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Summary We consider the problem of high-dimensional regression under nonconstant error variances. Despite being a common phenomenon in biological applications, heteroscedasticity has, so far, been largely ignored in high-dimensional analysis of genomic data sets. We propose a new methodology that allows nonconstant error variances for high-dimensional estimation and model selection. Our method incorporates heteroscedasticity by simultaneously modeling both the mean and variance components via a novel doubly regularized approach. Extensive Monte Carlo simulations indicate that our proposed procedure can result in better estimation and variable selection than existing methods when heteroscedasticity arises from the presence of predictors explaining error variances and outliers. Further, we demonstrate the presence of heteroscedasticity in and apply our method to an expression quantitative trait loci (eQTLs) study of 112 yeast segregants. The new procedure can automatically account for heteroscedasticity in identifying the eQTLs that are associated with gene expression variations and lead to smaller prediction errors. These results demonstrate the importance of considering heteroscedasticity in eQTL data analysis. [ABSTRACT FROM AUTHOR]

Background: Many questions in statistical genomics can be formulated in terms of variable selection of candidate biological factors for modeling a trait or quantity of interest. Often, in these applications, additional covariates describing clinical, demographical or experimental effects must be included a priori as mandatory covariates while allowing the selection of a large number of candidate or optional variables. As genomic studies routinely require mandatory covariates, it is of interest to propose principled methods of variable selection that can incorporate mandatory covariates.Methods: In this article, we propose the ridge-lasso hybrid estimator (ridle), a new penalized regression method that simultaneously estimates coefficients of mandatory covariates while allowing selection for others. The ridle provides a principled approach to mitigate effects of multicollinearity among the mandatory covariates and possible dependency between mandatory and optional variables. We provide detailed empirical and theoretical studies to evaluate our method. In addition, we develop an efficient algorithm for the ridle. Software, based on efficient Fortran code with R-language wrappers, is publicly and freely available at https://sites.google.com/site/zhongyindaye/software .Results: The ridle is useful when mandatory predictors are known to be significant due to prior knowledge or must be kept for additional analysis. Both theoretical and comprehensive simulation studies have shown that the ridle to be advantageous when mandatory covariates are correlated with the irrelevant optional predictors or are highly correlated among themselves. A microarray gene expression analysis of the histologic grades of breast cancer has identified 24 genes, in which 2 genes are selected only by the ridle among current methods and found to be associated with tumor grade.Conclusions: In this article, we proposed the ridle as a principled sparse regression method for the selection of optional variables while incorporating mandatory ones. Results suggest that the ridle is advantageous when mandatory covariates are correlated with the irrelevant optional predictors or are highly correlated among themselves. [ABSTRACT FROM AUTHOR]

Cumulus cells ( CCs) have an important role during oocyte growth, competence acquisition, maturation, ovulation and fertilization. In an attempt to isolate potential biomarkers for bovine in vitro fertilization, we identified genes differentially expressed in bovine CCs from oocytes with different competence statuses, through microarray analysis. The model of follicle size, in which competent cumulus-oocyte complexes ( COCs) were recovered from bigger follicles (≥8.0 mm in diameter) and less competent ones from smaller follicles (1-3 mm), was used. We identified 4178 genes that were differentially expressed ( P < 0.05) in the two categories of CCs. The list was further enriched, through the use of a 2.5-fold change in gene expression as a cutoff value, to include 143 up-regulated and 80 down-regulated genes in CCs of competent COCs compared to incompetent COCs. These genes were screened according to their cellular roles, most of which were related to cell cycle, DNA repair, energy metabolism, metabolism of amino acids, cell signaling, meiosis, ovulation and inflammation. Three candidate genes up-regulated ( FGF11, IGFBP4, SPRY1) and three down-regulated ( ARHGAP22, COL18A1 and GPC4) in CCs from COCs of big follicles (≥8.1 mm) were selected for qPCR analysis. The selected genes showed the same expression patterns by qPCR and microarray analysis. These genes may be potential genetic markers that predict oocyte competence in in vitro fertilization routines. [ABSTRACT FROM AUTHOR]

In HIV infection, CD4 responses to opportunistic pathogens such as Candida albicans are lost early, but CMV-specific CD4 response persists. Little is currently known about HIV infection of CD4 T cells of different pathogen/antigen specificities. CFSE-Iabeled PBMCs were stimulated with CMV, tetanus toxoid (TT), and C albicans antigens and subsequently exposed to HIV. HIV infection was monitored by intracellular p24 in CFSElow population. We found that although TT- and C albicans-specific CD4 T cells were permissive, CMV-specific CD4 T cells were highly resistant to both R5 and X4 HIV. Quantification of HIV DNA in CFSElow cells showed a reduction of strong-stop and full-length DNA in CMV-specific cells compared with TT- and C albicans-specific cells. β Chemokine neutralization enhanced HIV infection in TT- and C albicans-specific cells, whereas HIV infection in CMV-specific cells remained low despite increased entry by β-Chemokine neutralization, suggesting postentry HIV restriction by CMV-specific cells. Microarray analysis (Gene Expression Omnibus accession number: GSE42853) revealed distinct transcriptional profiles that involved selective up-regulation of comprehensive innate antiviral genes in CMV-specific cells, whereas TT- and C albicans-specific cells mainly up-regulated Th17 inflammatory response. Our data suggest a mechanism for the persistence of CMV-specific CD4 response and earlier loss of mucosal Th17-associated TT- and C albicans-specific CD4 response in AIDS. (Blood. 2013;121(7):1136-1144) [ABSTRACT FROM AUTHOR]

Although the specific functions of sleep have not been completely elucidated, the literature has suggested that sleep is essential for proper homeostasis. Sleep loss is associated with changes in behavioral, neurochemical, cellular, and metabolic function as well as impaired immune response. Using high-resolution microarrays we evaluated the gene expression profiles of healthy male volunteers who underwent 60 h of prolonged wakefulness (PW) followed by 12 h of sleep recovery (SR). Peripheral whole blood was collected at 8 am in the morning before the initiation of PW (Baseline), after the second night of PW, and one night after SR. We identified over 500 genes that were differentially expressed. Notably, these genes were related to DNA damage and repair and stress response, as well as diverse immune system responses, such as natural killer pathways including killer cell lectin-like receptors family, as well as granzymes and T-cell receptors, which play important roles in host defense. These results support the idea that sleep loss can lead to alterations in molecular processes that result in perturbation of cellular immunity, induction of inflammatory responses, and homeostatic imbalance. Moreover, expression of multiple genes was downregulated following PW and upregulated after SR compared with PW, suggesting an attempt of the body to re-establish internal homeostasis. In silico validation of alterations in the expression of CETN3, DNAJC, and CEACAM genes confirmed previous findings related to the molecular effects of sleep deprivation. Thus, the present findings confirm that the effects of sleep loss are not restricted to the brain and can occur intensely in peripheral tissues. [ABSTRACT FROM AUTHOR]

An abstract of the conference paper "Distinct gene expression profiles associated with the susceptibility of pathogen-specific CD4+ T cells to HIV-1 infection," by H. Hu and colleagues are presented.