The value of gametoclonal variation in breeding for quantitative traits in flue-cured tobacco (Nicotiana tabacum L.)

Summary In tobacco (Nicotiana tabacum L.), anther-derived doubled haploid populations have been shown to exhibit large amounts of unexpected genetic variation and a severe depression in cured leaf yield when compared to conventionally inbred genotypes from comparable sources. A previous study had predicted that the yield depression observed in a doubled haploid population-derived from a near homozygous cultivar, NC95, might be overcome through a recurrent selection program. In the current study, progress from three cycles of full-sib family selection for improved yield in an anther-culture derived population of NC95 was measured, as well as the remaining genetic variation within the population. A design II experiment was conducted in the population following three cycles of selection. Results indicate that the NC95 yield level has been recovered in the third selection cycle population. Although most of the genetic variation in the population appears to be exhausted, the additive genetic variance among maternal half-sib families for yield is significant, and it appears that continued yield improvement can be made through recurrent selection. Significant additive-genetic variance for yield was found among maternal half-sib families but was essentially zero among the paternal half-sib families, suggesting that remaining genetic variation is not being transmitted through pollen. One possible explanation results from the phenomenon of DNA amplification that can occur during the anther culture process, and that may enable extraordinary recombinational events and reduce the viability of male gametes.     

Early real-time estimation of the basic reproduction number of emerging or reemerging infectious diseases in a community with heterogeneous contact pattern: Using data from Hong Kong 2009 H1N1 Pandemic Influenza as an illustrative example

Emerging and re-emerging infections such as SARS (2003) and pandemic H1N1 (2009) have caused concern for public health researchers and policy makers due to the increased burden of these diseases on health care systems. This concern has prompted the use of mathematical models to evaluate strategies to control disease spread, making these models invaluable tools to identify optimal intervention strategies. A particularly important quantity in infectious disease epidemiology is the basic reproduction number, R_0. Estimation of this quantity is crucial for effective control responses in the early phase of an epidemic. In our previous study, an approach for estimating the basic reproduction number in real time was developed. This approach uses case notification data and the structure of potential transmission contacts to accurately estimate R₀ from the limited amount of information available at the early stage of an outbreak. Based on this approach, we extend the existing methodology; the most recent method features intra- and inter-age groups contact heterogeneity. Given the number of newly reported cases at the early stage of the outbreak, with parsimony assumptions on removal distribution and infectivity profile of the diseases, experiments to estimate real time R₀ under different levels of intra- and inter-group contact heterogeneity using two age groups are presented. We show that the new method converges more quickly to the actual value of R₀ than the previous one, in particular when there is high-level intra-group and inter-group contact heterogeneity. With the age specific contact patterns, number of newly reported cases, removal distribution, and information about the natural history of the 2009 pandemic influenza in Hong Kong, we also use the extended model to estimate R₀ and age-specific R₀.