Analysis of oligonucleotide array experiments with repeated measures using mixed models

BACKGROUND: Two or more factor mixed factorial experiments are becoming increasingly common in microarray data analysis. In this case study, the two factors are presence (Patients with Alzheimer's disease) or absence (Control) of the disease, and brain regions including olfactory bulb (OB) or cerebellum (CER). In the design considered in this manuscript, OB and CER are repeated measurements from the same subject and, hence, are correlated. It is critical to identify sources of variability in the analysis of oligonucleotide array experiments with repeated measures and correlations among data points have to be considered. In addition, multiple testing problems are more complicated in experiments with multi-level treatments or treatment combinations. RESULTS: In this study we adopted a linear mixed model to analyze oligonucleotide array experiments with repeated measures. We first construct a generalized F test to select differentially expressed genes. The Benjamini and Hochberg (BH) procedure of controlling false discovery rate (FDR) at 5% was applied to the P values of the generalized F test. For those genes with significant generalized F test, we then categorize them based on whether the interaction terms were significant or not at the α-level (α(new )= 0.0033) determined by the FDR procedure. Since simple effects may be examined for the genes with significant interaction effect, we adopt the protected Fisher's least significant difference test (LSD) procedure at the level of α(new )to control the family-wise error rate (FWER) for each gene examined. CONCLUSIONS: A linear mixed model is appropriate for analysis of oligonucleotide array experiments with repeated measures. We constructed a generalized F test to select differentially expressed genes, and then applied a specific sequence of tests to identify factorial effects. This sequence of tests applied was designed to control for gene based FWER

Resistance to Gray Leaf Spot of Maize: Genetic Architecture and Mechanisms Elucidated through Nested Association Mapping and Near-Isogenic Line Analysis

Citation: Benson, J. M., Poland, J. A., Benson, B. M., Stromberg, E. L., & Nelson, R. J. (2015). Resistance to Gray Leaf Spot of Maize: Genetic Architecture and Mechanisms Elucidated through Nested Association Mapping and Near-Isogenic Line Analysis. Plos Genetics, 11(3), 23. https://doi.org/10.1371/journal.pgen.1005045Gray leaf spot (GLS), caused by Cercospora zeae-maydis and Cercospora zeina, is one of the most important diseases of maize worldwide. The pathogen has a necrotrophic lifestyle and no major genes are known for GLS. Quantitative resistance, although poorly understood, is important for GLS management. We used genetic mapping to refine understanding of the genetic architecture of GLS resistance and to develop hypotheses regarding the mechanisms underlying quantitative disease resistance (QDR) loci. Nested association mapping (NAM) was used to identify 16 quantitative trait loci (QTL) for QDR to GLS, including seven novel QTL, each of which demonstrated allelic series with significant effects above and below the magnitude of the B73 reference allele. Alleles at three QTL, qGLS1.04, qGLS2.09, and qGLS4.05, conferred disease reductions of greater than 10%. Interactions between loci were detected for three pairs of loci, including an interaction between iqGLS4.05 and qGLS7.03. Near-isogenic lines (NILs) were developed to confirm and fine-map three of the 16 QTL, and to develop hypotheses regarding mechanisms of resistance. qGLS1.04 was fine-mapped from an interval of 27.0 Mb to two intervals of 6.5 Mb and 5.2 Mb, consistent with the hypothesis that multiple genes underlie highly significant QTL identified by NAM. qGLS2.09, which was also associated with maturity (days to anthesis) and with resistance to southern leaf blight, was narrowed to a 4-Mb interval. The distance between major leaf veins was strongly associated with resistance to GLS at qGLS4.05. NILs for qGLS1.04 were treated with the C. zeae-maydis toxin cercosporin to test the role of host-specific toxin in QDR. Cercosporin exposure increased expression of a putative flavin-monooxygenase (FMO) gene, a candidate detoxification-related gene underlying qGLS1.04. This integrated approach to confirming QTL and characterizing the potential underlying mechanisms advances the understanding of QDR and will facilitate the development of resistant varieties

Identification of gene expression patterns using planned linear contrasts

BACKGROUND: In gene networks, the timing of significant changes in the expression level of each gene may be the most critical information in time course expression profiles. With the same timing of the initial change, genes which share similar patterns of expression for any number of sampling intervals from the beginning should be considered co-expressed at certain level(s) in the gene networks. In addition, multiple testing problems are complicated in experiments with multi-level treatments when thousands of genes are involved. RESULTS: To address these issues, we first performed an ANOVA F test to identify significantly regulated genes. The Benjamini and Hochberg (BH) procedure of controlling false discovery rate (FDR) at 5% was applied to the P values of the F test. We then categorized the genes with a significant F test into 4 classes based on the timing of their initial responses by sequentially testing a complete set of orthogonal contrasts, the reverse Helmert series. For genes within each class, specific sequences of contrasts were performed to characterize their general \u27fluctuation\u27 shapes of expression along the subsequent sampling time points. To be consistent with the BH procedure, each contrast was examined using a stepwise Studentized Maximum Modulus test to control the gene based maximum family-wise error rate (MFWER) at the level of alphanew determined by the BH procedure. We demonstrated our method on the analysis of microarray data from murine olfactory sensory epithelia at five different time points after target ablation. CONCLUSION: In this manuscript, we used planned linear contrasts to analyze time-course microarray experiments. This analysis allowed us to characterize gene expression patterns based on the temporal order in the data, the timing of a gene\u27s initial response, and the general shapes of gene expression patterns along the subsequent sampling time points. Our method is particularly suitable for analysis of microarray experiments in which it is often difficult to take sufficiently frequent measurements and/or the sampling intervals are non-uniform

Identification of gene expression patterns using planned linear contrasts

BACKGROUND: In gene networks, the timing of significant changes in the expression level of each gene may be the most critical information in time course expression profiles. With the same timing of the initial change, genes which share similar patterns of expression for any number of sampling intervals from the beginning should be considered co-expressed at certain level(s) in the gene networks. In addition, multiple testing problems are complicated in experiments with multi-level treatments when thousands of genes are involved. RESULTS: To address these issues, we first performed an ANOVA F test to identify significantly regulated genes. The Benjamini and Hochberg (BH) procedure of controlling false discovery rate (FDR) at 5% was applied to the P values of the F test. We then categorized the genes with a significant F test into 4 classes based on the timing of their initial responses by sequentially testing a complete set of orthogonal contrasts, the reverse Helmert series. For genes within each class, specific sequences of contrasts were performed to characterize their general \u27fluctuation\u27 shapes of expression along the subsequent sampling time points. To be consistent with the BH procedure, each contrast was examined using a stepwise Studentized Maximum Modulus test to control the gene based maximum family-wise error rate (MFWER) at the level of alphanew determined by the BH procedure. We demonstrated our method on the analysis of microarray data from murine olfactory sensory epithelia at five different time points after target ablation. CONCLUSION: In this manuscript, we used planned linear contrasts to analyze time-course microarray experiments. This analysis allowed us to characterize gene expression patterns based on the temporal order in the data, the timing of a gene\u27s initial response, and the general shapes of gene expression patterns along the subsequent sampling time points. Our method is particularly suitable for analysis of microarray experiments in which it is often difficult to take sufficiently frequent measurements and/or the sampling intervals are non-uniform

Predator water balance alters intraguild predation in a streamsidefood web

Previous work suggests that animal water balance can influence trophic interactions, with predators increasing their consumption of water-laden prey to meet water demands.But it is unclear how the need for water interacts with the need for energy to drive trophic interactions under shifting conditions. Using manipulative field experiments, we show that water balance influences the effects of top predators on prey with contrasting ratios of water and energy, altering the frequency of intraguild predation. Water-stressed top predators (large spiders) negatively affect water-laden basal prey (crickets), especially male prey with higher water content, whereas alleviation of water limitation causes top predators to switch to negatively affecting energy-rich midlevel predators (small spiders). Thus, the relative water and energy content of multiple prey, combined with the water demand of the top predator, influences trophic interactions in ways that can alter the strength of intraguild predation. These findings underscore the need for integration of multi resource approaches for understanding implications of global change for food webs

Predictors of Arterial Stiffness in Law Enforcement Officers

Background: Compare arterial stiffness among law enforcement officers (LEOs) versus general population normative values and identify predictors of arterial stiffness in LEOs. Methods: Seventy male LEOs (age: 24–54 years) completed body composition, blood pressures, physical activity level, and carotid-femoral pulse wave velocity (cfPWV) measurements. T-tests and regression analyses were utilized to compare LEO data to normative data and predict cfPWV, respectively. Results: Compared to similar age strata within the general population, cfPWV was lower among LEO’s under 30-years (mean difference = −0.6 m·s−1), but higher among LEOs 50–55-years (mean difference = 1.1 m·s−1). Utilizing regression, age, relative body fat, and diastolic blood pressure explained the greatest variance in LEO’s cfPWV (adj. R2 = 0.56, p \u3c 0.001). Conclusion: This investigation demonstrated that arterial stiffness may progress more rapidly in LEOs and LEOs’ relative body fat and blood pressure may primarily affect arterial stiffness and risk of CVD

Quadratic regression analysis for gene discovery and pattern recognition for non-cyclic short time-course microarray experiments

BACKGROUND: Cluster analyses are used to analyze microarray time-course data for gene discovery and pattern recognition. However, in general, these methods do not take advantage of the fact that time is a continuous variable, and existing clustering methods often group biologically unrelated genes together. RESULTS: We propose a quadratic regression method for identification of differentially expressed genes and classification of genes based on their temporal expression profiles for non-cyclic short time-course microarray data. This method treats time as a continuous variable, therefore preserves actual time information. We applied this method to a microarray time-course study of gene expression at short time intervals following deafferentation of olfactory receptor neurons. Nine regression patterns have been identified and shown to fit gene expression profiles better than k-means clusters. EASE analysis identified over-represented functional groups in each regression pattern and each k-means cluster, which further demonstrated that the regression method provided more biologically meaningful classifications of gene expression profiles than the k-means clustering method. Comparison with Peddada et al.'s order-restricted inference method showed that our method provides a different perspective on the temporal gene profiles. Reliability study indicates that regression patterns have the highest reliabilities. CONCLUSION: Our results demonstrate that the proposed quadratic regression method improves gene discovery and pattern recognition for non-cyclic short time-course microarray data. With a freely accessible Excel macro, investigators can readily apply this method to their microarray data

Comparative Analysis of Microbial Sensing Molecules in Mucosal Tissues with Aging

Host-bacterial interactions at mucosal surfaces require recognition of the bacteria by host cells enabling targeted responses to maintain tissue homeostasis. It is now well recognized that an array of host-derived pattern recognition receptors (PRRs), both cell-bound and soluble, are critical to innate immune engagement of microbes via microbial-associated molecular patterns (MAMP). This report describes the use of a nonhuman primate model to evaluate changes in the expression of these sensing molecules related to aging in healthy gingival tissues. Macaca mulatta aged 3-24 years were evaluated clinically and gingival tissues obtained, RNA isolated and microarray analysis conducted for gene expression of the sensing pattern recognition receptors (PRRs). The results demonstrated increased expression of various PRRs in healthy aging gingiva including extracellular (CD14, CD209, CLEC4E, TLR4), intracellular (NAIP, IFIH1, DAI) and soluble (PTX4, SAA1) PRRs. Selected PRRs were also correlated with both bleeding on probing (BOP) and pocket depth (PD) in the animals. These findings suggest that aged animals express altered levels of various PRRs that could affect the ability of the tissues to interact effectively with the juxtaposed microbial ecology, presumably contributing to an enhanced risk of periodontitis even in clinically healthy oral mucosal tissues with aging

The Trophic Life Cycle Stage of the Opportunistic Fungal Pathogen \u3cem\u3ePneumocystis murina\u3c/em\u3e Hinders the Ability of Dendritic Cells to Stimulate CD4\u3csup\u3e+\u3c/sup\u3e T Cell Responses

The life cycle of the opportunistic fungal pathogen Pneumocystis murina consists of a trophic stage and an ascus-like cystic stage. Infection with the cyst stage induces proinflammatory immune responses, while trophic forms suppress the cytokine response to multiple pathogen-associated molecular patterns (PAMPs), including β-glucan. A targeted gene expression assay was used to evaluate the dendritic cell response following stimulation with trophic forms alone, with a normal mixture of trophic forms and cysts, or with β-glucan. We demonstrate that stimulation with trophic forms downregulated the expression of multiple genes normally associated with the response to infection, including genes encoding transcription factors. Trophic forms also suppressed the expression of genes related to antigen processing and presentation, including the gene encoding the major histocompatibility complex (MHC) class II transactivator, CIITA. Stimulation of dendritic cells with trophic forms, but not a mixture of trophic forms and cysts, reduced the expression of MHC class II and the costimulatory molecule CD40 on the surface of the cells. These defects in the expression of MHC class II and costimulatory molecules corresponded with a reduced capacity for trophic form-loaded dendritic cells to stimulate CD4+ T cell proliferation and polarization. These data are consistent with the delayed innate and adaptive responses previously observed in immunocompetent mice inoculated with trophic forms compared to responses in mice inoculated with a mixture of trophic forms and cysts. We propose that trophic forms broadly inhibit the ability of dendritic cells to fulfill their role as antigen-presenting cells

Heart Failure in Humans Reduces Contractile Force in Myocardium from Both Ventricles

This study measured how heart failure affects the contractile properties of the human myocardium from the left and right ventricles. The data showed that maximum force and maximum power were reduced by approximately 30% in multicellular preparations from both ventricles, possibly because of ventricular remodeling (e.g., cellular disarray and/or excess fibrosis). Heart failure increased the calcium (Ca2+) sensitivity of contraction in both ventricles, but the effect was bigger in right ventricular samples. The changes in Ca2+ sensitivity were associated with ventricle-specific changes in the phosphorylation of troponin I, which indicated that adrenergic stimulation might induce different effects in the left and right ventricles