Identification of a new gene mutated in Fraser syndrome and mouse myelencephalic blebs

Fraser syndrome is a recessive, multisystem disorder presenting with cryptophthalmos, syndactyly and renal defects and associated with loss-of-function mutations of the extracellular matrix protein FRAS1. Fras1 mutant mice have a blebbed phenotype characterized by intrauterine epithelial fragility generating serous and, later, hemorrhagic blisters. The myelencephalic blebs (my) strain has a similar phenotype. We mapped my to Frem2, a gene related to Fras1 and Frem1, and showed that a Frem2 gene-trap mutation was allelic to my. Expression of Frem2 in adult kidneys correlated with cyst formation in my homozygotes, indicating that the gene is required for maintaining the differentiated state of renal epithelia. Two individuals with Fraser syndrome were homozygous with respect to the same missense mutation of FREM2, confirming genetic heterogeneity. This is the only missense mutation reported in any blebbing mutant or individual with Fraser syndrome, suggesting that calcium binding in the CALXbeta-cadherin motif is important for normal functioning of FREM2.     

Evaluating volatility and interval forecasts

A widely used approach to evaluating volatility forecasts uses a regression framework which measures the bias and variance of the forecast. We show that the associated test for bias is inappropriate before introducing a more suitable procedure which is based on the test for bias in a conditional mean forecast. Although volatility has been the most common measure of the variability in a financial time series, in many situations confidence interval forecasts are required. We consider the evaluation of interval forecasts and present a regression‐based procedure which uses quantile regression to assess quantile estimator bias and variance. We use exchange rate data to illustrate the proposal by evaluating seven quantile estimators, one of which is a new non‐parametric autoregressive conditional heteroscedasticity quantile estimator. The empirical analysis shows that the new evaluation procedure provides useful insight into the quality of quantile estimators. Copyright © 1999 John Wiley & Sons, Ltd.