STATISTICAL ANALYSIS OF GENE EXPRESSION MICROARRAYS

This manuscript is composed of two major sections. In the first section of the manuscript we introduce some of the biological principles that form the bases of cDNA microarrays and explain how the different analytical steps introduce variability and potential biases in gene expression measurements that can sometimes be dificult to properly address. We address statistical issues associated to the measurement of gene expression (e.g., image segmentation, spot identification), to the correction for back-ground fluorescence and to the normalization and re-scaling of data to remove effects of dye, print-tip and others on expression. In this section of the manuscript we also describe the standard statistical approaches for estimating treatment effect on gene expression, and briefly address the multiple comparisons problem, often referred to as the big p small n paradox. In the second major section of the manuscript, we discuss the use of multiple scans as a means to reduce the variability of gene expression estimates. While the use of multiple scans under the same laser and sensor settings has already been proposed (Romualdi et al. 2003), we describe a general hierarchical modeling approach proposed by Love and Carriquiry (2005) that enables use of all the readings obtained under varied laser and sensor settings for each slide in the analyses, even if the number of readings per slide vary across slides. This technique also uses the varied settings to correct for some amount of the censoring discussed in the first section. It is to be expected that when combining scans and correcting for censoring, the estimate of gene expression will have smaller variance than it would have if based on a single spot measurement. In turn, expression estimates with smaller variance are expected to increase the power of statistical tests performed on them

An Empirical Method for Establishing Positional Confidence Intervals Tailored for Composite Interval Mapping of QTL

BACKGROUND: Improved genetic resolution and availability of sequenced genomes have made positional cloning of moderate-effect QTL realistic in several systems, emphasizing the need for precise and accurate derivation of positional confidence intervals (CIs) for QTL. Support interval (SI) methods based on the shape of the QTL likelihood curve have proven adequate for standard interval mapping, but have not been shown to be appropriate for use with composite interval mapping (CIM), which is one of the most commonly used QTL mapping methods. RESULTS: Based on a non-parametric confidence interval (NPCI) method designed for use with the Haley-Knott regression method for mapping QTL, a CIM-specific method (CIM-NPCI) was developed to appropriately account for the selection of background markers during analysis of bootstrap-resampled data sets. Coverage probabilities and interval widths resulting from use of the NPCI, SI, and CIM-NPCI methods were compared in a series of simulations analyzed via CIM, wherein four genetic effects were simulated in chromosomal regions with distinct marker densities while heritability was fixed at 0.6 for a population of 200 isolines. CIM-NPCIs consistently capture the simulated QTL across these conditions while slightly narrower SIs and NPCIs fail at unacceptably high rates, especially in genomic regions where marker density is high, which is increasingly common for real studies. The effects of a known CIM bias toward locating QTL peaks at markers were also investigated for each marker density case. Evaluation of sub-simulations that varied according to the positions of simulated effects relative to the nearest markers showed that the CIM-NPCI method overcomes this bias, offering an explanation for the improved coverage probabilities when marker densities are high. CONCLUSIONS: Extensive simulation studies herein demonstrate that the QTL confidence interval methods typically used to positionally evaluate CIM results can be dramatically improved by accounting for the procedural complexity of CIM via an empirical approach, CIM-NPCI. Confidence intervals are a critical measure of QTL utility, but have received inadequate treatment due to a perception that QTL mapping is not sufficiently precise for procedural improvements to matter. Technological advances will continue to challenge this assumption, creating even more need for the current improvement to be refined

Gene expression patterns during somatic embryo development and germination in maize Hi II cultures

Gene expression changes associated with embryogenic callus formation and with somatic embryo maturation and germination were examined in a regenerationproficient hybrid line of Zea mays, Hi II. 12,060 element maize cDNA microarrays were used to generate gene expression profiles from embryogenic calli induced to undergo embryo maturation and germination. No statistically significant gene expression changes were detected in comparing embryogenic with total callus. On the other hand, over 1,000 genes showed significant time variation during somatic embryo development. In general, a substantial number of genes were downregulated during embryo maturation, largely histone and ribosomal protein genes, which may result from a slow down in cell proliferation and growth during embryo maturation. The expression of these genes dramatically recovered at germination. Other genes upregulated during embryo maturation included genes encoding hydrolytic enzymes (nucleases, glucosidases and proteases) and a few storage genes (zein and caleosin), which are good candidates for developmental marker genes. Germination is accompanied by the upregulation of a number of stress response and membrane transporter genes, and, as expected, greening is associated with the upregulation of many genes encoding photosynthetic and chloroplast components. Thus, some, but not all genes, typically associated with zygotic embryogenesis are significantly up or downregulated during somatic embryogenesis in Hi II maize line regeneration

Daily HIV pre-exposure prophylaxis (PrEP) with tenofovir disoproxil fumarate-emtricitabine reduced Streptococcus and increased Erysipelotrichaceae in rectal microbiota.

Daily PrEP is highly effective at preventing HIV-1 acquisition, but risks of long-term tenofovir disoproxil fumarate plus emtricitabine (TDF-FTC) include renal decline and bone mineral density decrease in addition to initial gastrointestinal side effects. We investigated the impact of TDF-FTC on the enteric microbiome using rectal swabs collected from healthy MSM before PrEP initiation and after 48 to 72 weeks of adherent PrEP use. The V4 region of the 16S ribosomal RNA gene sequencing showed that Streptococcus was significantly reduced from 12.0% to 1.2% (p = 0.036) and Erysipelotrichaceae family was significantly increased from 0.79% to 3.3% (p = 0.028) after 48-72 weeks of daily PrEP. Catenibacterium mitsuokai, Holdemanella biformis and Turicibacter sanguinis were increased within the Erysipelotrichaceae family and Streptococcus agalactiae, Streptococcus oralis, Streptococcus mitis were reduced. These changes were not associated with host factors including PrEP duration, age, race, tenofovir diphosphate blood level, any drug use and drug abuse, suggesting that the observed microbiome shifts were likely induced by daily PrEP use. Long-term PrEP resulted in increases of Catenibacterium mitsuokai and Holdemanella biformis, which have been associated with gut microbiome dysbiosis. Our observations can aid in characterizing PrEP's side effects, which is likely to improve PrEP adherence, and thus HIV-1 prevention

The HIV Genomic Incidence Assay Meets False Recency Rate and Mean Duration of Recency Infection Performance Standards.

HIV incidence is a primary metric for epidemic surveillance and prevention efficacy assessment. HIV incidence assay performance is evaluated via false recency rate (FRR) and mean duration of recent infection (MDRI). We conducted a meta-analysis of 438 incident and 305 chronic specimens' HIV envelope genes from a diverse global cohort. The genome similarity index (GSI) accurately characterized infection stage across diverse host and viral factors. All except one chronic specimen had GSIs below 0.67, yielding a FRR of 0.33 [0-0.98] %. We modeled the incidence assay biomarker dynamics with a logistic link function assuming individual variabilities in a Beta distribution. The GSI probability density function peaked close to 1 in early infection and 0 around two years post infection, yielding MDRI of 420 [361, 467] days. We tested the assay by newly sequencing 744 envelope genes from 59 specimens of 21 subjects who followed from HIV negative status. Both standardized residuals and Anderson-Darling tests showed that the test dataset was statistically consistent with the model biomarker dynamics. This is the first reported incidence assay meeting the optimal FRR and MDRI performance standards. Signatures of HIV gene diversification can allow precise cross-sectional surveillance with a desirable temporal range of incidence detection

Prenatal methylmercury exposure and DNA methylation in seven-year-old children in the Seychelles Child Development Study

Background Methylmercury (MeHg) is present in fish and is a neurotoxicant at sufficiently high levels. One potential mechanism of MeHg toxicity early in life is epigenetic dysregulation that may affect long-term neurodevelopment. Altered DNA methylation of nervous system-related genes has been associated with adult mental health outcomes. Objective To assess associations between prenatal MeHg exposure and DNA methylation (at the cytosine of CG dinucleotides, CpGs) in three nervous system-related genes, encoding brain-derived neurotropic factor (BDNF), glutamate receptor subunit NR2B (GRIN2B), and the glucocorticoid receptor (NR3C1), in children who were exposed to MeHg in utero. Methods We tested 406 seven-year-old Seychellois children participating in the Seychelles Child Development Study (Nutrition Cohort 2), who were prenatally exposed to MeHg from maternal fish consumption. Total mercury in maternal hair (prenatal MeHg exposure measure) collected during pregnancy was measured using atomic absorption spectroscopy. Methylation in DNA from the children’s saliva was measured by pyrosequencing. To assess associations between prenatal MeHg exposure and CpG methylation at seven years of age, we used multivariable linear regression models adjusted for covariates. Results We identified associations with prenatal MeHg exposure for DNA methylation of one GRIN2B CpG and two NR3C1 CpGs out of 12 total CpG sites. Higher prenatal MeHg was associated with higher methylation for each CpG site. For example, NR3C1 CpG3 had an expected increase of 0.03-fold for each additional 1 ppm of prenatal MeHg (B = 0.030, 95% CI 0.001, 0.059; p = 0.047). Several CpG sites associated with MeHg are located in transcription factor binding sites and the observed methylation changes are predicted to lead to lower gene expression. Conclusions In a population of people who consume large amounts of fish, we showed that higher prenatal MeHg exposure was associated with differential DNA methylation at seven years of age at specific CpG sites that may influence neurodevelopment and mental health