A Survey of Phytophthora spp. in Eastern Indian Nurseries and Their Sensitivity to Six Oomycete-Targeted Commercial Fungicides.

A survey of the flori-horticultural nurseries in eastern India found Phytophthora nicotianae to be the most widespread Phytophthora species associated with different foliar symptoms of nursery plants and identified the presence of P. palmivora in eastern Indian nurseries for the first time. The survey also led to the first worldwide finding of P. nicotianae on Dipteracanthus prostratus (Poir.) Nees; Ocimum tenuiflorum L. (syn. Ocimum sanctum L.); Philodendron xanadu Croat, Mayo & J. Boos; and Pyrostegia venusta (Ker-Gawl.) Miers and P. palmivora on Episcia cupreata (Hook.) Hanst., as well as the first report from India of P. nicotianae on Spathiphyllum wallisii Regel; Anthurium andraeanum Linden ex André; and Adenium obesum (Forsk.) Roem. & Schult. Sensitivity to commercial fungicides Glazer 35WS, Rallis India (metalaxyl, FRAC code 4); Ridomil Gold, Syngenta (mefenoxam + mancozeb); Revus, Syngenta (mandipropamid, FRAC code 40); Aliette Bayer (fosetyl-Al, FRAC code 33); Acrobat, BASF (dimethomorph, FRAC code 40); and Amistar, Syngenta (azoxystrobin, FRAC code 11) was analyzed, showing EC50 values ranging from 0.75 to 16.39 ppm, 0.74 to 1.45 ppm, 2.43 to 17.21 ppm, 63.81 to 327.31 ppm, 8.88 to 174.69 ppm, and 0.1 to 1.13 ppm, respectively, with no cross-resistance of the isolates to the fungicides. The baseline information produced about these Phytophthora spp. from ornamental and horticultural host associations could help prevent the pathogens from becoming primary drivers of new disease outbreaks and their large-scale distribution beyond their natural endemic ranges.

Large sub-clonal variation in Phytophthora infestans from recent severe late blight epidemics in India.

The population structure of the Phytophthora infestans populations that caused the recent 2013-14 late blight epidemic in eastern India (EI) and northeastern India (NEI) was examined. The data provide new baseline information for populations of P. infestans in India. A migrant European 13_A2 genotype was responsible for the 2013-14 epidemic, replacing the existing populations. Mutations have generated substantial sub-clonal variation with 24 multi-locus genotypes (MLGs) found, of which 19 were unique variants not yet reported elsewhere globally. Samples from West Bengal were the most diverse and grouped alongside MLGs found in Europe, the UK and from neighbouring Bangladesh but were not linked directly to most samples from south India. The pathogen population was broadly more aggressive on potato than on tomato and resistant to the fungicide metalaxyl. Pathogen population diversity was higher in regions around the international borders with Bangladesh and Nepal. Overall, the multiple shared MLGs suggested genetic contributions from UK and Europe in addition to a sub-structure based on the geographical location within India. Our data indicate the need for improved phytosanitary procedures and continuous surveillance to prevent the further introduction of aggressive lineages of P. infestans into the country.

Coalescent: an open-science framework for importance sampling in coalescent theory.

Background. In coalescent theory, computer programs often use importance sampling to calculate likelihoods and other statistical quantities. An importance sampling scheme can exploit human intuition to improve statistical efficiency of computations, but unfortunately, in the absence of general computer frameworks on importance sampling, researchers often struggle to translate new sampling schemes computationally or benchmark against different schemes, in a manner that is reliable and maintainable. Moreover, most studies use computer programs lacking a convenient user interface or the flexibility to meet the current demands of open science. In particular, current computer frameworks can only evaluate the efficiency of a single importance sampling scheme or compare the efficiencies of different schemes in an ad hoc manner. Results. We have designed a general framework (http://coalescent.sourceforge.net; language: Java; License: GPLv3) for importance sampling that computes likelihoods under the standard neutral coalescent model of a single, well-mixed population of constant size over time following infinite sites model of mutation. The framework models the necessary core concepts, comes integrated with several data sets of varying size, implements the standard competing proposals, and integrates tightly with our previous framework for calculating exact probabilities. For a given dataset, it computes the likelihood and provides the maximum likelihood estimate of the mutation parameter. Well-known benchmarks in the coalescent literature validate the accuracy of the framework. The framework provides an intuitive user interface with minimal clutter. For performance, the framework switches automatically to modern multicore hardware, if available. It runs on three major platforms (Windows, Mac and Linux). Extensive tests and coverage make the framework reliable and maintainable. Conclusions. In coalescent theory, many studies of computational efficiency consider only effective sample size. Here, we evaluate proposals in the coalescent literature, to discover that the order of efficiency among the three importance sampling schemes changes when one considers running time as well as effective sample size. We also describe a computational technique called "just-in-time delegation" available to improve the trade-off between running time and precision by constructing improved importance sampling schemes from existing ones. Thus, our systems approach is a potential solution to the "2(8) programs problem" highlighted by Felsenstein, because it provides the flexibility to include or exclude various features of similar coalescent models or importance sampling schemes.

Coalescent: an open-source and scalable framework for exact calculations in coalescent theory.

BACKGROUND: Currently, there is no open-source, cross-platform and scalable framework for coalescent analysis in population genetics. There is no scalable GUI based user application either. Such a framework and application would not only drive the creation of more complex and realistic models but also make them truly accessible. RESULTS: As a first attempt, we built a framework and user application for the domain of exact calculations in coalescent analysis. The framework provides an API with the concepts of model, data, statistic, phylogeny, gene tree and recursion. Infinite-alleles and infinite-sites models are considered. It defines pluggable computations such as counting and listing all the ancestral configurations and genealogies and computing the exact probability of data. It can visualize a gene tree, trace and visualize the internals of the recursion algorithm for further improvement and attach dynamically a number of output processors. The user application defines jobs in a plug-in like manner so that they can be activated, deactivated, installed or uninstalled on demand. Multiple jobs can be run and their inputs edited. Job inputs are persisted across restarts and running jobs can be cancelled where applicable. CONCLUSIONS: Coalescent theory plays an increasingly important role in analysing molecular population genetic data. Models involved are mathematically difficult and computationally challenging. An open-source, scalable framework that lets users immediately take advantage of the progress made by others will enable exploration of yet more difficult and realistic models. As models become more complex and mathematically less tractable, the need for an integrated computational approach is obvious. Object oriented designs, though has upfront costs, are practical now and can provide such an integrated approach.