Selection of antigenically advanced variants of seasonal influenza viruses.

Influenza viruses mutate frequently, necessitating constant updates of vaccine viruses. To establish experimental approaches that may complement the current vaccine strain selection process, we selected antigenic variants from human H1N1 and H3N2 influenza virus libraries possessing random mutations in the globular head of the haemagglutinin protein (which includes the antigenic sites) by incubating them with human and/or ferret convalescent sera to human H1N1 and H3N2 viruses. We also selected antigenic escape variants from human viruses treated with convalescent sera and from mice that had been previously immunized against human influenza viruses. Our pilot studies with past influenza viruses identified escape mutants that were antigenically similar to variants that emerged in nature, establishing the feasibility of our approach. Our studies with contemporary human influenza viruses identified escape mutants before they caused an epidemic in 2014-2015. This approach may aid in the prediction of potential antigenic escape variants and the selection of future vaccine candidates before they become widespread in nature.This work was supported by the Bill & Melinda Gates Foundation Global Health Grant OPPGH5383; National Institute of Allergy and Infectious Diseases (NIAID) Public Health Service research grants (USA); ERATO (Japan Science and Technology Agency); the Center for Research on Influenza Pathogenesis (CRIP) funded by the NIAID Contracts HHSN266200700010C and HHSN27 2201400008C; the Japan Initiative for Global Research Network on Infectious Diseases; Grants-in-Aid for Specially Promoted Research from the Ministry of Education, Culture, Sports, Science, and Technology, Japan; Grants-in-Aid from the Ministry of Health, Labour and Welfare, Japan; grants from the Strategic Basic Research Program of the Japan Science and Technology Agency; and by the Advanced Research & Development Programs for Medical Innovation from the Japan Agency for Medical Research and Development (AMED). C.A.R. was supported by a University Research Fellowship from the Royal Society. The authors acknowledge a Netherlands Organisation for Scientific Research (NWO) VICI grant, European Union (EU) FP7 programs EMPERIE (223498) and ANTIGONE (278976); Human Frontier Science Program (HFSP) program grant P0050/2008; Wellcome 087982AIA; and NIH Director's Pioneer Award DP1-OD000490-01. D.F.B and D.J.S. acknowledge CamGrid, the University of Cambridge distributed computer system. The Melbourne WHO Collaborating Centre for Reference and Research on Influenza is supported by the Australian Government Department of Health.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nmicrobiol.2016.5

Selection of antigenically advanced variants of seasonal influenza viruses

Influenza viruses mutate frequently, necessitating constant updates of vaccine viruses. To establish experimental approaches that may complement the current vaccine strain selection process, we selected antigenic variants from human H1N1 and H3N2 influenza virus libraries possessing random mutations in the globular head of the haemagglutinin protein (which includes the antigenic sites) by incubating them with human and/or ferret convalescent se

A Statistical Model for Estimating Maternal-Zygotic Interactions and Parent-of-Origin Effects of QTLs for Seed Development

Proper development of a seed requires coordinated exchanges of signals among the three components that develop side by side in the seed. One of these is the maternal integument that encloses the other two zygotic components, i.e., the diploid embryo and its nurturing annex, the triploid endosperm. Although the formation of the embryo and endosperm contains the contributions of both maternal and paternal parents, maternally and paternally derived alleles may be expressed differently, leading to a so-called parent-of-origin or imprinting effect. Currently, the nature of how genes from the maternal and zygotic genomes interact to affect seed development remains largely unknown. Here, we present a novel statistical model for estimating the main and interaction effects of quantitative trait loci (QTLs) that are derived from different genomes and further testing the imprinting effects of these QTLs on seed development. The experimental design used is based on reciprocal backcrosses toward both parents, so that the inheritance of parent-specific alleles could be traced. The computing model and algorithm were implemented with the maximum likelihood approach. The new strategy presented was applied to study the mode of inheritance for QTLs that control endoreduplication traits in maize endosperm. Monte Carlo simulation studies were performed to investigate the statistical properties of the new model with the data simulated under different imprinting degrees. The false positive rate of imprinting QTL discovery by the model was examined by analyzing the simulated data that contain no imprinting QTL. The reciprocal design and a series of analytical and testing strategies proposed provide a standard procedure for genomic mapping of QTLs involved in the genetic control of complex seed development traits in flowering plants