Conserved Role of unc-79 in Ethanol Responses in Lightweight Mutant Mice

The mechanisms by which ethanol and inhaled anesthetics influence the nervous system are poorly understood. Here we describe the positional cloning and characterization of a new mouse mutation isolated in an N-ethyl-N-nitrosourea (ENU) forward mutagenesis screen for animals with enhanced locomotor activity. This allele, Lightweight (Lwt), disrupts the homolog of the Caenorhabditis elegans (C. elegans) unc-79 gene. While Lwt/Lwt homozygotes are perinatal lethal, Lightweight heterozygotes are dramatically hypersensitive to acute ethanol exposure. Experiments in C. elegans demonstrate a conserved hypersensitivity to ethanol in unc-79 mutants and extend this observation to the related unc-80 mutant and nca-1;nca-2 double mutants. Lightweight heterozygotes also exhibit an altered response to the anesthetic isoflurane, reminiscent of unc-79 invertebrate mutant phenotypes. Consistent with our initial mapping results, Lightweight heterozygotes are mildly hyperactive when exposed to a novel environment and are smaller than wild-type animals. In addition, Lightweight heterozygotes exhibit increased food consumption yet have a leaner body composition. Interestingly, Lightweight heterozygotes voluntarily consume more ethanol than wild-type littermates. The acute hypersensitivity to and increased voluntary consumption of ethanol observed in Lightweight heterozygous mice in combination with the observed hypersensitivity to ethanol in C. elegans unc-79, unc-80, and nca-1;nca-2 double mutants suggests a novel conserved pathway that might influence alcohol-related behaviors in humans

BIOINFORMATICS ORIGINAL PAPER Genome analysis A genotype calling algorithm for affymetrix SNP arrays

Motivation: A classification algorithm, based on a multi-chip, multi-SNP approach is proposed for Affymetrix SNP arrays. Current procedures for calling genotypes on SNP arrays process all the features associated with one chip and one SNP at a time. Using a large training sample where the genotype labels are known, we develop a supervised learning algorithm to obtain more accurate classification results on new data. The method we propose, RLMM, is based on a robustly fitted, linear model and uses the Mahalanobis distance for classification. The chip-to-chip non-biological variance is reduced through normalization. This model-based algorithm captures the similarities across genotype groups and probes, as well as across thousands of SNPs for accurate classification. In this paper, we apply RLMM to Affymetrix 100 K SNP array data, present classification results and compare them with genotype calls obtained from the Affymetrix procedure DM, as well as to the publicly available genotype calls from the HapMap project. Availability: The RLMM software is implemented in R and is available from Bioconductor or from the first author a

The Impact of an Inaccurate Diagnostic Biomarker on Phase II Clinical Trials in The Development of Targeted Therapy.

Current research in oncology aims at developing targeted therapies to treat the heterogeneous patient population. Successful development 1 of a targeted therapy requires a biomarker that identifies patients who are most likely to benefit from the treatment. However, most biomark-ers are inherently inaccurate. We present a simulation study to examine how the sensitivity and specificity of a single, binary biomarker influ-ences the Cox estimates of hazard ratios in phase II clinical trials. We discuss how the bias introduced by marker inaccuracy impacts the de-cision of whether to carry a drug forward to a phase III clinical trial. Finally, we propose a bootstrap-based method for reducing the bias of the Cox estimator, in the presence of an inaccurate marker

A genotype calling algorithm for Affymetrix SNP arrays

∗ To whom correspondence should be addressed Motivation: A classification algorithm, based on a multi-chip, multi-SNP approach is proposed for Affymetrix SNP arrays. Current procedures for calling genotypes on SNP arrays process all the features associated with one chip and one SNP at a time. Using a large training sample where the genotype labels are known, we develop a supervised learning algorithm to obtain more accurate classification results on new data. The method we propose, RLMM, is based on a robustly fitted, linear model and uses the Mahalanobis distance for classification. The chip-to-chip non-biological variance is reduced through normalization. This model-based algorithm captures the similarities across genotype groups and probes, as well as across thousands of SNPs for accurate classification. In this paper, we apply RLMM to Affymetrix 100K SNP array data, present classification results and compare them to genotype calls obtained from the Affymetrix procedure DM, as well as to the publicly available genotype calls from the HapMap project. Availability: The RLMM software is implemented in R and is available from the first author a

Conserved role of unc-79 in ethanol responses in lightweight mutant mice.

The mechanisms by which ethanol and inhaled anesthetics influence the nervous system are poorly understood. Here we describe the positional cloning and characterization of a new mouse mutation isolated in an N-ethyl-N-nitrosourea (ENU) forward mutagenesis screen for animals with enhanced locomotor activity. This allele, Lightweight (Lwt), disrupts the homolog of the Caenorhabditis elegans (C. elegans) unc-79 gene. While Lwt/Lwt homozygotes are perinatal lethal, Lightweight heterozygotes are dramatically hypersensitive to acute ethanol exposure. Experiments in C. elegans demonstrate a conserved hypersensitivity to ethanol in unc-79 mutants and extend this observation to the related unc-80 mutant and nca-1;nca-2 double mutants. Lightweight heterozygotes also exhibit an altered response to the anesthetic isoflurane, reminiscent of unc-79 invertebrate mutant phenotypes. Consistent with our initial mapping results, Lightweight heterozygotes are mildly hyperactive when exposed to a novel environment and are smaller than wild-type animals. In addition, Lightweight heterozygotes exhibit increased food consumption yet have a leaner body composition. Interestingly, Lightweight heterozygotes voluntarily consume more ethanol than wild-type littermates. The acute hypersensitivity to and increased voluntary consumption of ethanol observed in Lightweight heterozygous mice in combination with the observed hypersensitivity to ethanol in C. elegans unc-79, unc-80, and nca-1;nca-2 double mutants suggests a novel conserved pathway that might influence alcohol-related behaviors in humans