Loss-of-function mutations in UDP-Glucose 6-Dehydrogenase cause recessive developmental epileptic encephalopathy

Developmental epileptic encephalopathies are devastating disorders characterized by intractable epileptic seizures and developmental delay. Here, we report an allelic series of germline recessive mutations in UGDH in 36 cases from 25 families presenting with epileptic encephalopathy with developmental delay and hypotonia. UGDH encodes an oxidoreductase that converts UDP-glucose to UDP-glucuronic acid, a key component of specific proteoglycans and glycolipids. Consistent with being loss-of-function alleles, we show using patients’ primary fibroblasts and biochemical assays, that these mutations either impair UGDH stability, oligomerization, or enzymatic activity. In vitro, patient-derived cerebral organoids are smaller with a reduced number of proliferating neuronal progenitors while mutant ugdh zebrafish do not phenocopy the human disease. Our study defines UGDH as a key player for the production of extracellular matrix components that are essential for human brain development. Based on the incidence of variants observed, UGDH mutations are likely to be a frequent cause of recessive epileptic encephalopathy

A simple approach to obtain comparable Shigella sonnie MLVA results across laboratories

tMultilocus variable-number tandem repeat analysis (MLVA) is a promising subtyping tool to comple-ment pulsed-field gel electrophoresis for discriminating closely related strains of some monomorphicorganisms, including Shigella sonnei, which is one of the major foodborne pathogens. However, MLVAresults are usually difficult to compare directly between laboratories, impeding the application of MLVAas a subtyping tool for disease surveillance and investigation of common outbreaks across regions orcountries. It has long been a big challenge in seeking an approach that can be implemented to obtaincomparable MLVA results across laboratories. By implementing a panel of calibration strains in each par-ticipating laboratory for data normalization, the MLVA results of 20 test strains were comparable eventhough some analytical conditions were different among the laboratories. This approach is simple, pro-tocol independent, and easy to implement in every laboratory, and a small calibration set is sufficient togenerate mathematical equations for accurate copy number conversio

Experimental assessment of the accuracy of genomic selection in sugarcane

The authors wish to thank T. Dumont, C. Lallemand, I. Promi, R. Tibere, M. Carbel, J. M. Coupan, O. Calvados and N. Lubin for field work, M. Hoarau for lab work. This study was funded by the eRcane company, by CIRAD (Centre de Cooperation Internationale en Recherche Agronomique pour le Developpement) ATP-SEPANG project grant, by the Conseil Regional de la Reunion, by the European Union (European regional development fund-ERDF), by ANR (Agence Nationale de la Recherche) Delicas project grant ANR-08-GENM-001, ANR Grass biofuel project grant ANR-07-GPLA-018-005 and by the ANRT (Association Nationale de la Recherche et de la Technologie) through the CIFRE Ph.D grant No600/2012 of M. Gouy.International audienceSugarcane cultivars are interspecific hybrids with an aneuploid, highly heterozygous polyploid genome. The complexity of the sugarcane genome is the main obstacle to the use of marker-assisted selection in sugarcane breeding. Given the promising results of recent studies of plant genomic selection, we explored the feasibility of genomic selection in this complex polyploid crop. Genetic values were predicted in two independent panels, each composed of 167 accessions representing sugarcane genetic diversity worldwide. Accessions were genotyped with 1,499 DArT markers. One panel was phenotyped in Reunion Island and the other in Guadeloupe. Ten traits concerning sugar and bagasse contents, digestibility and composition of the bagasse, plant morphology, and disease resistance were used. We used four statistical predictive models: bayesian LASSO, ridge regression, reproducing kernel Hilbert space, and partial least square regression. The accuracy of the predictions was assessed through the correlation between observed and predicted genetic values by cross validation within each panel and between the two panels. We observed equivalent accuracy among the four predictive models for a given trait, and marked differences were observed among traits. Depending on the trait concerned, within-panel cross validation yielded median correlations ranging from 0.29 to 0.62 in the Reunion Island panel and from 0.11 to 0.5 in the Guadeloupe panel. Cross validation between panels yielded correlations ranging from 0.13 for smut resistance to 0.55 for brix. This level of correlations is promising for future implementations. Our results provide the first validation of genomic selection in sugarcane

A study on factors for retailers implementing CPFR — A fuzzy AHP analysis

[[abstract]]Since collaborative, planning, forecasting, and replenishment (CPFR) was first proposed in 1998, numerous studies have focused on exploring its implementation in retailing contexts. While a considerable body of research has emphasized reduced costs, increased sales and improved forecasting ability, there has been a lack of research on the importance of each of the various factors which affect such implementations. In order to find out the critical success factors affecting CPFR implementation, this paper first collected related influence factors regarding adopting CPFR or business to business (B2B) information systems, and further constructed a factor table with a three-layer hierarchical structure. A pair wise analytic hierarchy process (AHP) questionnaire was designed and distributed to experts who were familiar with implementing CPFR in the retailing industry. After questionnaires were returned, we found out the weights of each impact factor by using a fuzzy analytic hierarchy process (fuzzy AHP) approach. The importance of each critical impact factor was investigated, and the paths of the critical success factors were also analyzed. The results of this study can provide more precise information with regard to allocating optimal resources for retailers implementing CPFR