Effector Genomics Accelerates Discovery and Functional Profiling of Potato Disease Resistance and Phytophthora Infestans Avirulence Genes

Potato is the world's fourth largest food crop yet it continues to endure late blight, a devastating disease caused by the Irish famine pathogen Phytophthora infestans. Breeding broad-spectrum disease resistance (R) genes into potato (Solanum tuberosum) is the best strategy for genetically managing late blight but current approaches are slow and inefficient. We used a repertoire of effector genes predicted computationally from the P. infestans genome to accelerate the identification, functional characterization, and cloning of potentially broad-spectrum R genes. An initial set of 54 effectors containing a signal peptide and a RXLR motif was profiled for activation of innate immunity (avirulence or Avr activity) on wild Solanum species and tentative Avr candidates were identified. The RXLR effector family IpiO induced hypersensitive responses (HR) in S. stoloniferum, S. papita and the more distantly related S. bulbocastanum, the source of the R gene Rpi-blb1. Genetic studies with S. stoloniferum showed cosegregation of resistance to P. infestans and response to IpiO. Transient co-expression of IpiO with Rpi-blb1 in a heterologous Nicotiana benthamiana system identified IpiO as Avr-blb1. A candidate gene approach led to the rapid cloning of S. stoloniferum Rpi-sto1 and S. papita Rpi-pta1, which are functionally equivalent to Rpi-blb1. Our findings indicate that effector genomics enables discovery and functional profiling of late blight R genes and Avr genes at an unprecedented rate and promises to accelerate the engineering of late blight resistant potato varieties

The DUX-25 after Twenty-Five Years: New Analyses and Reference Data

Twenty-five years after its inception, we present new analyses and reference data for the DUX-25, a questionnaire on health-related quality of life for children 8–17 years old and their parents as proxy. Data from 774 healthy children and their caregivers were collected through web-based data collection. Participants were recruited via primary and secondary schools in the Netherlands. The DUX-25 showed adequate psychometric qualities. Using exploratory and confirmatory factor analyses, we were able to support the theorized four-factor model. In addition, a model with five factors emerged in which the factor ‘Social’ was divided into ‘Social Close’ and ‘Social Far’. A comparison of the outcomes of the PedsQL with those of the DUX-25 provides evidence for a high construct validity of the DUX-25. With the new updated reference data, the DUX-25 can still be used in inpatient and outpatient settings to measure health-related quality of life of children with chronic conditions

Sex differences in children's health status as measured by the Pediatric Quality of Life Inventory (PedsQL)™: cross-sectional findings from a large school-based sample in the Netherlands

Background: Previous research has shown that female adolescents and adults report lower health status than their male peers. Possibly, this discrepancy already develops during childhood. We collected sex-specific data with the Pediatric Quality of Life Inventory (PedsQL) in a large school-based sample. Methods: The online version of the PedsQL was administered to healthy Dutch children aged 5–7 years (parent proxy-report), 8–12 years (parent proxy-report and child self-report), and 13–17 years (parent proxy-report and child self-report), recruited through regular primary and secondary schools. Sex differences were assessed using t-tests or Mann–Whitney U-tests. Wilcoxon signed-rank tests and intraclass correlation coefficients served to compare parent proxy-reports with child self-reports. Multivariable linear regression analyses were used to assess the associations of sex of the child, age, and parental educational level with PedsQL scores. Results: Eight hundred eighty-two parents and five hundred eighty one children were recruited from 15 different schools in the Netherlands. Parents of 8-to-12-year-olds reported higher scores on School Functioning for girls than for boys (mean difference [MD]: 6.56, p < 0.001). Parents of 13-to-17-year-olds reported lower scores on Physical and Emotional Functioning for girls than for boys (MDs: 2.14 and 5.79, p = 0.014 and p < 0.001, respectively). Girls aged 8–12 years reported lower scores than boys in this age group on Physical Functioning (MD: 3.09, p = 0.005). Girls aged 13–17 years reported lower scores than boys in this age group on Physical Functioning (MD: 3.67, p < 0.001), Emotional Functioning (MD: 8.11, p < 0.001), and the Total Score (MD 3.26, p = 0.004). No sex differences were found in children aged 5–7 years. Agreement between child self-reports and parent proxy-reports was poor to moderate. Conclusions: Girls generally had lower PedsQL scores than boys, both in parent proxy-reports and in child self-reports. We recommend to apply sex-specific data when assessing health status using the PedsQL

Sol<it>R</it>gene: an online database to explore disease resistance genes in tuber-bearing <it>Solanum </it>species

Abstract Background The cultivated potato (Solanum tuberosum L.) is an important food crop, but highly susceptible to many pathogens. The major threat to potato production is the Irish famine pathogen Phytophthora infestans, which causes the devastating late blight disease. Potato breeding makes use of germplasm from wild relatives (wild germplasm) to introduce resistances into cultivated potato. The Solanum section Petota comprises tuber-bearing species that are potential donors of new disease resistance genes. The aim of this study was to explore Solanum section Petota for resistance genes and generate a widely accessible resource that is useful for studying and implementing disease resistance in potato. Description The SolRgene database contains data on resistance to P. infestans and presence of R genes and R gene homologues in Solanum section Petota. We have explored Solanum section Petota for resistance to late blight in high throughput disease tests under various laboratory conditions and in field trials. From resistant wild germplasm, segregating populations were generated and assessed for the presence of resistance genes. All these data have been entered into the SolRgene database. To facilitate genetic and resistance gene evolution studies, phylogenetic data of the entire SolRgene collection are included, as well as a tool for generating phylogenetic trees of selected groups of germplasm. Data from resistance gene allele-mining studies are incorporated, which enables detection of R gene homologs in related germplasm. Using these resources, various resistance genes have been detected and some of these have been cloned, whereas others are in the cloning pipeline. All this information is stored in the online SolRgene database, which allows users to query resistance data, sequences, passport data of the accessions, and phylogenic classifications. Conclusion Solanum section Petota forms the basis of the SolRgene database, which contains a collection of resistance data of an unprecedented size and precision. Complemented with R gene sequence data and phylogenetic tools, SolRgene can be considered the primary resource for information on R genes from potato and wild tuber-bearing relatives.</p

Identification of mega-environments in Europe and effect of allelic variation at maturity E loci on adaptation of European soybean

Soybean cultivation holds great potential for a sustainable agriculture in Europe, but adaptation remains a central issue. In this large mega-environment (MEV) study, 75 European cultivars from five early maturity groups (MGs 000-II) were evaluated for maturity-related traits at 22 locations in 10 countries across Europe. Clustering of the locations based on phenotypic similarity revealed six MEVs in latitudinal direction and suggested several more. Analysis of maturity identified several groups of cultivars with phenotypic similarity that are optimally adapted to the different growing regions in Europe. We identified several haplotypes for the allelic variants at the E1, E2, E3 and E4 genes, with each E haplotype comprising cultivars from different MGs. Cultivars with the same E haplotype can exhibit different flowering and maturity characteristics, suggesting that the genetic control of these traits is more complex and that adaptation involves additional genetic pathways, for example temperature requirement. Taken together, our study allowed the first unified assessment of soybean-growing regions in Europe and illustrates the strong effect of photoperiod on soybean adaptation and MEV classification, as well as the effects of the E maturity loci for soybean adaptation in Europe