Michael A. Newton

On differential variability of expression ratios: improving statistical inference about gene expression changes from microarray data.

We consider the problem of inferring fold changes in gene expression from cDNA microarray data. Standard procedures focus on the ratio of measured fluorescent intensities at each spot on the microarray, but to do so is to ignore the fact that the variation of such ratios is not constant. Estimates of gene expression changes are derived within a simple hierarchical model that accounts for measurement error and fluctuations in absolute gene expression levels. Significant gene expression changes are identified by deriving the posterior odds of change within a similar model. The methods are tested via simulation and are applied to a panel of Escherichia coli microarrays.

MicroRNA 29c is down-regulated in nasopharyngeal carcinomas, up-regulating mRNAs encoding extracellular matrix proteins.

Using highly sensitive microarray-based procedures, we identified eight microRNAs (miRNAs) showing robust differential expression between 31 laser-capture-microdissected nasopharyngeal carcinomas (NPCs) and 10 normal healthy nasopharyngeal epithelial samples. In particular, miRNA mir-29c was expressed at one-fifth the levels in tumors as in normal epithelium. In NPC tumors, the lower mir-29c levels correlated with higher levels of multiple mRNAs whose 3′ UTRs can bind mir-29c at target sequences conserved across many vertebrates. In cultured cells, introduction of mir-29c down-regulated these genes at the level of mRNA and inhibited expression of luciferase encoded by vectors having the 3′ UTRs of these genes. Moreover, for each of several genes tested, mutating the mir-29c target sites in the 3′ UTR abrogated mir-29c-induced inhibition of luciferase expression. Most of the mir-29c-targeted genes identified encode extracellular matrix proteins, including multiple collagens and laminin γ1, that are associated with tumor cell invasiveness and metastatic potential, prominent characteristics of NPC. Thus, we identify eight miRNAs differentially expressed in NPC and demonstrate the involvement of one in regulating genes involved in metastasis.

Drosophila RNAi screen identifies host genes important for influenza virus replication

All viruses rely on host cell proteins and their associated mechanisms to complete the viral life cycle. Identifying the host molecules that participate in each step of virus replication could provide valuable new targets for antiviral therapy, but this goal may take several decades to achieve with conventional forward genetic screening methods and mammalian cell cultures. Here we describe a novel genome-wide RNA interference (RNAi) screen in Drosophila that can be used to identify host genes important for influenza virus replication. After modifying influenza virus to allow infection of Drosophila cells and detection of influenza virus gene expression, we tested an RNAi library against 13,071 genes (90% of the Drosophila genome), identifying over 100 for which suppression in Drosophila cells significantly inhibited or stimulated reporter gene (Renilla luciferase) expression from an influenza-virus-derived vector. The relevance of these findings to influenza virus infection of mammalian cells is illustrated for a subset of the Drosophila genes identified; that is, for three implicated Drosophila genes, the corresponding human homologues ATP6V0D1, COX6A1 and NXF1 are shown to have key functions in the replication of H5N1 and H1N1 influenza A viruses, but not vesicular stomatitis virus or vaccinia virus, in human HEK 293 cells. Thus, we have demonstrated the feasibility of using genome-wide RNAi screens in Drosophila to identify previously unrecognized host proteins that are required for influenza virus replication. This could accelerate the development of new classes of antiviral drugs for chemoprophylaxis and treatment, which are urgently needed given the obstacles to rapid development of an effective vaccine against pandemic influenza and the probable emergence of strains resistant to available drugs.

Fundamental Differences in Cell Cycle Deregulation in Human Papillomavirus–Positive and Human Papillomavirus–Negative Head/Neck and Cervical Cancers

Human papillomaviruses (HPV) are associated with nearly all cervical cancers, 20% to 30% of head and neck cancers (HNC), and other cancers. Because HNCs also arise in HPV-negative patients, this type of cancer provides unique opportunities to define similarities and differences of HPV-positive versus HPV-negative cancers arising in the same tissue. Here, we describe genome-wide expression profiling of 84 HNCs, cervical cancers, and site-matched normal epithelial samples in which we used laser capture microdissection to enrich samples for tumor-derived versus normal epithelial cells. This analysis revealed that HPV(+) HNCs and cervical cancers differed in their patterns of gene expression yet shared many changes compared with HPV(-) HNCs. Some of these shared changes were predicted, but many others were not. Notably, HPV(+) HNCs and cervical cancers were found to be up-regulated in their expression of a distinct and larger subset of cell cycle genes than that observed in HPV(-) HNC. Moreover, HPV(+) cancers overexpressed testis-specific genes that are normally expressed only in meiotic cells. Many, although not all, of the hallmark differences between HPV(+) HNC and HPV(-) HNC were a direct consequence of HPV and in particular the viral E6 and E7 oncogenes. This included a novel association of HPV oncogenes with testis-specific gene expression. These findings in primary human tumors provide novel biomarkers for early detection of HPV(+) and HPV(-) cancers, and emphasize the potential value of targeting E6 and E7 function, alone or combined with radiation and/or traditional chemotherapy, in the treatment of HPV(+) cancers.

Random-set methods identify distinct aspects of the enrichment signal in gene-set analysis

A prespecified set of genes may be enriched, to varying degrees, for genes that have altered expression levels relative to two or more states of a cell. Knowing the enrichment of gene sets defined by functional categories, such as gene ontology (GO) annotations, is valuable for analyzing the biological signals in microarray expression data. A common approach to measuring enrichment is by cross-classifying genes according to membership in a functional category and membership on a selected list of significantly altered genes. A small Fishers exact test

Karyotypic abnormalities in human induced pluripotent stem cells and embryonic stem cells

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Phylogenetic Inference for Binary Data on Dendograms Using Markov Chain Monte Carlo

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20q gain associates with immortalization : 20q13.2 amplification correlates with genome instability in human papillomavirus 16 E7 transformed human uroepithelial cells

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High-resolution human genome structure by single-molecule analysis

table is indicative of enrichment. Other category analysis methods retain the quantitative gene-level scores and measure significance by referring a category-level statistic to a permutation distribution associated with the original differential expression problem. We describe a class of random-set scoring methods that measure distinct components of the enrichment signal. The class includes Fishers test based on selected genes and also tests that average gene-level evidence across the category. Averaging and selection methods are compared empirically using Affymetrix data on expression in nasopharyngeal cancer tissue, and theoretically using a location model of differential expression. We find that each method has a domain of superiority in the state space of enrichment problems, and that both methods have benefits in practice. Our analysis also addresses two problems related to multiple-category inference, namely, that equally enriched categories are not detected with equal probability if they are of different sizes, and also that there is dependence among category statistics owing to shared genes. Random-set enrichment calculations do not require Monte Carlo for implementation. They are made available in the R package allez.

Genome-Wide Expression Profiling Reveals EBV-Associated Inhibition of MHC Class I Expression in Nasopharyngeal Carcinoma

313 cytogenetic aberration at presentation, we would estimate that at high passage at least 25% of the cultures would show some aberration (lower bound column). Finally, no shared aberration types show a strong difference between ESCs and iPSCs, but the +8 and isochromsome 20q classes exhibit some difference (P = 0.04/0.02). Supplementary Figure 2 illustrates five cases in more detail. Although the probability of aneuploidy is enhanced with time in culture, the presence of recurrent aberrations very early after derivation (Supplementary Table 1 and Supplementary Fig. 1a,b) and their absence in high-passage cultures do not support a strict correlation between increasing passage number and acquisition of karyotypic abnormalities. Recurrent cytogenetic abnormalities, including aneuploidies of chromosomes 8, 12, 17, 20 and X, are acquired in many different cell lines4–7. Human embryos and blastocysts (the source of ESCs) also exhibit chromosomal instability, defined by cellto-cell variability8. Single-cell, array-based analysis of embryos obtained from couples with normal fertility showed high levels of intra-embryonic mosaicism for structural and numerical abnormalities9. Notably, our data show that the recurrent chromosome abnormalities in human ESC and iPSC cultures are similar to each other and distinct from those reported in embryos, both in frequency and in type. Embryos appear to have a high proportion of large segmental aneuploidies with very few cytogenetically normal blastocysts9. This suggests that the basis for the development of cytogenetic aberrations in cultured pluripotent cells can be distinguished from that in the embryo. Maintenance of a stable karyotype is required for clinical use of pluripotent stem cell lines10 and is important for the reproducibility of experimental data. Karyotypic abnormalities in human induced pluripotent stem cells and embryonic stem cells