Spontaneous and Fungicide-Induced Genomic Variation in .

Stress from exposure to sublethal fungicide doses may cause genomic instability in fungal plant pathogens, which may accelerate the emergence of fungicide resistance or other adaptive traits. In a previous study, five strains of were exposed to sublethal doses of four fungicides with different modes of action, and genotyping showed that such exposure induced mutations. The goal of the present study was to characterize genome-wide mutations in response to sublethal fungicide stress in and study the effect of genomic background on the mutational repertoire.

epiflows: an R package for risk assessment of travel-related spread of disease.

As international travel increases worldwide, new surveillance tools are needed to help identify locations where diseases are most likely to be spread and prevention measures need to be implemented. In this paper we present , an R package for risk assessment of travel-related spread of disease.  produces estimates of the expected number of symptomatic and/or asymptomatic infections that could be introduced to other locations from the source of infection.

Genetic Differentiation and Clonal Expansion of Chinese Populations from Tomato and Other Crops in China.

is an important pathogen of vegetable and fruit crops but little is known about its population structure and genetics in China. We hypothesized that the geographic populations of in China would be genetically differentiated by host, geographic location, and/or year. In this study, we collected 393 isolates representing 28 populations from tomato, cherry, and nectarine from 2006 to 2014 in China.

Epidemic curves made easy using the R package .

The epidemiological curve (epicurve) is one of the simplest yet most useful tools used by field epidemiologists, modellers, and decision makers for assessing the dynamics of infectious disease epidemics. Here, we present the free, open-source package incidence for the R programming language, which allows users to easily compute, handle, and visualise epicurves from unaggregated linelist data. This package was built in accordance with the development guidelines of the R Epidemics Consortium (RECON), which aim to ensure robustness and reliability through extensive automated testing, documentation, and good coding practices.

Outbreak analytics: a developing data science for informing the response to emerging pathogens.

Despite continued efforts to improve health systems worldwide, emerging pathogen epidemics remain a major public health concern. Effective response to such outbreaks relies on timely intervention, ideally informed by all available sources of data. The collection, visualization and analysis of outbreak data are becoming increasingly complex, owing to the diversity in types of data, questions and available methods to address them.

Population structure and phenotypic variation of from dry bean () in the United States.

The ascomycete pathogen is a necrotrophic pathogen on over 400 known host plants, and is the causal agent of white mold on dry bean. Currently, there are no known cultivars of dry bean with complete resistance to white mold. For more than 20 years, bean breeders have been using white mold screening nurseries (wmn) with natural populations of to screen new cultivars for resistance.

apex: phylogenetics with multiple genes.

Genetic sequences of multiple genes are becoming increasingly common for a wide range of organisms including viruses, bacteria and eukaryotes. While such data may sometimes be treated as a single locus, in practice, a number of biological and statistical phenomena can lead to phylogenetic incongruence. In such cases, different loci should, at least as a preliminary step, be examined and analysed separately.

Developing educational resources for population genetics in R: an open and collaborative approach.

The r computing and statistical language community has developed a myriad of resources for conducting population genetic analyses. However, resources for learning how to carry out population genetic analyses in r are scattered and often incomplete, which can make acquiring this skill unnecessarily difficult and time consuming. To address this gap, we developed an online community resource with guidance and working demonstrations for conducting population genetic analyses in r.

Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality.

To gain a detailed understanding of how plant microbes evolve and adapt to hosts, pesticides, and other factors, knowledge of the population dynamics and evolutionary history of populations is crucial. Plant pathogen populations are often clonal or partially clonal which requires different analytical tools. With the advent of high throughput sequencing technologies, obtaining genome-wide population genetic data has become easier than ever before.

Population Structure of Pythium irregulare, P. ultimum, and P. sylvaticum in Forest Nursery Soils of Oregon and Washington.

Pythium species are important soilborne pathogens occurring in the forest nursery industry of the Pacific Northwest. However, little is known about their genetic diversity or population structure and it is suspected that isolates are moved among forest nurseries on seedling stock and shared field equipment. In order to address these concerns, a total of 115 isolates of three Pythium species (P.

Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction.

Many microbial, fungal, or oomcyete populations violate assumptions for population genetic analysis because these populations are clonal, admixed, partially clonal, and/or sexual. Furthermore, few tools exist that are specifically designed for analyzing data from clonal populations, making analysis difficult and haphazard. We developed the R package poppr providing unique tools for analysis of data from admixed, clonal, mixed, and/or sexual populations.

Involving undergraduates in the annotation and analysis of global gene expression studies: creation of a maize shoot apical meristem expression database.

Through a multi-university and interdisciplinary project we have involved undergraduate biology and computer science research students in the functional annotation of maize genes and the analysis of their microarray expression patterns. We have created a database to house the results of our functional annotation of >4400 genes identified as being differentially regulated in the maize shoot apical meristem (SAM). This database is located at http://sam.