Mixture modeling provides an effective approach to the differential expression problem in microarray data analysis. Methods based on fully parametric mixture models are available, but lack of fit in some examples indicates that more flexible models may be beneficial. Existing, more flexible, mixture models work at the level of one-dimensional gene-specific summary statistics, and so when there are relatively few measurements per gene these methods may not provide sensitive detectors of differential expression. We propose a hierarchical mixture model to provide methodology that is both sensitive in detecting differential expression and sufficiently flexible to account for the complex variability of normalized microarray data. EM-based algorithms are used to fit both parametric and semiparametric versions of the model. We restrict attention to the two-sample comparison problem; an experiment involving Affymetrix microarrays and yeast translation provides the motivating case study. Gene-specific posterior probabilities of differential expression form the basis of statistical inference; they define short gene lists and false discovery rates. Compared to several competing methodologies, the proposed methodology exhibits good operating characteristics in a simulation study, on the analysis of spike-in data, and in a cross-validation calculation.

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Brome mosaic virus (BMV), a member of the alphavirus-like superfamily of human-, animal-, and plant-infecting (ϩ)RNA viruses, has been studied as a model for viral RNA replication, encapsidation, recombination, and other processes (3). BMV has three genomic RNAs. RNAs 1 and 2 encode the interacting, multifunctional 1a helicase-like and 2a polymerase RNA replication factors (4, 5), which form endoplasmic reticulum (ER) membrane-associated RNA replication complexes with functional similarities to the replicative cores of retrovirus and double-strand (ds)RNA virus virions (6). RNA3 encodes protein 3a that enables infection spread between cells in natural hosts. The negative-strand [(Ϫ) RNA]3 replication intermediate also serves as a template for synthesis of a subgenomic (sg) mRNA, RNA4, which encodes the viral coat protein (Fig. 1A).The yeast Saccharomyces cerevisiae has proven a valuable model for normal and disease processes in human and other cells. The unusual ability of BMV to direct its genomic RNA replication, gene expression, encapsidation, and other processes in this yeast (7,8) has allowed traditional yeast mutagenic analyses that have identified host genes involved in multiple steps of BMV RNA replication and gene expression. Such host genes encode a wide variety of functions and contribute to diverse replication steps, including supporting and regulating viral translation, selecting and recruiting viral RNAs as replication templates, activating the RNA replication complex through chaperones, and providing a lipid profile compatible with membrane-associated viral RNA replication (9-14; reviewed in refs. 2 and 15).Here, we sought to develop a more rapid, global method to systematically identify yeast host factors with effects on BMV RNA replication by using an ordered array of yeast deletion strains (16) to assay virus replication in the absence of each of Ϸ4,500 yeast factors, which is Ϸ80% of the yeast genome. We describe screening this deletion array by using a whole-cell assay based on BMV-directed Renilla luciferase (Rluc) expression by pathways dependent on viral RNA replication and viral RNAdirected sg mRNA synthesis. The assay identified nearly 100 host genes whose absence repressed or enhanced BMV-directed Rluc expression by 3-to 25-fold. The results provide a significantly expanded view of virus-host interactions and should advance understanding of virus and cell pathways. Materials and MethodsYeast. YMI04 and ded1i yeast were described (11). Strains BY4743 (WT; ref. 17) and the homozygous diploid deletion series (BY4743 strain background; ref. 16) were from Research Genetics (Huntsville, AL). Standard yeast techniques were used (18), except for 96-well transformations, which were based on a one-step procedure (19). Briefly, yeast were grown to saturation overnight at 30°C in 96-well plates (1.2 ml per well), pelleted, suspended in 100 l of transformation mix (0.18 M LiAc, pH 5.5, 36% polyethylene glycol-3350, 90 mM DTT, 0.5 mg͞ml sheared salmon sperm DNA, and 20 g͞ml of each plasmid), incubate...

Inevitably, viruses depend on host factors for their multiplication. Here, we show that hepatitis C virus (HCV) RNA translation and replication depends on Rck/p54, LSm1, and PatL1, which regulate the fate of cellular mRNAs from translation to degradation in the 5 -3 -deadenylation-dependent mRNA decay pathway. The requirement of these proteins for efficient HCV RNA translation was linked to the 5 and 3 untranslated regions (UTRs) of the viral genome. Furthermore, LSm1-7 complexes specifically interacted with essential cis-acting HCV RNA elements located in the UTRs. These results bridge HCV life cycle requirements and highly conserved host proteins of cellular mRNA decay. The previously described role of these proteins in the replication of 2 other positive-strand RNA viruses, the plant brome mosaic virus and the bacteriophage Qß, pinpoint a weak spot that may be exploited to generate broad-spectrum antiviral drugs.deadenylation-dependent mRNA decay ͉ HCV ͉ host factors ͉ LSm1-7 ͉ Rck/p54