Biomedical subjects

Jeanette N McClintick

Publications and source records attributed to Jeanette N McClintick.

6 recordsLinked to original sources

PubMed2006

Effects of filtering by Present call on analysis of microarray experiments.

BACKGROUND: Affymetrix GeneChips are widely used for expression profiling of tens of thousands of genes. The large number of comparisons can lead to false positives. Various methods have been used to reduce false positives, but they have rarely been compared or quantitatively evaluated. Here we describe and evaluate a simple method that uses the detection (Present/Absent) call generated by the Affymetrix microarray suite version 5 software (MAS5) to remove data that is not reliably detected before further analysis, and compare this with filtering by expression level. We explore the effects of various thresholds for removing data in experiments of different size (from 3 to 10 arrays per treatment), as well as their relative power to detect significant differences in expression. RESULTS: Our approach sets a threshold for the fraction of arrays called Present in at least one treatment group. This method removes a large percentage of probe sets called Absent before carrying out the comparisons, while retaining most of the probe sets called Present. It preferentially retains the more significant probe sets (p < or = 0.001) and those probe sets that are turned on or off, and improves the false discovery rate. Permutations to estimate false positives indicate that probe sets removed by the filter contribute a disproportionate number of false positives. Filtering by fraction Present is effective when applied to data generated either by the MAS5 algorithm or by other probe-level algorithms, for example RMA (robust multichip average). Experiment size greatly affects the ability to reproducibly detect significant differences, and also impacts the effect of filtering; smaller experiments (3-5 samples per treatment group) benefit from more restrictive filtering (> or =50% Present). CONCLUSION: Use of a threshold fraction of Present detection calls (derived by MAS5) provided a simple method that effectively eliminated from analysis probe sets that are unlikely to be reliable while preserving the most significant probe sets and those turned on or off; it thereby increased the ratio of true positives to false positives.

Algorithms↗

PubMed2006

Differential gene induction by type I and type II interferons and their combination.

Type I and type II interferons (IFNs) bind to different cell surface receptors but activate overlapping signal transduction pathways. We examined the effects of a type I IFN (IFN-alphacon1) and a type II IFN (IFN-gamma1b) on gene expression in A549 cells and demonstrate that there is a common set of genes modulated by both IFNs as well as a set of genes specifically regulated by each, reflecting the activation of different signaling pathways. In particular, IFN-gamma induced many more genes of the signaling pathways, apoptosis, and cytokine interactions than did IFN-alpha. Even with genes induced by both IFNs there were distinctive quantitative differences in expression. IFN-gamma1b plays a major role in the induction and regulation of the complement pathway. Previous work has shown a synergistic antiviral and antiproliferative effect of type I and type II IFNs in cell culture and in the treatment of tumors in mice. We demonstrate that a majority of genes showed an additive effect of IFN-alphacon1 and IFN-gamma1b, but a subset of genes is synergistically induced; these include ISG20, MX2, OAS2, and other genes known to be involved in the antiviral response, TRAIL (TNFSF10) and caspases involved in apoptosis and chemokine genes RANTES, CXCL10, and CXCL11. Greater than additive transcription of some of these genes in the presence of both IFNs was confirmed by real-time kinetic RT-PCR. Elevated induction of many of these genes may be sufficient to explain the synergistic antiviral and antitumor effects of this combination of IFNs in vivo.

Antineoplastic Agents↗

PubMed2005

Global effects of vitamin A deficiency on gene expression in rat liver: evidence for hypoandrogenism.

Vitamin A (retinol) metabolites are ligands for transcription factors that regulate many genes. The liver is the main storage depot for retinol and plays a role in vitamin A homeostasis. To better understand the effects of vitamin A deficiency on liver gene expression, we produced retinol deficiency in male rats by feeding a diet low in retinol for 53 days after weaning and examined the effects on gene expression in liver using Affymetrix oligonucleotide microarrays. We detected expression of 41% of the 8799 probe sets represented on the RGU-34A GeneChips. Vitamin A deficiency resulted in major changes in liver gene expression: 805 genes (22% of all genes detected) differed at P<or=.05 (false discovery rate <0.143). Genes involved in fatty acid metabolism, peroxisomal function, glycolysis, glutamate metabolism and the urea cycle were altered. The expression of many sexually dimorphic genes was altered toward a feminized or senescent pattern of gene expression in the liver. Retinol deficiency also produces a shift toward increased protein and fat catabolism and decreased fatty acid synthesis.

Androgens↗

PubMed2005

Characterization of a transgenic mouse line lacking photoreceptor development within the ventral retina.

A unique transgenic mouse line was generated by incorporating a minigene that contained a cone-specific human cone transducin alpha-subunit (GNAT2) promoter, an attenuated diphtheria toxin A (DTA) gene, and an enhancer element from human interphotoreceptor retinoid-binding protein (IRBP) gene. This transgenic mouse line is designated h-GNAT2pro-DTA. During postnatal retinal development, both transgenic and non-transgenic retinas showed similar morphology and thickness at P1. Between ages P8 and P30, all retinal layers became recognizable in non-transgenic and also in transgenic dorsal retinas. However, in the ventral retina of the transgenic mice the photoreceptor layers did not develop. This aberration occurred as a result of abnormal cellular development, rather than as a consequence of retinal degeneration. In adult transgenic animals, approximately 44% of the retina located dorsally appeared morphologically normal, whereas 32% of the retina located ventrally was completely lacking photoreceptor development. The 24% mid-retinal region exhibited transitional morphology containing malformed photoreceptors. At P360 or older, the thickness of retina layers was reduced in both dorsal and ventral regions. The abnormality observed in transgenic retinas involved mainly the photoreceptors; the other retinal cell types were all present in both dorsal and ventral retinas. Since the DTA gene was only expressed in cone cells, the absence of cone photoreceptors in the transgenic retina was to be expected. However, what was unexpected was the concomitant absence of rod photoreceptors in the ventral retina, suggesting that the presence of cones may be important for the development of rods. This new transgenic line can lead to better understanding of photoreceptor development, and may serve as a new animal model for studying photoreceptor-related retinal diseases.

Animals↗

PubMed2004

Global effect of PEG-IFN-alpha and ribavirin on gene expression in PBMC in vitro.

Using oligonucleotide microarrays, we have examined the expression of 22,000 genes in peripheral blood cells treated with pegylated interferon-alpha2b (PEG-IFN-alpha) and ribavirin. Treatment with ribavirin had very little effect on gene expression, whereas treatment with PEG-IFN-alpha had a dramatic effect, modulating the expression of approximately 1000 genes (at p < 0.001). In addition to genes previously reported to be induced by type I or type II IFNs, many novel genes were found to be upregulated, including transcription factors, such as ATF3, ATF4, properdin, a key regulator of the complement pathway, a homeobox gene (HESX1), and an RNA editing enzyme (apobec3). Chemokines CXCL10 and CXCL11 were upregulated, whereas CXCL5 was downregulated. Cytokines interleukin-15 (IL-15) and IL-18 were also significantly induced, whereas IL-1alpha and IL-1beta were downregulated. Most other interleukins were not affected. The results of the microarrays were confirmed by kinetic real-time PCR. These data indicate that IFN treatment causes upregulation of genes associated with the stress response, apoptosis, and signaling, and an equal number of genes are downregulated, including those associated with protein synthesis, specific cytokines and chemokines and other biosynthetic functions.

Cells, Cultured↗

PubMed2003

Reproducibility of oligonucleotide arrays using small samples.

BACKGROUND: Low RNA yields from small tissue samples can limit the use of oligonucleotide microarrays (Affymetrix GeneChips). Methods using less cRNA for hybridization or amplifying the cRNA have been reported to reduce the number of transcripts detected, but the effect on realistic experiments designed to detect biological differences has not been analyzed. We systematically explore the effects of using different starting amounts of RNA on the ability to detect differential gene expression. RESULTS: The standard Affymetrix protocol can be used starting with only 2 micrograms of total RNA, with results equivalent to the recommended 10 micrograms. Biological variability is much greater than the technical variability introduced by this change. A simple amplification protocol described here can be used for samples as small as 0.1 micrograms of total RNA. This amplification protocol allows detection of a substantial fraction of the significant differences found using the standard protocol, despite an increase in variability and the 5' truncation of the transcripts, which prevents detection of a subset of genes. CONCLUSIONS: Biological differences in a typical experiment are much greater than differences resulting from technical manipulations in labeling and hybridization. The standard protocol works well with 2 micrograms of RNA, and with minor modifications could allow the use of samples as small as 1 micrograms. For smaller amounts of starting material, down to 0.1 micrograms RNA, differential gene expression can still be detected using the single cycle amplification protocol. Comparisons of groups of four arrays detect many more significant differences than comparisons of three arrays.

Nucleic Acid Hybridization↗