Survival of blackleg pathogen inoculum in canola stubble under simulated flooding conditions

Non-Peer ReviewedBlackleg of canola (Brassica napus), caused by two Leptosphaeria spp, is a significant constraint to canola production worldwide except in china where only the less virulent L. biglobosa has been reported. In China, the disease is caused by a less pathogenic species, L. biglobosa, and there is a concern that importing canola from Canada may introduce the virulent L. maculans, impacting the crop there negatively. In China, canola (or rapeseed) production is centered in several eastern and central provinces where winter rapeseed is often followed by paddy rice that normally is flooded for weeks during late spring and summer. L. maculans or L. biglobosa in diseased canola stubbles serves as the key inoculum source to cause blackleg, and it has been questioned if the flooding practice may help suppress the inoculum. A study was initiated to determine the effect of flooding temperature (12 to 40°C) and duration (2 to 12 weeks) on survival of blackleg pathogen in canola stubbles. Experiments were set up on a Thermogradient Plate that is capable of simultaneously creating 96 independent temperature settings. Diseased stubbles with > scale-3 level of basal stem-canker symptoms used for the experiments were collected from a Westar canola plot in Melfort after 2011 harvest. Flooded stubbles were sampled every two weeks, surface sterilized, and incubated on V8-juice medium amended with antibiotics for 10 days to observe pycnidia cultures of L. maculans or L. biglobosa as the evidence of pathogen survival. Two trials were set up in RCBD with four replications, and pathogen incidence data (based on 25 stubble pieces per replicated) were subject to ANOVA. Significant reduction (P= 0.01) of pathogen incidence was observed at 2-week flooding treatment relative to control (non-flooded) and there was no pathogen recovery after 4weeks of flooding till 12 weeks of experiment. Lower flooding temperatures of 12oC and 16oC appeared to be slightly less effective than higher temperatures (20-40 oC) in reducing pathogen survival. Stubble tissues degraded sharply after 2weeks (contrast, P= 0.05) in response to the flooding temperature and the dry weight was reduced more substantially (40%) at higher temperatures. Virulence of any survived pathogen propagule after flooding is still intact and survival at any temperature or duration of flooding does not differentiate between L. maculans or L. biglobosa. High proportion of survived blackleg pathogen (pycnidia) from flooding were L. maculans (67%) and the rest L. biglobosa (33.0%) under Westar cotyledon test

Sequence-Based Genotyping for Marker Discovery and Co-Dominant Scoring in Germplasm and Populations

Conventional marker-based genotyping platforms are widely available, but not without their limitations. In this context, we developed Sequence-Based Genotyping (SBG), a technology for simultaneous marker discovery and co-dominant scoring, using next-generation sequencing. SBG offers users several advantages including a generic sample preparation method, a highly robust genome complexity reduction strategy to facilitate de novo marker discovery across entire genomes, and a uniform bioinformatics workflow strategy to achieve genotyping goals tailored to individual species, regardless of the availability of a reference sequence. The most distinguishing features of this technology are the ability to genotype any population structure, regardless whether parental data is included, and the ability to co-dominantly score SNP markers segregating in populations. To demonstrate the capabilities of SBG, we performed marker discovery and genotyping in Arabidopsis thaliana and lettuce, two plant species of diverse genetic complexity and backgrounds. Initially we obtained 1,409 SNPs for arabidopsis, and 5,583 SNPs for lettuce. Further filtering of the SNP dataset produced over 1,000 high quality SNP markers for each species. We obtained a genotyping rate of 201.2 genotypes/SNP and 58.3 genotypes/SNP for arabidopsis (n = 222 samples) and lettuce (n = 87 samples), respectively. Linkage mapping using these SNPs resulted in stable map configurations. We have therefore shown that the SBG approach presented provides users with the utmost flexibility in garnering high quality markers that can be directly used for genotyping and downstream applications. Until advances and costs will allow for routine whole-genome sequencing of populations, we expect that sequence-based genotyping technologies such as SBG will be essential for genotyping of model and non-model genomes alike

SNPSelect: A scalable and flexible targeted sequence-based genotyping solution.

In plant breeding the use of molecular markers has resulted in tremendous improvement of the speed with which new crop varieties are introduced into the market. Single Nucleotide Polymorphism (SNP) genotyping is routinely used for association studies, Linkage Disequilibrium (LD) and Quantitative Trait Locus (QTL) mapping studies, marker-assisted backcrosses and validation of large numbers of novel SNPs. Here we present the KeyGene SNPSelect technology, a scalable and flexible multiplexed, targeted sequence-based, genotyping solution. The multiplex composition of SNPSelect assays can be easily changed between experiments by adding or removing loci, demonstrating their content flexibility. To demonstrate this versatility, we first designed a 1,056-plex maize assay and genotyped a total of 374 samples originating from an F2 and a Recombinant Inbred Line (RIL) population and a maize germplasm collection. Next, subsets of the most informative SNP loci were assembled in 384-plex and 768-plex assays for further genotyping. Indeed, selection of the most informative SNPs allows cost-efficient yet highly informative genotyping in a custom-made fashion, with average call rates between 88.1% (1,056-plex assay) and 99.4% (384-plex assay), and average reproducibility rates between duplicate samples ranging from 98.2% (1056-plex assay) to 99.9% (384-plex assay). The SNPSelect workflow can be completed from a DNA sample to a genotype dataset in less than three days. We propose SNPSelect as an attractive and competitive genotyping solution to meet the targeted genotyping needs in fields such as plant breeding

Saliva oxytocin, cortisol, and testosterone levels in adolescent boys with autism spectrum disorder, oppositional defiant disorder/conduct disorder and typically developing individuals

The aim of the current study was to compare levels of oxytocin, cortisol, and testosterone in adolescents with either autism spectrum disorder (ASD), or oppositional defiant disorder (ODD)/conduct disorder (CD), and in typically developing individuals (TDI), and relate hormone levels to severity and subtype of aggression and callous-unemotional (CU) traits. Saliva concentrations of oxytocin, cortisol, and testosterone were assessed in 114 male participants (N = 49 ASD, N = 37 ODD/CD, N = 28 TDI,) aged 12-19 years (M = 15.4 years, SD = 1.9). The ASD and the ODD/CD groups had significantly lower levels of oxytocin than the TDI group, and the ODD/CD group had significantly higher levels of testosterone than the ASD group. There were no group effects on cortisol levels. Group differences remained for oxytocin after correcting for the influence of CU traits, but were not significant after controlling for aggression. Results for testosterone became non-significant after correction for either CU traits or aggression. Across groups, higher levels of CU traits were related to higher levels of cortisol and testosterone, however, proactive and reactive aggression were unrelated to all three hormonal levels. The current findings show that, regardless of cognitive ability or comorbid disorders, the diagnostic groups (ASD, ODD/CD) differ from each other by their hormonal levels, with the ASD group characterized by relative low level of oxytocin, and the ODD/CD group by a relative low level of oxytocin and high level of testosterone. These group effects were partly driven by differences in CU traits between the groups

Bioinformatics analysis workflow for SBG.

<p>The Illumina data are first processed to remove low quality reads. The reference sequences are generated by clustering the unique reads present within the dataset. The reads are subsequently aligned to the reference sequences and variation called using the GATK Unified Genotyper. Lastly, the final set of SNPs and genotypes are generated by removing SNPs not meeting the threshold for percentage of missing data and expected genotypic frequencies.</p

Variant calling for the arabidopsis and lettuce sequence datasets.

<p>Variant calling for the arabidopsis and lettuce sequence datasets.</p

Overview of SBG.

<p>(A) The sequencing complexity of genomic DNA is reduced using a combination of rare and frequent cutting enzymes. (B) Sequencing adapters containing sample identification tags are ligated to the restriction fragments to construct SBG libraries. SBG libraries are amplified and sequenced using Illumina sequencing platforms. Only read 1 will be sequenced for single-end sequencing, while both read 1 and read 2 will be sequenced for paired-end sequencing. (C) SNPs are mined between the samples and simultaneously genotyped using the SBG bioinformatics analysis workflow.</p

Parent-based SNP genotyping in the arabidopsis and lettuce sequence datasets after removing SNPs displaying extreme genotypic frequencies and an excessive number of missing genotypes.

<p>Parent-based SNP genotyping in the arabidopsis and lettuce sequence datasets after removing SNPs displaying extreme genotypic frequencies and an excessive number of missing genotypes.</p