Protein-DNA interaction mapping using genomic tiling path microarrays in Drosophila.
Ontology highlight
ABSTRACT:
SUBMITTER: Sun LV
PROVIDER: S-EPMC170935 | biostudies-literature | 2003 Aug
REPOSITORIES: biostudies-literature
Publications
Protein-DNA interaction mapping using genomic tiling path microarrays in Drosophila.
Sun Ling V LV Chen Liang L Greil Frauke F Negre Nicolas N Li Tong-Ruei TR Cavalli Giacomo G Zhao Hongyu H Van Steensel Bas B White Kevin P KP
Proceedings of the National Academy of Sciences of the United States of America 20030722 16
We demonstrate the use of a chromosomal walk (or "tiling path") printed as DNA microarrays for mapping protein-DNA interactions across large regions of contiguous genomic DNA in Drosophila melanogaster. Microarrays were constructed with genomic DNA fragments 430-920 bp in length, covering 2.9 million base pairs of the Adh-cactus region of chromosome 2 and 85,000 base pairs of the 82F region of chromosome 3. We performed DNA localization mapping for the heterochromatin protein HP1 and for the seq ...[more]
Similar Datasets
Project description:Traditional microarrays use probes complementary to known genes to quantitate the differential gene expression between two or more conditions. Genomic tiling microarray experiments differ in that probes that span a genomic region at regular intervals are used to detect the presence or absence of transcription. This difference means the same sets of biases and the methods for addressing them are unlikely to be relevant to both types of experiment. We introduce the informatics challenges arising in the analysis of tiling microarray experiments as open problems to the scientific community and present initial approaches for the analysis of this nascent technology.
| S-EPMC1855044 | biostudies-literature
Project description:INTRODUCTION: Breast cancer metastasis is a complex, multi-step biological process. Genetic mutations along with epigenetic alterations in the form of DNA methylation patterns and histone modifications contribute to metastasis-related gene expression changes and genomic instability. So far, these epigenetic contributions to breast cancer metastasis have not been well characterized, and there is only a limited understanding of the functional mechanisms affected by such epigenetic alterations. Furthermore, no genome-wide assessments have been undertaken to identify altered DNA methylation patterns in the context of metastasis and their effects on specific functional pathways or gene networks. METHODS: We have used a human gene promoter tiling microarray platform to analyze a cell line model of metastasis to lymph nodes composed of a poorly metastatic MDA-MB-468GFP human breast adenocarcinoma cell line and its highly metastatic variant (468LN). Gene networks and pathways associated with metastasis were identified, and target genes associated with epithelial-mesenchymal transition were validated with respect to DNA methylation effects on gene expression. RESULTS: We integrated data from the tiling microarrays with targets identified by Ingenuity Pathways Analysis software and observed epigenetic variations in genes implicated in epithelial-mesenchymal transition and with tumor cell migration. We identified widespread genomic hypermethylation and hypomethylation events in these cells and we confirmed functional associations between methylation status and expression of the CDH1, CST6, EGFR, SNAI2 and ZEB2 genes by quantitative real-time PCR. Our data also suggest that the complex genomic reorganization present in cancer cells may be superimposed over promoter-specific methylation events that are responsible for gene-specific expression changes. CONCLUSION: This is the first whole-genome approach to identify genome-wide and gene-specific epigenetic alterations, and the functional consequences of these changes, in the context of breast cancer metastasis to lymph nodes. This approach allows the development of epigenetic signatures of metastasis to be used concurrently with genomic signatures to improve mapping of the evolving molecular landscape of metastasis and to permit translational approaches to target epigenetically regulated molecular pathways related to metastatic progression.
| S-EPMC2575535 | biostudies-literature
Project description:Array-based comparative genomic hybridization (CGH) measures copy-number variations at multiple loci simultaneously, providing an important tool for studying cancer and developmental disorders and for developing diagnostic and therapeutic targets. Arrays for CGH based on PCR products representing assemblies of BAC or cDNA clones typically require maintenance, propagation, replication, and verification of large clone sets. Furthermore, it is difficult to control the specificity of the hybridization to the complex sequences that are present in each feature of such arrays. To develop a more robust and flexible platform, we created probe-design methods and assay protocols that make oligonucleotide microarrays synthesized in situ by inkjet technology compatible with array-based comparative genomic hybridization applications employing samples of total genomic DNA. Hybridization of a series of cell lines with variable numbers of X chromosomes to arrays designed for CGH measurements gave median ratios for X-chromosome probes within 6% of the theoretical values (0.5 for XY/XX, 1.0 for XX/XX, 1.4 for XXX/XX, 2.1 for XXXX/XX, and 2.6 for XXXXX/XX). Furthermore, these arrays detected and mapped regions of single-copy losses, homozygous deletions, and amplicons of various sizes in different model systems, including diploid cells with a chromosomal breakpoint that has been mapped and sequenced to a precise nucleotide and tumor cell lines with highly variable regions of gains and losses. Our results demonstrate that oligonucleotide arrays designed for CGH provide a robust and precise platform for detecting chromosomal alterations throughout a genome with high sensitivity even when using full-complexity genomic samples.
| S-EPMC535426 | biostudies-literature
Project description:With lower manufacturing cost, high spot density, and flexible probe design, genomic tiling microarrays are ideal for comprehensive transcriptome studies. Typically, transcriptome profiling using microarrays involves reverse transcription, which converts RNA to cDNA. The cDNA is then labeled and hybridized to the probes on the arrays, thus the RNA signals are detected indirectly. Reverse transcription is known to generate artifactual cDNA, in particular the synthesis of second-strand cDNA, leading to false discovery of antisense RNA. To address this issue, we have developed an effective method using RNA that is directly labeled, thus by-passing the cDNA generation. This paper describes this method and its application to the mapping of transcriptome profiles.RNA extracted from laboratory cultures of Porphyromonas gingivalis was fluorescently labeled with an alkylation reagent and hybridized directly to probes on genomic tiling microarrays specifically designed for this periodontal pathogen. The generated transcriptome profile was strand-specific and produced signals close to background level in most antisense regions of the genome. In contrast, high levels of signal were detected in the antisense regions when the hybridization was done with cDNA. Five antisense areas were tested with independent strand-specific RT-PCR and none to negligible amplification was detected, indicating that the strong antisense cDNA signals were experimental artifacts.An efficient method was developed for mapping transcriptome profiles specific to both coding strands of a bacterial genome. This method chemically labels and uses extracted RNA directly in microarray hybridization. The generated transcriptome profile was free of cDNA artifactual signals. In addition, this method requires fewer processing steps and is potentially more sensitive in detecting small amount of RNA compared to conventional end-labeling methods due to the incorporation of more fluorescent molecules per RNA fragment.
| S-EPMC3031212 | biostudies-literature
Project description:Streptococcus suis is an important zoonotic pathogen that can cause meningitis and sepsis in both pigs and humans. Infections in humans have been sporadic worldwide but two severe outbreaks occurred in China in recent years, while infections in pigs are a major problem in the swine industry. Some S. suis strains are more pathogenic than others with 2 sequence types (ST), ST1 and ST7, being well recognized as highly pathogenic. We analyzed 31 isolates from 23 serotypes and 25 STs by NimbleGen tiling microarray using the genome of a high pathogenicity (HP) ST1 strain, GZ1, as reference and a new algorithm to detect gene content difference. The number of genes absent in a strain ranged from 49 to 225 with a total of 632 genes absent in at least one strain, while 1346 genes were found to be invariably present in all strains as the core genome of S. suis, accounting for 68% of the GZ1 genome. The majority of genes are located in chromosomal blocks with two or more contiguous genes. Sixty two blocks are absent in two or more strains and defined as regions of difference (RDs), among which 26 are putative genomic islands (GIs). Clustering and statistical analyses revealed that 8 RDs including 6 putative GIs and 21 genes within these RDs are significantly associated with HP. Three RDs encode known virulence related factors including the extracellular factor, the capsular polysaccharide and a SrtF pilus. The strains were divided into 5 groups based on population genetic analysis of multilocus sequence typing data and the distribution of the RDs among the groups revealed gain and loss of RDs in different groups. Our study elucidated the gene content diversity of S. suis and identified genes that potentially promote HP.
| S-EPMC3068143 | biostudies-literature
Project description:The Drosophila (fruit fly) model system has been instrumental in our current understanding of human biology, development, and diseases. Here, we used a high-throughput yeast two-hybrid (Y2H)-based technology to screen 102 bait proteins from Drosophila melanogaster, most of them orthologous to human cancer-related and/or signaling proteins, against high-complexity fly cDNA libraries. More than 2300 protein-protein interactions (PPI) were identified, of which 710 are of high confidence. The computation of a reliability score for each protein-protein interaction and the systematic identification of the interacting domain combined with a prediction of structural/functional motifs allow the elaboration of known complexes and the identification of new ones. The full data set can be visualized using a graphical Web interface, the PIMRider (http://pim.hybrigenics.com), and is also accessible in the PSI standard Molecular Interaction data format. Our fly Protein Interaction Map (PIM) is surprisingly different from the one recently proposed by Giot et al. with little overlap between the two data sets. Analysis of the differences in data sets and methods suggests alternative strategies to enhance the accuracy and comprehensiveness of the post-genomic generation of broad-scale protein interaction maps.
| S-EPMC551564 | biostudies-literature
Project description:BackgroundDNA microarray technology allows the analysis of genome structure and dynamics at genome-wide scale. Expression microarrays (EMA) contain probes for annotated open reading frames (ORF) and are widely used for the analysis of differential gene expression. By contrast, tiling microarrays (TMA) have a much higher probe density and provide unbiased genome-wide coverage. The purpose of this study was to develop a protocol to exploit the high resolution of TMAs for quantitative measurement of DNA strand-specific differential expression of annotated and non-annotated transcripts.ResultsWe extensively filtered probes present in Affymetrix Genechip Yeast Genome 2.0 expression and GeneChip S. pombe 1.0FR tiling microarrays to generate custom Chip Description Files (CDF) in order to compare their efficiency. We experimentally tested the potential of our approach by measuring the differential expression of 4904 genes in the yeast Schizosaccharomyces pombe growing under conditions of oxidative stress. The results showed a Pearson correlation coefficient of 0.943 between both platforms, indicating that TMAs are as reliable as EMAs for quantitative expression analysis. A significant advantage of TMAs over EMAs is the possibility of detecting non-annotated transcripts generated only under specific physiological conditions. To take full advantage of this property, we have used a target-labelling protocol that preserves the original polarity of the transcripts and, therefore, allows the strand-specific differential expression of non-annotated transcripts to be determined. By using a segmentation algorithm prior to generating the corresponding custom CDFs, we identified and quantitatively measured the expression of 510 transcripts longer than 180 nucleotides and not overlapping previously annotated ORFs that were differentially expressed at least 2-fold under oxidative stress.ConclusionsWe show that the information derived from TMA hybridization can be processed simultaneously for high-resolution qualitative and quantitative analysis of the differential expression of well-characterized genes and of previously non-annotated and antisense transcripts. The consistency of the performance of TMA, their genome-wide coverage and adaptability to updated genome annotations, and the possibility of measuring strand-specific differential expression makes them a tool of choice for the analysis of gene expression in any organism for which TMA platforms are available.
| S-EPMC2858035 | biostudies-literature
Project description:Pax-6 genes encode evolutionarily conserved transcription factors capable of activating the gene-expression program required to build an eye. When ectopically expressed in Drosophila imaginal discs, Pax-6 genes induce the eye formation on the corresponding appendages of the adult fly. We used two different Drosophila full-genome DNA microarrays to compare gene expression in wild-type leg discs versus leg discs where eyeless, one of the two Drosophila Pax-6 genes, was ectopically expressed. We validated these data by analyzing the endogenous expression of selected genes in eye discs and identified 371 genes that are expressed in the eye imaginal discs and up-regulated when an eye morphogenetic field is ectopically induced in the leg discs. These genes mainly encode transcription factors involved in photoreceptor specification, signal transducers, cell adhesion molecules, and proteins involved in cell division. As expected, genes already known to act downstream of eyeless during eye development were identified, together with a group of genes that were not yet associated with eye formation.
| S-EPMC153041 | biostudies-literature
Project description:One of the principal challenges in systems biology is to uncover the networks of protein-protein interactions that underlie most biological processes. To date, experimental efforts directed at this problem have largely produced only qualitative networks that are replete with false positives and false negatives. Here, we describe a domain-centered approach--compatible with genome-wide investigations--that enables us to measure the equilibrium dissociation constant (K(D)) of recombinant PDZ domains for fluorescently labeled peptides that represent physiologically relevant binding partners. Using a pilot set of 22 PDZ domains, 4 PDZ domain clusters, and 20 peptides, we define a gold standard dataset by determining the K(D) for all 520 PDZ-peptide combinations using fluorescence polarization. We then show that microarrays of PDZ domains identify interactions of moderate to high affinity (K(D) < or = 10 microM) in a high-throughput format with a false positive rate of 14% and a false negative rate of 14%. By combining the throughput of protein microarrays with the fidelity of fluorescence polarization, our domain/peptide-based strategy yields a quantitative network that faithfully recapitulates 85% of previously reported interactions and uncovers new biophysical interactions, many of which occur between proteins that are co-expressed. From a broader perspective, the selectivity data produced by this effort reveal a strong concordance between protein sequence and protein function, supporting a model in which interaction networks evolve through small steps that do not involve dramatic rewiring of the network.
| S-EPMC2533859 | biostudies-literature
Project description:We have developed a method for interpreting genomic tiling array data, implemented as the program TranscriptionDetector. Probed loci expressed above background are identified by combining replicates in a way that makes minimal assumptions about the data. We performed medium-resolution Anopheles gambiae tiling array experiments and found extensive transcription of both coding and non-coding regions. Our method also showed improved detection of transcriptional units when applied to high-density tiling array data for ten human chromosomes.
| S-EPMC1779562 | biostudies-literature