Fine-Scale Genetic Structure of \u3ci\u3eMonilinia fructicola\u3c/i\u3e During Brown Rot Epidemics Within Individual Peach Tree Canopies

The purpose of this study was to determine the fine-scale genetic structure of populations of the brown rot pathogen Monilinia fructicola within individual peach tree canopies to better understand within-tree plant pathogen diversity and to complement previous work on spatiotemporal development of brown rot disease at the canopy level. Across 3 years in a total of six trees, we monitored disease development, collected isolates from every M. fructicola symptom during the course of the season, and created high-resolution three-dimensional maps of all symptom and isolate locations within individual canopies using an electromagnetic digitizer. Each canopy population (65 to 173 isolates per tree) was characterized using a set of 13 microsatellite markers and analyzed for evidence of spatial genetic autocorrelation among isolates during the epidemic phase of the disease. Results showed high genetic diversity (average uh = 0.529) and high genotypic diversity (average D = 0.928) within canopies. The percentage of unique multilocus genotypes within trees was greater for blossom blight isolates (78.2%) than for fruit rot isolates (51.3%), indicating a greater contribution of clonal reproduction during the preharvest epidemic. For fruit rot isolates, between 54.2 and 81.7% of isolates were contained in one to four dominant clonal genotypes per tree having at least 10 members. All six fruit rot populations showed positive and significant spatial genetic autocorrelation for distance classes between 0.37 and 1.48 m. Despite high levels of within-tree pathogen diversity, the contribution of locally available inoculum combined with short-distance dispersal is likely the main factor generating clonal population foci and associated spatial genetic clustering within trees

Spatio-temporal Patterns of Pre-harvest Brown Rot Epidemics within Individual Peach Tree Canopies

Tree canopies are architecturally complex and pose several challenges for measuring and character-izing spatial patterns of disease. Recently developed methods for fine-scale canopy mapping and three-dimensional spatial pattern analysis were applied in a 3-year study to characterize spatio-temporal development of pre-harvest brown rot of peach, caused by Monilinia fructicola, in 13 trees of different maturity classes. We observed a negative correlation between an index of disease aggregation and disease incidence in the same tree (r = −0.653, P \u3c 0.0001), showing that trees with higher brown rot incidence had lower aggregation of affected fruit in their canopies. Significant (P ≤ 0.05) within-canopy aggregation among symptomatic fruit was most pronounced for early-maturing cultivars and/or early in the epidemic. This is consistent with the notion of a greater importance of localized, within-tree sources of inoculum at the beginning of the epidemic. Four of five trees having \u3e10 blossom blight symptoms per tree showed a significant positive spatial association of pre-harvest fruit rot to blossom blight within the same canopy. Spatial association analyses further revealed one of two out-comes for the association of new fruit rot symptoms with previous fruit rot symptoms in the same tree, whereby the relationship was either not significant or exhibited a significant negative associa-tion. In the latter scenario, the newly diseased fruit were farther apart from previously symptomatic fruit than expected by random chance. This unexpected result could have been due to uneven fruit ripening in different sectors of the canopy, which could have affected the timing of symptom devel-opment and thus led to negative spatial associations among symptoms developing over time in a tree

Spatio-temporal Patterns of Pre-harvest Brown Rot Epidemics within Individual Peach Tree Canopies

Tree canopies are architecturally complex and pose several challenges for measuring and character-izing spatial patterns of disease. Recently developed methods for fine-scale canopy mapping and three-dimensional spatial pattern analysis were applied in a 3-year study to characterize spatio-temporal development of pre-harvest brown rot of peach, caused by Monilinia fructicola, in 13 trees of different maturity classes. We observed a negative correlation between an index of disease aggregation and disease incidence in the same tree (r = −0.653, P \u3c 0.0001), showing that trees with higher brown rot incidence had lower aggregation of affected fruit in their canopies. Significant (P ≤ 0.05) within-canopy aggregation among symptomatic fruit was most pronounced for early-maturing cultivars and/or early in the epidemic. This is consistent with the notion of a greater importance of localized, within-tree sources of inoculum at the beginning of the epidemic. Four of five trees having \u3e10 blossom blight symptoms per tree showed a significant positive spatial association of pre-harvest fruit rot to blossom blight within the same canopy. Spatial association analyses further revealed one of two out-comes for the association of new fruit rot symptoms with previous fruit rot symptoms in the same tree, whereby the relationship was either not significant or exhibited a significant negative associa-tion. In the latter scenario, the newly diseased fruit were farther apart from previously symptomatic fruit than expected by random chance. This unexpected result could have been due to uneven fruit ripening in different sectors of the canopy, which could have affected the timing of symptom devel-opment and thus led to negative spatial associations among symptoms developing over time in a tree

Characterization of Three-Dimensional Spatial Aggregation and Association Patterns of Brown Rot Symptoms within Intensively Mapped Sour Cherry Trees

Characterization of spatial patterns of plant disease can provide insights into important epidemiological processes such as sources of inoculum, mechanisms of dissemination, and reproductive strategies of the pathogen population. While two-dimensional patterns of disease (among plants within fields) have been studied extensively, there is limited information on three-dimensional patterns within individual plant canopies. Reported here are the detailed mapping of different symptom types of brown rot (caused by Monilinia laxa) in individual sour cherry tree (Prunus cerasus) canopies, and the application of spatial statistics to the resulting data points to de-termine patterns of symptom aggregation and association. Methods – A magnetic digitizer was uti-lized to create detailed three-dimensional maps of three symptom types (blossom blight, shoot blight, and twig canker) in eight sour cherry tree canopies during the green fruit stage of develop-ment. The resulting point patterns were analyzed for aggregation (within a given symptom type) and pairwise association (between symptom types) using a three-dimensional extension of nearest-neighbor analysis. Key Results – Symptoms of M. laxa infection were generally aggregated within the canopy volume, but there was no consistent pattern for one symptom type to be more or less aggre-gated than the other. Analysis of spatial association among symptom types indicated that previous year’s twig cankers may play an important role in influencing the spatial pattern of current year’s symptoms. This observation provides quantitative support for the epidemiological role of twig can-kers as sources of primary inoculum within the tree. Conclusions – Presented here is a new approach to quantify spatial patterns of plant disease in complex fruit tree canopies using point pattern anal-ysis. This work provides a framework for quantitative analysis of three-dimensional spatial patterns within the finite tree canopy, applicable to many fields of research

Spatial Patterns of Brown Rot Epidemics and Development of Microsatellite Markers for Analyzing Fine-Scale Genetic Structure of \u3ci\u3eMonilinia fructicola\u3c/i\u3e Populations Within Peach Tree Canopies

To better understand the fine-scale spatial dynamics of brown rot disease and corresponding fungal genotypes, we analyzed three-dimensional spatial patterns of pre-harvest fruit rot caused by Monilinia fructicola in individual peach tree canopies and developed microsatellite markers for canopy-level population genetics analyses. Using a magnetic digitizer, high-resolution maps of fruit rot development in five representative trees were generated, and M. fructicola was isolated from each affected fruit. To characterize disease aggregation, nearest-neighbor distances among symptomatic fruit were calculated and compared with appropriate random simulations. Within-canopy disease aggregation correlated negatively with the number of diseased fruit per tree (r = −0.827, P = 0.0009), i.e., aggregation was greatest when the number of diseased fruit was lowest. Sixteen microsatellite primers consistently amplified polymorphic regions in a geographically diverse test population of 47 M. fructicola isolates. None of the test isolates produced identical multilocus genotypes, and the number of alleles per locus ranged from 2 to 16. We are applying these markers to determine fine-scale population structure of the pathogen within and among canopies

Spatial Patterns of Brown Rot Epidemics and Development of Microsatellite Markers for Analyzing Fine-Scale Genetic Structure of \u3ci\u3eMonilinia fructicola\u3c/i\u3e Populations Within Peach Tree Canopies

To better understand the fine-scale spatial dynamics of brown rot disease and corresponding fungal genotypes, we analyzed three-dimensional spatial patterns of pre-harvest fruit rot caused by Monilinia fructicola in individual peach tree canopies and developed microsatellite markers for canopy-level population genetics analyses. Using a magnetic digitizer, high-resolution maps of fruit rot development in five representative trees were generated, and M. fructicola was isolated from each affected fruit. To characterize disease aggregation, nearest-neighbor distances among symptomatic fruit were calculated and compared with appropriate random simulations. Within-canopy disease aggregation correlated negatively with the number of diseased fruit per tree (r = −0.827, P = 0.0009), i.e., aggregation was greatest when the number of diseased fruit was lowest. Sixteen microsatellite primers consistently amplified polymorphic regions in a geographically diverse test population of 47 M. fructicola isolates. None of the test isolates produced identical multilocus genotypes, and the number of alleles per locus ranged from 2 to 16. We are applying these markers to determine fine-scale population structure of the pathogen within and among canopies

Constraints on new interactions from neutron scattering experiments

Constraints for the constants of hypothetical Yukawa-type corrections to the Newtonian gravitational potential are obtained from analysis of neutron scattering experiments. Restrictions are obtained for the interaction range between 10^{-12} and 10^{-7} cm, where Casimir force experiments and atomic force microscopy are not sensitive. Experimental limits are obtained also for non-electromagnetic inverse power law neutron-nucleus potential. Some possibilities are discussed to strengthen these constraints.Comment: 18 pages, 3 figure

Freshwater monitoring by nanopore sequencing.

While traditional microbiological freshwater tests focus on the detection of specific bacterial indicator species, including pathogens, direct tracing of all aquatic DNA through metagenomics poses a profound alternative. Yet, in situ metagenomic water surveys face substantial challenges in cost and logistics. Here, we present a simple, fast, cost-effective and remotely accessible freshwater diagnostics workflow centred around the portable nanopore sequencing technology. Using defined compositions and spatiotemporal microbiota from surface water of an example river in Cambridge (UK), we provide optimised experimental and bioinformatics guidelines, including a benchmark with twelve taxonomic classification tools for nanopore sequences. We find that nanopore metagenomics can depict the hydrological core microbiome and fine temporal gradients in line with complementary physicochemical measurements. In a public health context, these data feature relevant sewage signals and pathogen maps at species level resolution. We anticipate that this framework will gather momentum for new environmental monitoring initiatives using portable devices

Freshwater monitoring by nanopore sequencing.

While traditional microbiological freshwater tests focus on the detection of specific bacterial indicator species, including pathogens, direct tracing of all aquatic DNA through metagenomics poses a profound alternative. Yet, in situ metagenomic water surveys face substantial challenges in cost and logistics. Here, we present a simple, fast, cost-effective and remotely accessible freshwater diagnostics workflow centred around the portable nanopore sequencing technology. Using defined compositions and spatiotemporal microbiota from surface water of an example river in Cambridge (UK), we provide optimised experimental and bioinformatics guidelines, including a benchmark with twelve taxonomic classification tools for nanopore sequences. We find that nanopore metagenomics can depict the hydrological core microbiome and fine temporal gradients in line with complementary physicochemical measurements. In a public health context, these data feature relevant sewage signals and pathogen maps at species level resolution. We anticipate that this framework will gather momentum for new environmental monitoring initiatives using portable devices