School of Mathematics and Statistics - Research Publications

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    Impaired thermogenesis and adipose tissue development in mice with fat-specific disruption of insulin and IGF-1 signalling
    Boucher, J ; Mori, MA ; Lee, KY ; Smyth, G ; Liew, CW ; Macotela, Y ; Rourk, M ; Bluher, M ; Russell, SJ ; Kahn, CR (NATURE PUBLISHING GROUP, 2012-06)
    Insulin and insulin-like growth factor 1 (IGF-1) have important roles in adipocyte differentiation, glucose tolerance and insulin sensitivity. Here to assess how these pathways can compensate for each other, we created mice with a double tissue-specific knockout of insulin and IGF-1 receptors to eliminate all insulin/IGF-1 signalling in fat. These FIGIRKO mice had markedly decreased white and brown fat mass and were completely resistant to high fat diet-induced obesity and age- and high fat diet-induced glucose intolerance. Energy expenditure was increased in FIGIRKO mice despite a >85% reduction in brown fat mass. However, FIGIRKO mice were unable to maintain body temperature when placed at 4 °C. Brown fat activity was markedly decreased in FIGIRKO mice but was responsive to β3-receptor stimulation. Thus, insulin/IGF-1 signalling has a crucial role in the control of brown and white fat development, and, when disrupted, leads to defective thermogenesis and a paradoxical increase in basal metabolic rate.
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    Neither loss of Bik alone, nor combined loss of Bik and Noxa, accelerate murine lymphoma development or render lymphoma cells resistant to DNA damaging drugs
    Happo, L ; Phipson, B ; Smyth, GK ; Strasser, A ; Scott, CL (NATURE PUBLISHING GROUP, 2012-05)
    The pro-apoptotic BH3-only protein, BIK, is widely expressed and although many critical functions in developmental or stress-induced death have been ascribed to this protein, mice lacking Bik display no overt abnormalities. It has been postulated that Bik can serve as a tumour suppressor, on the basis that its deficiency and loss of apoptotic function have been reported in many human cancers, including lymphoid malignancies. Evasion of apoptosis is a major factor contributing to c-Myc-induced tumour development, but despite this, we found that Bik deficiency did not accelerate Eμ-Myc-induced lymphomagenesis. Co-operation between BIK and NOXA, another BH3-only protein, has been previously described, and was attributed to their complementary binding specificities to distinct subsets of pro-survival BCL-2 family proteins. Nevertheless, combined deficiency of Bik and Noxa did not alter the onset of Eμ-Myc transgene induced lymphoma development. Moreover, although p53-mediated induction of Bik has been reported, neither Eμ-Myc/Bik(-/-) nor Eμ-Myc/Bik(-/-)Noxa(-/-) lymphomas were more resistant than control Eμ-Myc lymphomas to killing by DNA damaging drugs, either in vitro or in vivo. These results suggest that Bik, even in combination with Noxa, is not a potent suppressor of c-Myc-driven tumourigenesis or critical for chemotherapeutic drug-induced killing of Myc-driven tumours.
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    Camera: a competitive gene set test accounting for inter-gene correlation
    Wu, D ; Smyth, GK (OXFORD UNIV PRESS, 2012-09)
    Competitive gene set tests are commonly used in molecular pathway analysis to test for enrichment of a particular gene annotation category amongst the differential expression results from a microarray experiment. Existing gene set tests that rely on gene permutation are shown here to be extremely sensitive to inter-gene correlation. Several data sets are analyzed to show that inter-gene correlation is non-ignorable even for experiments on homogeneous cell populations using genetically identical model organisms. A new gene set test procedure (CAMERA) is proposed based on the idea of estimating the inter-gene correlation from the data, and using it to adjust the gene set test statistic. An efficient procedure is developed for estimating the inter-gene correlation and characterizing its precision. CAMERA is shown to control the type I error rate correctly regardless of inter-gene correlations, yet retains excellent power for detecting genuine differential expression. Analysis of breast cancer data shows that CAMERA recovers known relationships between tumor subtypes in very convincing terms. CAMERA can be used to analyze specified sets or as a pathway analysis tool using a database of molecular signatures.
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    Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation
    McCarthy, DJ ; Chen, Y ; Smyth, GK (OXFORD UNIV PRESS, 2012-05)
    A flexible statistical framework is developed for the analysis of read counts from RNA-Seq gene expression studies. It provides the ability to analyse complex experiments involving multiple treatment conditions and blocking variables while still taking full account of biological variation. Biological variation between RNA samples is estimated separately from the technical variation associated with sequencing technologies. Novel empirical Bayes methods allow each gene to have its own specific variability, even when there are relatively few biological replicates from which to estimate such variability. The pipeline is implemented in the edgeR package of the Bioconductor project. A case study analysis of carcinoma data demonstrates the ability of generalized linear model methods (GLMs) to detect differential expression in a paired design, and even to detect tumour-specific expression changes. The case study demonstrates the need to allow for gene-specific variability, rather than assuming a common dispersion across genes or a fixed relationship between abundance and variability. Genewise dispersions de-prioritize genes with inconsistent results and allow the main analysis to focus on changes that are consistent between biological replicates. Parallel computational approaches are developed to make non-linear model fitting faster and more reliable, making the application of GLMs to genomic data more convenient and practical. Simulations demonstrate the ability of adjusted profile likelihood estimators to return accurate estimators of biological variability in complex situations. When variation is gene-specific, empirical Bayes estimators provide an advantageous compromise between the extremes of assuming common dispersion or separate genewise dispersion. The methods developed here can also be applied to count data arising from DNA-Seq applications, including ChIP-Seq for epigenetic marks and DNA methylation analyses.