ,2 and byrimetry) . Stemmineparated ,7. The peparated . In SephRD study .Tg) of hyper-quenched liquid water is known to be around 136 K (−137 °C) [Tg of water in a G25 gel (assumed to be around −50 °C) is too high. The Tg of the water in the G25 gel was estimated from the temperature where the liquid water disappears in the ESR (Electron Spin Resonance) spectra obtained by using a spin probe method. The water in the G25 gel is partially trapped by the polymer network and turns into a glassy state at the time of freezing initiation, presumably as a consequence of the close interaction with the hydroxy groups located at the surface of the dextran network structures via the hydrogen bonds. The high Tg value of the water in the gel can thus be explained. In fact, the Tg of bulk water confined in MCM-41 nanopores was suggested to be 210 K [As the glass transition temperature (−137 °C) , the Tg ® G25 gel is characteristic of non-equilibrium freezing after substantial supercooling, and it is not observed after equilibrium freezing [Cp), the isothermal compressibility, and so forth have indicated a divergence at around −45 °C, the behavior of said divergence is a matter of concern [The occurrence of ice crystallization during rewarming observed with Sephadexfreezing . In thisfreezing . Althoug concern ,12 and i concern —have alsIce crystals exist in aggregates as ice grains, and small ice grains are formed as a consequence of the formation of small ice crystals. Then, the sizes of the ice grains observed reflect the sizes of ice crystals that are formed. Although it might be true that the size of ice crystals (and therefore the ice grains formed) are different depending on the density of the crosslinks or on the polymer network structure, the information obtained by the diffraction pattern of the two-dimensional XRD is unsatisfactory, as there is no information on the distribution of the ice grains in the gels. The direct observation of ice grains at a high resolution is desirable for the understanding of the frozen state. The observation of the beads by SEM (scanning electron microscope) after freeze-drying is possible. However, there is concern that the technique will lead to changes in the polymer network during the freeze-drying treatment.® gel beads was conducted by the X-ray CT (computed tomography) imaging technique. Recently, the X-ray CT technique has been improved, making it possible to acquire three-dimensional images of the microstructure of foods or biological systems [® beads was conducted at SPring-8, a synchrotron radiation facility in Japan. The detection of ice grains in the micrometer range by using a beam line in the facility was anticipated. The observation of the freeze-dried Sephadex® beads by SEM was also conducted for comparison.In the present study, the in situ observation of the ice grains formed in Sephadex systems ,15. The To understand the frozen state of gels, it is necessary to obtain information about the ordered structure of the polymer network forming the gel as well as the size of the ice grains that are smaller than a micrometer. For that purpose, synchrotron radiation-sourced SAXS  measurements were also carried out at SPring-8. For the analysis of the completeness of ice crystals determining the shape of the ice grains, WAXD (wide-angle X-ray diffraction) measurements were carried out together with SAXS measurements in the XRD study. As the XRD study deals with the structure of dimensions that are smaller than the beads, the term “gel” was used for the XRD experiment instead of “beads.”® beads with different crosslink densities, as well as to comprehend the frozen state, especially that of the G25 gel, that leads to ice crystallization during rewarming.The objective of the present study was to analyze the shape and distribution of the ice grains formed in the Sephadex® beads after rapid cooling are shown in Typical X-ray CT images obtained with SephadexIn the case of G10 beads, ice due to unabsorbed water was seen around the beads. Slits observed dark in some beads were due to the cracks formed during freezing. However, spots due to the ice grains were not identified in the internal region of G10 beads, indicating that ice grains smaller than ~1 μm were formed in the beads. In the internal region of G25 and G50 beads, the ice grains were not identified either. Several fragments of the beads observed in the image of G25 beads were probably made by breakage during the sample packing into the capillary.Typical X-ray CT images obtained with the beads after slow cooling are shown in ® beads, there was a difference in the appearance of the surface as well as in the degree of the connection between adjacent beads. G10 beads were isolated from each other. On the other hand, adjacent G50 beads were ready to stick together. The degree of stickiness of G25 beads resided between G10 and G50 beads. Large spots observed on the margin of G10 beads were probably due to the ice grains. With G25 beads, large spots were also observed on the margin of the beads. However, no large ice grains were observed on the margin of G50 beads. Among the three kinds of SephadexThe dark spots of 3‒5 μm in diameter observed in the internal region of G25 beads were due to the ice grains, though they are not very abundant. With G10 and G50 beads, spots due to the ice grains larger than ~1 μm were not identified in the internal region.X-ray CT images obtained with refrozen G25 beads re-cooled from −9 °C  are shown in ® beads observed by SEM after freeze-drying are shown in ® beads used.Sephadex® gels. On the other hand, in the WAXD measurement, Bragg peaks due to the hexagonal ice observed at around 0.155‒0.175 for the scattering vector q (10 × nm−1) indicated the different temperature dependence among the three Sephadex® gels, G15, G25, and G100, as shown in The SAXS measurement was carried out to obtain information about the structure of the polymer network or the size of the ice grains smaller than the micrometer order. However, characteristics dependent on the density of crosslinks were not confirmed with the frozen SephadexBragg peaks of a frozen G25 gel observed at −40 °C showed a remarkable tailing suggesting the formation of small incomplete ice crystals or the presence of glassy water. With the increase in temperature, the peaks became narrow at temperatures between −20 and −15 °C, where an ice crystallization exotherm during rewarming was initiated in the DSC trace. The narrowing trend continued to −5 °C and the peaks disappeared at temperatures between −5 and 0 °C, where ice melted. Bragg peaks observed with a frozen G25 gel depending on the freezing condition are shown in Bragg peaks of a frozen G15 gel observed at −40 °C also showed a slight tailing , which w® beads was made possible with a spatial resolution of ~1 μm. As a result, it is necessary to change the interpretation of the size and distribution of the ice grains formed in the beads that was held previously.By the present study of X-ray CT measurement using synchrotron radiation, the in situ observation of the ice grains in Sephadex® beads was estimated to be frozen during slow cooling [By the previous study of the two-dimensional XRD measurement, it was interpreted that ice crystals of larger size were formed in a G10 gel compared to those in G25 and G100 gels, as many clear spots were observed on the three concentric rings due to the diffractions by hexagonal ice in the image . MoreoveIn the internal region of G25 beads, a small number of ice grains of 3‒5 μm in diameter were observed after slow cooling. Although the ice grains were observed in G25 beads, most of the ice grains that formed in the rest of the beads were smaller than ~1 μm, as they were not visible in the image. This is consistent with the results obtained from the two-dimensional XRD study where the powder diffraction pattern was observed . In the There were no surface-treated layers observed in G50 beads. Instead, G50 beads containing 50 wt % water were ready to stick together, probably by means of the tangling bonds of the polymer chains existing on the bead surface. In this connection, G100 beads with lower crosslink densities than G50 beads became too sticky, losing the bead structure when they were added with water , making From the results of the WAXD measurement, the formation of small incomplete ice crystals in a G25 gel was indicated, as Bragg peaks showed a remarkable tailing. The result is consistent with that of the two-dimensional XRD study where continuous but dim images due to the diffractions by powder crystals was obtained for hexagonal ice. Moreover, the presence of glassy water in a frozen G25 gel was indicated, though not decisive . A sligh® gels depending on the density of the crosslinks was made clearer by the experiments of a synchrotron radiation-sourced X-ray CT and an XRD. However, the frozen state of the gels of submicron order remains unclarified. More precise SAXS measurements are necessary. Concerning ice crystallization during rewarming, the presence of glassy water in a G25 gel is still unconfirmed. Detection of the glass transition in the frozen gel is desirable for this clarification [It is certain that the frozen state of the Sephadexfication .® gels containing 50 wt % water was analyzed by using a synchrotron radiation-sourced X-ray CT and XRD.The frozen state of Sephadex® beads were observed with a spatial resolution of ~1 μm. As a result, ice grains larger than ~1 μm were hardly observed in the beads after slow cooling, independent of the crosslink density. In G25 beads, a small number of ice grains of 3‒5 μm in diameter were observed after slow cooling, but most of the ice grains formed in the beads were smaller than ~1 μm. Ice grains larger than 10 μm in diameter were successfully observed in the refrozen G25 beads re-cooled from the temperature of the completion of ice crystallization during rewarming. These results obtained by the X-ray CT measurement were consistent with those previously obtained by two-dimensional XRD measurement. By X-ray CT, the ice grains in SephadexThe results obtained by XRD—especially by WAXD—corresponded well with those obtained by X-ray CT. The observation of a remarkable tailing in Bragg peaks due to the diffraction by hexagonal ice indicated the formation of small incomplete ice crystals or the presence of glassy water in a G25 gel. With the refrozen G25 gel re-cooled from the temperature of the completion of ice crystallization during rewarming, the tailing in Bragg peaks disappeared, which indicated the formation of large and stable ice crystals, as were observed by X-ray CT.® beads were found to depend on the crosslink density.Finally, the size and distribution of the ice grains formed in Sephadex® beads with different crosslink densities  were obtained from GE Healthcare UK Ltd. . The size of the beads’ diameter was 40–120 μm for G10, G15, and G100 and 50‒150 μm for G25 and G50, and the order of the density of the crosslinks is G10 > G15 > G25 > G50 > G100. The exclusion limits in Mw/Da reported are 700, 1500, 5000, 30,000, and 100,000, and the amounts of water absorption in the swollen state (mL g−1DM) are 1.0, 1.5. 2.5, 5.0, and 10.0 for G10, G15, G25, G50, and G100, respectively [Sephadexectively . In the ® G10, G25, and G50 were used in this experiment. G100 beads became too sticky, losing their bead structure when they were added with water, making it difficult to prepare G100 bead samples in quartz capillaries. So, G50 beads were used for the X-ray CT measurement instead of G100 beads as the bead sample with low crosslink densities (see the Discussion section). After having been dried at 60 °C for 20 h, each Sephadex® bead sample containing 50 wt % water was prepared by the addition of distilled water to the dried beads. For the preparation of samples used in the X-ray CT measurement, the beads were densely packed by 2‒3 mm length in a quartz capillary with an outside diameter of 0.7 mm and about 10 mm length. Both ends of the capillary containing bead samples were then sealed with silicon grease to prevent the evaporation of water. Samples prepared were cooled from 20 to −40 °C at the rate of 1 °C min−1 by using a programmable freezer and kept below −40 °C until the measurement. In the case of G25, the refrozen samples re-cooled from the temperature of the completion of ice crystallization during rewarming (−11 to −5 °C) to −40 °C were also prepared. Cooling and re-cooling rates were 1 °C min−1, and the heating rate during rewarming was 5 °C min−1. Rapid freezing where samples were put into a deep freezer controlled at −85 °C prior to the measurement was also conducted. The cooling rate at that time was ca. 60 °C min−1.Sephadex2 vapor introduced into the sample holder, and was measured with a thermocouple made of chromel-alumel. Frozen samples set on the turntable were continuously rotated 180 degrees at a rate of 1.2 degrees per second. The transmission images were acquired by using an X-ray imaging system composed of an AA50 X-ray imaging unit and a C4880-41S CCD camera  set at the distance of 25 mm from the sample. A photograph of the apparatus for the X-ray CT measurement is shown in The X-ray CT measurement was carried out using the beam line of BL46XU at SPring-8 . The X-ray wavelength was 0.1 nm, corresponding to 12.4 keV in energy. The angle of X-ray mirrors necessary to eliminate contamination of the X-ray by higher-order harmonics was set at 3.56 mrad. The size of the X-ray beam was 1 mm × 1 mm. The temperature of the frozen samples in the sample holder on the turntable (sample stage) was kept at about −40 °C by regulating the ejection speed of LN−1 by using a programmable freezer. After being freeze-dried, the beads were fixed on the aluminum stage with carbon tape and were sputter-coated with gold. Freeze-dried beads broken with a hammer were also prepared to observe the inside of the beads. SEM images were taken with a JSM-6010 PLUS_LA .Samples for the observation by SEM were prepared in the same way as for the X-ray CT measurement. Sample beads of G10, G25, and G50 containing 50 wt % water were cooled to −40 °C at the rate of 1 °C min® beads of G15, G25, and G100 were used without drying. Samples containing ca. 50 wt % water were put in cells with 5 mm inner diameter and 2 mm width, and were sealed with a pair of Kapton film windows of 25 μm in thickness. Samples were cooled from 25 to −40 °C at a rate of ca. 13 °C min−1, followed by stepwise heating to 25 °C with a temperature interval of 5 °C for G25 and G100, and 10 °C for G15. Annealing time at each temperature was about 5 min. Measurements of SAXS and WAXD were carried out using the beam line of BL40B2 at SPring-8. The X-ray wavelength was 0.1 nm, and the size of the X-ray beam was 0.1 mm × 0.1 mm. The range for scattering vector q (from the range for SAXS to that for WAXD) covered 0.04 < q (10 × nm−1) < 2.2, corresponding to 16‒0.28 nm of the real space. Camera length was 4153 cm for SAXS and 39 cm for WAXD. Exposure time for data acquisition was 60 s.For the XRD measurement, Sephadex


We describe a case of a 20-month-old girl with probable congenital Zika virus infection and normal neurodevelopment, despite microcephaly and abnormal neuroimaging. This case raises questions about early prognostic markers and draws attention to the need for investigation in suspected Zika cases, even if the child’s early neurodevelopment is normal. Flavivirus, family Flaviviridae) that was first isolated in 1947 from monkeys in the Zika Forest in Uganda , length was 45 cm (−1.1 SD), and head circumference was 29.5 cm (−2.4 SD)  .Neurodevelopment is a dynamic process that depends on the interaction between neurobiological and environmental factors. Children initially developing within the expected range for their age group may experience a slowdown as demands of neurodevelopment become more extensive. We cannot make inferences about long-term prognosis from the patient’s condition at 20 months of age. Developmental evolution should be determined prospectively, using the same instrument so that results can be compared over time.This report has 2 main limitations. First, molecular confirmation of Zika virus infection in the mother or the child was not possible. Second, we did not perform PCR or culture for cytomegalovirus. Nevertheless, the child’s Zika virus IgM was positive in the neonatal period, and her mother’s clinical symptoms suggested Zika virus infection during pregnancy, which occurred during the Zika virus epidemic in Brazil, in one of the most affected areas.This case may indicate a broader spectrum in congenital Zika syndrome, raising questions about early prognostic markers. Our findings draw attention to the need for detailed evaluation even for typically developing children with possible congenital Zika virus infection who receive medical attention later.Additional information about infant with probable congenital Zika virus infection, Brazil.


Ebola virus is known for several outbreaks of hemorrhagic fever in West Africa. This RNA virus is linked tohigh fatality and easy transmission. Recently, an effective vaccine and a monoclonal antibody cocktail have been introduced tocombat Ebola virus infection. The matrix protein VP40 of Ebola virus is a known drug target and it is essential for viral lifecycle through participation in RNA transcription as well as for the budding of the mature virus. It is known thatresidues phenylalanine 125 and arginine 134 of VP40 are involved in the interaction with RNA. Therefore, it isof interest to screen VP40 with millions of compounds at the mcule.com database for potential inhibitors. The outputhits were ranked according to their minimum binding energy to matrix protein VP40. We further calculated thepharmacokinetics and toxicology properties for the best five hits using several predictive ADME analysis web tools. We report acandidate lead (compound #5: ((10R)-10-(4-hydroxyphenyl)-11,12,14,16-tetraazatetracyclo hexadeca-1(16),2(7),3,5,8,12,14-heptaen-8-ol)) with high drug-likeness score, promising lead-likeness behaviour and high median lethal dose.The candidate lead compound #5 engages in hydrogen bonding and hydrophobic interactions with VP40 active site residues. Thus, the leadcompound #5 is recommended for further in vitro and in vivo validations for further consideration. The Ebola virus (EboV) is an antisense RNA virus that had been responsible for several outbreaks of hemorrhagic fever mainly in West Africa. This virus has been categorized as a bio-weapon hazard due to its high transmission capacity with fatality rate of about 90%,2.AttempThe matrix protein VP40 is localized below Ebola virus envelope and it is considered the most abundant viral protein. VP40 plSeveral previous studies had virtually screened large chemicals databases like zinc database and traditional Chinese medicine (TCM) database ,16. In We have used mcule.com  online pTo elaborate our understanding of ligand-target interactions, we repeated virtual docking studies for the top five hits generated with mcule.com webserver. The employed docking protocol was similar to the one discussed above except that we have increased exhaustiveness of search to a maximum value of eight. For this analysis, we used AutoDockvinaversion 1.1.2 installed on our local machine . UCSF chWe used two webservers, namely pkCSM  and SwisThe chemical structures and characteristics for the top five hits as screened virtually against Ebola virus VP40 protein are shown inDue to its high fatality rate and transmission capacity, Ebola virus has been recognized as type "A" bio-weapon microorganism ,2. ManagAccording to 2,7.011,15]hexadeca-1(16),2(7),3,5,8,12,14-heptaen-8-ol) possesses high drug-likeness score and displays lead-likeness features. Molecular docking analysis shows that compound #5 forms optimal hydrogen bonding with hydrophobic interactions at the active site of the matrix protein VP40. The compound also has high LD50 value as compared to other filtered hits. Therefore, the lead compound #5 is recommended for further consideration and evaluation using in vitro and in vivo modelsThe known protein target of VP40 from Ebola virus was screened with 42 million compounds in mcule.com database for potential lead inhibitors.The filtered hits were ranked based on their minimum binding energy and the top five compounds were selected for detailed study. Various pharmacokinetics and toxicology properties were estimated by using available predictive regression and molecular similarity tools. The lead compound #5 ((10R)-10-(4-hydroxyphenyl)-11,12,14,16-tetraazatetracyclo[7.7.0.0


Potato virus U isolate detected in a Peruvian potato sample collected in 1977 produced the first genome sequence of this virus. When this genome sequence was compared with those of other nepoviruses, the amino acid sequences of RNA1 and RNA2 were most similar to those of subgroup C nepoviruses.A  Potato virus U isolate detected in a Peruvian potato sample collected in 1977 produced the first genome sequence of this virus. When this genome sequence was compared with those of other nepoviruses, the amino acid sequences of RNA1 and RNA2 were most similar to those of subgroup C nepoviruses.A  Solanum tuberosum subsp. andigena) showing bright yellow leaf markings. The virus was mechanically transmissible to 44 species from 7 plant families. However, it proved difficult to reestablish systemic infection with it in potato plants, so it may predominantly infect potato roots and rarely invade the infected plants systemically or, alternatively, be mostly associated with other as yet unknown plant species, only infecting potato occasionally. The virus was serologically unrelated to 17 other nepoviruses, including Arracacha virus A (Potato black ringspot virus (Potato virus U (PVU)  (Blueberry latent virus (54%)   and Blueus 54%) . The PVUnt virus  and Soybal virus , respectal virus  with the studies , 4, and % . The Pepovirus .MH716806 (RNA1) and MH716805 (RNA2). Raw data were deposited in the SRA under accession number SAMN10081142, part of BioProject number PRJNA491634.The sequences described here were deposited in GenBank under accession numbers


In large intensive beef production systems, the identification of sick animals is difficult. We hypothesized that sick bulls would change daily activities when sick. Thus, the use of activity monitoring devices might allow for the early identification of sick bulls. The device used measured steps counts, lying time, lying bouts, and frequency and time at the feed bunk. Sick bulls started to behave differently from healthy bulls at least 10 days before the appearance of clinical signs. The prediction model identified bulls at risk of becoming sick 9 days before the visual diagnostic based on the time attending to the feed bunk, the time lying, and the frequency of lying bouts. The validation indicated that the prediction resulted in 50% false positives and 7% false negatives. Activity monitoring systems may be useful tools to identify bulls at risk of becoming sick.vs. sick bulls. The model was developed with 70% of the data, and the remaining 30% was used for the validation. Healthy bulls did 2422 ± 128 steps/day, had 28 ± 1 lying bouts/day, spent 889 ± 12 min/day lying, and attended the feed bunk 8 ± 0.2 times/d for a total of 95 ± 8 min/day. From the total of bulls enrolled in the study, 71 (9.2%) were diagnosed sick. Their activities changed at least 10 days before the clinical signs of disease. Bulls at risk of becoming sick were predicted 9 days before clinical signs with a sensitivity and specificity of 79% and 81%, respectively. The validation of the model resulted in a sensitivity, specificity, and accuracy of 92%, 42%, and 82 %, respectively, and a 50% false positive and 12.5% false negative rates. Results suggest that activity-monitoring systems may be useful in the early identification of sick bulls. However, the high false positive rate may require further refinement.Bulls  were fitted with an activity monitoring device for three months to study if behavior could be used for early detection of diseases. The device measured the number of steps, lying time, lying bouts, and frequency and time of attendance at the feed bunk. All healthy bulls (n = 699) throughout the trial were used to describe the normal behavior. A match-pair test was used to assign healthy bulls for the comparison  Mortality and morbidity at arrival are common in beef production systems . Owners The early identification of sick animals may allow for an early and targeted therapy and, eventually, decrease antibiotic use . HoweverRecently, a variety of automatic activity monitoring devices have been developed and can assist farm personnel in the early detection of diseases ,8. Feedi®, Syva, Ciudad Real, Spain) and were treated with an internal and external anti-parasitic treatment . Seven days after the first vaccine, all bulls were revaccinated. Bulls were housed in a dirt floor open-air facility with an average space of 7 m2/bull, and had continuous access to water and dry food. The concentrate  was offered in a 6 m long feed bunk, straw in a separate 15 m long feed bunk, and water was provided through an automatic waterer. Bulls were monitored in the lots for 12 ± 2 weeks.Crossbred bulls  originating from auction markets in northern Spain  were supplied to the receiving facility and monitored during the first three months after their arrival. The experiment was conducted from July 2016 to March 2018. There were four groups of bulls that arrived at the farm in July (n = 33), March (n = 212), June (n = 252), and October (n = 273). All groups were managed in an all-out all-in program between groups. On the day of arrival, bulls were vaccinated against Pasteurella and pneumonia . The device consists of an accelerometer that measured daily steps counts (n/day), lying bouts (n/day), and lying time (min/day). An electromagnetic field-generating antenna was located along the feed bunk to detect bulls which front leg was less than 30 ± 2 cm from the feed bunk to allow the calculation of the number of visits (n/day) and its duration (min/day) at the feed bunk. Data collected was transmitted wirelessly every 6 min to a computer with a system-specific software . The system has been described in detail and validated for feedlot cattle . Bulls Ip < 0.05 and trends reported at 0.05 ≤ p < 0.10.All statistical analyses were performed with SAS . For the normal behavior, only bulls that had no treatment during all the study were used. A descriptive analysis was conducted for the entire period, and univariate analysis (ANOVA) was performed to identify differences by age for each behavioral index. Significance was declared at A matched pair design was used to assign bulls to the healthy group for comparisons. For each sick bull, we identified three healthy bulls that were on the same date, the same group, and similar age (±4 d) and weight at entry (±17 kg). For sick bulls that were treated multiple times, only the first treatment event was considered. Day 0 was defined as the day of sickness diagnosis, and the database contained records from day −10 to day +10. Once the database was generated, a multivariate linear mixed model was built to describe differences for each behavioral index between sick and healthy bulls. The model included bulls health status , season , age at entry, days around the treatment event (from −10 to +10), and the interaction between days and health status as fixed effects. The animal was considered a random effect. When an interaction was significant, the SLICE option of SAS was used to evaluate these differences.p < 0.20 were initially included in the model. The backward stepwise procedure was used to exclude variables from the regression model until all predictors remaining were significant. For each model, the sensitivity (Se) and the specificity (Sp) were calculated for each possible cutoff point, as described by Dohoo et al. [For the development and validation of the model, 70% of the original dataset was used to develop the prediction model, and the remaining 30% was used to measure the performance of the model. To build the prediction model, multivariate logistic regression was performed on the days before the first treatment event to identify variables that were associated with health status. This model included the fixed effects of age at entry, season, and all behavior indexes. Age at entry was included in all prediction models. All predictors with a o et al. . The cuto et al. . The Se p < 0.05) except in the frequency of meals where no differences were observed (p > 0.10). Bulls daily average in step counts and lying bouts (p < 0.05), and attendance to the feed bunk and lying time (p < 0.05). Only bulls that had no treatment during all the study were used to describe the normal behavior n = 699; . Bulls ang bouts A,D increing time C,E decrevs. 213, respectively) in all behavior measurements from 10 days before to 10 days after the first treatment event. All behavior indexes were affected by bull’s health status. Of the total of 770 bulls enrolled in the study, 71 had at least one episode of sickness, which represents an overall incidence of 9.2%. The mortality rate during this experiment was 1.2% of enrolled bulls. p < 0.05; −9 and 4; p < 0.10), 22% less lying bouts , and spent less time lying  compared with healthy bulls. Bulls attended the feed bunk 15% fewer times , and spent 18% less time at the feed bunk  than healthy bulls. Differences between healthy and sick bulls started to be evident from at least 10 day before the first treatment event took place. Sick bulls did in average 15% fewer steps  and shorter time (9.7 vs. 7.6 min) per meal 7 days before feedlot staff noticed any clinical sign.For most of the activities monitored, the largest difference compared with healthy bulls occurred the day when farm personnel identified the animal as potentially sick . This prl et al.  found thl et al.  also repl et al.  observedl et al.  found thl et al.  reportedOverall, sick bulls showed changes in daily activities already at 10 days before the diagnostic of the disease. We monitored bulls behavior from 10 days before the sickness based on previous studies that observed changes in behavior 2 to 6 days before the observation of clinical signs ,14,16,26To our knowledge, our study is the first to develop a model to predict diseases in bulls with a formal validation using an independent dataset. Because we considered it important to select the earliest date for an early treatment, the analysis was conducted on individual days. According to our results, the prediction model developed using the training database on day −9 had a Se and an Sp of 79% and 81%, respectively. The Se and the Sp were similar to the results found in previous studies predicting different diseases. For example, Marchesini et al.  reportedThe application of the prediction model at day −9 in the independent dataset  resulted in an acceptable overall accuracy (82%). However, the low specificity (42%) resulted in a high FPR (50%). The FPR represents the percentage of animals that would be treated without any need. However, the high FPR should be interpreted in the context of current preventive practices. In many farms, preventive treatments are conducted in all animals upon arrival. In the current experiment, the incidence of diseases was around 10%. A 50% FPR implies that twice as many animals (20%) would be treated. However, when preventive treatments are commonly provided to all animals [Activity monitoring devices may be useful tools for the early identification of bulls at risk of becoming sick. The most reliable prediction model was able to identify these bulls 9 days before the visual detection of clinical signs by farm personnel. However, the high FPR found could affect the reliability of this prediction, which deserves further refinement.


Poaceae. To examine viruses infecting winter barley in Korea, we carried out a comprehensive study of barley RNA viromes using next-generation sequencing (NGS). A total of 110 barley leaf samples from 17 geographical locations were collected. NGS followed by extensive bioinformatics analyses revealed six different barley viromes: Barley yellow mosaic virus (BaYMV), Barley mild mosaic virus (BaMMV), Barley yellow dwarf virus (BYDV), Hordeum vulgare endornavirus (HvEV), and Barley virus G (BVG). BaYMV and HvEV were identified in all libraries, while other viruses were identified in some specific library. Based on the number of virus-associated reads, BaYMV was a dominant virus infecting winter barley in Korea causing yellow disease symptoms. We obtained nearly complete genomes of six BaYMV isolates and two BaMMV isolates. Phylogenetic analyses indicate that BaYMV and BaMMV were largely grouped based on geographical regions such as Asia and Europe. Single nucleotide polymorphisms analyses suggested that most BaYMV and BaMMV showed strong genetic variations; however, BaYMV isolate Jeonju and BaMMV isolate Gunsan exhibited a few and no SNPs, respectively, suggesting low level of genetic variation. Taken together, this is the first study of barley RNA viromes in Korea.Barley is a kind of cereal grass belonging to the family  Hordeum vulgare L.) is a kind of cereal grass belonging to the family Poaceae. Since its first cultivation in temperate regions in Eurasia about 10,000 years ago, barley has been used as animal feed and fermentable materials for beer and whisky production1. Barley is the fourth biggest import crop, after maize, rice, and wheat, based on production. In Korea, winter barley is usually cultivated and is mostly consumed as polished barley mixed with rice; however, it can also be used as materials for bread, noodle, pastes, tea, beverage, and oils.Barley  and Barley mild mosaic virus (BaMMV), which are members of the genus Bymovirus in the family Potyviridae, are well known. Both are important viruses infecting barley, causing yellow mosaic disease and leading to serious yield loss4. Both BaYMV and BaMMV are single-strand viruses, and their genomes are composed of two RNA segments, RNA1 and RNA28. Both soil-borne BaYMV and BaMMV are transmitted by the fungal vector Polymyxa graminis10.To date, several viruses infecting barley have been identified Table . Of idenBarley yellow dwarf virus (BYDV) is a single-stranded RNA virus in the genus Luteovirus in the family Luteoviridae causing yellowing symptoms11. BYDV presenting in the phloem of the infected plants is transmitted by aphids, and several serotypes of BYDV are classified based on the aphid vector12.Barley stripe mosaic virus (BSMV) in the genus Hordeivirus usually infects two monocot crops such as barley and wheat; however, BSMV infects more than 250 plant species13. In addition, BSMV based vector is widely used for virus-induced gene silencing (VIGS) in barley and wheat14. Hordeum mosaic virus (HoMV) in the genus Rymovirus was initially isolated from barley in Alberta in Canada and infects plants in the family Poaceae such as wheat, oat, and rye15.rym4 and rym5, are known to be effective against a barley yellow disease complex composed of BaMMV and BaYMV16. However, a previous study has identified a new BaYMV strain capable of breaking rym4-associated resistance in barley in Belgium17. In addition, The barley accession PI1963 carrying the rym11 gene confers resistance against all European strains of barley yellow mosaic disease19.Several studies to identify genes conferring resistance to two bymoviruses have been reported. For example, two resistance genes, 22. Several different kinds of libraries have been prepared by using small RNAs, double-stranded (ds) RNAs, mRNAs, and ribosomal RNA-depleted total RNAs for NGS. For example, complete genome sequence of Hordeum vulgare endornavirus (HvEV), which has a dsRNA genome, has been obtained from dsRNA extraction followed by NGS using MiSeq23. In addition, complete genome sequence of Barley yellow striate mosaic virus (BYSMV) in the genus Cytorhabdovirus was assembled by small RNA sequencing followed by Sanger-sequencing24. Moreover, RNA-sequencing followed by Sanger-sequencing revealed complete genome sequence of Barley virus G (BVG) in the genus Polerovirus25. Furthermore, a recent study has revealed a diversity of bymoviruses in barley in France using NGS and Sanger-sequencing methods26.Recent rapid advances of next-generation sequencing (NGS) facilitate the identification of novel plant viruses and assembly of viral genomesIn order to examine viruses infecting barley in Korea, we carried out a comprehensive study of barley RNA viromes using NGS. For that, we collected 110 barley samples from 17 geographical locations in six different provinces. Samples were pooled based on the collected provinces and used for library preparation. Extensive bioinformatics analyses revealed six different barley viromes in Korea.de novo transcriptome assembly using two different assemblers, Trinity and Velvet. The number of obtained contigs ranged from 62,074 (library B) to 250,090 (library D) by Trinity, whereas the number of contigs ranged from 997,502 (library B) to 4,103,731 (library D) , and Valsa ceratosperma hypovirus 1 (VcHV1)  to 36 (library F) Fig. . The num1) Table . Based o1) Table . In contNext, we calculated the proportion of virus-associated contigs and reads in each library Fig. . The proWe examined the geographical distribution of identified viruses Fig. . We founWe calculated virus accumulation in each library based on read number and copy number. Copy number was calculated by total read number divided by each viral genome size Fig. . In all Using virus-associated contigs, we obtained six nearly complete genomes of BaYMV from six libraries Fig.  and two The sizes of assembled BaMMV RNA1 were 7,269 (library A) and 7,263 nt (library B), whereas the sizes of assembled BaMMV RNA2 were 3,523 nt (library A) and 3,524 nt (library B) Fig. . InteresBased on assembled genome sequences for BaYMV and BaMMV, we generated phylogenetic trees. Since each virus is composed of two RNA fragments, two independent phylogenetic trees for each virus were generated Fig. . The twoPhylogenetic trees based on BaMMV RNA1 and RNA2 sequences also displayed two different groups of BaMMV isolates Fig. . The twoIn order to confirm infection of identified viruses by NGS, we conducted RT-PCR using newly designed primers. To increase reliability of RT-PCR, we designed at least two different primer-pairs for each RNA fragment of four viruses, BaYMV, BaMMV, HvEV, and BVG Fig. . Using f23. A recent study has examined genetic diversity of bymoviruses infecting barley in France using NGS and Sanger-sequencing, revealing that BaYMV-2 was responsible for the symptoms observed in varieties carrying the resistance gene rym4.Recently, several NGS-based studies have been conducted for viruses infecting barley. For instance, dsRNA extraction followed by NGS was used to determine the complete genome sequences of HvEV, which is composed of dsRNASoil-borne wheat mosaic virus (SBWMV), by RT-PCR using individual barley samples collected from the same major winter barley cultivation regions27. However, we did not identify SBWMV in our study. Moreover, BSMV was not identified in our study. BSMV has been identified in a wide range of areas in the world, including North Africa, North America, Europe, and Asia28. Thus, it is necessary to prevent the introduction of BSMV to avoid causing a serious loss of barley yield in Korea.As compared to the previous studies associated with viruses infecting barley, our study focuses on barley RNA viromes associated with identification of viruses infecting barley, as well as geographical distribution and genetic diversity of identified viruses in Korea. We successfully identified several viruses  by NGS followed by bioinformatics analyses. In addition, our study found that there were at least three different serotypes of BYDV infecting barley in Korea. Infection of BYDV strains PAV and MAV in barley and wheat have been reported in Korea; however, BYDV strains GAV and PAS infecting barley have not been reported in Korea. Moreover, we identified HvEV infecting barley in Korea for the first time. Prior to conducting barley virome study, we examined infection of three major viruses, BaYMV, BaMMV, and 29. On the other hand, seed propagated plants are usually transmitted by insect vectors; therefore, it is efficient to pool samples for the identification of viruses infecting a plant species in different geographical regions. Accordingly, 110 samples from 17 geographical regions were pooled according to six different provinces. As we expected, each library contains a different list of viruses infecting barley, suggesting that geographical region is an important factor for the composition of viruses in each virome. However, several problems can be generated by pooling of samples which is a cost-effective approach in the virome study. For example, as discussed previously30, the misalignment of sequence reads could have occurred due to the presence of different virus isolates and the improper reference genome, although we used a consensus genome sequence assembled from NGS data. In fact, NGS is an effective method for identifying viral recombination31. However, the pooling of samples might interfere with the correct interpretation of recombination events due to a possible mixture of multiple virus isolates. Thus, our results might contain such problems.Although NGS is now generally used in many research areas, however, the price of NGS is still high for several individual samples in parallel. For the virome study of fruit trees that are mechanically infected by viruses, the library preparation using individual fruit trees followed by NGS is useful to decipher the viromes of individual fruit cultivars20. Based on their results, the yield of viral sequences was dependent on each viral genome organization. In our study, we prepared cDNA libraries for NGS using oligo-dT primers in order to facilitate identification of two bymoviruses containing poly-A tail: BaYMV and BaMMV. However, it was not surprising that viruses composed of dsRNAs can be also be identified by mRNA libraries, as shown in other previous studies33.There is still a dispute over the optimal method for plant virome study. A recent study has compared two different libraries using as small RNAs and ribosomal RNA-depleted total RNA, respectively, for NGS-based virus identification in plants27. Furthermore, double infection of BaYMV and BaMMV was also confirmed in the barley samples of libraries A and E by NGS, as shown in the previous study by RT-PCR27. In particular, RT-PCR confirmed that all seven barley samples in Yeonggwang (library A) were co-infected by BaYMV, BaMMV, and HvEV (data not shown). HvEV is vertically transmitted by pollen and ovule infection34 and appears to be a non-pathogenic virus like other known endornaviruses that infect plants. Thus, the infection rate of HvEV in cultivated barley may be very high due to vertical transmission via seeds.Viruses most commonly infecting barley were BaYMV and HvEV, while other viruses including BaMMV, BYDV, and BVG were identified in specific libraries. Based on read number and copy number associated with identified viruses, BaYMV was the dominant virus in all six libraries. This result suggests that BaYMV could be a major virus in barley grown in Korea, which might be associated with yellow mosaic symptoms. Similarly, our previous study using RT-PCR also showed a high infection rate of single BaYMV in barley in KoreaFor four viruses, we conducted RT-PCR with two independent primer-pairs. Read numbers and RT-PCR results for each virus give the level of virus accumulation in each library. Except for HvEV, read number from NGS was correlated with band intensity from RT-PCR. In case of HvEV, the read number from NGS was low in all six libraries; however, the intensity of amplified RT-PCR products was high. Since HvEV is composed of dsRNA, it cannot be well recovered by an mRNA library using oligo-dT primer followed by NGS. Therefore, the quantification of virus accumulation should be carefully assessed by a combination of several methods.Size of RNA fragment was an important factor to estimate virus accumulation by NGS. In general, a large number of virus-associated reads could be obtained from a large genome fragment of a virus. In case of BaYMV and BaMMV, which each consist of two RNA fragments, the number of reads from RNA1 was always higher than that from RNA2, since it is bigger than RNA1. In contrast, the copy number of BaYMV RNA2 was slightly higher than that of BaYMV RNA1, although we hypothesized that the copy numbers for RNA1 and RNA2 might be equal.de novo. Six BaYMV genomes and two BaMMV genomes were assembled by NGS followed by two de novo genome assemblers, Trinity and Velvet. The advantages and disadvantage for these two assemblers for virome study have previously been described32. Using assembled genomes, we studied phylogenetic relationships of BaYMV and BaMMV. Phylogenetic trees showed two distinct groups, which were divided by geographical region, Europe and Far East Asia. Historically, many barley plants in Korea have been collected by the Japanese during Japanese occupation, and many of them have been reintroduced to Korea35. Therefore, all Korean BaYMV and BaMMV isolates are in the same clade with Japanese isolates. Among five BaYMV isolates, four isolates showed sequence similarity to the known Japan strain K05. The BaYMV strain K05 was used as a template for the construction of infectious cDNA clones of a BaYMV leading to yellow mosaic disease in winter barley36. Based on those results, we suppose that BaYMV infecting barley in Korea that is closely related to strain K05 could be a major virus causing yellow mosaic disease in winter barley in Korea. Moreover, two BaMMV isolates were grouped in the known Japanese BaMMV strain Na1, which showed pathogenicity in different barley cultivars37, suggesting their possible pathogenicity.Due to the presence of poly-A tail in two bymoviruses, reads associated with two viruses were high enough to assemble two genomes 38. Our previous study also showed that the mutation rate of a plant virus or a viroid varied in different plants29. Therefore, we carefully hypothesized that libraries showing high mutation rates for identified viruses in our study might contain barley samples possessing the viruses with high mutation rates. Moreover, it is likely that not all, but a few, barley samples in the same library contained the viruses with high mutation rates.In our study, the collected samples were pooled for the library preparation. The advantages of pooling samples might be the reduction of NGS cost and increase in the possibility of identifying viruses at a time. However, the disadvantage of pooling samples is that we cannot obtain detailed information on the viruses infecting a single plant. In general, a single plant is also frequently infected by diverse viruses or different isolates of a virus. Although we examined the SNPs of an individual assembled virus in our study, the SNP information did not represent the individual virus, but a collection of several isolates due to pooling samples. For example, SNPs for BaYMV and BaMMV using NGS data showed high mutation rates because pooled samples might contain a mixture of diverse isolates/strains for two viruses. However, BaYMV isolate Jeonju and BaMMV isolate Gunsan exhibited a few and no SNPs, respectively, suggesting low levels of genetic variation. Although samples were pooled, the mutation rates for two viruses were not correlated with the number of pooled samples. Library D pooled from 25 samples exhibited three SNPs for BaYMV, whereas Library A pooled from seven samples and Library F pooled from 12 samples showed 351 and 289 SNPs, respectively, for BaYMV. We next examined the correlation between the number of SNPs and the number of collected regions. The number of SNPs for BaYMV in Libraries A (one region), E (six regions), and F (two regions) was very high, while that in Library D (five regions) was very low, suggesting no correlation between the mutation rates and the number of collected regions. In fact, virus mutation is highly dependent on virus type, host type, and environmental conditionsIn summary, six barley RNA viromes in this study provide a comprehensive overview of viruses infecting winter barley in Korea. Although several viruses infecting barley have been identified, we found that BaYMV was the dominant virus associated with yellow mosaic disease symptoms in Korea. Furthermore, phylogenetic trees using assembled viral genomes suggest that geographical region is a main factor to group BaYMV and BaMMV isolates/strains. Moreover, SNP analyses for BaYMV and BaMMV revealed genetic variations of two viruses in different geographical regions.We collected 110 winter barley leaf samples from 17 geographical regions in Korea in March 2016. The 17 regions are the main winter barley production areas in Korea. Most barley samples showed yellow mosaic disease symptoms; however, some barley samples did not show any symptoms. The 110 samples were pooled according to six different provinces in Korea. Detailed information about geographical regions and the six different provinces can be found in Table Pooled barley leaf samples were frozen using liquid nitrogen and ground with a pestle and mortar. Total RNA was extracted using the RNeasy Plant Mini Kit  according to manufacturer’s manuals. The quality and quantity of extracted total RNA were measured using an Agilent 2100 Bioanalyzer  and gel electrophoresis. The extracted total RNAs were used for the library preparation for RNA sequencing using the NEBNext Ultra™ RNA Library Prep Kit for Illumina in accordance with the manufacturer’s instructions . In brief, we extracted mRNAs with poly-A tail using poly-T oligo-attached magnetic beads. The first strand of cDNA was synthesized by the purified mRNAs followed by a second strand of cDNA. After that, the adenylation of 3′ ends was conducted. Adapters were ligated, and PCR amplification was carried out to selectively enrich DNA fragments with adapters and amplify the amount of DNA in the library, respectively. The 2100 Bioanalyzer was used for quality control of the generated libraries . The six prepared libraries were paired-end sequenced by Macrogen Co.  using the HiSeq2000 platform.29. In brief, two different methods, Trinity program  with default parameters39 and Velvet/Oases assembler (version 0.2.08)40, were used for de novo transcriptome assembly. Assembled contigs in each transcriptome were subjected to MEGABLAST41 with a cut-off E-value of 1e−6 search against NCBI’s viral reference database downloaded from https://www.ncbi.nlm.nih.gov/genome/viruses/. Only virus-associated contigs were selected after deleting endogenous virus-like sequences.We used the same bioinformatics analyses to identify viruses in the assembled transcriptome as described previously32. ClustalW program implemented in the MEGA7 program was used to align contigs on the assembled viral genomes42. Again, we aligned raw sequence reads on the assembled viral genome to confirm consensus sequences using a Burrows-Wheeler Aligner (BWA) program with default parameters43.Nearly complete genomes for six BaYMV and two BaMMV genomes were assembled based on contigs generated by Trinity and Velvet assemblers as previously describedhttp://www.ncbi.nlm.nih.gov/genbank/). Each RNA fragment sequence for each virus was aligned using the ClustalW program with default parameters. In de novo transcriptome assembly, some virus-associated contigs include partial sequences derived from the host plant. Those sequences can be identified by BLASTN search and sequence alignment on the reference virus genomes. Those unnecessary sequences derived from the host plant and poly-A tails at the 5′ and 3′ regions were deleted. We manually edited aligned sequences. A phylogenetic tree was constructed using the MEGA7 program with the neighbor-joining method with 1,000 bootstrap replicates and Kimura 2-parameter distance42.To generate phylogenetic trees for BaYMV and BaMMV, six BaYMV and two BaMMV genomes were used. Each virus is a bipartite virus composed of two RNA fragments. Therefore, four independent phylogenetic trees were constructed. BLASTN was conducted to find known BaYMV and BaMMV genome sequences using the assembled BaYMV and BaMMV RNA fragments as a query against GenBank , and the cycling conditions were 50 °C for 30 min, 95 °C for 15 min followed by 30 cycles at 95 °C for 20 sec, 50 °C to 56 °C for 40 sec , and 72 °C for 1 min, with a final extension at 72 °C for 5 min. The amplified RT-PCR products were confirmed by gel electrophoresis followed by EtBr staining. The amplified RT-PCR product was cloned in the pGEM-T-Easy Vector  followed by Sanger sequencing.Supporting informationTable S1Table S2