Directed Mammalian Gene Regulatory Networks Using Expression and Comparative Genomic Hybridization Microarray Data from Radiation Hybrids

Meiotic mapping of quantitative trait loci regulating expression (eQTLs) has allowed the construction of gene networks. However, the limited mapping resolution of these studies has meant that genotype data are largely ignored, leading to undirected networks that fail to capture regulatory hierarchies. Here we use high resolution mapping of copy number eQTLs (ceQTLs) in a mouse-hamster radiation hybrid (RH) panel to construct directed genetic networks in the mammalian cell. The RH network covering 20,145 mouse genes had significant overlap with, and similar topological structures to, existing biological networks. Upregulated edges in the RH network had significantly more overlap than downregulated. This suggests repressive relationships between genes are missed by existing approaches, perhaps because the corresponding proteins are not present in the cell at the same time and therefore unlikely to interact. Gene essentiality was positively correlated with connectivity and betweenness centrality in the RH network, strengthening the centrality-lethality principle in mammals. Consistent with their regulatory role, transcription factors had significantly more outgoing edges (regulating) than incoming (regulated) in the RH network, a feature hidden by conventional undirected networks. Directed RH genetic networks thus showed concordance with pre-existing networks while also yielding information inaccessible to current undirected approaches

SNP microarray analyses reveal copy number alterations and progressive genome reorganization during tumor development in SVT/t driven mice breast cancer

BACKGROUND: Tumor development is known to be a stepwise process involving dynamic changes that affect cellular integrity and cellular behavior. This complex interaction between genomic organization and gene, as well as protein expression is not yet fully understood. Tumor characterization by gene expression analyses is not sufficient, since expression levels are only available as a snapshot of the cell status. So far, research has mainly focused on gene expression profiling or alterations in oncogenes, even though DNA microarray platforms would allow for high-throughput analyses of copy number alterations (CNAs). METHODS: We analyzed DNA from mouse mammary gland epithelial cells using the Affymetrix Mouse Diversity Genotyping array (MOUSEDIVm520650) and calculated the CNAs. Segmental copy number alterations were computed based on the probeset CNAs using the circular binary segmentation algorithm. Motif search was performed in breakpoint regions (inter-segment regions) with the MEME suite to identify common motif sequences. RESULTS: Here we present a four stage mouse model addressing copy number alterations in tumorigenesis. No considerable changes in CNA were identified for non-transgenic mice, but a stepwise increase in CNA was found during tumor development. The segmental copy number alteration revealed informative chromosomal fragmentation patterns. In inter-segment regions (hypothetical breakpoint sides) unique motifs were found. CONCLUSIONS: Our analyses suggest genome reorganization as a stepwise process that involves amplifications and deletions of chromosomal regions. We conclude from distinctive fragmentation patterns that conserved as well as individual breakpoints exist which promote tumorigenesis

Copy Number Networks to Guide Combinatorial Therapy of Cancer and Proliferative Disorders

Interaction networks can be charted by seeking gene pairs that are amplified and/or deleted in tandem, even when located at a distance on the genome. Our experience with radiation hybrid (RH) panels, a library of cell clones that have been used for genetic mapping, have shown this tool can pinpoint statistically significant patterns of co-inherited gene pairs. In fact, we were able to identify gene pairs specifically associated with the mechanism of cell survival at single gene resolution. Further, the RH network can be used to provide single gene specificity for cancer networks constructed from correlated copy number alterations (CNAs). In a survival network for glioblastoma, we found that the epidermal growth factor receptor (EGFR) oncogene interacted with 46 genes. Of these genes, ten (22%) happened to be targets for existing drugs. Here, we highlight the potential of CNA networks to guide combinatorial drug treatment in cancer, autoimmunity and atherosclerosis

Effects of genome-wide copy number variation on expression in mammalian cells

<p>Abstract</p> <p>Background</p> <p>There is only a limited understanding of the relation between copy number and expression for mammalian genes. We fine mapped <it>cis </it>and <it>trans </it>regulatory loci due to copy number change for essentially all genes using a human-hamster radiation hybrid (RH) panel. These loci are called copy number expression quantitative trait loci (ceQTLs).</p> <p>Results</p> <p>Unexpected findings from a previous study of a mouse-hamster RH panel were replicated. These findings included decreased expression as a result of increased copy number for 30% of genes and an attenuated relationship between expression and copy number on the X chromosome suggesting an <it>Xist </it>independent form of dosage compensation. In a separate glioblastoma dataset, we found conservation of genes in which dosage was negatively correlated with gene expression. These genes were enriched in signaling and receptor activities. The observation of attenuated X-linked gene expression in response to increased gene number was also replicated in the glioblastoma dataset. Of 523 gene deserts of size > 600 kb in the human RH panel, 325 contained <it>trans </it>ceQTLs with -log₁₀<it>P </it>> 4.1. Recently discovered genes, ultra conserved regions, noncoding RNAs and microRNAs explained only a small fraction of the results, suggesting a substantial portion of gene deserts harbor as yet unidentified functional elements.</p> <p>Conclusion</p> <p>Radiation hybrids are a useful tool for high resolution mapping of <it>cis </it>and <it>trans </it>loci capable of affecting gene expression due to copy number change. Analysis of two independent radiation hybrid panels show agreement in their findings and may serve as a discovery source for novel regulatory loci in noncoding regions of the genome.</p

Directed mammalian gene regulatory networks using expression and comparative genomic hybridization microarray data from radiation hybrids.

Meiotic mapping of quantitative trait loci regulating expression (eQTLs) has allowed the construction of gene networks. However, the limited mapping resolution of these studies has meant that genotype data are largely ignored, leading to undirected networks that fail to capture regulatory hierarchies. Here we use high resolution mapping of copy number eQTLs (ceQTLs) in a mouse-hamster radiation hybrid (RH) panel to construct directed genetic networks in the mammalian cell. The RH network covering 20,145 mouse genes had significant overlap with, and similar topological structures to, existing biological networks. Upregulated edges in the RH network had significantly more overlap than downregulated. This suggests repressive relationships between genes are missed by existing approaches, perhaps because the corresponding proteins are not present in the cell at the same time and therefore unlikely to interact. Gene essentiality was positively correlated with connectivity and betweenness centrality in the RH network, strengthening the centrality-lethality principle in mammals. Consistent with their regulatory role, transcription factors had significantly more outgoing edges (regulating) than incoming (regulated) in the RH network, a feature hidden by conventional undirected networks. Directed RH genetic networks thus showed concordance with pre-existing networks while also yielding information inaccessible to current undirected approaches

Variação estrutural no número de cópias e sua implicação na expressão de microRNA em humanos

Tese (doutorado)—Universidade de Brasília, Faculdade de Medicina, Programa de Pós-Graduação em Patologia Molecular, 2014.Variações no número de cópias (do inglês Copy Number Variation - CNV) são segmentos iguais a ou maiores que 1 kilobase que apresentam variações estruturais como deleções e duplicações. Constituem uma fração de variação genética importante, que interagem, modulam ou direcionam a expressão gênica. MicroRNA são pequenos RNA de aproximadamente 20 nucleotídeos que regulam a expressão gênica pós-transcricional. O objetivo desta Tese foi analisar a expressão de microRNA com relação às variações estruturais do número de cópias dos respectivos genes em humanos, as regiões de CNV-miRNA. Foram selecionadas 11 regiões de provável polimorfismo no número de cópias além de duas regiões invariáveis como controle positivo, que foram avaliadas por triagem molecular em PCR quantitativa em uma amostra de 103 indivíduos da população brasileira. Em seguida, uma segunda amostragem de 30 indivíduos tiveram DNA e RNA coletados de células mononucleadas do sangue (PBMC) e de epitélio bucal e RNA total do plasma para respectiva quantificação da expressão desses microRNA. Para elucidar questões relativas à dosagem gênica, a expressão de microRNA foi comparada com o número de cópias das respectivas regiões gênicas. Das regiões que apresentaram polimorfismo (CNV-miR-570, -miR-499, -miR-126, -miR-150, -miR-338, - miR-1275), apenas uma não teve o microRNA quantificado (CNV-miR-499) por não ter apresentado amplificação nos tecidos e também no plasma. Os microRNA miR-570 e miR-338, tiveram uma expressão relativa crescente de acordo com o número de cópias para frações de PBMC (e plasma somente para o miR-570), no entanto, estatisticamente não significativas. Numa simulação populacional pelo método Monte Carlo (n = 1.000), foi identificada diferença significativa para o miR-570, com taxa de mudança progressiva relativa entre ao número de cópias. A hipótese de que o número de cópias de uma região contendo genes miRNA pode afetar a regulação da expressão de genes abre uma perspectiva de novas pesquisas envolvendo a variabilidade fenotípica. ______________________________________________________________________________________________ ABSTRACTCopy number variation (CNV) are DNA segments of 1 kilobase or larger, showing structural variations, such as deletions, insertions or duplications. It constitutes a significant fraction of genetic variation that directly interacts or modulates gene expression. MicroRNA is a class of small RNA of about 20 nucleotides that regulates post-transcriptional gene expression. The aim of this Thesis was to analyze the expression of microRNA regarding the number of copies of their respective genes in humans, the CNV-miRNA regions. Eleven regions of probable polymorphisms in addition to two invariable control regions were selected and evaluated by quantitative PCR molecular screening in a sample of 103 individuals of the Brazilian population. Then, a second sample of 30 subjects had DNA and RNA collected from blood mononuclear cells (PBMC), oral epithelium and total RNA from plasma, quantified the expression of those microRNAs and compared with the number of copies, aiming to elucidate the relative response to gene dosage. From the regions that showed polymorphism (CNV-miR-570, -miR-499, -miR-126, miR-150, -miR- 338, -miR-1275) only one was unable to have the microRNA quantified (miR-499) for failing to provide amplification in tissues and plasma. The microRNA miR-570 and miR-338 had an increased relative expression according to the respective number of copies for PBMC fraction (and plasma only for miR-570), though not statistically significant. In a population simulation by Monte Carlo method (n = 1,000), a significant difference was identified to miR-570, with progressive rate of relative change between the categories of number of copies. The hypothesis that the copy number variation of a region containing miRNA genes can affect the regulation of gene expression opens a new perspective for research regarding phenotypic variability

Investigation of the effects of MAS5, RMA and GCRMA preprocessing methods on an affymetrix zebrafish genechip dataset using statistical and network parameters

Ankara : Department of Molecular Biology and Genetics and the Institute of Engineering and Sciences of Bilkent University, 2010.Thesis (Master's) -- Bilkent University, 2010.Includes bibliographical references leaves 77-84.Microarray data preprocessing is an important determinant of the accuracy and repeatability of expression profiling studies. Recent studies have focused on comparison of preprocessing methodologies using differential expression analysis of spike-in datasets and qRT-PCR confirmations. Other approaches include comparison of array-wise and probe-wise correlation and of selected gene network parameters. However, zebrafish GeneChip datasets have not been used in such comparisons; furthermore, detailed analysis of upregulated and downregulated gene sets with respect to known network parameters are not well characterized across different preprocessing methodologies. In this study we re-analyzed a public zebrafish hypoxia microarray dataset (GSE4989; Marques et al. 2008) using MAS5, RMA, and gcRMA methods. Comparisons were made in terms of differentially expressed gene sets and defined network parameters, namely, clustering coefficient, degree distribution, and betwenness centrality. Our findings indicated that gcRMA and RMA exhibited greater similarity to each other in terms of differentially expressed genes, and network parameters. In addition, the network analysis demonstrated that upregulated and downregulated gene sets had distinct network structures; downregulated probesets had greater clustering coefficients and degree distributions for positively correlated probesets in all three preprocessing methods. However, gcRMA and RMA methods accentuated this difference further than MAS5 did, suggesting that preprocessing methods differ in their modulation of gene expression network structure. A selected group of probesets that showed invariant network structure parameters across RMA, gcRMA and MAS5 was determined and analyzed functionally for the zebrafish hypoxia dataset. The results of this thesis suggest that preprocessing methods may alter network structure of the datasets differentially with respect to upregulated and downregulated gene sets. Accordingly, it might be beneficial to filter differentially expressed genes that are robust to such network topology modulation to increase the repeatability of gene sets.Öztürk, Ahmet RaşitM.S