Time-sampled population sequencing reveals the interplay of selection and genetic drift in experimental evolution of Potato virus Y

[EN] RNA viruses are one of the fastest evolving biological entities. Within their hosts, they exist as genetically diverse populations (i.e., viral mutant swarms), which are sculpted by different evolutionary mechanisms, such as mutation, natural selection and genetic drift, and also the interactions between genetic variants within the mutant swarms. To elucidate the mechanisms that modulate the population diversity of an important plant pathogenic virus, we performed evolution experiments with Potato virus Y (PVY) in potato genotypes that differ in their defense response against the virus. Using deep sequencing of small RNAs, we followed the temporal dynamics of standing and newly-generated variation in the evolving viral lineages. A time-sampled approach allowed us to: (i) reconstruct theoretical haplotypes in the starting population by using clustering of single nucleotide polymorphisms' trajectories and (ii) use quantitative population genetics approaches to estimate the contribution of selection and genetic drift, and their interplay, to the evolution of the virus. We detected imprints of strong selective sweeps and narrow genetic bottlenecks, followed by the shift in frequency of selected haplotypes. Comparison of patterns of viral evolution in differently susceptible host genotypes indicated possible diversifying evolution of PVY in the less susceptible host (efficient in the accumulation of salicylicacid).This study was supported by the Slovenian Research Agency (grants L4-5525 and P4-0165 and Ph.D. grant to D.K.). Work in Valencia was supported by Spain Ministry of Economy and Competitiveness (grant BFU2015-65037-P to S.F.E.), and short-term scientific mission support was provided to D.K. in the frame of EU-funded COST action FA1407.Kutnjak, D.; Elena Fito, SF.; Ravnikar, M. (2017). Time-sampled population sequencing reveals the interplay of selection and genetic drift in experimental evolution of Potato virus Y. Journal of Virology. 91(16):1-17. https://doi.org/10.1128/JVI.00690-17S1179116Andino, R., & Domingo, E. (2015). Viral quasispecies. Virology, 479-480, 46-51. doi:10.1016/j.virol.2015.03.022Ohshima, K., Nomiyama, R., Mitoma, S., Honda, Y., Yasaka, R., & Tomimura, K. (2016). Evolutionary rates and genetic diversities of mixed potyviruses in Narcissus. Infection, Genetics and Evolution, 45, 213-223. doi:10.1016/j.meegid.2016.08.036Froissart, R., Roze, D., Uzest, M., Galibert, L., Blanc, S., & Michalakis, Y. (2005). Recombination Every Day: Abundant Recombination in a Virus during a Single Multi-Cellular Host Infection. PLoS Biology, 3(3), e89. doi:10.1371/journal.pbio.0030089Tromas, N., Zwart, M. P., Poulain, M., & Elena, S. F. (2014). Estimation of the in vivo recombination rate for a plant RNA virus. Journal of General Virology, 95(3), 724-732. doi:10.1099/vir.0.060822-0Simon-Loriere, E., & Holmes, E. C. (2011). Why do RNA viruses recombine? Nature Reviews Microbiology, 9(8), 617-626. doi:10.1038/nrmicro2614Zwart, M. P., & Elena, S. F. (2015). Matters of Size: Genetic Bottlenecks in Virus Infection and Their Potential Impact on Evolution. Annual Review of Virology, 2(1), 161-179. doi:10.1146/annurev-virology-100114-055135Neher, R. A. (2013). Genetic Draft, Selective Interference, and Population Genetics of Rapid Adaptation. Annual Review of Ecology, Evolution, and Systematics, 44(1), 195-215. doi:10.1146/annurev-ecolsys-110512-135920Elena, S. F., Fraile, A., & García-Arenal, F. (2014). Evolution and Emergence of Plant Viruses. Advances in Virus Research, 161-191. doi:10.1016/b978-0-12-800098-4.00003-9Longdon, B., Brockhurst, M. A., Russell, C. A., Welch, J. J., & Jiggins, F. M. (2014). The Evolution and Genetics of Virus Host Shifts. PLoS Pathogens, 10(11), e1004395. doi:10.1371/journal.ppat.1004395Vassilakos, N., Simon, V., Tzima, A., Johansen, E., & Moury, B. (2015). Genetic Determinism and Evolutionary Reconstruction of a Host Jump in a Plant Virus. Molecular Biology and Evolution, 33(2), 541-553. doi:10.1093/molbev/msv222Stapleford, K. A., Coffey, L. L., Lay, S., Bordería, A. V., Duong, V., Isakov, O., … Vignuzzi, M. (2014). Emergence and Transmission of Arbovirus Evolutionary Intermediates with Epidemic Potential. Cell Host & Microbe, 15(6), 706-716. doi:10.1016/j.chom.2014.05.008Remold, S. K., Rambaut, A., & Turner, P. E. (2008). Evolutionary Genomics of Host Adaptation in Vesicular Stomatitis Virus. Molecular Biology and Evolution, 25(6), 1138-1147. doi:10.1093/molbev/msn059Foll, M., Poh, Y.-P., Renzette, N., Ferrer-Admetlla, A., Bank, C., Shim, H., … Jensen, J. D. (2014). Influenza Virus Drug Resistance: A Time-Sampled Population Genetics Perspective. PLoS Genetics, 10(2), e1004185. doi:10.1371/journal.pgen.1004185Bedhomme, S., Lafforgue, G., & Elena, S. F. (2011). Multihost Experimental Evolution of a Plant RNA Virus Reveals Local Adaptation and Host-Specific Mutations. Molecular Biology and Evolution, 29(5), 1481-1492. doi:10.1093/molbev/msr314Hillung, J., Cuevas, J. M., Valverde, S., & Elena, S. F. (2014). EXPERIMENTAL EVOLUTION OF AN EMERGING PLANT VIRUS IN HOST GENOTYPES THAT DIFFER IN THEIR SUSCEPTIBILITY TO INFECTION. Evolution, 68(9), 2467-2480. doi:10.1111/evo.12458Acevedo, A., Brodsky, L., & Andino, R. (2013). Mutational and fitness landscapes of an RNA virus revealed through population sequencing. Nature, 505(7485), 686-690. doi:10.1038/nature12861Foll, M., Shim, H., & Jensen, J. D. (2014). WFABC: a Wright-Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled data. Molecular Ecology Resources, 15(1), 87-98. doi:10.1111/1755-0998.12280Bordería, A. V., Isakov, O., Moratorio, G., Henningsson, R., Agüera-González, S., Organtini, L., … Vignuzzi, M. (2015). Group Selection and Contribution of Minority Variants during Virus Adaptation Determines Virus Fitness and Phenotype. PLOS Pathogens, 11(5), e1004838. doi:10.1371/journal.ppat.1004838Kessinger, T. A., Perelson, A. S., & Neher, R. A. (2013). Inferring HIV Escape Rates from Multi-Locus Genotype Data. Frontiers in Immunology, 4. doi:10.3389/fimmu.2013.00252SCHOLTHOF, K.-B. G., ADKINS, S., CZOSNEK, H., PALUKAITIS, P., JACQUOT, E., HOHN, T., … FOSTER, G. D. (2011). Top 10 plant viruses in molecular plant pathology. Molecular Plant Pathology, 12(9), 938-954. doi:10.1111/j.1364-3703.2011.00752.xKarasev, A. V., & Gray, S. M. (2013). Continuous and Emerging Challenges of Potato virus Y in Potato. Annual Review of Phytopathology, 51(1), 571-586. doi:10.1146/annurev-phyto-082712-102332Kogovšek, P., Pompe-Novak, M., Baebler, Š., Rotter, A., Gow, L., Gruden, K., … Ravnikar, M. (2010). Aggressive and mild Potato virus Y isolates trigger different specific responses in susceptible potato plants. Plant Pathology, 59(6), 1121-1132. doi:10.1111/j.1365-3059.2010.02340.xBAEBLER, Š., KREČIČ-STRES, H., ROTTER, A., KOGOVŠEK, P., CANKAR, K., KOK, E. J., … RAVNIKAR, M. (2009). PVYNTNelicits a diverse gene expression response in different potato genotypes in the first 12 h after inoculation. Molecular Plant Pathology, 10(2), 263-275. doi:10.1111/j.1364-3703.2008.00530.xStare, T., Ramšak, Ž., Blejec, A., Stare, K., Turnšek, N., Weckwerth, W., … Gruden, K. (2015). Bimodal dynamics of primary metabolism-related responses in tolerant potato-Potato virus Y interaction. BMC Genomics, 16(1). doi:10.1186/s12864-015-1925-2Kogovšek, P., Pompe-Novak, M., Petek, M., Fragner, L., Weckwerth, W., & Gruden, K. (2016). Primary Metabolism, Phenylpropanoids and Antioxidant Pathways Are Regulated in Potato as a Response to Potato virus Y Infection. PLOS ONE, 11(1), e0146135. doi:10.1371/journal.pone.0146135Baebler, Š., Stare, K., Kovač, M., Blejec, A., Prezelj, N., Stare, T., … Gruden, K. (2011). Dynamics of Responses in Compatible Potato - Potato virus Y Interaction Are Modulated by Salicylic Acid. PLoS ONE, 6(12), e29009. doi:10.1371/journal.pone.0029009Baebler, Š., Witek, K., Petek, M., Stare, K., Tušek-Žnidarič, M., Pompe-Novak, M., … Hennig, J. (2014). Salicylic acid is an indispensable component of the Ny-1 resistance-gene-mediated response against Potato virus Y infection in potato. Journal of Experimental Botany, 65(4), 1095-1109. doi:10.1093/jxb/ert447Singh, D. P., Moore, C. A., Gilliland, A., & Carr, J. P. (2004). Activation of multiple antiviral defence mechanisms by salicylic acid. Molecular Plant Pathology, 5(1), 57-63. doi:10.1111/j.1364-3703.2004.00203.xKutnjak, D., Rupar, M., Gutierrez-Aguirre, I., Curk, T., Kreuze, J. F., & Ravnikar, M. (2015). Deep Sequencing of Virus-Derived Small Interfering RNAs and RNA from Viral Particles Shows Highly Similar Mutational Landscapes of a Plant Virus Population. Journal of Virology, 89(9), 4760-4769. doi:10.1128/jvi.03685-14Zagordi, O., Bhattacharya, A., Eriksson, N., & Beerenwinkel, N. (2011). ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data. BMC Bioinformatics, 12(1). doi:10.1186/1471-2105-12-119Prosperi, M. C. F., & Salemi, M. (2011). QuRe: software for viral quasispecies reconstruction from next-generation sequencing data. Bioinformatics, 28(1), 132-133. doi:10.1093/bioinformatics/btr627Prabhakaran, S., Rey, M., Zagordi, O., Beerenwinkel, N., & Roth, V. (2014). HIV Haplotype Inference Using a Propagating Dirichlet Process Mixture Model. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11(1), 182-191. doi:10.1109/tcbb.2013.145Dynan, W., Fox, K., & Stoddard, B. (2013). Editorial: NAR Surveys the Past, Present and Future of Restriction Endonucleases. Nucleic Acids Research, 42(1), 1-2. doi:10.1093/nar/gkt1324Töpfer, A., Marschall, T., Bull, R. A., Luciani, F., Schönhuth, A., & Beerenwinkel, N. (2014). Viral Quasispecies Assembly via Maximal Clique Enumeration. PLoS Computational Biology, 10(3), e1003515. doi:10.1371/journal.pcbi.1003515Schirmer, M., Sloan, W. T., & Quince, C. (2012). Benchmarking of viral haplotype reconstruction programmes: an overview of the capacities and limitations of currently available programmes. Briefings in Bioinformatics, 15(3), 431-442. doi:10.1093/bib/bbs081Lang, G. I., Rice, D. P., Hickman, M. J., Sodergren, E., Weinstock, G. M., Botstein, D., & Desai, M. M. (2013). Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations. Nature, 500(7464), 571-574. doi:10.1038/nature12344Zwart, M. P., Daròs, J.-A., & Elena, S. F. (2012). Effects of Potyvirus Effective Population Size in Inoculated Leaves on Viral Accumulation and the Onset of Symptoms. Journal of Virology, 86(18), 9737-9747. doi:10.1128/jvi.00909-12Ruiz-Jarabo, C. M., Arias, A., Baranowski, E., Escarmís, C., & Domingo, E. (2000). Memory in Viral Quasispecies. Journal of Virology, 74(8), 3543-3547. doi:10.1128/jvi.74.8.3543-3547.2000Pruss, G. J., Lawrence, C. B., Bass, T., Li, Q. Q., Bowman, L. H., & Vance, V. (2004). The potyviral suppressor of RNA silencing confers enhanced resistance to multiple pathogens. Virology, 320(1), 107-120. doi:10.1016/j.virol.2003.11.027Alamillo, J. M., Saénz, P., & García, J. A. (2006). Salicylic acid-mediated and RNA-silencing defense mechanisms cooperate in the restriction of systemic spread of plum pox virus in tobacco. The Plant Journal, 48(2), 217-227. doi:10.1111/j.1365-313x.2006.02861.xYu, D., Fan, B., MacFarlane, S. A., & Chen, Z. (2003). Analysis of the Involvement of an Inducible Arabidopsis RNA-Dependent RNA Polymerase in Antiviral Defense. Molecular Plant-Microbe Interactions®, 16(3), 206-216. doi:10.1094/mpmi.2003.16.3.206Miyashita, S., Ishibashi, K., Kishino, H., & Ishikawa, M. (2015). Viruses Roll the Dice: The Stochastic Behavior of Viral Genome Molecules Accelerates Viral Adaptation at the Cell and Tissue Levels. PLOS Biology, 13(3), e1002094. doi:10.1371/journal.pbio.1002094Kogovšek, P., Gow, L., Pompe-Novak, M., Gruden, K., Foster, G. D., Boonham, N., & Ravnikar, M. (2008). Single-step RT real-time PCR for sensitive detection and discrimination of Potato virus Y isolates. Journal of Virological Methods, 149(1), 1-11. doi:10.1016/j.jviromet.2008.01.025Weller, S. A., Elphinstone, J. G., Smith, N. C., Boonham, N., & Stead, D. E. (2000). Detection of Ralstonia solanacearumStrains with a Quantitative, Multiplex, Real-Time, Fluorogenic PCR (TaqMan) Assay. Applied and Environmental Microbiology, 66(7), 2853-2858. doi:10.1128/aem.66.7.2853-2858.2000Gutiérrez-Aguirre, I., Rački, N., Dreo, T., & Ravnikar, M. (2015). Droplet Digital PCR for Absolute Quantification of Pathogens. Methods in Molecular Biology, 331-347. doi:10.1007/978-1-4939-2620-6_24Rupar, M., Faurez, F., Tribodet, M., Gutiérrez-Aguirre, I., Delaunay, A., Glais, L., … Ravnikar, M. (2015). Fluorescently Tagged Potato virus Y: A Versatile Tool for Functional Analysis of Plant-Virus Interactions. Molecular Plant-Microbe Interactions®, 28(7), 739-750. doi:10.1094/mpmi-07-14-0218-taLi, H., & Durbin, R. (2009). Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics, 25(14), 1754-1760. doi:10.1093/bioinformatics/btp324Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., … Homer, N. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics, 25(16), 2078-2079. doi:10.1093/bioinformatics/btp352Nelson, C. W., Moncla, L. H., & Hughes, A. L. (2015). SNPGenie: estimating evolutionary parameters to detect natural selection using pooled next-generation sequencing data: Table 1. Bioinformatics, btv449. doi:10.1093/bioinformatics/btv449Suzuki R Shimodaira H . 2015. pvclust: hierarchical clustering with P values via multiscale bootstrap resampling. R package version 2.0-0. https://cran.r-project.org/web/packages/pvclust/

European stone fruit Yellows phytoplasma in Japanese plum and Myrobalan plum in Bosnia and Herzegovina

Stone fruits from commercial as well as abandoned orchards were evaluated for European Stone Fruit Yellows phytoplasma (ESFY) presence during 2004-2007 years. Orchards were monitored in western and southern districts of Bosnia and Herzegovina. In the first survey conducted in period of 2004 till 2005 the causal agent of ESFY was identified on peach (Prunus persica) and apricot (Prunus armeniaca) plants in both surveyed districts. During 2007, a new survey was performed and samples were taken from symptomatic and symptomless plants of European plum (Prunus domestica), Japanese plum (Prunus salicina), Myrobalan plum (Prunus cerasifera) and cherry (Prunus avium). Samples were analyzed using real-time PCR and nested PCR approaches. In this extended survey, the presence of ESFY phytoplasma was additionally identified in Japanese plum and myrobalan plum trees.Keywords: Bosnia and Herzegovina, myrobalan plum, Japanese plum, phytoplasma, ESFY, PC

Deep sequencing of virus derived small interfering RNAs and RNA from viral particles shows highly similar mutational landscape of a plant virus population.

RNA viruses exist within a host as a population of mutant sequences, often referred to as quasispecies. Within a host, sequences of RNA viruses constitute several distinct but interconnected pools, such as RNA packed in viral particles, double-stranded RNA, and virus-derived small interfering RNAs. We aimed to test if the same representation of within-host viral population structure could be obtained by sequencing different viral sequence pools. Using ultradeep Illumina sequencing, the diversity of two coexisting Potato virus Y sequence pools present within a plant was investigated: RNA isolated from viral particles and virus-derived small interfering RNAs (the derivatives of a plant RNA silencing mechanism). The mutational landscape of the within-host virus population was highly similar between both pools, with no notable hotspots across the viral genome. Notably, all of the single-nucleotide polymorphisms with a frequency of higher than 1.6% were found in both pools. Some unique single-nucleotide polymorphisms (SNPs) with very low frequencies were found in each of the pools, with more of them occurring in the small RNA (sRNA) pool, possibly arising through genetic drift in localized virus populations within a plant and the errors introduced during the amplification of silencing signal. Sequencing of the viral particle pool enhanced the efficiency of consensus viral genome sequence reconstruction. Nonhomologous recombinations were commonly detected in the viral particle pool, with a hot spot in the 3′ untranslated and coat protein regions of the genome. We stress that they present an important but often overlooked aspect of virus population diversity. IMPORTANCE This study is the most comprehensive whole-genome characterization of a within-plant virus population to date and the first study comparing diversity of different pools of viral sequences within a host. We show that both virus-derived small RNAs and RNA from viral particles could be used for diversity assessment of within-plant virus population, since they show a highly congruent portrayal of the virus mutational landscape within a plant. The study is an important baseline for future studies of virus population dynamics, for example, during the adaptation to a new host. The comparison of the two virus sequence enrichment techniques, sequencing of virus-derived small interfering RNAs and RNA from purified viral particles, shows the strength of the latter for the detection of recombinant viral genomes and reconstruction of complete consensus viral genome sequence

Benthic sediment as stores and sources of bacteria and viruses in streams:A comparison of baseflow vs. stormflow longitudinal transport and residence times

International audienceThe presence of bacteria and viruses in freshwater represents a global health risk. The substantial spatial and temporal variability of microbes leads to difficulties in quantifying the risks associated with their presence in freshwater. Fine particles, including bacteria and viruses are transported and accumulated into shallow streambed (i.e., benthic) sediment, delaying the downstream transmission during baseflow conditions but contributing to their resuspension and transport downstream during stormflow events. Direct measurements of pathogen accumulation in benthic sediments are rare. Until now, the dynamic role of benthic sediment as both a store and source of microbes, has not been quantified. In this study, we analyze microbial abundance in benthic sediment along a 1 km reach of an intermittent Mediterranean stream receiving inputs from the effluent of a wastewater treatment plant, a known point source of microbes in streams. We sampled benthic sediment during a summer drought when the wastewater effluent constituted 100% of the stream flow, and thus, large accumulation and persistence of pathogens along the streambed was expected. We measured the abundance of total bacteria, Escherichia coli (as a fecal indicator), and presence of enteric rotavirus (RoV) and norovirus (NoV). The abundance of E. coli, based on qPCR detection, was high (4.99∙102 g/cm2 or ∼ 1 ng/μL) along the first 100 m downstream of the wastewater effluent input and in general decreased with distance from the source, with presence of RoV and NoV along the study reach. A particle tracking model was applied, that uses stream water velocity as an input, and accounts for microbial exchange into, immobilization, degradation, and resuspension out of benthic sediment during baseflow and stormflow. Rates of exchange into benthic sediment were 3 orders of magnitude higher during stormflow, but residence times were proportionately lower, resulting in increased longitudinal connectivity from up to downstream during stormflow. Model simulations demonstrated mechanistically how the rates of exchange into and out of the benthic sediment resulted in benthic sediment to act as a store during baseflow and a source during stormflow

Amino Acid Metabolic Origin as an Evolutionary Influence on Protein Sequence in Yeast

The metabolic cycle of Saccharomyces cerevisiae consists of alternating oxidative (respiration) and reductive (glycolysis) energy-yielding reactions. The intracellular concentrations of amino acid precursors generated by these reactions oscillate accordingly, attaining maximal concentration during the middle of their respective yeast metabolic cycle phases. Typically, the amino acids themselves are most abundant at the end of their precursor’s phase. We show that this metabolic cycling has likely biased the amino acid composition of proteins across the S. cerevisiae genome. In particular, we observed that the metabolic source of amino acids is the single most important source of variation in the amino acid compositions of functionally related proteins and that this signal appears only in (facultative) organisms using both oxidative and reductive metabolism. Periodically expressed proteins are enriched for amino acids generated in the preceding phase of the metabolic cycle. Proteins expressed during the oxidative phase contain more glycolysis-derived amino acids, whereas proteins expressed during the reductive phase contain more respiration-derived amino acids. Rare amino acids (e.g., tryptophan) are greatly overrepresented or underrepresented, relative to the proteomic average, in periodically expressed proteins, whereas common amino acids vary by a few percent. Genome-wide, we infer that 20,000 to 60,000 residues have been modified by this previously unappreciated pressure. This trend is strongest in ancient proteins, suggesting that oscillating endogenous amino acid availability exerted genome-wide selective pressure on protein sequences across evolutionary time

Mice have a transcribed L-threonine aldolase/GLY1 gene, but the human GLY1 gene is a non-processed pseudogene

BACKGROUND: There are three pathways of L-threonine catabolism. The enzyme L-threonine aldolase (TA) has been shown to catalyse the conversion of L-threonine to yield glycine and acetaldehyde in bacteria, fungi and plants. Low levels of TA enzymatic activity have been found in vertebrates. It has been suggested that any detectable activity is due to serine hydroxymethyltransferase and that mammals lack a genuine threonine aldolase. RESULTS: The 7-exon murine L-threonine aldolase gene (GLY1) is located on chromosome 11, spanning 5.6 kb. The cDNA encodes a 400-residue protein. The protein has 81% similarity with the bacterium Thermotoga maritima TA. Almost all known functional residues are conserved between the two proteins including Lys242 that forms a Schiff-base with the cofactor, pyridoxal-5'-phosphate. The human TA gene is located at 17q25. It contains two single nucleotide deletions, in exons 4 and 7, which cause frame-shifts and a premature in-frame stop codon towards the carboxy-terminal. Expression of human TA mRNA was undetectable by RT-PCR. In mice, TA mRNA was found at low levels in a range of adult tissues, being highest in prostate, heart and liver. In contrast, serine/threonine dehydratase, another enzyme that catabolises L-threonine, is expressed very highly only in the liver. Serine dehydratase-like 1, also was most abundant in the liver. In whole mouse embryos TA mRNA expression was low prior to E-15 increasing more than four-fold by E-17. CONCLUSION: Mice, the western-clawed frog and the zebrafish have transcribed threonine aldolase/GLY1 genes, but the human homolog is a non-transcribed pseudogene. Serine dehydratase-like 1 is a putative L-threonine catabolising enzyme

Dynamics of Responses in Compatible Potato - Potato virus Y Interaction Are Modulated by Salicylic Acid

To investigate the dynamics of the potato – Potato virus Y (PVY) compatible interaction in relation to salicylic acid - controlled pathways we performed experiments using non-transgenic potato cv. Désirée, transgenic NahG-Désirée, cv. Igor and PVYNTN, the most aggressive strain of PVY. The importance of salicylic acid in viral multiplication and symptom development was confirmed by pronounced symptom development in NahG-Désirée, depleted in salicylic acid, and reversion of the effect after spraying with 2,6-dichloroisonicotinic acid (a salicylic acid - analogue). We have employed quantitative PCR for monitoring virus multiplication, as well as plant responses through expression of selected marker genes of photosynthetic activity, carbohydrate metabolism and the defence response. Viral multiplication was the slowest in inoculated potato of cv. Désirée, the only asymptomatic genotype in the study. The intensity of defence-related gene expression was much stronger in both sensitive genotypes (NahG-Désirée and cv. Igor) at the site of inoculation than in asymptomatic plants (cv. Désirée). Photosynthesis and carbohydrate metabolism gene expression differed between the symptomatic and asymptomatic phenotypes. The differential gene expression pattern of the two sensitive genotypes indicates that the outcome of the interaction does not rely simply on one regulatory component, but similar phenotypical features can result from distinct responses at the molecular level

Sex- and age-related differences in the management and outcomes of chronic heart failure: an analysis of patients from the ESC HFA EORP Heart Failure Long-Term Registry

Aims: This study aimed to assess age- and sex-related differences in management and 1-year risk for all-cause mortality and hospitalization in chronic heart failure (HF) patients. Methods and results: Of 16 354 patients included in the European Society of Cardiology Heart Failure Long-Term Registry, 9428 chronic HF patients were analysed [median age: 66 years; 28.5% women; mean left ventricular ejection fraction (LVEF) 37%]. Rates of use of guideline-directed medical therapy (GDMT) were high (angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, beta-blockers and mineralocorticoid receptor antagonists: 85.7%, 88.7% and 58.8%, respectively). Crude GDMT utilization rates were lower in women than in men (all differences: P\ua0 64 0.001), and GDMT use became lower with ageing in both sexes, at baseline and at 1-year follow-up. Sex was not an independent predictor of GDMT prescription; however, age >75 years was a significant predictor of GDMT underutilization. Rates of all-cause mortality were lower in women than in men (7.1% vs. 8.7%; P\ua0=\ua00.015), as were rates of all-cause hospitalization (21.9% vs. 27.3%; P\ua075 years. Conclusions: There was a decline in GDMT use with advanced age in both sexes. Sex was not an independent predictor of GDMT or adverse outcomes. However, age >75 years independently predicted lower GDMT use and higher all-cause mortality in patients with LVEF 6445%