Comparative evaluation of gene-set analysis methods

<p>Abstract</p> <p>Background</p> <p>Multiple data-analytic methods have been proposed for evaluating gene-expression levels in specific biological pathways, assessing differential expression associated with a binary phenotype. Following Goeman and Bühlmann's recent review, we compared statistical performance of three methods, namely Global Test, ANCOVA Global Test, and SAM-GS, that test "self-contained null hypotheses" Via. subject sampling. The three methods were compared based on a simulation experiment and analyses of three real-world microarray datasets.</p> <p>Results</p> <p>In the simulation experiment, we found that the use of the asymptotic distribution in the two Global Tests leads to a statistical test with an incorrect size. Specifically, p-values calculated by the scaled <it>χ</it>²distribution of Global Test and the asymptotic distribution of ANCOVA Global Test are too liberal, while the asymptotic distribution with a quadratic form of the Global Test results in p-values that are too conservative. The two Global Tests with permutation-based inference, however, gave a correct size. While the three methods showed similar power using permutation inference after a proper standardization of gene expression data, SAM-GS showed slightly higher power than the Global Tests. In the analysis of a real-world microarray dataset, the two Global Tests gave markedly different results, compared to SAM-GS, in identifying pathways whose gene expressions are associated with <it>p53 </it>mutation in cancer cell lines. A proper standardization of gene expression variances is necessary for the two Global Tests in order to produce biologically sensible results. After the standardization, the three methods gave very similar biologically-sensible results, with slightly higher statistical significance given by SAM-GS. The three methods gave similar patterns of results in the analysis of the other two microarray datasets.</p> <p>Conclusion</p> <p>An appropriate standardization makes the performance of all three methods similar, given the use of permutation-based inference. SAM-GS tends to have slightly higher power in the lower <it>α</it>-level region (i.e. gene sets that are of the greatest interest). Global Test and ANCOVA Global Test have the important advantage of being able to analyze continuous and survival phenotypes and to adjust for covariates. A free Microsoft Excel Add-In to perform SAM-GS is available from <url>http://www.ualberta.ca/~yyasui/homepage.html</url>.</p

Designing and sample size calculation in presence of heterogeneity in biological studies involving high-throughput data.

The designing and determination of sample size are important for conducting high-throughput biological experiments such as proteomics experiments and RNA-Seq expression studies, thus leading to better understanding of complex mechanisms underlying various biological processes. The variations in the biological data or technical approaches to data collection lead to heterogeneity for the samples under study. We critically worked on the issues of technical and biological heterogeneity. The quantitative measurements based on liquid chromatography (LC) coupled with mass spectrometry (MS) often suffer from the problem of missing values (MVs) and data heterogeneity. We considered a proteomics data set generated from human kidney biopsy material to investigate the technical effects of sample preparation and the quantitative MS. We studied the effect of tissue storage methods (TSMs) and tissue extraction methods (TEMs) on data analysis. There are two TSMs: frozen (FR) and FFPE (formalin-fixed paraffin embedded); and three TEMs: MAX, TX followed by MAX and SDS followed by MAX. We assessed the impact of different strategies to analyze the data while considering heterogeneity and MVs. We found that the FFPE is better than that of FR for tissue storage. We also found that the one-step TEM (MAX) is better than those of two-steps TEMs. Furthermore, we found the imputation method is a better approach than excluding the proteins with MVs or using unbalanced design. We introduce a web application, PWST (Proteomics Workflow Standardization Tool) to standardize the proteomics workflow. The tool will be helpful in deciding the most suitable choice for each step and studying the variability associated with technical steps as well as the effects of continuous variables. We have used the special cases of general linear model - ANCOVA and ANOVA with fixed effects to study the effects due to various sources of variability. We introduce an interactive tool, “SATP: Statistical Analysis Tool for Proteomics”, for analyzing proteomics expression data that is scalable to large clinical proteomic studies. The user can perform differential expression analysis of proteomics data either at the protein or peptide level using multiple approaches. We have developed statistical approaches for calculating sample size for proteomics experiments under allocation and cost constraints. We have developed R programs and a shiny app “SSCP: Sample Size Calculator for Proteomics Experiment” for computing sample sizes. We have proposed statistical approaches for calculating sample size for RNA-Seq experiments considering allocation and cost. We have developed R programs and shiny apps to calculate sample size for conducting RNA-Seq experiments

GSAASeqSP: A Toolset for Gene Set Association Analysis of RNA-Seq Data

RNA-Seq is quickly becoming the preferred method for comprehensively characterizing whole transcriptome activity, and the analysis of count data from RNA-Seq requires new computational tools. We developed GSAASeqSP, a novel toolset for genome-wide gene set association analysis of sequence count data. This toolset offers a variety of statistical procedures via combinations of multiple gene-level and gene set-level statistics, each having their own strengths under different sample and experimental conditions. These methods can be employed independently, or results generated from multiple or all methods can be integrated to determine more robust profiles of significantly altered biological pathways. Using simulations, we demonstrate the ability of these methods to identify association signals and to measure the strength of the association. We show that GSAASeqSP analyses of RNA-Seq data from diverse tissue samples provide meaningful insights into the biological mechanisms that differentiate these samples. GSAASeqSP is a powerful platform for investigating molecular underpinnings of complex traits and diseases arising from differential activity within the biological pathways. GSAASeqSP is available at http://gsaa.unc.edu

ROLE OF ERBB4 SPLICING IN PARVALBUMIN INTERNEURON MATURATION AND SCHIZOPHRENIA

Cognitive dysfunction is a core and clinically-critical feature of schizophrenia. Certain cognitive deficits, such as impaired working memory, appear to emerge from altered gamma oscillations in the dorsolateral prefrontal cortex (DLPFC). Cortical gamma oscillations require the activity of parvalbumin (PV) interneurons and reduced PV interneuron activity in schizophrenia has been proposed to be due to deficient excitatory drive to these neurons. Synaptic pruning coincides with the period in which individuals with schizophrenia typically present their first clinical symptoms and thus an excessive pruning of excitatory inputs to PV interneurons in the DLPFC during development could provide the neural substrate for altered prefrontal gamma oscillations and working memory dysfunction in schizophrenia. However, evidence for pruning or pathogenic loss of excitatory inputs to PV interneurons in development and schizophrenia, respectively, and molecular mechanisms underlying these processes have not been identified. The formation of excitatory synapses on PV interneurons is mediated by ErbB4 signaling pathway. ErbB4 transcript is alternatively spliced and each splice variant is associated with different functional effects. In schizophrenia, the total ErbB4 expression is unaltered, but alternative splicing of ErbB4 is dysregulated, suggesting that ErbB4 splicing shifts may provide molecular mechanisms for modulating the excitatory synapse number on PV interneurons. Using a top-down translational approach, I first characterized the association between dysregulated ErbB4 splicing shifts and fewer excitatory inputs to PV interneurons in a human cohort of comparison subjects and schizophrenia subjects. Then I assessed the developmental context of this relationship in a cohort of non-human primates with different ages. Finally, I investigated the cause-and-effect relationship between ErbB4 splicing shifts and excitatory synapse number on PV interneurons using rat primary neuronal culture. Data from these different experimental systems converge onto the hypothesis that developmental shifts in ErbB4 splicing induce pruning of excitatory synapses on PV interneurons and deficits in this process result in a loss of excitatory inputs to PV interneurons in schizophrenia. Therefore, work from this dissertation reinforces the view that schizophrenia is a neurodevelopmental disorder with disturbances in the maturation of prefrontal cortical circuitry

Assessing Reproducibility and Value in Genomic Signatures

Consider a genomic signature to be a set of genes whose measured expression is transformed into a prediction of an outcome of interest. Such signatures are the bases of a set of FDA-approved medical tests for predicting the risk of distal recurrence and differential survival in breast cancer patients [84, 83, 63]. The goal of these tests is to provide clinicians with an additional piece of prognostic information that may affect their decision making pertaining to the treatment of a breast cancer patient. As it stands, the tests based on these genomic signatures (MammaPrint, Oncotype DX, Prosigna) are not part of the standard of care for a patient, and there are many issues in the translation of these discoveries from bench to bedside that hinder their reliable use [24]. These issues range from insufficiently thorough validation [86], to technical errors or oversights [5,46], to outright retraction of results [75]. In addition to the lack of impact in clinical practice, the difficulty of translating these genomic discoveries represents uncertainty about the viability of clinical genomics in general. The vast majority of genetic quantities that are routinely evaluated for a patient were discovered and characterized prior to the era of high-throughput genomics, e.g. [28, 88, 77, 34, 51]. Although there have been one-off successes [89] and a wide range of candidate and pathway discoveries [85], the costs have been great relative to the payout in terms of widespread clinical use [14]. By examining issues at the point of translation, we can begin to provide a clearer picture of what is possible and realistic to accomplish in the clinic with the discoveries that we have from the high-thorughput era

Molecular, behavioural and morphological comparisons of sperm adaptations in a fish with alternative reproductive tactics

In species with alternative reproductive tactics, there is much empirical support that parasitically spawning males have larger testes and greater sperm numbers as an evolved response to a higher degree of sperm competition, but support for higher sperm performance (motility, longevity and speed) by such males is inconsistent. We used the sand goby (Pomatoschistus minutus) to test whether sperm performance differed between breeding-coloured males (small testes, large mucus-filled sperm-duct glands; build nests lined with sperm-containing mucus, provide care) and parasitic sneaker-morph males (no breeding colouration, large testes, rudimentary sperm-duct glands; no nest, no care). We compared motility (per cent motile sperm), velocity, longevity of sperm, gene expression of testes and sperm morphometrics between the two morphs. We also tested if sperm-duct gland contents affected sperm performance. We found a clear difference in gene expression of testes between the male morphs with 109 transcripts differentially expressed between the morphs. Notably, several mucin genes were upregulated in breeding-coloured males and two ATP-related genes were upregulated in sneaker-morph males. There was a partial evidence of higher sperm velocity in sneaker-morph males, but no difference in sperm motility. Presence of sperm-duct gland contents significantly increased sperm velocity, and nonsignificantly tended to increase sperm motility, but equally so for the two morphs. The sand goby has remarkably long-lived sperm, with only small or no decline in motility and velocity over time (5 min vs. 22 h), but again, this was equally true for both morphs. Sperm length (head, flagella, total and flagella-to-head ratio) did not differ between morphs and did not correlate with sperm velocity for either morph. Thus, other than a clear difference in testes gene expression, we found only modest differences between the two male morphs, confirming previous findings that increased sperm performance as an adaptation to sperm competition is not a primary target of evolution.</p

PYRAMIDAL CELLS: ROLE IN PRIMATE PREFRONTAL CORTEX CIRCUITRY DURING POSTNATAL DEVELOPMENT AND SCHIZOPHRENIA

Cognitive deficits constitute a core feature of schizophrenia, are persistent across the course of the illness and are the best predictor of long-term functional outcome. Dysfunction in certain cognitive processes, such as working memory, are common in subjects with schizophrenia and have been attributed to aberrant function of the dorsolateral prefrontal cortex (DLPFC). This dysfunction appears to reflect, at least in part, alterations in excitatory neurotransmission. Cortical pyramidal neurons, the principal source of cortical glutamate neurotransmission, exhibit highly robust molecular and morphological alterations in schizophrenia. These alterations appear to be most pronounced in DLPFC deep layer 3, the same microcircuit necessary for the generation of neural oscillations in the γ-frequency range that sustain working memory function. Understanding how dysfunction in DLPFC cortical circuits in deep layer 3 might give rise to the pathophysiology of altered γ-frequency oscillations and working memory deficits in schizophrenia require an interrogation of the mechanisms by which these neuropathological alterations may arise, but also the normal developmental trajectories of these vulnerable microcircuits. In this dissertation, we provide evidence for pyramidal cell type-specific molecular disturbances and synapse-specific structural impairments in DLPFC deep layer 3, and cell type-specific and layer-specific nature of postnatal developmental refinements in pyramidal cells in the DLPFC, within the circuitry that subserves γ-frequency oscillations and working memory. Accordingly, we have identified alterations in the expression of numerous molecular regulators of the actin cytoskeleton in a layer-specific and cell type-specific manner in DLPFC deep layer 3 in individuals with schizophrenia that might be a critical “upstream” cause in the pathogenesis of the illness. Additionally, using novel triple-label fluorescence immunohistochemistry and spinning-disk confocal microscopy, we characterize specific synaptic connections onto DLPFC deep layer 3 pyramidal cells in schizophrenia. Finally, we demonstrate that the developmental trajectories of primate DLPFC deep layer 3 pyramidal neurons are protracted, and layer-specific and posit that the molecular maturation of GABA synapses on pyramidal cells may account, at least in part, for the maturation of synchronized pyramidal cell firing which is crucial for γ-frequency oscillations

Skeletal element elongation and interdigital tissue regression in developing bat limbs: a gene expression analysis

Vertebrate limbs classically illustrate the morphological diversity of homologous structure. Bat limbs exemplify this, having strikingly divergent limbs: wings with asymmetrically elongated digit elements, supporting expansive membranes; and hindlimbs with short, symmetrical, free digits. An understanding of the genes, interactions and events that shape bat limbs, will inform conventional models of development. This dissertation characterised differential expression of Meis2, in the context of interdigital regression, and the 5'HoxD genes in the context of digit formation in developing bat autopods (CS15 - CS18). Meis2 is involved in limb proximodistal patterning, and has been shown to promote proliferation, and survival of cells in other developmental contexts. Meis2 had strong expression in the expanding bat forelimb interdigits, with lowered expression in mouse and bat hindlimb interdigits, and did not correspond with Hoxa13 expression, which was reduced in the forelimb. Autopod expression was independent of retinoic acid (RA) signalling, with genes involved in RA synthesis ( Rdh10 , Aldha2 ) , degradation ( Cyp26b1 ) and signalling (Rar β) expressed in bat limbs. Altered expression patterns of Aldha2 and Cyp26b1, indicate that this pathway may be modulated in the forelimb. Meis2 is suggested to play a role in interdigital tissue retention, enhancing cell proliferation and contributing to wing expansion. 5'HoxD genes (Hoxd10 - 13) are involved in limb patterning, digit formation and growth. Their modular autopod expression domains correspond to the bat skeletal element phenotype, with strong overexpression of Hoxd10 - 11 (and to a lesser extent Hoxd12) in the forelimb posterior elements (digits II - V), which are highly elongated, and a loss of expression of these genes in hindlimb digits. These genes were not expressed in a typical reverse collinear relationship, with absolute q PCR revealing highest expression of Hoxd10. While the coding protein sequence of these genes appeared highly conserved between bats and other mammals, several changes were found in the CsC region of the digit enhancer Prox, some of which were associated with alterations in transcription binding sites. These findings indicate that Hoxd10 - 12 expressions contribute to the altered skeletal element morphologies of bat forelimbs and hindlimbs. This study makes a valuable contribution to the growing body of work that explores bat limb development and the evolutionary adaptation s of these unique structures

Gut Microbiota and Metabolic Disorders

Obesity and its co-morbidities, such as metabolic syndrome (MetS), non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes, have increased over the last few decades like an epidemic. So far the mechanisms of many metabolic diseases are not known in detail and currently there are not enough effective means to prevent and treat them. Several recent studies have shown that the unbalanced gut microbiota composition (GMC) and activity have an influence on the fat accumulation in the body. Further, it seems that the GMC of obese individuals differs from the lean. The aim of this study was to investigate whether there are differences between the GMC of metabolically impaired overweight/obese (MetS group), metabolically healthy overweight/obese and normal-weight individuals. In addition, the mechanisms by which the gut bacteria as well as their specific structures, such as flagellin (FLG) that stimulates the Toll-like receptor 5 (TLR5) affect metabolism, were investigated both in vivo and in vitro in human adipocytes and hepatocytes. The results of this study show that the abundance of certain gram-positive bacteria belonging to the Clostridial cluster XIV was higher in the MetS group subjects compared to their metabolically healthy overweight/obese and lean counterparts. Metabolically impaired subjects tended to also have a greater abundance of potentionally inflammatory Enterobacteria in their gut and thus seemed to have aberrant GMC. In addition, it was found that subjects with a high hepatic fat content (HHFC group) had less Faecalibacterium prausnitzii in their gut than individuals with low hepatic fat content. Further gene expression analysis revealed that the HHFC group also had increased inflammation cascades in their adipose tissue. Additionally, metabolically impaired individuals displayed an increased expression of FLG-recognizing TLR5 in adipose tissue, and the TLR5 expression levels associated positively both with liver fat content and insulin resistance in humans. These changes in the adipose tissue may further contribute to the impaired metabolism observed, such as insulin resistance and dyslipidemia. In vitro -studies showed that the FLG-induced TLR5 activation in adipocytes enhanced the hepatic fat accumulation by decreasing insulin signaling and mitochondrial functions and increasing triglyceride synthesis due to increased glycerol secretion from adipocytes. In conclusion, the findings of this study suggest that it may be possible that the novel prevention and personalized treatment strategies based on GM modulation will succesfully be developed for obesity and metabolic disorders in the future.Siirretty Doriast