151 research outputs found
Metagenomic analysis of viruses associated with maize lethal necrosis in Kenya
Background: Maize lethal necrosis is caused by a synergistic co-infection of Maize chlorotic mottle virus (MCMV) and a specific member of the Potyviridae, such as Sugarcane mosaic virus (SCMV), Wheat streak mosaic virus (WSMV) or Johnson grass mosaic virus (JGMV). Typical maize lethal necrosis symptoms include severe yellowing and leaf drying from the edges. In Kenya, we detected plants showing typical and atypical symptoms. Both groups of plants often tested negative for SCMV by ELISA. Methods: We used next-generation sequencing to identify viruses associated to maize lethal necrosis in Kenya through a metagenomics analysis. Symptomatic and asymptomatic leaf samples were collected from maize and sorghum representing sixteen counties. Results: Complete and partial genomes were assembled for MCMV, SCMV, Maize streak virus (MSV) and Maize yellow dwarf virus-RMV (MYDV-RMV). These four viruses (MCMV, SCMV, MSV and MYDV-RMV) were found together in 30 of 68 samples. A geographic analysis showed that these viruses are widely distributed in Kenya. Phylogenetic analyses of nucleotide sequences showed that MCMV, MYDV-RMV and MSV are similar to isolates from East Africa and other parts of the world. Single nucleotide polymorphism, nucleotide and polyprotein sequence alignments identified three genetically distinct groups of SCMV in Kenya. Variation mapped to sequences at the border of NIb and the coat protein. Partial genome sequences were obtained for other four potyviruses and one polerovirus. Conclusion: Our results uncover the complexity of the maize lethal necrosis epidemic in Kenya. MCMV, SCMV, MSV and MYDV-RMV are widely distributed and infect both maize and sorghum. SCMV population in Kenya is diverse and consists of numerous strains that are genetically different to isolates from other parts of the world. Several potyviruses, and possibly poleroviruses, are also involved
Temperature-Dependent \u3ci\u3eWsm1\u3c/i\u3e and \u3ci\u3eWsm2\u3c/i\u3e Gene-Specific Blockage of Viral Long-Distance Transport Provides Resistance to \u3ci\u3eWheat streak mosaic virus\u3c/i\u3e and \u3ci\u3eTriticum mosaic virus\u3c/i\u3e in Wheat
Wheat streak mosaic virus (WSMV) and Triticum mosaic virus (TriMV) are economically important viral pathogens of wheat. Wheat cvs.Mace, carrying the Wsm1 gene, is resistant toWSMV and TriMV, and Snowmass, with Wsm2, is resistant to WSMV. Viral resistance in both cultivars is temperature sensitive and is effective at 18˚C or below but not at higher temperatures. The underlying mechanisms of viral resistance of Wsm1 and Wsm2, nonallelic single dominant genes, are not known. In this study, we found that fluorescent protein–tagged WSMV and TriMV elicited foci that were approximately similar in number and size at 18 and 24˚C, on inoculated leaves of resistant and susceptible wheat cultivars. These data suggest that resistant wheat cultivars at 18˚C facilitated efficient cell-to-cell movement. Additionally,
WSMV and TriMVefficiently replicated in inoculated leaves of resistant wheat cultivars at 18˚C but failed to establish systemic infection, suggesting that Wsm1- and Wsm2-mediated resistance debilitated viral long-distance transport. Furthermore, we found that neither virus was able to enter the leaf sheaths of inoculated leaves or crowns of resistant wheat cultivars at 18˚C but both were able to do so at 24˚C. Thus, wheat cvs.Mace and Snowmass provide resistance at the long-distance movement stage by specifically blocking virus entry into the vasculature. Taken together, these data suggest that both Wsm1 and Wsm2 genes similarly confer virus resistance by temperature-dependent impairment of viral long-distance movement
Impact of KRAS mutation status on the efficacy of immunotherapy in lung cancer brain metastases
Immune checkpoint inhibitors (ICIs) have resulted in improved outcomes in non-small cell lung cancer (NSCLC) patients. However, data demonstrating the efficacy of ICIs in NSCLC brain metastases (NSCLCBM) is limited. We analyzed overall survival (OS) in patients with NSCLCBM treated with ICIs within 90 days of NSCLCBM diagnosis (ICI-90) and compared them to patients who never received ICIs (no-ICI). We reviewed 800 patients with LCBM who were diagnosed between 2010 and 2019 at a major tertiary care institution, 97% of whom received stereotactic radiosurgery (SRS) for local treatment of BM. OS from BM was compared between the ICI-90 and no-ICI groups using the Log-Rank test and Cox proportional-hazards model. Additionally, the impact of KRAS mutational status on the efficacy of ICI was investigated. After accounting for known prognostic factors, ICI-90 in addition to SRS led to significantly improved OS compared to no-ICI (12.5 months vs 9.1, p \u3c 0.001). In the 109 patients who had both a known PD-L1 expression and KRAS status, 80.4% of patients with KRAS mutation had PD-L1 expression vs 61.9% in wild-type KRAS patients (p = 0.04). In patients without a KRAS mutation, there was no difference in OS between the ICI-90 vs no-ICI cohort with a one-year survival of 60.2% vs 54.8% (p = 0.84). However, in patients with a KRAS mutation, ICI-90 led to a one-year survival of 60.4% vs 34.1% (p = 0.004). Patients with NSCLCBM who received ICI-90 had improved OS compared to no-ICI patients. Additionally, this benefit appears to be observed primarily in patients with KRAS mutations that may drive the overall benefit, which should be taken into account in the development of future trials
Conservation of Gene Order and Content in the Circular Chromosomes of ‘Candidatus Liberibacter asiaticus’ and Other Rhizobiales
‘Ca. Liberibacter asiaticus,’ an insect-vectored, obligate intracellular bacterium associated with citrus-greening disease, also called “HLB," is a member of the Rhizobiales along with nitrogen-fixing microsymbionts Sinorhizobium meliloti and Bradyrhizobium japonicum, plant pathogen Agrobacterium tumefaciens and facultative intracellular mammalian pathogen Bartonella henselae. Comparative analyses of their circular chromosomes identified 514 orthologous genes shared among all five species. Shared among all five species are 50 identical blocks of microsyntenous orthologous genes (MOGs), containing a total of 283 genes. While retaining highly conserved genomic blocks of microsynteny, divergent evolution, horizontal gene transfer and niche specialization have disrupted macrosynteny among the five circular chromosomes compared. Highly conserved microsyntenous gene clusters help define the Rhizobiales, an order previously defined by 16S RNA gene similarity and herein represented by the three families: Bartonellaceae, Bradyrhizobiaceae and Rhizobiaceae. Genes without orthologs in the other four species help define individual species. The circular chromosomes of each of the five Rhizobiales species examined had genes lacking orthologs in the other four species. For example, 63 proteins are encoded by genes of ‘Ca. Liberibacter asiaticus’ not shared with other members of the Rhizobiales. Of these 63 proteins, 17 have predicted functions related to DNA replication or RNA transcription, and some of these may have roles related to low genomic GC content. An additional 17 proteins have predicted functions relevant to cellular processes, particularly modifications of the cell surface. Seventeen unshared proteins have specific metabolic functions including a pathway to synthesize cholesterol encoded by a seven-gene operon. The remaining 12 proteins encoded by ‘Ca. Liberibacter asiaticus’ genes not shared with other Rhizobiales are of bacteriophage origin. ‘Ca. Liberibacter asiaticus’ shares 11 genes with only Sinorhizobium meliloti and 12 genes are shared with only Bartonella henselae
A Game-Theoretic Model of Interactions between Hibiscus Latent Singapore Virus and Tobacco Mosaic Virus
Mixed virus infections in plants are common in nature and their interactions affecting host plants would depend mainly on plant species, virus strains, the order of infection and initial amount of inoculum. Hence, the prediction of outcome of virus competition in plants is not easy. In this study, we applied evolutionary game theory to model the interactions between Hibiscus latent Singapore virus (HLSV) and Tobacco mosaic virus (TMV) in Nicotiana benthamiana under co-infection in a plant host. The accumulation of viral RNA was quantified using qPCR at 1, 2 and 8 days post infection (dpi), and two different methods were employed to predict the dominating virus. TMV was predicted to dominate the game in the long run and this prediction was confirmed by both qRT-PCR at 8 dpi and the death of co-infected plants after 15 dpi. In addition, we validated our model by using data reported in the literature. Ten out of fourteen reported co-infection outcomes agreed with our predictions. Explanations were given for the four interactions that did not agree with our model. Hence, it serves as a valuable tool in making long term predictions using short term data obtained in virus co-infections
Two Plant Bacteria, S. meliloti and Ca. Liberibacter asiaticus, Share Functional znuABC Homologues That Encode for a High Affinity Zinc Uptake System
The Znu system, encoded for by znuABC, can be found in multiple genera of bacteria and has been shown to be responsible for the import of zinc under low zinc conditions. Although this high-affinity uptake system is known to be important for both growth and/or pathogenesis in bacteria, it has not been functionally characterized in a plant-associated bacterium. A single homologue of this system has been identified in the plant endosymbiont, Sinorhizobium meliloti, while two homologous systems were found in the destructive citrus pathogen, Candidatus Liberibacter asiaticus. To understand the role of these protein homologues, a complementation assay was devised allowing the individual genes that comprise the system to be assayed independently for their ability to reinstate a partially-inactivated Znu system. Results from the assays have demonstrated that although all of the genes from S. meliloti were able to restore activity, only one of the two Ca. Liberibacter asiaticus encoded gene clusters contained genes that were able to functionally complement the system. Additional analysis of the gene clusters reveals that distinct modes of regulation may also exist between the Ca. Liberibacter asiaticus and S. meliloti import systems despite the intracellular-plant niche common to both of these bacteria
Transcriptome Profiling of Citrus Fruit Response to Huanglongbing Disease
Huanglongbing (HLB) or “citrus greening” is the most destructive citrus disease worldwide. In this work, we studied host responses of citrus to infection with Candidatus Liberibacter asiaticus (CaLas) using next-generation sequencing technologies. A deep mRNA profile was obtained from peel of healthy and HLB-affected fruit. It was followed by pathway and protein-protein network analysis and quantitative real time PCR analysis of highly regulated genes. We identified differentially regulated pathways and constructed networks that provide a deep insight into the metabolism of affected fruit. Data mining revealed that HLB enhanced transcription of genes involved in the light reactions of photosynthesis and in ATP synthesis. Activation of protein degradation and misfolding processes were observed at the transcriptomic level. Transcripts for heat shock proteins were down-regulated at all disease stages, resulting in further protein misfolding. HLB strongly affected pathways involved in source-sink communication, including sucrose and starch metabolism and hormone synthesis and signaling. Transcription of several genes involved in the synthesis and signal transduction of cytokinins and gibberellins was repressed while that of genes involved in ethylene pathways was induced. CaLas infection triggered a response via both the salicylic acid and jasmonic acid pathways and increased the transcript abundance of several members of the WRKY family of transcription factors. Findings focused on the fruit provide valuable insight to understanding the mechanisms of the HLB-induced fruit disorder and eventually developing methods based on small molecule applications to mitigate its devastating effects on fruit production
Emergence and phylodynamics of Citrus tristeza virus in Sicily, Italy
[EN] Citrus tristeza virus (CTV) outbreaks were detected in Sicily island, Italy for the first time in 2002. To gain insight into the evolutionary forces driving the emergence and phylogeography of these CTV populations, we determined and analyzed the nucleotide sequences of the p20 gene from 108 CTV isolates collected from 2002 to 2009. Bayesian phylogenetic analysis revealed that mild and severe CTV isolates belonging to five different clades (lineages) were introduced in Sicily in 2002. Phylogeographic analysis showed that four lineages co-circulated in the main citrus growing area located in Eastern Sicily. However, only one lineage (composed of mild isolates) spread to distant areas of Sicily and was detected after 2007. No correlation was found between genetic variation and citrus host, indicating that citrus cultivars did not exert differential selective pressures on the virus. The genetic variation of CTV was not structured according to geographical location or sampling time, likely due to the multiple introduction events and a complex migration pattern with intense co- and recirculation of different lineages in the same area. The phylogenetic structure, statistical tests of neutrality and comparison of synonymous and nonsynonymous substitution rates suggest that weak negative selection and genetic drift following a rapid expansion may be the main causes of the CTV variability observed today in Sicily. Nonetheless, three adjacent amino acids at the p20 N-terminal region were found to be under positive selection, likely resulting from adaptation events.A.W. and S.F.E. were supported by grant BFU2012-30805 from the Spanish Secretaria de Estado de Investigacion, Desarrollo e Innovacion and by a grant 22371 from the John Templeton Foundation. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Davino, S.; Willemsen, A.; Panno. Stefano; Davino, M.; Catara, A.; Elena Fito, SF.; Rubio, L. (2013). Emergence and phylodynamics of Citrus tristeza virus in Sicily, Italy. PLoS ONE. 8:66700-66700. doi:10.1371/journal.pone.0066700S66700667008Domingo, E., & Holland, J. J. (1997). RNA VIRUS MUTATIONS AND FITNESS FOR SURVIVAL. Annual Review of Microbiology, 51(1), 151-178. doi:10.1146/annurev.micro.51.1.151Grenfell, B. T. (2004). Unifying the Epidemiological and Evolutionary Dynamics of Pathogens. Science, 303(5656), 327-332. doi:10.1126/science.1090727Moya, A., Holmes, E. C., & González-Candelas, F. (2004). The population genetics and evolutionary epidemiology of RNA viruses. Nature Reviews Microbiology, 2(4), 279-288. doi:10.1038/nrmicro863Gray, R. R., Tatem, A. J., Lamers, S., Hou, W., Laeyendecker, O., Serwadda, D., … Salemi, M. (2009). Spatial phylodynamics of HIV-1 epidemic emergence in east Africa. AIDS, 23(14), F9-F17. doi:10.1097/qad.0b013e32832faf61Holmes, E. C. (2008). Evolutionary History and Phylogeography of Human Viruses. Annual Review of Microbiology, 62(1), 307-328. doi:10.1146/annurev.micro.62.081307.162912Pybus, O. G., Suchard, M. A., Lemey, P., Bernardin, F. J., Rambaut, A., Crawford, F. W., … Delwart, E. L. (2012). Unifying the spatial epidemiology and molecular evolution of emerging epidemics. Proceedings of the National Academy of Sciences, 109(37), 15066-15071. doi:10.1073/pnas.1206598109Talbi, C., Lemey, P., Suchard, M. A., Abdelatif, E., Elharrak, M., Jalal, N., … Bourhy, H. (2010). Phylodynamics and Human-Mediated Dispersal of a Zoonotic Virus. PLoS Pathogens, 6(10), e1001166. doi:10.1371/journal.ppat.1001166Vijaykrishna, D., Bahl, J., Riley, S., Duan, L., Zhang, J. X., Chen, H., … Guan, Y. (2008). Evolutionary Dynamics and Emergence of Panzootic H5N1 Influenza Viruses. PLoS Pathogens, 4(9), e1000161. doi:10.1371/journal.ppat.1000161Gómez, P., Sempere, R. N., Aranda, M. A., & Elena, S. F. (2012). Phylodynamics of Pepino mosaic virus in Spain. European Journal of Plant Pathology, 134(3), 445-449. doi:10.1007/s10658-012-0019-0Lefeuvre, P., Martin, D. P., Harkins, G., Lemey, P., Gray, A. J. A., Meredith, S., … Heydarnejad, J. (2010). The Spread of Tomato Yellow Leaf Curl Virus from the Middle East to the World. PLoS Pathogens, 6(10), e1001164. doi:10.1371/journal.ppat.1001164TOMITAKA, Y., & OHSHIMA, K. (2006). A phylogeographical study of the Turnip mosaic virus population in East Asia reveals an ‘emergent’ lineage in Japan. Molecular Ecology, 15(14), 4437-4457. doi:10.1111/j.1365-294x.2006.03094.xWu, B., Blanchard-Letort, A., Liu, Y., Zhou, G., Wang, X., & Elena, S. F. (2011). Dynamics of Molecular Evolution and Phylogeography of Barley yellow dwarf virus-PAV. PLoS ONE, 6(2), e16896. doi:10.1371/journal.pone.0016896MORENO, P., AMBRÓS, S., ALBIACH-MARTÍ, M. R., GUERRI, J., & PEÑA, L. (2008). Citrus tristeza virus: a pathogen that changed the course of the citrus industry. Molecular Plant Pathology, 9(2), 251-268. doi:10.1111/j.1364-3703.2007.00455.xTatineni, S., Robertson, C. J., Garnsey, S. M., & Dawson, W. O. (2011). A plant virus evolved by acquiring multiple nonconserved genes to extend its host range. Proceedings of the National Academy of Sciences, 108(42), 17366-17371. doi:10.1073/pnas.1113227108Folimonova, S. Y. (2012). Superinfection Exclusion Is an Active Virus-Controlled Function That Requires a Specific Viral Protein. Journal of Virology, 86(10), 5554-5561. doi:10.1128/jvi.00310-12Bar-Joseph, M., Marcus, R., & Lee, R. F. (1989). The Continuous Challenge of Citrus Tristeza Virus Control. Annual Review of Phytopathology, 27(1), 291-316. doi:10.1146/annurev.py.27.090189.001451Davino, S., Rubio, L., & Davino, M. (2005). Molecular analysis suggests that recent Citrus tristeza virus outbreaks in Italy were originated by at least two independent introductions. European Journal of Plant Pathology, 111(3), 289-293. doi:10.1007/s10658-003-2815-zAlbiach-Marti, M. R., Mawassi, M., Gowda, S., Satyanarayana, T., Hilf, M. E., Shanker, S., … Dawson, W. O. (2000). Sequences of Citrus Tristeza Virus Separated in Time and Space Are Essentially Identical. Journal of Virology, 74(15), 6856-6865. doi:10.1128/jvi.74.15.6856-6865.2000Rubio, L., Ayllon, M. A., Kong, P., Fernandez, A., Polek, M., Guerri, J., … Falk, B. W. (2001). Genetic Variation of Citrus Tristeza Virus Isolates from California and Spain: Evidence for Mixed Infections and Recombination. Journal of Virology, 75(17), 8054-8062. doi:10.1128/jvi.75.17.8054-8062.2001Silva, G., Marques, N., & Nolasco, G. (2011). The evolutionary rate of citrus tristeza virus ranks among the rates of the slowest RNA viruses. Journal of General Virology, 93(2), 419-429. doi:10.1099/vir.0.036574-0Mawassi, M., Mietkiewska, E., Gofman, R., Yang, G., & Bar-Joseph, M. (1996). Unusual Sequence Relationships Between Two Isolates of Citrus Tristeza Virus. Journal of General Virology, 77(9), 2359-2364. doi:10.1099/0022-1317-77-9-2359Vives, M. C., Dawson, W. O., Flores, R., L√≥pez, C., Albiach-Mart√≠, M. R., Rubio, L., … Moreno, P. (1999). The complete genome sequence of the major component of a mild citrus tristeza virus isolate. Journal of General Virology, 80(3), 811-816. doi:10.1099/0022-1317-80-3-811Martín, S., Elena, S. F., Guerri, J., Moreno, P., Sambade, A., Rubio, L., … Vives, M. C. (2009). Contribution of recombination and selection to molecular evolution of Citrus tristeza virus. Journal of General Virology, 90(6), 1527-1538. doi:10.1099/vir.0.008193-0Vives, M. C., Rubio, L., Sambade, A., Mirkov, T. E., Moreno, P., & Guerri, J. (2005). Evidence of multiple recombination events between two RNA sequence variants within a Citrus tristeza virus isolate. Virology, 331(2), 232-237. doi:10.1016/j.virol.2004.10.037D’Urso, F., Sambade, A., Moya, A., Guerri, J., & Moreno, P. (2003). Variation of haplotype distributions of two genomic regions of Citrus tristeza virus populations from eastern Spain. Molecular Ecology, 12(2), 517-526. doi:10.1046/j.1365-294x.2000.01747.xSambade, A., Rubio, L., Garnsey, S. M., Costa, N., Muller, G. W., Peyrou, M., … Moreno, P. (2002). Comparison of viral RNA populations of pathogenically distinct isolates of Citrus tristeza virus : application to monitoring cross-protection. Plant Pathology, 51(3), 257-265. doi:10.1046/j.1365-3059.2002.00720.xReed, J. C., Kasschau, K. D., Prokhnevsky, A. I., Gopinath, K., Pogue, G. P., Carrington, J. C., & Dolja, V. V. (2003). Suppressor of RNA silencing encoded by Beet yellows virus. Virology, 306(2), 203-209. doi:10.1016/s0042-6822(02)00051-xFolimonova, S. Y., Robertson, C. J., Shilts, T., Folimonov, A. S., Hilf, M. E., Garnsey, S. M., & Dawson, W. O. (2009). Infection with Strains of Citrus Tristeza Virus Does Not Exclude Superinfection by Other Strains of the Virus. Journal of Virology, 84(3), 1314-1325. doi:10.1128/jvi.02075-09Kong, P., Rubio, L., Polek, M., & Falk, B. W. (2000). Virus Genes, 21(3), 139-145. doi:10.1023/a:1008198311398Powell, C. A., Pelosi, R. R., Rundell, P. A., & Cohen, M. (2003). Breakdown of Cross-Protection of Grapefruit from Decline-Inducing Isolates of Citrus tristeza virus Following Introduction of the Brown Citrus Aphid. Plant Disease, 87(9), 1116-1118. doi:10.1094/pdis.2003.87.9.1116Roistacher C, Dodds J. (1993) Failure of 100 mild Citrus tristeza virus isolates from california to cross protect against a challenge by severe sweet orange stem pitting isolates. Proc 12th Conf IOCV: 100–107.Ayllón, M. A., Rubio, L., Sentandreu, V., Moya, A., Guerri, J., & Moreno, P. (2006). Variations in Two Gene Sequences of Citrus Tristeza Virus after Host Passage. Virus Genes, 32(2), 119-128. doi:10.1007/s11262-005-6866-4Ayllón, M. A., Rubio, L., Moya, A., Guerri, J., & Moreno, P. (1999). The Haplotype Distribution of Two Genes of Citrus Tristeza Virus Is Altered after Host Change or Aphid Transmission. Virology, 255(1), 32-39. doi:10.1006/viro.1998.9566Sentandreu, V., Castro, J. A., Ayllón, M. A., Rubio, L., Guerri, J., González-Candelas, F., … Moya, A. (2005). Evolutionary analysis of genetic variation observed in citrus tristeza virus (CTV) after host passage. Archives of Virology, 151(5), 875-894. doi:10.1007/s00705-005-0683-xMatos, L. A., Hilf, M. E., Cayetano, X. A., Feliz, A. O., Harper, S. J., & Folimonova, S. Y. (2013). Dramatic Change in Citrus tristeza virus Populations in the Dominican Republic. Plant Disease, 97(3), 339-345. doi:10.1094/pdis-05-12-0421-reDavino, S., Davino, M., Sambade, A., Guardo, M., & Caruso, A. (2003). The First Citrus tristeza virus Outbreak Found in a Relevant Citrus Producing Area of Sicily, Italy. Plant Disease, 87(3), 314-314. doi:10.1094/pdis.2003.87.3.314aRUBIO, L., AYLLONl, M. A., GUERRI, J., PAPPU, H., NIBLETT, C., & MORENO, P. (1996). Differentiation of citrus tristeza closterovirus (CTV) isolates by single-strand conformation polymorphism analysis of the coat protein gene. Annals of Applied Biology, 129(3), 479-489. doi:10.1111/j.1744-7348.1996.tb05770.xLarkin, M. A., Blackshields, G., Brown, N. P., Chenna, R., McGettigan, P. A., McWilliam, H., … Higgins, D. G. (2007). Clustal W and Clustal X version 2.0. Bioinformatics, 23(21), 2947-2948. doi:10.1093/bioinformatics/btm404Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M., & Kumar, S. (2011). MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods. Molecular Biology and Evolution, 28(10), 2731-2739. doi:10.1093/molbev/msr121Kosakovsky Pond, S. L., Posada, D., Gravenor, M. B., Woelk, C. H., & Frost, S. D. W. (2006). GARD: a genetic algorithm for recombination detection. Bioinformatics, 22(24), 3096-3098. doi:10.1093/bioinformatics/btl474Martin, D. P., Lemey, P., Lott, M., Moulton, V., Posada, D., & Lefeuvre, P. (2010). RDP3: a flexible and fast computer program for analyzing recombination. Bioinformatics, 26(19), 2462-2463. doi:10.1093/bioinformatics/btq467Librado, P., & Rozas, J. (2009). DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics, 25(11), 1451-1452. doi:10.1093/bioinformatics/btp187Kimura M. (1985) The neutral theory of molecular evolution. Cambridge Univ Pr.Weir, B. S., & Cockerham, C. C. (1984). Estimating F-Statistics for the Analysis of Population Structure. Evolution, 38(6), 1358. doi:10.2307/2408641Pond, S. L. K., & Frost, S. D. W. (2005). Datamonkey: rapid detection of selective pressure on individual sites of codon alignments. Bioinformatics, 21(10), 2531-2533. doi:10.1093/bioinformatics/bti320Drummond, A. J., & Rambaut, A. (2007). BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology, 7(1), 214. doi:10.1186/1471-2148-7-214Bielejec, F., Rambaut, A., Suchard, M. A., & Lemey, P. (2011). SPREAD: spatial phylogenetic reconstruction of evolutionary dynamics. Bioinformatics, 27(20), 2910-2912. doi:10.1093/bioinformatics/btr481Stamatakis, A. (2006). RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics, 22(21), 2688-2690. doi:10.1093/bioinformatics/btl446Ott M, Zola J, Stamatakis A, Aluru S. (2007) Large-scale maximum likelihood-based phylogenetic analysis on the IBM BlueGene/L. Proceedings of the 19th ACM/IEEE conference on Supercomputing. Article No. 4.Shimodaira, H., & Hasegawa, M. (1999). Multiple Comparisons of Log-Likelihoods with Applications to Phylogenetic Inference. Molecular Biology and Evolution, 16(8), 1114-1116. doi:10.1093/oxfordjournals.molbev.a026201Soria-Carrasco, V., Talavera, G., Igea, J., & Castresana, J. (2007). The K tree score: quantification of differences in the relative branch length and topology of phylogenetic trees. Bioinformatics, 23(21), 2954-2956. doi:10.1093/bioinformatics/btm466Puigbo, P., Garcia-Vallve, S., & McInerney, J. O. (2007). TOPD/FMTS: a new software to compare phylogenetic trees. Bioinformatics, 23(12), 1556-1558. doi:10.1093/bioinformatics/btm13
Incidence of \u3ci\u3eWheat streak mosaic virus, Triticum mosaic virus\u3c/i\u3e, and \u3ci\u3eWheat mosaic virus\u3c/i\u3e in Wheat Curl Mites Recovered from Maturing Winter Wheat Spikes
Wheat curl mites (WCM; Aceria tosichella) transmit Wheat streak mosaic virus (WSMV), Triticum mosaic virus (TriMV), and Wheat mosaic virus (WMoV) to wheat (Triticum aestivum L.) in the Great Plains region of the United States. These viruses can be detected in single, double, or triple combinations in leaf samples. Information on incidence of viruses inWCM at the end of the growing season is scant. The availability of this information can enhance our knowledge of the epidemiology ofWCM-transmitted viruses. This research was conducted to determine the frequency of occurrence of WSMV, TriMV, and WMoV in WCM populations on fieldcollected maturing wheat spikes and to determine differences in WCM densities in three geographical regions (southeast, west-central, and panhandle) in Nebraska. Maturing wheat spikes were collected from 83 fields across Nebraska in 2011 and 2012. The spikes were placed in proximity to wheat seedlings (three- to four-leaf stage) inWCM-proof cages in a growth chamber and on sticky tape.WCM that moved off the drying wheat spikes in cages infested the wheat seedlings. WCM that moved off wheat spikes placed on sticky tape were trapped on the tape and were counted under a dissecting microscope. At 28 days after infestation, the wheat plants were tested for the presence ofWSMV, TriMV, orWMoV using enzyme-linked immunosorbent assay and multiplex polymerase chain reaction. WSMV was the most predominant virus detected in wheat seedlings infested with WCM from field-collected spikes. Double (TriMV+WSMV or WMoV+WSMV) or triple (TriMV+ WMoV +WSMV) virus detections were more frequent (47%) than single detections (5%) of TriMV or WSMV. Overall, 81% of the wheat seedlings infested with WCM tested positive for at least one virus. No significant association (P \u3e 0.05) was found between regions for WCM trapped on tape. These results suggest that WCM present on mature wheat spikes harbor multiple wheat viruses and may explain high virus incidence when direct movement of WCM into emerging winter wheat occurs in the fall
\u3ci\u3eTriticum mosaic virus\u3c/i\u3e exhibits limited population variation yet shows evidence of parallel evolution after replicated serial passage in wheat
An infectious cDNA clone of Triticum mosaic virus (TriMV) (genus Poacevirus; family Potyviridae) was used to establish three independent lineages in wheat to examine intra-host population diversity levels within protein 1 (P1) and coat protein (CP) cistrons over time. Genetic variation was assessed at passages 9, 18 and 24 by single-strand conformation polymorphism, followed by nucleotide sequencing. The founding P1 region genotype was retained at high frequencies in most lineage/passage populations, while the founding CP genotype disappeared after passage 18 in two lineages.We found that rare TriMV genotypes were present only transiently and lineages followed independent evolutionary trajectories, suggesting that genetic drift dominates TriMV evolution. These results further suggest that experimental populations of TriMV exhibit lower mutant frequencies than that of Wheat streak mosaic virus (genus Tritimovirus; family Potyviridae) in wheat. Nevertheless, there was evidence for parallel evolution at a synonymous site in the TriMV CP cistron
- …
