Wheat rusts never sleep but neither do sequencers: will pathogenomics transform the way plant diseases are managed?

Field pathogenomics adds highly informative data to surveillance surveys by enabling rapid evaluation of pathogen variability, population structure and host genotype

Characterization of Clinically-Attenuated Burkholderia mallei by Whole Genome Sequencing: Candidate Strain for Exclusion from Select Agent Lists

is an understudied biothreat agent responsible for glanders which can be lethal in humans and animals. Research with this pathogen has been hampered in part by constraints of Select Agent regulations for safety reasons. Whole genomic sequencing (WGS) is an apt approach to characterize newly discovered or poorly understood microbial pathogens. genome. Therefore, the strain by itself is unlikely to revert naturally to its virulent phenotype. There were other genes present in one strain and not the other and vice-versa. was both avirulent in the natural host ponies, and did not possess T3SS associated genes may be fortuitous to advance biodefense research. The deleted virulence-essential T3SS is not likely to be re-acquired naturally. These findings may provide a basis for exclusion of SAVP1 from the Select Agent regulation or at least discussion of what else would be required for exclusion. This exclusion could accelerate research by investigators not possessing BSL-3 facilities and facilitate the production of reagents such as antibodies without the restraints of Select Agent regulation

Single nucleotide polymorphism discovery in elite north american potato germplasm

BACKGROUND: Current breeding approaches in potato rely almost entirely on phenotypic evaluations; molecular markers, with the exception of a few linked to disease resistance traits, are not widely used. Large-scale sequence datasets generated primarily through Sanger Expressed Sequence Tag projects are available from a limited number of potato cultivars and access to next generation sequencing technologies permits rapid generation of sequence data for additional cultivars. When coupled with the advent of high throughput genotyping methods, an opportunity now exists for potato breeders to incorporate considerably more genotypic data into their decision-making. RESULTS: To identify a large number of Single Nucleotide Polymorphisms (SNPs) in elite potato germplasm, we sequenced normalized cDNA prepared from three commercial potato cultivars: 'Atlantic', 'Premier Russet' and 'Snowden'. For each cultivar, we generated 2 Gb of sequence which was assembled into a representative transcriptome of (~)28-29 Mb for each cultivar. Using the Maq SNP filter that filters read depth, density, and quality, 575,340 SNPs were identified within these three cultivars. In parallel, 2,358 SNPs were identified within existing Sanger sequences for three additional cultivars, 'Bintje', 'Kennebec', and 'Shepody'. Using a stringent set of filters in conjunction with the potato reference genome, we identified 69,011 high confidence SNPs from these six cultivars for use in genotyping with the Infinium platform. Ninety-six of these SNPs were used with a BeadXpress assay to assess allelic diversity in a germplasm panel of 248 lines; 82 of the SNPs proved sufficiently informative for subsequent analyses. Within diverse North American germplasm, the chip processing market class was most distinct, clearly separated from all other market classes. The round white and russet market classes both include fresh market and processing cultivars. Nevertheless, the russet and round white market classes are more distant from each other than processing are from fresh market types within these two groups. CONCLUSIONS: The genotype data generated in this study, albeit limited in number, has revealed distinct relationships among the market classes of potato. The SNPs identified in this study will enable high-throughput genotyping of germplasm and populations, which in turn will enable more efficient marker-assisted breeding efforts in potato

Facilitative parenting and children's social, emotional and behavioural adjustment

Facilitative parenting (FP) supports the development of children’s social and emotional competence and effective peer relationships. Previous research has shown that FP discriminates between children bullied by peers from children who are not bullied, according to reports of teachers. This study investigates the association between FP and children’s social, emotional and behavioral problems, over and above the association with dysfunctional parenting (DP). 215 parents of children aged 5–11 years completed questionnaires about parenting and child behavior, and children and teachers completed measures of child bullying victimization. As predicted, FP accounted for variance in teacher reports of children’s bullying victimization as well as parent reports of children’s social and emotional problems and prosocial behavior better than that accounted for by DP. However for children’s reports of peer victimization the whole-scale DP was a better predictor than FP. Contrary to predictions, FP accounted for variance in conduct problems and hyperactivity better than DP. When analyses were replicated substituting subscales of dysfunctional and FP, a sub-set of FP subscales including Warmth, Supports Friendships, Not Conflicting, Child Communicates and Coaches were correlated with low levels of problems on a broad range of children’s adjustment problems. Parent–child conflict accounted for unique variance in children’s peer victimization (teacher report), peer problems, depression, emotional problems, conduct problems and hyperactivity. The potential relevance of FP as a protective factor for children against a wide range of adjustment problems is discussed

A Multiparent Advanced Generation Inter-Cross to Fine-Map Quantitative Traits in Arabidopsis thaliana

Identifying natural allelic variation that underlies quantitative trait variation remains a fundamental problem in genetics. Most studies have employed either simple synthetic populations with restricted allelic variation or performed association mapping on a sample of naturally occurring haplotypes. Both of these approaches have some limitations, therefore alternative resources for the genetic dissection of complex traits continue to be sought. Here we describe one such alternative, the Multiparent Advanced Generation Inter-Cross (MAGIC). This approach is expected to improve the precision with which QTL can be mapped, improving the outlook for QTL cloning. Here, we present the first panel of MAGIC lines developed: a set of 527 recombinant inbred lines (RILs) descended from a heterogeneous stock of 19 intermated accessions of the plant Arabidopsis thaliana. These lines and the 19 founders were genotyped with 1,260 single nucleotide polymorphisms and phenotyped for development-related traits. Analytical methods were developed to fine-map quantitative trait loci (QTL) in the MAGIC lines by reconstructing the genome of each line as a mosaic of the founders. We show by simulation that QTL explaining 10% of the phenotypic variance will be detected in most situations with an average mapping error of about 300 kb, and that if the number of lines were doubled the mapping error would be under 200 kb. We also show how the power to detect a QTL and the mapping accuracy vary, depending on QTL location. We demonstrate the utility of this new mapping population by mapping several known QTL with high precision and by finding novel QTL for germination data and bolting time. Our results provide strong support for similar ongoing efforts to produce MAGIC lines in other organisms

Computational models in plant-pathogen interactions: the case of Phytophthora infestans

<p>Abstract</p> <p>Background</p> <p><it>Phytophthora infestans </it>is a devastating oomycete pathogen of potato production worldwide. This review explores the use of computational models for studying the molecular interactions between <it>P. infestans </it>and one of its hosts, <it>Solanum tuberosum</it>.</p> <p>Modeling and conclusion</p> <p>Deterministic logistics models have been widely used to study pathogenicity mechanisms since the early 1950s, and have focused on processes at higher biological resolution levels. In recent years, owing to the availability of high throughput biological data and computational resources, interest in stochastic modeling of plant-pathogen interactions has grown. Stochastic models better reflect the behavior of biological systems. Most modern approaches to plant pathology modeling require molecular kinetics information. Unfortunately, this information is not available for many plant pathogens, including <it>P. infestans</it>. Boolean formalism has compensated for the lack of kinetics; this is especially the case where comparative genomics, protein-protein interactions and differential gene expression are the most common data resources.</p