Acute pancreatitis is associated with significant morbidity and mortality. In the United States, more than 3,00,000 patients are admitted and about 20,000 die from acute pancreatitis per year. In Taiwan, the incidence rate of acute pancreatitis is 0.03% and the mortality rate among severe acute pancreatitis is 16.3%. The aim of the study was to evaluate the impact of the global budgeting system on health service utilization, health care expenditures, and quality of care among patients with acute pancreatitis in Taiwan.The National Health Insurance Research Database (NHIRD) was used for analysis. Data on patients with acute pancreatitis diagnosed during the period 2000 and 2001 were used as baseline data, and data from 2004 and 2005 were used as post-intervention data. The length of stay (LOS), diagnostic costs, drug cost, therapy costs, total costs, risk of readmission within 14 days, and risk of revisiting the emergency department (ED) within 3 days of discharge before and after implementation of the global budgeting system were compared and analyzed.P < .001)). The mean total costs before and after implementation of the global budget system were Taiwan dollars (NT$) 28,290.66 ± 1576.32 and NT$ 42,341.83 ± 2285.23, respectively. The mean rate of revisiting the ED within 3 days decreased from 9.9 ± 0.9% before adoption of global budgeting to 7.2 ± 0.6% after implementation of the system. The mean 14-day re-admission rates before and after introduction of global budgeting were 11.6 ± 1.0% and 7.9 ± 0.7%, respectively.Data on 2810 patients with acute pancreatitis were analyzed in this study. There was a significant difference in mean LOS before and after introduction of the global budget system (7.34 ± 0.22 days and 7.82 ± 0.22 days, respectively; The global budget system was associated with significantly longer length of stay, higher health care expenditures, and better quality of care in patients treated for acute pancreatitis. The pancreas is a source of hormones, insulin, and glucagons that are important for regulating metabolism. The key exocrine function of the pancreas is to produce pancreatic juices that contain water, bicarbonate, and various digestive enzymes.Acute pancreatitis is a common disease and is associated with significant morbidity and mortality. Although it has a mild and self-liming course, it can be severe and cause complications that carry a significant risk of death. In the United States, more than 3,00,000 patients are admitted with incident pancreatitis and about 20,000 die from the disease each year.–10 It has been found that only 5% to 10% of patients with alcoholism develop acute pancreatitis, which argues that genetic or environmental cofactors are important in the development of alcoholic pancreatitis. Smoking is another important cofactor.–15There are 2 types of acute pancreatitis, interstitial  and necrotizing . The leading causes of pancreatitis are gallstones, which are responsible for about 40% of cases, and alcoholism, which is responsible for about 35% of cases.,16 Two key diagnostic tests for acute pancreatitis involve measuring the levels of serum amylase and serum lipase. Measurement of serum amylase is a very sensitive diagnostic test, but has low specificity. Measurement of serum lipase, however, has a much higher sensitivity (90%) and specificity (90%) for diagnosing acute pancreatitis. Treatment for acute pancreatitis includes pain control, intravenous fluids, pancreatic rest, and monitoring for complications. Aggressive surgical intervention may be necessary for patients who have signs of infected necrosis and whose disease is not controllable by conservative methods. Nutrition should be instituted within a few days.Patients who present with 2 of the following 3 manifestations are diagnosed as having acute pancreatitis: characteristic upper abdominal pain, elevated levels of pancreatic enzymes, and findings of ultrasonography (US), computed tomography (CT) or magnetic resonance imaging (MRI) suggesting acute pancreatitis. Epigastric pain radiating to the back, nausea, and vomiting are the main symptoms of acute pancreatitis. Abdominal pain, which occurs in about 95% of cases, typically occurs acutely, and rapidly reaches maximum intensity.–24 The global budgeting program adopted in Taiwan is an expenditure-cap system with a “floating point value” mechanism. The national budget for a given year is determined before the end of the previous year by consultation between the BNHI and hospital representatives. The aggregate level of expenditure in the previous year and age structure of the population determine the size of the national budget. The monetary value of each point has been equal to the fixed budget divided by the number of points that all hospitals claim, so it fluctuates to precisely match the pre-determined budget. Reimbursement to providers is based on an existing FFS schedule, which lists a relative value or number of points for each item of service. The degree of cuts in reimbursement was measured based on the quarterly monetary value of each point.The National Health Insurance (NHI) program is the backbone of the health care system in Taiwan. The NHI is the major source of health financing and covers 99% of the population. National health care expenditure in Taiwan increased from 5.3% to 6.0% of gross national product during the period 1995 to 2001. The NHI used to operate on a fee-for-service (FFS) basis and as a result health care spending increased by approximately 50% during the period 1995 to 2001. In order to prevent unlimited and rapid growth of spending on health care, the Bureau of National Health Insurance (BNHI) implemented global budgeting to modify the FFS mechanism in 2002. Global budgeting in Taiwan is an overall spending target, designed to limit the volume of service and its total price.The objectives of this study were to compare the health service utilization , health care expenditures , and the quality of care  within 3 days) before and after adoption of the global budgeting system.2This was a pre-post comparison study. The study was based in part on data from the National Health Insurance Research Database (NHIRD) provided by the BNHI, Department of Health and managed by the National Health Research Institutes. The database contains registration files and original claims data for reimbursement. The NHIRD is provided to scientists in Taiwan for research purposes. Each year, the BNHI collects data from the National Health Insurance program and sorts it into data files. These data files are de-identified by scrambling the identification codes of both patients and medical facilities and then sent to the National Health Research Institutes to form the original files contained in the NHIRD.Based on the registration files and original claims data in the NHIRD, specific data subsets can be re-constructed for research purposes. The registration datasets, systemic sampling inpatient expenditures by admissions (DD file) and systemic sampling ambulatory care expenditures by visits (CD file) were used in this study. The interpretation and conclusions contained herein do not represent those of the Bureau of National Health Insurance, the Department of Health, or the National Health Research Institutes.2.1 A total of 1 million cases of systemic sampling dataset were used in this study.Approximately, 0.2% of the ambulatory care expenditures, by visit, CD file extracted by systematic sampling method on a monthly basis, together with the related records in details of ambulatory care orders form the systematic sampling CD file; 5% of the inpatient expenditures, by admission, DD file extracted by systematic sampling method on a monthly basis, together with the related records in details of inpatient orders form the systematic sampling DD file.2.2Subjects in systemic sampling CD and systemic sampling DD files with a clinical diagnosis of acute pancreatitis, ICD-9 code 577.0, in 2000, 2001, 2004, and 2005 were recruited for comparison and analysis. ICD-9 577.0 was used to define the disease in both inpatient and ambulatory codes. One time ICD-9 coding was used to be scrutinized before they can define the acute pancreatitis. The definition of readmission was that readmission event for the treatment of acute pancreatitis. The admission and readmission events need the same ICD-9 coding. Therefore, data from 2003 were not used in this study.The global budget system in Taiwan was fully implemented in 2002; therefore, data from 2000 and 2001 were used as baseline data . Data from 2004 and 2005 were used as post intervention data . In 2003, there was an outbreak of Severe Acute Respiratory Syndrome (SARS) in Taiwan. It has been reported that SARS had an impact on health care utilization.2.3–29A score of 1 was added when the subjects had co-morbid myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, connective tissue disease, peptic ulcer disease, mild liver disease, or diabetes without end-organ damage. A score of 2 was added when the subjects had co-morbid hemiplegia, moderate or severe renal disease, diabetes with end-organ damage, tumor without metastases, leukemia, or lymphoma. A score of 3 was added when the subjects had co-morbid moderate or severe liver disease. A score of 6 was added when the subjects had co-morbid metastatic solid tumors or acquired immunodeficiency syndrome (AIDS). The total score was obtained by adding the relative weight of all co-morbidities. For each decade > 40 years of age, a score of 1 is added to the sum of the above-mentioned scores.2.4In Taiwan, health insurance premiums are calculated as a percentage of an individual's monthly salary. There were 7 income levels in this study: Level 0, no monthly income; Level 1, monthly salary income below Taiwan dollars (NT$) 17,280; Level 2, monthly salary income ranging from NT$ 17,281 to NT$ 22,800; Level 3, monthly salary income ranging from NT$ 22,801 to NT$ 28,800; Level 4, monthly salary ranging from NT$ 28,801 to NT$ 36,300; Level 5, monthly salary income ranging from NT$ 36,301 to NT$ 45,800; Level 6, monthly salary above NT$ 45,801  of China Medical University (CMU-REC-101-012). The IRB specifically waived the consent requirement.2.6http://w3.nhri.org.tw/nhird//date_01.html) are maintained in the NHIRD (http://nhird.nhri.org.tw/). The NHRI is a nonprofit foundation established by the government.All data and related metadata were deposited in an appropriate public repository. The data on the study population that were obtained from the NHIRD , diagnostic costs, drug costs, therapy costs, total costs, rate of revisiting the ED within 3 days, and 14-day re-admission rate before and after implementation of the global budget system.Data are described as mean ± standard deviation (SD). The Multilevel and mixed-effects models were employed to determine the impact of several independent variables on LOS, diagnostic costs, drug costs, therapy costs, total costs, the risk of revisiting the ED within 3 days, and the risk of being readmitted within 14 days after discharge. Mixed-effects modeling is basically regression analysis that takes into account 2 kinds of effect sizes: fixed effects (intercepts and slopes that describe the population as a whole) and random effects (intercepts and slopes that can vary across subgroups of the sample).There were 2 nested levels in this study: hospital accreditation levels and regional levels. There are three accreditation hospital levels in Taiwan: medical centers, regional hospitals, and local hospitals. Taiwan is divided into 6 geographical areas that include Taipei city, northern Taiwan, central Taiwan, southern Taiwan, Kaoshiung, and eastern Taiwan. The independent variables evaluated in this study included pre-post global budgeting, age, gender, income state index, Charlson Comorbidity Index, the 3 hospital levels, and the 6 geographic areas in Taiwan.P-value of .05 was considered to represent statistical significance.All statistical analyses were performed on a personal computer using the statistical package STATA for Windows . A 3P < .001), income state index (P = .04), and Charlson Comorbidity Index (P < .001) before and after the global budgeting system went into effect. There was no significant difference in male to female ratio before and after adoption of the global budget system (P = .10)  were recruited in this study. The mean ages of subjects before and after global budgeting were 47.75 ± 0.47 years and 50.83 ± 0.42 years, respectively. In the pre-budget group, 74% of the subjects were men and in the post-budget group, 75% of the subjects were men. The mean income state index before implementation of the global budgeting system was 1.79 ± 0.05 and that after adoption of the system was 1.74 ± 0.04. The mean Charlson Comorbidity Index before global budgeting was 0.75 ± 0.04 and that after introduction of the system was 1.00 ± 0.03. There were significant differences in age (P = .001 for LOS and P < .001 for others)  before and after global budgeting were NT$ 2085.70 ± 64.42 and NT$ 2875.96 ± 86.96, respectively. The mean drug costs before and after implementation of the global budget system were NT$ 6363.78 ± 547.30 and NT$ 8723.39 ± 665.60, respectively. The mean therapy costs before and after the global budget were NT$ 1074.26 ± 137.10 and NT$ 3412.97 ± 320.40, respectively. The mean total costs before and after adoption of global budgeting were NT$ 28,290.66 ± 1576.32 and NT$ 42,341.83 ± 2285.23, respectively. The mean 3-day re-visit rate to the ED decreased from 9.9 ± 0.9% at baseline to 7.2 ± 0.6% after implementation of the global budget system. The mean 14-day re-admission rates before and after the global budget went into effect were 11.6 ± 1.0% and 7.9 ± 0.7%. There were significant differences in LOS, diagnostic costs, drug costs, therapy total costs, 3-day ED revisit rate, and 14-day re-admission rate before and after adoption of global budgeting (3.1 The Poisson regression model was fitted using option IRR (incidence-rate ratio) to obtain exponential estimates. Global budgeting did not have a significant impact on LOS . Male gender was associated with a significantly shorter LOS than female gender . In addition, LOS was positively correlated with age and Charlson Comorbidity Index . There was a significantly negative correlation between income state index and LOS . Compared with medical centers, there was no significant difference in LOS between regional hospitals or local hospitals . Compared with hospitals in Taipei city, LOS differed significantly among hospitals in northern Taiwan, central Taiwan, southern Taiwan, Kaoshiung city, and eastern Taiwan  . Male gender was associated with significantly lower diagnostic costs than female gender . There was no significant correlation between age and diagnostic costs . There was, however, a significantly negative correlation between income state index and diagnostic costs . Furthermore, there was a significantly positive correlation between Charlson Comorbidity Index and diagnostic costs . Compared with medical centers, there was no significant difference in diagnostic costs between regional hospitals and local hospitals . Compared with diagnostic costs incurred in hospitals in Taipei city, there were no significant differences in diagnostic costs among hospitals in northern Taiwan, central Taiwan, southern Taiwan, Kaoshiung city, and eastern Taiwan  . Male gender was associated with significantly lower drug costs than female gender . There was a significantly positive correlation between age and drug costs . There was, however, no significant correlation between income state index or Charlson Comorbidity Index and drug costs . Compared with medical centers, there was no significant difference in drug costs between regional hospitals and local hospitals . Compared with hospitals in Taipei city, there was no significant difference in drug costs among hospitals in northern Taiwan, central Taiwan, southern Taiwan, Kaoshiung city, and eastern Taiwan .A mixed-effects linear model was used for analysis. Because drug costs were skewed to the right, data were converted to natural logarithm for statistical analysis. Global budgeting did not have a significant impact on drug costs . There was no significant correlation between gender, age, or income state index and therapy costs . There was, however, a significantly positive correlation between Charlson Comorbidity Index and therapy costs . Compared with medical centers, there was no significant difference in therapy costs between regional hospitals and local hospitals . Compared with hospitals in Taipei city, there were no significant differences in therapy costs among hospitals in northern Taiwan, central Taiwan, southern Taiwan, Kaoshiung city, and eastern Taiwan  . Male gender was associated with significantly lower total costs . There was a significantly positive correlation between age and total costs . There was, however, no significant correlation between income state index and total costs . There was a significantly positive correlation between Charlson Comorbidity Index and total costs . Compared with medical centers, there was no significant difference in total costs between regional hospitals and local hospitals . Compared with hospitals in Taipei city, there was no significant difference in total costs among hospitals in northern Taiwan, central Taiwan, southern Taiwan, Kaoshiung city, or eastern Taiwan  . In addition, there was no significant correlation between age, gender or income state index, and risk of revisiting the ED within 3 days . There was, however, a significantly negative correlation between Charlson Comorbidity Index and risk of revisiting the ED . Compared with medical centers, there was no significant difference in the risk of revisiting the ED within 3 days between regional hospitals and local hospitals . Compared with hospitals in Taipei city, there was no significant difference in the risk of revisiting the ED within 3 days among hospitals in northern Taiwan, central Taiwan, southern Taiwan, Kaoshiung city, or eastern Taiwan  . There were no significant correlations between age, gender, income state index, or Charlson Comorbidity Index and the risk of readmission within 14 days . In addition, there was no significant difference in the risk of being readmitted within 14 days between medical centers and regional hospitals . However, patients treated in local hospitals were at significantly lower risk of readmission within 14 days than patients treated in medical centers . Compared with hospitals in Taipei city, there was no significant difference in the risk of readmission within 14 days among hospitals in northern Taiwan, central Taiwan, southern Taiwan, Kaoshiung city, and eastern Taiwan   for the same period (Appendix 1). Possible reasons for the incremental increases in health care expenditures during the study period include longer LOS, older age, and the presence of more comorbidities in the study population. Another possible cause is that the in an expenditure cap system, the budget is fixed ex ante but the reimbursement prices are determined ex poste. Once the services have been provided, the prices of those services are adjusted so that the fixed budget will cover them. In this type of situation, providers are in a situation similar to Cournot competitors, having to make supply decisions before knowing the price they will receive for the service, because the price of the service will be determined by the summed supply decisions of all the providers. Each provider will have an incentive to increase their supply and result in a rise in the total costs post global budgeting.Possible cause of significant incremental mean costs is the extreme values of costs, because the mean values will be affected by extreme values. The incremental rates in mean diagnostic costs, drug costs, therapy costs and total costs were 0.38, 0.37, 2.18, and 0.50. The different rates in median diagnostic costs, drug costs, therapy costs and total costs were 0.23, −0.08, 0, and 0.21. Differences in median costs were much smaller than the mean costs. There was no difference in median therapy costs before and after global budgeting. The median drug cost after global budgeting was even lower than that before global budgeting. There was no significant difference in health care expenditures for acute pancreatitis between hospitals with different accreditation levels or between different geographic areas in Taiwan. Those patient characteristics were not available from the database; it is, therefore, not clear whether those factors played a role in early readmission in this study. The reasons why patients treated in local hospitals were at a lower risk of readmission within 14 days than patients in medical centers is also not clear. Whether patients with acute pancreatitis in local hospitals received better quality care than patients in medical centers or whether patients in medical centers had more risk factors for early re-admission needs to be investigated.The risk of revisiting the ED within 3 days and the risk of being readmitted within 14 days were significantly lower after global budgeting went into effect. Those findings indicate that the quality of care of patients with acute pancreatitis improved after adoption of the global budgeting system. Improvements in care may be attributed to the use of more effective antibiotics, advances in standard operative procedures, and better-trained medical providers. After adjusting for other covariates, there was a significantly negative correlation between global budgeting and the risk of readmission within 14 days. The impact of global budgeting on the risk of revisiting the ED within 3 days, however, was not significant. Neither hospital accreditation level nor geographic area was associated with the risk of revisiting the ED within 3 days. Nevertheless, patients treated at local hospitals were at significantly lower risk of readmission within 14 days than patients treated at medical centers. Risk factors for early re-admission in patients with acute pancreatitis include moderate to heavy alcohol use, persistent gastrointestinal symptoms , and diet at the time of discharge.In Taiwan's market-driven health-care system, 65% of hospitals are private . Sixty-three percent of physicians are salaried employees of hospitals, some receiving bonus payments based on productivity. In response to an expenditure cap, physicians increased their activity levels including do more tests, provide more complex and high-priced procedures which make diagnostic costs, therapy costs, and total costs significantly increased after global budgeting. The major treatment for acute pancreatitis includes supportive care, fluid resuscitation, transfer to intensive care unit and enteral feeding. Since routine use of prophylactic antibiotics in patients with severe acute pancreatitis and/or sterile necrosis is not recommended; drug costs after global budget were not affected significantly. It has been reported that the launch of global budgets leads to an increase in the quantity of medical services supply to maximize profits. In order to maximize revenue, the medical providers in Taiwan present incentives to increase medical care utilization and result in significantly longer length of stay after global budgeting. Market competition between hospitals continues to increase in the health-care industry. For survival, hospitals must focus on quality of care. Furthermore, if the hospital has the plans to improve its service quality, there is more room for a hospital to negotiate the expenditure cap with the BNHI. Thus quality of care significantly improved after global budgeting in Taiwan.This study was subject to limitations. First, the NHIRD provides no detailed information on patients regarding factors such as their lifestyle, habits, body mass index, physical activity, socioeconomic status, or family history; all of which are possible confounding factors in this study. Second, the evidence derived from a cohort study is generally of lower methodological quality than that from randomized trials because a cohort study is subject to many biases related to the necessary adjustments for confounding factors. Despite the meticulous design of this study and its adequate control of confounding factors, biases could remain because of possibly unmeasured or unknown confounding factors. Third, the registries in the NHI claims are primarily used for administrative billing and are not verified for scientific purposes. Because of the anonymity of the identification numbers, obtaining additional information by directly contacting the patients was not possible. The accuracy of medical coding in the claims data may affect the data validity. However, the data on the diagnoses in the NHIRD are highly reliable. The insurance system has mechanisms to monitor the insurance claims.5The global budget system was associated with significantly longer length of stay, higher health care expenditures, and better quality of care in patients treated for acute pancreatitis.Provision of study materials: Ya-Lin Ko, Jyun-Wei Wang, Hui-Mei Hsu, Chia-Hung Kao, Chun-Yi Lin.Data collection: Ya-Lin Ko, Jyun-Wei Wang, Hui-Mei Hsu, Chia-Hung Kao, Chun-Yi Lin.Data analysis and interpretation: Ya-Lin Ko, Jyun-Wei Wang, Hui-Mei Hsu, Chia-Hung Kao, Chun-Yi Lin.Final approval: Ya-Lin Ko, Jyun-Wei Wang, Hui-Mei Hsu, Chia-Hung Kao, Chun-Yi Lin.Conceptualization: Chun-Yi Lin.Data curation: Chun-Yi Lin.Formal analysis: Ya-Lin Ko, Jyun-Wei Wang, Chia-Hung Kao, Chun-Yi Lin.Funding acquisition: Chun-Yi Lin.Investigation: Chun-Yi Lin.Methodology: Chun-Yi Lin.Project administration: Chun-Yi Lin.Resources: Chun-Yi Lin.Writing – original draft: Chun-Yi Lin.Writing – review & editing: Hui-Mei Hsu, Chun-Yi Lin.


Cattle populations are highly amenable to the genetic mapping of male reproductive traits because longitudinal data on ejaculate quality and dense microarray-derived genotypes are available for thousands of artificial insemination bulls. Two young Nordic Red bulls delivered sperm with low progressive motility  during a semen collection period of more than four months. The bulls were related through a common ancestor on both their paternal and maternal ancestry. Thus, a recessive mode of inheritance of asthenospermia was suspected.P = 0.018). Whole genome-sequencing uncovered that both asthenospermic bulls were homozygous for a mutation that disrupts a canonical 5′ splice donor site of CCDC189 encoding the coiled-coil domain containing protein 189. Transcription analysis showed that the derived allele activates a cryptic splice site resulting in a frameshift and premature termination of translation. The mutated CCDC189 protein is truncated by more than 40%, thus lacking the flagellar C1a complex subunit C1a-32 that is supposed to modulate the physiological movement of the sperm flagella. The mutant allele occurs at a frequency of 2.5% in Nordic Red cattle.Both bulls were genotyped at 54,001 SNPs using the Illumina BovineSNP50 Bead chip. A scan for autozygosity revealed that they were identical by descent for a 2.98 Mb segment located on bovine chromosome 25. This haplotype was not found in the homozygous state in 8557 fertile bulls although five homozygous haplotype carriers were expected (https://omia.org/OMIA002167/9913/).Our study in cattle uncovered that CCDC189 is required for physiological movement of sperm flagella thus enabling active progression of spermatozoa and fertilization. A direct gene test may be implemented to monitor the asthenospermia-associated allele and prevent the birth of homozygous bulls that are infertile. Our results have been integrated in the Online Mendelian Inheritance in Animals (OMIA) database (The online version of this article (10.1186/s12864-019-5628-y) contains supplementary material, which is available to authorized users. Impaired male fertility is a well-recognized and highly heterogeneous condition in many species including humans, mice and cattle  and sperm concentrations (1.94 Mio/μl) were within physiological ranges for bulls of their age. More than 80% of the spermatozoa in the ejaculates of both bulls were classified as viable and had typical morphology. However, less than 5% of the spermatozoa were progressively motile, thus not fulfilling the requirements for AI, whose threshold is at least 40%. Apart from producing ejaculates of insufficient quality, both young bulls were healthy and showed no apparent signs of disease.Frozen semen samples from both asthenospermic bulls were thawed and subjected to computer-assisted motility analysis and flow cytometric studies. Post-thawing, the velocity of the spermatozoa was between 10 and 14 μm/s. The velocity of spermatozoa in normospermic control bulls was between 38 and 48 μm/s . In two normospermic control bulls, more than 50% of the spermatozoa showed progressive motility after thawing while in the affected bulls, the proportion of motile spermatozoa was less than 10%. The discrepancy between computer-assisted and subjective motility evaluations (10 vs. 5%) results from spermatozoa displaying minor movement, i.e., the sperm tails bended peculiarly which was not classified as progressive motility in subjective microscopic sperm evaluation Additional file 2: Post-thaw sperm motility in a normospermic control bull. Video of frozen-thawed spermatozoa of an normospermic bull. (MOV 7371 kb)None of the 9 cows inseminated with semen of an asthenospermic bull conceived, whereas 42 of the 89 cows inseminated with normospermic semen did.In vitro fertilization success was tested using 470 offal oocytes. Using post-thaw semen from an asthenospermic bull, the embryo cleavage rate at 42 h post-insemination was only 11% (36 out of 320) compared to 70% (105 out of 150) using spermatozoa from a normospermic control bull. At day nine post-insemination, the embryo yield after embryo culture was only 0.9% (3 out of 320) for the asthenospermic bull compared to 23% (34 out of 150) for the normospermic bull. Moreover, the three embryos obtained using semen from the asthenospermic bull reached blastocyst stage only at day 9, indicating aberrantly slow development.in vivo and in vitro in both asthenospermic bulls, we suspected that this type of sterility may represent a genetic condition. The analysis of pedigree records revealed a common male ancestor (born in 1990) that was present either as great-great-great-grandfather or great-great-grandfather in both the maternal and paternal ancestry of both affected bulls , corroborating recessive inheritance of a deleterious allele.To identify the genomic region associated with asthenospermia, the two affected bulls were genotyped using the BovineSNP50 Bead chip. Following quality control, genotypes of 41,594 autosomal SNPs were available for genetic analyses. Assuming recessive inheritance of a deleterious mutation, the genotypes of both asthenospermic bulls were screened for the presence of long runs of homozygosity (ROH)  encoding the coiled-coil domain containing protein 189. Of the 126 candidate causal variants, only the splice donor site mutation in CCDC189 was predicted to be deleterious to protein function.In order to detect the causal mutation for the asthenospermia, we sequenced both affected bulls at approximately 12-fold genome coverage. The sequencing depth in the interval between 25,490,468 and 28,470,779 bp on chromosome 25, where both bulls shared an extended segment of autozygosity, did not differ from the average sequencing coverage , the polymorphism is located at GCF_002263795.1:Chr25:g.26880841C > T and ENSBTAT00000045037.4:c.472 + 1G > A, respectively. The derived T-allele disrupts a canonical splice site  using RNA extracted from testicular tissues of the two asthenospermic and two normospermic control bulls that were homozygous for the wild type allele. Using primers located at the junction of exons 3 and 4 (forward) and in exon 6 (reverse) we obtained 358 and 368 bp RT-PCR products in asthenospermic (mt/mt) and normospermic (wt/wt) bulls, respectively  is a sperm tail-associated protein that is mainly located in the principal piece and acrosome region of mature spermatozoa indicating that it may be required for their physiological activated progressive movement and acrosome reaction [CCDC189 leading to a frameshift in translation and premature translation termination. Considering that the mutant transcript including the premature stop codon is likely degraded via nonsense-mediated mRNA decay or, if not degraded via nonsense-mediated mRNA decay, would lack a large part of the flagellar C1a complex subunit (C1a-32), that is an integral constituent of the central pair of flagellar microtubules, the splice donor site of CCDC189 most likely represents a loss-of-function variant. Aberrations of the C1a microtubule projection of the central pair impair the physiological beating of flagella whose axonemes are normally organized otherwise [Chlamydomonas mutants lacking constituents of the flagellar C1a projection [Most likely the causal variant for asthenospermia disrupts a canonical 5′ splice donor site of bovine reaction . The velreaction , 42, 43.therwise , 45. It therwise , 46. Postherwise . Both buCCDC189 encoding the coiled-coil domain containing protein 189 causes immotile sperm with defective mitochondria thus resulting in male sterility both in vivo and in vitro. The mutation occurs in Nordic Red dairy cattle at a low frequency. Direct gene testing facilitates the efficient monitoring of the deleterious allele in the population.Our study in cattle revealed that a naturally occurring deleterious allele of Two fifteen-months old bulls from the Nordic Red dairy cattle breed that were born in 2012 and 2013 were housed at an AI center in order to collect their semen for AI. Both bulls were apparently healthy and their andrological status was considered as normal, i.e., they showed no signs of disease, the size of their testicles was within the normal range and their libido was normal. During a period of more than four months, 11 and 27 ejaculates, respectively, of both bulls were collected once or twice a week by technicians at the AI center. Semen from bulls of documented normal sperm quality and fertility, of the same breed and age interval, was likewise collected, processed and examined. Testicular tissue samples were collected immediately after slaughter, frozen in liquid nitrogen and stored at − 80 °C.Immediately after semen collection, sperm motility, viability and morphology of fresh ejaculates were subjectively assessed by technicians at the AI center. Sperm motility was evaluated using a microscope equipped with phase contrast optics. Sperm concentration and plasma membrane viability were assessed using a flow-cytometer . None of5 spermatozoa in 10 μL) were placed on a pre-warmed 76 × 26 mm Menzel-Gläser microscope slide  covered by a pre-warmed coverslip on a thermal plate (38 °C). Slides were analyzed using an upright Zeiss Axio Scope A1 light microscope equipped with a 10x phase contrast objective  connected via a CMOS camera  to a computer running the Qualisperm™ software . The Qualisperm™ technology is based on fluorescence correlation spectroscopy-analysis of single particles (spermatozoa) in confocal volume elements. Individual spermatozoa are projected on a pixel grid of the CMOS camera and the algorithm calculates the number of fluctuations in each pixel using a correlation function of sperm numbers and translation classes, thus determining the speed (velocity) distribution of spermatozoa, from which proportions of motility classes are calculated [Velocity (μm/sec), and percentages of spermatozoa with total and progressive motility were assessed using frozen-thawed ejaculates. Semen droplets (2.4 × 10lculated .Sperm viability (membrane integrity) and early membrane destabilization changes (YO-PRO-1+/PI-), degree of mitochondrial activity (Mitotracker Deep Red+) and superoxide production (MitoSOX+), production of reactive oxygen species  and lipid peroxidation (BODIPY+) were assessed using a Gallios™ flow cytometer  equipped with standards optics. In all investigations, we assessed 25,000 events per sample with a flow rate of 500 cells per second.The total ATP concentration of frozen-thawed spermatozoa was analyzed using the ATP Determination Kit A22066 (Molecular Probes TM Invitrogen detection technologies) according to the manufacturer’s protocol. Samples of an asthenospermic and normospermic bull were analyzed using a Kikkoman Lumitester C-100 luminometer .2O, stained in 1% uranyl acetate, dehydrated in graded series of ethanol , and embedded in Epoxy resin through increasing concentrations  using PELCO Biowave+ tissue processor, and then cured at 60 °C for 3 days. Embedded blocks were sectioned using Leica FC6 microtome and a DIATOME diamond knife with 45° angle into 60 nm sections and mounted on Quantifoil copper grids with formvar carbon films. Sections were post-stained with 2% uranyl acetate followed by lead citrate. Grids were imaged using FEI Morgani 268 electron microscope operated at 100 kV at 20 k magnification.Transmission electron microscopy on spermatozoa of two asthenospermic and one normospermic bull was performed using frozen-thawed semen samples. After thawing, semen samples were washed twice in phosphate buffered saline (PBS), fixed with 2.5% glutaraldehyde and 2% paraformaldehyde in PBS for 2 h on ice and pelleted at 6000 g. Pellets were washed in PBS, post-fixed in 1% osmium tetroxide, washed in ddHin vivo at a conventional Finnish cattle herd within one breeding season; ninety-eight cows in oestrus were inseminated by the farmer either with semen from one of two bulls with asthenospermia (n = 9) or a control bull with normal semen quality (n = 89). Insemination success was controlled by a trained veterinarian.Fertility of two asthenospermic bulls was tested In vitro fertilization (IVF) success, with embryo cleavage rate at 42 h post insemination and embryo yield at 9 days post insemination as end-points, was tested for an asthenospermic and a normospermic bull, using 470 offal oocytes. Ovaries of slaughtered cows were collected at a commercial slaughterhouse and transported to the laboratory in saline at room temperature. In the laboratory, follicles of 2–8 mm in diameter were aspirated with an 18 G needle and a 20 ml syringe. Cumulus-oocyte complexes (COC) were collected from the aspirated follicular fluid and 470 good quality COC were selected for maturation. Unless stated otherwise, all the chemicals were purchased from Sigma-Aldrich . COC were matured for 24 h in TCM199 with glutamax-I  supplemented with 0.25 mM Na-pyruvate, 100 IU/ml penicillin, 100 μg/ml streptomycin, 2 ng/ml FSH , 1 μg/ml β-estradiol (E-2257) and 10% heat inactivated fetal bovine serum (FBS)  at 38.5 °C in maximal humidity in 5% CO2 in air. Following maturation, 320 and 150 COC were inseminated using washed frozen–thawed semen from an asthenospermic and a normospermic control bull of proven fertility in IVF, respectively, at a concentration of 1 million spermatozoa per ml at 38.5 °C in maximal humidity in 5% CO2 in air for 20 h. During IVF spermatozoa capacitation and movement were stimulated with 10 μg/ml heparin and PHE (20 μM penicillamine - 10 μM hypotaurine – 1 μM epinephrine), respectively. After fertilization, presumptive zygotes were cultured in G1/G2 media  supplemented with fatty-acid-free bovine serum albumin (4 mg/ml) at 38.5 °C in maximal humidity in an atmosphere of 5% O2 and 5% CO2. Cleavage rates of oocytes were recorded at 30 and 42 h post insemination. The number and quality of blastocysts were recorded at day 8 and 9 (IVF = day 0).n = 2) and 17 paternal half-sibs of the affected bulls. Genotypes for these 119 bulls were also determined using the Illumina BovineSNP50 Bead chip comprising genotypes at 54,001 (version 1) or 54,609 SNPs (version 2). The chromosomal positions of the SNPs corresponded to the University of Maryland reference sequence of the bovine genome (UMD3.1) [Beagle [plink binary format [The two asthenospermic bulls were genotyped at 54,001 SNPs using the Illumina BovineSNP50 Bead chip using DNA purified from semen samples following standard DNA extraction protocols. To facilitate haplotype inference, we also considered genotypes of 119 fertile bulls from the Nordic Red dairy cattle breed, including the sires ((UMD3.1) . Followiy format  (.bed/.bhomozyg-function that was implemented in the plink (version 1.9) software tool [(--homozyg-kb 500) and at least 20 contiguous homozygous SNPs (--homozyg-snp 20) as ROH. ROH were identified within sliding windows of 40 SNPs (--homozyg-window-snp 40). For the identification of ROH, no heterozygous SNP were allowed within ROH (--homozyg-het 0). The R script that was used to identify and visualize ROH is available as Additional file Runs of homozygosity (ROH) were identified in both asthenospermic bulls using the are tool . Due to Genotypes contained in ROH in both asthenospermic bulls were manually inspected in order to determine whether the bulls were identical by descent (IBD) for the same haplotype . In regions where both affected bulls were IBD, the haplotypes of 119 fertile bulls (see above) were also inspected. Assuming recessive inheritance of a deleterious mutation, we considered IBD haplotypes as associated with asthenospermia if they were not detected in the homozygous state in 119 fertile bulls.http://www.ebi.ac.uk/ena) under primary accession number PRJEB29487. The raw sequencing reads were trimmed and filtered using fastp (version 0.19.4) [BWA mem algorithm (version 0.7.13) [SAMtools (version 1.8) [MarkDuplicates command of the Picard tools software suite (https://broadinstitute.github.io/picard/). Polymorphic sequence variants were identified using the Genome Analysis Toolkit  [Mosdepth software [Genomic DNA was prepared from semen samples of the two asthenospermic bulls according to standard DNA extraction protocols. Paired-end libraries were prepared using the paired-end TruSeq DNA sample preparation kit (Illumina) and sequenced using a HiSeq 2500 instrument (Illumina). We collected 252 and 270 million paired-end reads (125 base pairs) corresponding to an average (raw) genome coverage of 12- and 13-fold, respectively. The raw sequencing data of both asthenospermic bulls are available at the European Nucleotide Archive (ENA) ( 0.19.4)  using th 0.7.13) . Individion 1.8) . Duplicaion 4.0) . Sequencsoftware .Variant Effect Predictor (VEP) [Assuming that both bulls with asthenospermia were homozygous for the same recessively inherited variant, we screened the sequence data of the affected bulls for variants that were: a) located within the 2.98-Mb segment of autozygosity, b) homozygous for the non-reference allele in both bulls and c) never observed in the homozygous state in a control group of 237 animals from breeds other than Nordic Red dairy cattle that were obtained from Schwarzenbacher et al. . 126 varor (VEP)  tool. Geor (VEP) .CCDC189 (transcript-ID: ENSBTAT00000045037) in 118 sires that were either identified as heterozygous carriers of the asthenospermia-associated haplotype (N = 30) or have been used frequently in AI (N = 88). PCR reactions for genotyping were done with the DyNAzyme II DNA Polymerase  in a 10 μl volume of 1x PCR buffer, 0.2 mM dNTPs, 10 pmol primer mix (forward 5′- CAAGGTCCTGCCCTTAAGAA -3′) and reverse primer: (reverse 5′- ATGCCATCACTCTGGACCTC-3′) and 150 pg of DNA. The cycling conditions were the following: a) an initial denaturation at 95 °C for 3 min, b) 29 cycles of 30 s denaturation (94 °C), 30 s hybridization (58 °C), 30 s elongation (72 °C), and c) a final 3 min elongation (72 °C). PCR products were purified and directly sequenced using the BigDye Terminator Cycle Sequencing Kit . Electrophoresis of sequencing reactions was performed on 3500xL Genetic Analyzers , and sequences were visualized with Sequencher 5.4.6 .We estimated the frequency of the asthenospermia-associated haplotype in 8557 Nordic Red cattle from the Nordic genomic selection reference population that had been genotyped at more than 50,000 SNPs . Using SCCDC189 splice donor variant (GCA_000003055.3:Chr25:g.27138357C > T) and two control bulls that were homozygous for the wild type allele was extracted from testis tissues using the RNeasy Mini Kit (Qiagen) following manufacturer’s instructions. The quality and concentration of total RNA was analysed using Agilent’s 2100 Bioanalyzer and the Nanodrop ND-2000 spectrophotometer (Thermo Scientific). An amount of 500 ng of total RNA from each sample was reversely transcribed using QuantiTech Rev. Transcription kit (Qiagen). PCR reactions were done with the DyNAzyme II DNA Polymerase  in a 30 μl volume of 1 x PCR buffer, 0.2 mM dNTPs, 10 pmol primer mix (forward 5′-ACTGAGGAGATGAGGGAGGT-3′ and reverse primer: reverse 5′- TAGAGCTTGAAGTGGCGGAA-3′) and 50 ng of cDNA. The cycling conditions were the following: 1) an initial denaturation at 95 °C for 3 min, 2) 35 cycles of 30 s denaturation (94 °C), 30 s hybridization (61.8 °C), 1 min elongation (72 °C) and 3) a final 3 min elongation (72 °C). PCR products were separated on a 4% agarose gel and the length of the products was analysed using the Image Lab version 5.0 software (Bio-Rad Laboratories). PCR products were purified with QIAquick Gel Extraction kit (QIAgen) and sequenced using the BigDye Terminator Cycle Sequencing Kit . Electrophoresis of sequencing reactions was performed on 3500xL Genetic Analyzer , and sequences were visualized with Sequencher 5.4.6 .Total RNA from two bulls homozygous for the Additional file 3:Pedigree of two asthenospermic bulls. Pedigree of two affected bulls. Ovals and boxes represent female and male ancestors, respectively. The grey box highlights the most recent common ancestor (MRCA) that was present on both the maternal and paternal ancestry of both asthenospermic bulls. (PNG 199 kb)Additional file 4:plink binary format. The positions of the SNP correspond to the UMD3.1 assembly of the bovine genome. (ZIP 459 kb)Genotypes of two asthenospermic bulls. Genotypes at 41,594 SNPs for two asthenospermic bulls in Additional file 5:plink (version 1.9) to identify runs of homozygosity. (TXT 4 kb)R script to identify IBD segments in two asthenospermic bulls. R script to visualize runs of homozygosity in the genotype data of two asthenospermic bulls. This program uses as input the files provided as Additional file Additional file 6:Asthenospermia-associated haplotype. BovineSNP50 SNP identifiers, dbSNP identifiers, positions and asthenospermia-associated alleles of 45 adjacent SNPs of the BovineSNP50 Bead chip. The coding of the alleles is based on the Illumina TOP/BOT format. The chromosomal position of the SNP corresponds to the UMD3.1 assembly of the bovine genome. (CSV 2 kb)Additional file 7:Sequencing depth along chromosome 25 in two asthenospermic bulls. The depth of sequencing coverage in two asthenospermic bulls was calculated at bovine chromosome 25 in sliding windows of 5000 base pairs using the aligned reads. Grey background indicates the segment of extended homozygosity. The red line represents the position of the candidate causal variant- (PNG 604 kb)Additional file 8:Variant Effect Predictor tool. The quality of the sequence variant genotypes for both asthenospermic bulls is shown in columns 7 and 8. The number of heterozygous control animals (out of 237) is shown in column 9. The last column indicates the genotype distribution of 126 candidate causal variants  in 2669 animals of the 1000 bull genomes dataset. (TXT 51 kb)Candidate causal variants compatible with recessive inheritance of asthenospermia. Functional consequences of 126 candidate causal variants that were compatible with recessive inheritance of asthenospermia, i.e., they were homozygous for the alternate allele in two asthenospermic bulls and either heterozygous or homozygous for the reference allele in 237 healthy control animals. Variants were annotated using the Additional file 9:CCDC189. Autozygosity mapping on chromosome 25 (B). Blue and pale blue represent homozygous genotypes (AA and BB), heterozygous genotypes (AB) are displayed in light grey. White color indicates missing genotypes. The red bar indicates a common 2.98-Mb segment that was identical by descent in all four bulls. (PNG 1368 kb)Homozygosity mapping in four asthenospermic bulls. Homozygosity mapping in four asthenospermic bulls (A). Bulls 1 and 2 were already reported in the main part of the manuscript. Bulls 3 and 4 were additionally reported to us because they also produced immotile sperm. However, tissue or semen was not available for bulls 3 and 4. Blue and green color represent runs of homozygosity (ROH) that have been detected in four asthenospermic bulls. The red frame highlights the 2.98-Mb segment located on chromosome 25 that was never found in the homozygous state in normospermic bulls and that carries the splice donor variant in


Hybridization is a biological phenomenon increasingly recognized as an important evolutionary process in both plants and animals, as it is linked to speciation, radiation, extinction, range expansion and invasion, and allows for increased trait diversity in agricultural and horticultural systems. Estimates of hybridization frequency vary across taxonomic groups, but causes of this variation are unknown. Here, we ask on a global scale whether hybridization is linked to any of 11 traits related to plant life history, reproduction, genetic predisposition, and environment or opportunity. Given that hybridization is not evenly distributed across the plant tree of life, we use phylogenetic generalized least squares regression models and phylogenetic path analysis to detect statistical associations between hybridization and plant traits at both the family and genus levels. We find that perenniality and woodiness are each weakly associated with an increased frequency of hybridization in univariate analyses, but path analysis suggests that the direct linkage is between perenniality and increased hybridization . Weak associations between higher rates of hybridization and higher outcrossing rates, abiotic pollination syndromes, vegetative reproductive modes, larger genomes, and less variable genome sizes are detectable in some cases but not others. We argue that correlational evidence at the global scale, such as that presented here, provides a robust framework for forming hypotheses to examine and test drivers of hybridization at a more mechanistic level. Although historically thought of as rare, interspecific mating is increasingly recognized as an important evolutionary process. Hybridization can generate increased genetic and morphological variation and has been tied to increased diversification and other biological phenomena such as geographic range expansion and the success of invasive species. Here, we examine hybridization of plants on a global scale. Previous work has demonstrated that some plant groups hybridize more than others, but the reasons for this pattern remain unclear. We combine data from eight regional floras with trait data to test for associations between hybridization and different aspects of plant biology, such as life history, growth form, reproduction, and opportunity, all while accounting for the fact that plant lineages are related to each other.We find that plant groups that are dominated by perennial species and species with woody growth forms tend to hybridize more than those dominated by annual or herbaceous species. We also find weak evidence that frequent hybridization is found in plant families that are predominantly pollinated abiotically (such as by wind or water) or have higher rates of outcrossing, plant genera that have less variable genome sizes, and plant groups (both genera and families) that can reproduce asexually and have larger genome sizes. This study provides the first analysis of the global correlates of hybridization in plants. Although this correlational evidence does not provide any mechanistic explanations for these patterns, the trends we find are novel in terms of both geographic and taxonomic scale. The correlations detected provide robust hypotheses for understanding the conditions for hybridization and its contributions to evolution.Hybridization is increasingly recognized as an important evolutionary phenomenon in plants Mallet , animalsThere is evidence for hybridization in unexpected situations, for instance between distantly related species  to accommodate taxonomic changes since the publication of the floras.Only native and naturalized taxa were considered. Taxa clearly resulting from anthropogenic crosses  and taxa only in cultivation were ignored. We tallied intra‐ and intergeneric hybrids separately, and the latter were split between genera . We did not count hybrids among subspecies or probable primary intergradation  was also excluded. This resulted in a final sample size of 195 families for the family‐level analysis. For the genus‐level analysis, we were unable to place 34 genera in the phylogeny (see below), resulting in a final sample size of 1772 genera Table .n nonhybrid species:For completeness and comparability, we characterized hybridization for each family or group using two metrics: hybridization propensity and hybrid ratio. Hybridization propensity reflects the realized percentage of all possible hybrid combinations and is calculated as in Whitney et al. . For a tN is used as the denominator as a correction for opportunity, as the presence of more nonhybrid species means more opportunities to form both intra‐ and intergeneric hybrids. For a taxonomic group (genus) of n nonhybrid species:Although it is unrealistic that every pair of species within a group hybridizes . For each genus, numbers of both nonhybrids and hybrids were calculated by summing hybrid counts across all floras analyzed. No attempt was made to avoid “double counting” of hybrids formed from the same parents in different regions. Thus, each metric incorporates information on both the number of hybridizing taxa and the frequency with which they hybridize in different regions. Genus‐level metrics were calculated based on the observations across all floras, while family‐level metrics were weighted means of metrics of the component genera (weighted by species number in each genus). Both hybridization propensity and hybrid ratio measures were log‐transformed prior to analysis to more closely match assumptions of normality.The number of annual, biennial, and perennial species, and the number of herbaceous versus woody species were summed for each genus in each flora. The floras provided remarkably complete data on these variables (>95% species covered), but missing data on perenniality and woodiness of the species were determined from other sources . Species described as intermediate  were split between categories . Species were considered woody if they were characterized by substantial aboveground woody biomass, for example, “trees,” “shrubs,” “subshrubs,” “woody vines,” and “lianas.” Species with rootstocks as the only woody parts were considered herbaceous. For genus and family‐level analyses, we used the percentage of species scored as perennial and the percentage of species scored as perennial as our trait data Table .Data for several traits were downloaded from the TRY database . We assessed threatened status using data from the Red List  (Table P < 0.001) and a lower, but still significant, measure of phylogenetic signal in hybrid ratio   and for hybrid ratio was 0.086 (range = 0–1.196) Fig. . At the 1) Table . There wP < 0.001) (Table P < 0.001) and hybrid ratio  at the genus level  and for hybrid ratio was 0.060 (range = 0–1.609) Table . At the 1) Table . We alsoWe assessed 11 potential correlates of hybridization using data from the floras as well as other sources Table .P < 0.05) linking abiotic pollination syndrome to increased hybridization propensity and a trend (0.05 < P < 0.10) for links between both higher outcrossing rates and larger genome sizes and hybridization propensity  between less variable genome sizes and increased hybridization propensity and a significant association (after correcting for multiple comparisons) between more vegetative reproductive systems and hybridization propensity. There were trends for genera with more vegetative reproductive systems and larger genome sizes to have higher values of hybrid ratio , we examined relationships between hybridization and both perenniality and woodiness using phylogenetic path analyses Fig. . At bothFor comparative purposes, we present raw correlations in the Supporting Information table. Several relationships between traits and hybridization rate or propensity were detected in the raw analyses that were not detected in the phylogenetically corrected analyses, emphasizing the importance of examining these relationships in a phylogenetic context Table .formation of hybrids, followed by traits that may allow for the persistence of hybrids.Hybridization is not evenly distributed across the phylogenetic tree of life  mean that plants need to reproduce with another individual, necessitating the transfer of pollen, and increasing the odds of contacting and reproducing with another species when compared to selfing  or, conversely, increased fitness (heterosis). The persistence of a hybrid lineage could be linked to either overcoming the latter or sustaining the former (stabilized heterosis). Long lifespans  may allow hybrid individuals with partial sterility to still have high levels of lifetime fitness, as a small number of viable seeds produced over multiple seasons can result in many offspring over time  should result in acceleration of the loss of heterosis due to a rapid reduction in heterozygosity  tend to have stronger reproductive barriers between them than lineages that are more closely related (less time since divergence) (Coyne and Orr Our measures of hybridization were based on the number of unique hybrid combinations produced, either as a proportion of potential hybrid combinations or simply using the number of nonhybrid species as a denominator. Our findings using both hybridization propensity and hybrid ratio were largely consistent. Not only were they significantly correlated at both the family and genus levels Table  but theiAlthough this study examines published floras that span three different continents and one island group, our conclusions may be limited and biased by the geographic extent examined. All but two of our floras are from Europe and mainland North America, with the Victoria, Australia and Hawai'i floras representing the Pacific Region. Four of the floras are from mainland North America, and these include almost half of all species observations Table . To expaWe collected data on hybridization using a method suited to their detection in regional floras. There is increasing evidence for instances of hybridization that are not necessarily morphologically apparent but are inferred using genetic or molecular evidence (i.e., Cronn and Wendel R2 values, Table We found several phylogenetically informed associations between hybridization rates and plant attributes. Perenniality and woodiness across taxonomic levels, higher outcrossing rates and abiotic pollination syndromes at the family level, and less variable genome sizes at the genus level all associated with increased hybridization metrics and may be acting by increasing the formation of hybrids. Additionally, the associations between increased hybridization and perenniality, woodiness, outcrossing, and genome size, as well as more vegetative reproductive systems at the genus level, may be due to these factors increasing the persistence of hybrids that have already formed. We recognize that this evidence is correlational in nature and does not provide any causal inferences. Moreover, the explanatory power of our models was extremely low (as measured by adjusted Associate Editor: S. WrightFigure S1.Click here for additional data file.Table S1. Potential mechanisms underlying proposed associations between traits and hybridization.Table S2. Summary hybridization data collected from floras.Table S3. Summary information for trait data used in this study.Table S4. Raw correlations among traits and measures of hybridization.Table S5. Phylogenetic path analysis model summaries.Table S6. Phylogenetic path analysis model coefficients.Click here for additional data file.


Odocoileus virginianus) in 2017. This is the second report of mobuck virus in the United States and expands the known geographic range of this novel orbivirus into Florida.Here, we report the complete genome sequence of mobuck virus isolated from a Florida white-tailed deer ( Odocoileus virginianus) in 2017. This is the second report of mobuck virus in the United States and expands the known geographic range of this novel orbivirus into Florida.Here, we report the complete genome sequence of mobuck virus isolated from a Florida white-tailed deer ( Reoviridae is a diverse assemblage of nonenveloped double-stranded RNA viruses, some of which are notable human and veterinary pathogens. The genomes of reoviruses consist of 10 to 12 segments, encoding structural and nonstructural proteins  cells. The viral RNA was extracted and sequenced on an Illumina MiSeq sequencer as previously described  sequences (GenBank accession no. MNAF00000000) by using Kraken v1.0 , performed in CLC Genomic Workbench v10.1.1 against a custom virus database created from virus protein sequences retrieved from the UniProt Knowledgebase (https://www.uniprot.org/uniprot/), revealed that EHDV serotype 2 (EHDV-2) and mobuck virus (MBV) were present. The total length of the complete coding sequences of the 10 mobuck virus strain OV612 (MBV-OV612) segments was 18,792 bp , with a G+C content of 39.50%. After mosquito sequences were removed by Kraken, the quality of the assembly was determined by mapping the reads back to the MBV-OV612 complete coding sequences using Bowtie 2  that was suspected of having hemorrhagic disease. The presence of epizootic hemorrhagic disease virus (EHDV) genomic RNA in the homogenized spleen specimen was detected by reverse transcription-PCR (RT-PCR) (ken v1.0 , de novorameters . BLASTX Bowtie 2 . The aveMBV has been proposed as the prototype of a new species in the mosquito-borne clade of orbiviruses . Both MBMH801195 to MH801204 and SRP169613, respectively.The genome sequences for MBV-OV612 and raw sequence data have been deposited in NCBI GenBank and Sequence Read Archive under accession no.


Viruses are closely related to bacteria and human diseases. It is of great significance to predict associations between viruses and hosts for understanding the dynamics and complex functional networks in microbial community. With the rapid development of the metagenomics sequencing, some methods based on sequence similarity and genomic homology have been used to predict associations between viruses and hosts. However, the known virus-host association network was ignored in these methods.Escherichia coli is also predicted.We proposed a kernelized logistic matrix factorization with integrating different information to predict potential virus-host associations on the heterogeneous network (ILMF-VH) which is constructed by connecting a virus network with a host network based on known virus-host associations. The virus network is constructed based on oligonucleotide frequency measurement, and the host network is constructed by integrating oligonucleotide frequency similarity and Gaussian interaction profile kernel similarity through similarity network fusion. The host prediction accuracy of our method is better than other methods. In addition, case studies show that the host of crAssphage predicted by ILMF-VH is consistent with presumed host in previous studies, and another potential host The proposed model is an effective computational tool for predicting interactions between viruses and hosts effectively, and it has great potential for discovering novel hosts of viruses. The two main components of human microbes are bacterial and viral communities, which play a vital role in human health and diseases. Bacterial communities have been proved to be associated with human diseases, including some skin conditions  and gastThe traditional approach for identifying viruses has been implemented by isolating from cultured host strains, because viruses are acquired from cultured host cells, we can directly know the host of the given virus. However, culturing a virus at a high enough concentration may be challenging in experiments because it may require appropriate growth conditions, such as temperature, growth media as well as robust growth of target host strains , which iRecognizing hosts infected by viruses is important for understanding dynamics of viruses and their effects on microbial communities. Recently, some computational methods have been used to infer associations between viruses and hosts. Edwards  et al. ind hosts . This meentclass1pt{minimand hosts , which cBacteroides obtained from previous studies [Escherichia coli is also suggested. Because previous studies have shown that Escherichia coli is associated with human intestinal diseases, such as diarrhea [In this paper, we propose a logistic matrix factorization algorithm based on integrating multi-information on the heterogeneous network to predict potential virus-host associations (ILMF-VH). The main differences from previous studies are that our proposed method combines information of three networks to form a virus-host heterogeneous network and applies similar network fusion (SNF) to integrate multiple host information for constructing the host-host similarity network. We used the benchmark data of viral and bacterial genomes in NCBI, and verified that ILMF-VH obtained best performance compared with recent five network-based methods under five-fold cross validation. Moreover, the host prediction accuracy is 63.66% which is 24.66 and 13.29% higher than two recently proposed virus-host association prediction methods respectively, and it is 0.49% higher than our previous approach . In addi studies , and anodiarrhea , our resWe used the data adopted by Ahlgren et al. which collected accession numbers and taxonomies of 1427 viruses and 31,986 hosts. For the initial analysis, we selected a subset including 352 viruses whose hosts were at strain level . In addiNv and Nh represent the number of viruses and hosts, respectively. The associations between viruses and hosts are defined as an adjacency matrix vi is known to be associated with a host hj, then yij is set to 1; otherwise, yij is set to 0. In terms of elements in the adjacency matrix Y, the negative and positive interactions between viruses and hosts are represented by 0 and 1, respectively. In this work, firstly, we define a set of viruses which are positively related to hosts as V− = V\V+. Next, a set of hosts which are positively related to viruses is defined as H− = H\H+. Finally, similarities between viruses are calculated by oligonucleotide frequency (ONF) measures and expressed by As for our model, the virus set and host set are represented by k is set to 6, so we calculate the distance between k-mer frequency vectors of each pair of viruses or hosts. Finally, the virus-virus similarity matrix Sv and the host-host similarity matrix S(onf)h can be obtained.Recently, dissimilarity measurements based on k-mer frequencies have been applied to infer relationships between genomic sequences . Here, bument}d2∗ has a goIP(hi) of host hiis the i-th column of the adjacency matrix Y, which is a binary relationship vector representing associations between a host hiand each virus. The GIP kernel similarity between host hiand hj is calculated from their interaction profiles and defined as [Zou et al.  calculatfined as :1\documγh is used to control the kernel bandwidth and defined as:This is a kernel that represents the similarities between hosts. These kernels are called Gaussian kernels. The parameter Nh is the number of hosts. According to the previous study [Here, us study , we simpNh × Nh matrix Sh, respectively. Then, as for each similarity network, a normalized weight matrix p can be obtained by the following formula [The associations between hosts are measured by calculating ONF measures and GIP kernel similarity between hosts, respectively. Here, we introduce similar network fusion (SNF)  to integ formula :3\documS is the matrix element of Sh. Then, k nearest neighbor (KNN) is used to measure the local relationship as follows:Here Ni represents the number of neighbors in the host. This method filters out low-similar edges.Pv)( and KNNv) represents the ONF similarity between each pair of virus and host, and we integrate this sequence similarity information into the associated probability pij, which represents association probability of virus-host pair  and is defined as the logistic function:We developed a kernelized logistic matrix factorization algorithm based on network similarity fusion for predicting virus-host associations, and the flowchart of ILMF-VH model is shown in the Fig. c is set to 5. The conditional probability of Y is defined as:It is hypothesized that known relationships between viruses and hosts provide useful information for virus-host association prediction. Current importance weighting methods have been proven to be effective for personalized recommendations and drug-target interaction predictions , 28. We vi and host hi are defined as N(vi) ∈ V\vi and N(hj) ∈ H\hi, N(vi) and N(hi) represent the K1 neighbors of the virus vi or the host hi, respectively. K1 is set to 5 according to the experiment. The neighborhood information of viruses and hosts is represented by the adjacency matrices A and B, respectively. In terms of matrix A, if virus vm ∈ N(vi),aim = 0; in terms of matrix B, if host hn ∈ N(hj),bjn = 0 . The main purpose of virus-host association prediction is to minimize distances between vi/hi and nearest neighbors N(vi)/N(hi). We should try to minimize the following objective formula:In this work, we also use the neighborhood regularization method to regularize the logistic matrix factorization algorithm . The neaDv is Dh are Where tr(∙) is the trace of the matrix, σv and σh are expressed as the variance of Gaussian distribution of viruses and hosts, respectively. ‖∙‖F represents the Frobenius norm of the matrix, and W and H are randomly initialized using a Gaussian distribution with a mean of 0 and standard deviation of Where lgorithm  to solveW and H, vectors of the negative virus group or host group are learned only based on negative associations in the training process. However, some unknown virus-host associations may exist potential correlations. Based on previous studies, we replaced the vector of a negative virus/host with a linear combination of its neighbors in the positive set [K2 nearest neighbor sets for each virus and host separately and K2 is set to 5, according to the experimental study. We use N+(vi)/N+(hj) to express K2 nearest neighbors of vi ∈ V−/hj ∈ H− in V+/H+ . Therefore, wi and hj in Eq.  of SNF model on AUPR values  between the virus and all candidate hosts. Therefore, sequence alignment is an important part of extracting virus-host association signal, and it provides an efficient contribution indicator for this prediction result.Our approach supports the previous conclusion that candidate hosts belonging to Escherichia coli is also inferred. Recent studies have shown that [Escherichia coli strains grow harmlessly in the gut and rarely cause diseases in healthy individuals. However, many pathogenic strains can cause diarrhea or extraintestinal disease in both healthy and immunocompromised individuals. Our experimental results suggest that crAssphage may play an important role in these diseases. In general, our algorithmic model is effective in predicting potential hosts of new viruses.Our algorithm predicted host of crAssphage based on the metagenomics sequencing data, which is identical to the putative host at phylum level in previous studies. In addition, another potential host own that  most EscViral infection usually results in changes in the ecosystem function of host cells. Virus-host association studies can reveal complex virus-host network interactions and are important for understanding of microorganism diversity. Despite this, although some methods for virus-host association prediction have been proposed, the host prediction accuracy at the species level cannot be achieved very well and these methods need to be improved.Escherichia coli is associated with intestinal diseases. In general, it is important to study virus-host associations. Our research not only has potential to predict hosts of viruses, but also can be applied to predict virus-host associations.We present an effective method ILMF-VH for predicting virus-host associations. We performed the best performance compared to recent five network-based methods by five-fold cross-validation. Secondly, we compared the host prediction accuracy with several recently proposed virus-host association prediction methods , 17. OurAlthough some results have been achieved so far, there are still some problems that can be further studied in the future. First, the biology characteristics of viruses and hosts are abundant and varied. Apart from whole genome sequences, protein, amino acid, abundance profile and other related information might also have contribution to the prediction model. It needs further research to study what information provides a reliable basis for virus-host association prediction, and extracting appropriate characteristics of viruses and hosts are important for predicting results. Here, we integrate genome sequence information and known virus-host associations. In the future researches, we will consider adding different information sources of viruses and hosts to analyze impacts of different characteristics on prediction results.Additional file 1: Figure S1. The trend chart of AUPR values vary with the factorization factor k. Figure S2. The trend chart of AUPR values vary with regularization parameters α and β. Figure S3. The trend chart of AUPR values vary with the inverse of the variance λ. Figure S4. The trend chart of AUPR values vary with the learning rate parameter γ. Figure S5. The trend chart of AUPR values vary with the neighbor number parameter K.


Influenza is a major global public health threat as a result of its highly pathogenic variants, large zoonotic reservoir, and pandemic potential. Metagenomic viral sequencing offers the potential for a diagnostic test for influenza virus which also provides insights on transmission, evolution, and drug resistance and simultaneously detects other viruses. We therefore set out to apply the Oxford Nanopore Technologies sequencing method to metagenomic sequencing of respiratory samples. 2 to 103 genome copies/ml in pooled samples, observing a strong relationship between the viral titer and the proportion of influenza virus reads (P = 4.7 × 10−5). Applying our methods to clinical throat swabs, we generated influenza virus reads for 27/27 samples with mid-to-high viral titers  and 6/13 samples with low viral titers . No false-positive reads were generated from 10 influenza virus-negative samples. Thus, Nanopore sequencing operated with 83% sensitivity  and 100% specificity  compared to the current diagnostic standard. Coverage of full-length virus was dependent on sample composition, being negatively influenced by increased host and bacterial reads. However, at high influenza virus titers, we were able to reconstruct >99% complete sequences for all eight gene segments. We also detected a human coronavirus coinfection in one clinical sample. While further optimization is required to improve sensitivity, this approach shows promise for the Nanopore platform to be used in the diagnosis and genetic analysis of influenza virus and other respiratory viruses.Influenza is a major global public health threat as a result of its highly pathogenic variants, large zoonotic reservoir, and pandemic potential. Metagenomic viral sequencing offers the potential for a diagnostic test for influenza virus which also provides insights on transmission, evolution, and drug resistance and simultaneously detects other viruses. We therefore set out to apply the Oxford Nanopore Technologies sequencing method to metagenomic sequencing of respiratory samples. We generated influenza virus reads down to a limit of detection of 10 Influenza A virus is an RNA orthomyxovirus of approximately 13 kb in length, with an eight-segment genome. It is typically classified on the basis of hemagglutinin (HA) and neuraminidase (NA), of which there are 16 and 9 main variants, respectively  and for 3–Currently, most clinical diagnostic tests for influenza virus depend on detecting viral antigen or on PCR amplification of viral nucleic acid derived from respiratory samples . These t15–in vitro culture system, producing full-length genome sequences through direct RNA sequencing (The application of Oxford Nanopore Technologies (ONT) sequencing to generate full-length influenza virus sequences from clinical respiratory samples can address these challenges. ONT offers a “third-generation,” portable, real-time approach to generating long-read single-molecule sequence data, with demonstrated success across a range of viruses , 22–24. 22–quencing , or usinquencing  or influquencing .We therefore aimed to optimize a metagenomic protocol for detecting influenza viruses directly from clinical samples using Nanopore sequencing. We determine its sensitivity compared to that of existing diagnostic methods and its accuracy compared to short-read (Illumina) sequencing, using clinical samples from hospital patients during an influenza season and samples from a controlled laboratory infection in ferrets. Further optimization is required before the Nanopore method can be rolled out as a diagnostic test, but we highlight the potential impact of this technology in advancing molecular diagnostics for respiratory pathogens.TC]) were generated by the GeneXpert assay, and we used the influenza virus TC value to estimate the viral titers in clinical samples. Using the GeneXpert assay, up to 40 PCR cycles are performed before a sample is called negative . Quantification was not available for the BioFire results.We collected respiratory samples from the clinical microbiology laboratory at Oxford University Hospitals NHS Foundation Trust, a large tertiary referral teaching hospital in Southeast England. We worked with anonymized residual material from throat and nose swabs generated as a result of routine clinical investigations between January and May 2018. Samples were collected using a sterile polyester swab inoculated into 1 to 3 ml of sterile viral transport medium (VTM), using a standard approach described on the CDC website . During TC values . For the individual negative samples, we selected 10 individual throat swab samples that were influenza virus negative.For methodological assessment, we focused on four categories of samples, as follows: positive pool, negative pools, individual positive samples, and individual negative samples. For the positive pool, we pooled 19 throat swab samples that had tested positive for influenza A virus in the clinical diagnostic laboratory to provide a large enough sample to assess reproducibility . For theWe quantified viral titers in Hazara virus stocks and pooled influenza A virus-positive throat swabs by quantitative reverse transcription-PCR (qRT-PCR), using previously described assays and standards , 30.g for 2 min). cDNA libraries for this comparison were produced as described previously  before further processing versus using a hard spin  with a trisegmented genome of 11,980, 4,575, and 1,677 nucleotides in length (GenBank accession numbers KP406723 to KP406725). It is nonpathogenic in humans and would therefore not be anticipated to arise in any of our clinical samples. Cultured virions from an SW13 cell line were provided by the National Collection of Pathogenic Viruses .Prior to nucleic acid extraction, each sample was spiked with Hazara virus virions to a final concentration of 10g for 2 min. The supernatant was eluted without disturbing the pelleted material and was used in nucleic acid extraction. Total nucleic acid was extracted from 100 μl of supernatant using the QIAamp viral RNA kit (Qiagen) eluting in 50 μl of H2O, followed by a DNase treatment with Turbo DNase (Thermo Fisher Scientific) at 37°C for 30 min. RNA was purified and concentrated to 6 μl using the RNA Clean & Concentrator-5 kit (Zymo Research), following the manufacturer’s instructions. Randomly amplified cDNA was prepared for each sample using a sequence-independent single-primer amplification (SISPA) approach, adapted from our previously described workflow  before incubation for 10 min at 42°C. Second-strand synthesis was performed by the addition of 1 μl Sequenase buffer, 3.85 μl H2O, and 0.15 μl Sequenase (Affymetrix) prior to incubation for 8 min at 37°C, followed by the addition of 0.45 μl Sequenase dilution buffer and 0.15 μl Sequenase and a further incubation at 37°C for 8 min. Amplification of cDNA was performed in triplicate using 5 μl of the reaction mixture as input to a 50-μl AccuTaq LA (Sigma) reaction mixture, according to the manufacturer’s instructions, using 1 μl primer B (5′-GTTTCCCACTGGAGGATA-3′)  , with PChttps://www.protocols.io/view/one-pot-ligation-protocol-for-oxford-nanopore-libr-k9acz2e). Libraries were sequenced on FLO-MIN106 flow cells on the MinION Mk1b or GridION device (Oxford Nanopore Technologies), with sequencing proceeding for 48 h. Samples were batched according to the GeneXpert TC value .Multiplex sequencing libraries were prepared using 250 ng of cDNA from up to 12 samples as input to the SQK-LSK108 or SQK-LSK109 kit and barcoded individually using the EXP-NBD103 Native barcodes (Oxford Nanopore Technologies) and a modified One-pot protocol (Nextera XT V2 kit (Illumina) sequencing libraries were prepared using 1.5 ng of amplified cDNA, as per the manufacturer’s instructions, and sequenced on a 2 × 150-bp paired-end Illumina MiSeq run by the Genomics Services Development Unit of Public Health England.https://github.com/rrwick/Porechop). The reads were first taxonomically classified against the RefSeq database using Centrifuge v1.0.3 (https://github.com/pysam-developers/pysam). The subtype of the influenza A virus derived from each clinical sample was determined by the subtypes of the HA and NA reference sequences. A consensus sequence was built using Nanopolish v0.11.0 (https://github.com/zibraproject/zika-pipeline). For the Illumina data, reads were quality trimmed to a minimum score of Q30 across the read with Trimmomatic . Output base called fastq files were demultiplexed using Porechop v0.2.3 . Ferret samples were residual samples from an existing study  for whichttps://www.ebi.ac.uk/) under BioProject number PRJEB32861.Following the removal of human reads, our sequence data have been uploaded to the European Bioinformatics Institute (4 genome copies/ml. Using a sequence-independent single-primer amplification (SISPA) approach (6 genome copies/ml) to provide a large enough sample to assess reproducibility, with the Hazara virus control spiked in at 104 genome copies/ml. Enrichment for influenza virus and Hazara virus was similar for filtration versus centrifugation, based on read mapping to the viral genome . As centrifugation is simpler and less expensive, we selected this approach for all further testing.Our method protocol is shown in approach , followeSynthesis of tagged randomly primed cDNA and its subsequent amplification via SISPA  required6 genome copies/ml), we made three volumetric dilution series using three independent influenza virus-negative pools  of total reads and 1.2 × 103 ± 350 RPM, respectively. The pool 3 dilution series generated 260 ± 340 RPM Hazara virus reads across samples and showed a decreasing trend associated with increased dilution factor as increasingly more nonviral RNA was introduced from this high-background pool.We consistently retrieved Hazara virus reads from all three dilution series by Nanopore sequencing, independently of influenza virus titer in the sample . Sequenc4 ± 3.6 × 104 RPM mapping to the influenza A virus genome  but was also influenced by which negative pool was used for dilution, consistent with the pattern observed for the Hazara virus control. Sequencing the negative controls (pools with no influenza virus spike) generated no reads mapping to influenza virus. At influenza virus titers of <103 copies/ml, influenza virus reads were inconsistently detected across the samples , genome coverage was 81.4 to 99.4% (at 1× depth) for pools 1 and 2. Coverage in the high-background pool 3 was more varied . Within flow cells, barcode performance was inconsistent when using a stringent, dual-barcode, demultiplexing method  (Table S1).Having demonstrated our ability to retrieve influenza virus sequences from pooled influenza virus-positive material diluted with negative samples, we next applied our methods to individual anonymized clinical samples, with 40 samples testing influenza virus positive and 10 samples testing influenza virus negative in the clinical diagnostic laboratory. Data yield varied between flow cells . At a TC of >30, 6/13 samples generated influenza virus reads  . No reads classified as influenza virus were obtained from sequencing the 10 GeneXpert assay-negative samples (Table S1). Based on this small data set, sensitivity is 83% and specificity is 100% . There was a strong correlation between TC value and both the reads per sample classified as influenza virus (R2 = 0.60) and the number of influenza virus reads per million reads (R2 = 0.62) .Reads mapping to either the influenza A or B virus genome were present in all 27 samples with a  = 0.62) . The con4 genome copies/ml) was highly varied, demonstrating that levels of background nontarget RNA are a major source of intersample variation. The number of Hazara virus reads per sample ranged from 0 to 13.5 × 103 (0 to 3.5 × 104 RPM), with a median of 70 reads (160 RPM) and mean of 706 reads (1.7 × 103 RPM) (Table S1). Four (8%) of 50 samples generated no detectable Hazara virus reads, two with high numbers of influenza virus reads  acting to dilute the control signal. The other two samples contained no detectable influenza virus reads . The lack of control detection therefore indicates a loss of assay sensitivity due to high levels of background nucleic acid present in some samples.Detection of the control virus . From 4 of the samples, nearly complete genomes were obtained. A comparison of consensus sequences derived from Nanopore and Illumina sequencing showed 100% concordance, except one sample that showed 7 nucleotide differences  (Table S2).We reconstructed the phylogeny using consensus sequences for the HA gene . This de4 influenza A virus reads, suggesting coinfection. We also derived >4.0 × 104 reads from human metapneumovirus from an influenza virus-negative sample, providing a nearly complete genome (99.8% coverage) from one sample , further detailed previously , demonstrating the ability of metagenomics to produce sufficient data for influenza virus diagnostics and genome characterization, while also detecting and sequencing other common RNA viruses.Whole-genome viral sequencing, coupled with phylogenetic analysis and appropriate clinical metadata, can contribute to the accurate tracking of outbreaks across time and space . The metTC value and applied stringent barcode demultiplexing criteria; however, this reduces the total data available for analysis, typically by ∼50% but with variation between sequencing runs  guidelines  recommenal fluid .TC values in our clinical samples , the sensitivity of Nanopore sequencing was reduced compared to that of the current PCR-based test . Further optimization will be required to maximize the diagnostic yield from this group of samples without sacrificing specificity.At the higher TC value and Nanopore reads confirms semiquantitative output. Using samples from the ferret influenza virus model, collected under standardized laboratory conditions, we demonstrated excellent reproducibility of viral read proportions at a given viral titer across biological replicates. However, we observed heterogeneity in output between clinical samples as well as between Nanopore flow cells, suggesting that the current platform is not yet sufficiently reliable for reproducibly generating quantitative data. In addition, the detection of positive controls can be impaired in high-background samples.The correlation between Future application of this method will involve real-time laboratory testing of respiratory samples, running the platform head to head with existing clinical diagnostics to further assess sensitivity and specificity, and using influenza virus sequence data to investigate transmission events. Identifying instances of nosocomial transmission may shed light on health care-acquired infection, thus helping to improve infection control practice. Assessment of diversity within deep-sequence data sets provides an opportunity to investigate the relationship between within-host polymorphisms and clinical outcomes. Long-read sequences confer the potential advantage of identifying viral haplotypes and ascertaining the extent to which significant polymorphisms are transmitted together or independently . We haveThe current standard assay for influenza diagnosis employed within the large tertiary referral teaching hospital in which this study was performed is the GeneXpert assay (Cepheid), which detects influenza A and B viruses and respiratory syncytial virus (RSV). Wider testing is performed on a subset of samples using the BioFire FilmArray respiratory panel (bioMérieux), targeted at 20 common respiratory pathogens (17 viruses and 3 bacteria). These assays have the advantages over a metagenomic approach of higher sensitivity, shorter handling times, simpler laboratory workflow, and very rapid time to result . Compared to a metagenomic approach, their limitations are that no sequence data informative for molecular epidemiology and drug resistance typing are generated for the target pathogens, and that the assay will only detect the small number of pathogens targeted. Periodic refinement of such assays is required in the event of newly emergent pathogens or diverse strains of established pathogens leading to assay escape. This is not an issue affecting metagenomic sequencing, which has the ability to detect all RNA viruses in a sequence-independent manner. At the time of undertaking this laboratory work, the materials costs of the metagenomic sequencing were ∼£140 per sample when multiplexing six samples per flow cell and purchasing 48 flow cells together. The cost of the current influenza A/B and RSV GeneXpert test is ∼£56, and the BioFire RP panel costs ∼£139 per sample. The existing tests have the significant advantage of short handling times and simple processing, whereas the metagenomic sequencing requires ∼8 h and skilled laboratory staff.per se. Larger and more diverse data sets will be required to set more rigorous thresholds for base calling. Currently, it is wise to bear such potential issues in mind when comparing genome sequences generated by different technological platforms.Alternative approaches to generate sequence data include amplicon-based sequencing of the influenza virus genome , 52. HowThe per-read differences in base accuracy are also compensated for by the increased read length, providing further confidence in the case of individual read taxonomic assignment. Consideration of relative costs must also take into account other cost-saving attributes. These include the substantially lower infrastructure and startup costs of Nanopore sequencing, the unique ability to interrogate sequence data as they are generated in real time, and the potential for the portable MinION device to be utilized near to patient, potentially decreasing turnaround time, particularly for high-virus-load samples which may be identified within minutes. The throughput of the Nanopore flow cells allows for a small number of samples to be run immediately rather than requiring samples to be batched to reach a number sufficient to cost efficiently run a greater-throughput short-read sequencing device. In the future, the use of an even lower-throughput flow cell with the ONT Flongle adaptor may allow individual samples to be run per cell, offering quicker turnaround per sample and minimizing cross-sample contamination. A summary table comparing the different approaches is included in supplemental material (Table S3).2 genome copies per ml is possible from throat swab samples (a level comparable with PCR-based methods), but variation in the level of background nucleic acids between individual samples makes detection at this level inconsistent. Further development of methods to deplete host and bacterial RNA within the samples is required to improve the performance of the assay at TC values of >30. Enrichment of pathogen sequences within libraries through either target capture or amplification is also an effective method to reduce the limit of target detection (a priori knowledge of both which pathogens are to be targeted and the full range of circulating viral diversity as other targeted methods discussed above, albeit with increased tolerance for diversity over PCR-based methods. A further limitation compared to alternative sequencing technologies is the lack of confidence in determining the presence of minority variants due to the limited per-read accuracy, although we expect this to be addressed in future iterations of the ONT sequencing.The current limitations of metagenomic methods are their sensitivity in the context of low-pathogen-titer samples. PCR-based methods measure the absolute count of viral genome copies present within a sample. Metagenomic sequencing measures the proportion of total RNA that is viral. Metagenomic sequencing is therefore affected by the level of nontarget RNA within a given sample, whereas PCR is not. As demonstrated here , detectietection , 55 but In summary, while substantial further work is needed, our methods show promise for generating influenza virus sequences directly from respiratory samples. The “pathogen-agnostic” metagenomic sequencing approach offers an opportunity for simultaneous testing for a wide range of potential pathogens, providing a faster route to optimum treatment and contributing to antimicrobial stewardship. Longer term, this approach has promise as a routine laboratory test, providing data to inform treatment, vaccine design and deployment, infection control policies, and surveillance.