Tiling Array Analysis Research Articles

Poisson approximation for significance in genome-wide ChIP-chip tiling arrays

A genome-wide ChIP-chip tiling array study requires millions of simultaneous comparisons of hybridization for significance. Controlling the false positive rate in genome-wide tiling array studies is very important, because the number of computationally identified regions can easily go beyond the capability of experimental verification. No accurate and efficient method exists for evaluating statistical significance in tiling arrays. The Bonferroni method is overly conservative and the permutation test is time consuming for genome-wide studies. Motivated by the Poisson clumping heuristic, we propose an accurate and efficient method for evaluating statistical significance in genome-wide ChIP-chip tiling arrays. The method works accurately for any large number of multiple comparisons, and the computational cost for evaluating P-values does not increase with the total number of tests. Based on a moving window approach, we demonstrate how to combine results using various window sizes to increase the detection power while maintaining a specified type I error rate. We further introduce a new false discovery rate control that is more appropriate in measuring the false proportion of binding intervals in tiling array analysis. Our method is general and can be applied to many large-scale genomic and genetic studies. http://www.stat.psu.edu/~yuzhang/pass.tar

An Integrated Workflow for Analysis of ChIP-Chip Data

Although ChIP-chip is a powerful tool for genome-wide discovery of transcription factor target genes, the steps involving raw data analysis, identification of promoters, and correlation with binding sites are still laborious processes. Therefore, we report an integrated workflow for the analysis of promoter tiling arrays with the Genomatix ChipInspector system. We compare this tool with open-source software packages to identify PU.1 regulated genes in mouse macrophages. Our results suggest that ChipInspector data analysis, comparative genomics for binding site prediction, and pathway/network modeling significantly facilitate and enhance whole-genome promoter profiling to reveal in vivo sites of transcription factor-DNA interactions.

Whole genome transcription profiling of Anaplasma phagocytophilum in human and tick host cells by tiling array analysis

BackgroundAnaplasma phagocytophilum (Ap) is an obligate intracellular bacterium and the agent of human granulocytic anaplasmosis, an emerging tick-borne disease. Ap alternately infects ticks and mammals and a variety of cell types within each. Understanding the biology behind such versatile cellular parasitism may be derived through the use of tiling microarrays to establish high resolution, genome-wide transcription profiles of the organism as it infects cell lines representative of its life cycle (tick; ISE6) and pathogenesis (human; HL-60 and HMEC-1).ResultsDetailed, host cell specific transcriptional behavior was revealed. There was extensive differential Ap gene transcription between the tick (ISE6) and the human (HL-60 and HMEC-1) cell lines, with far fewer differentially transcribed genes between the human cell lines, and all disproportionately represented by membrane or surface proteins. There were Ap genes exclusively transcribed in each cell line, apparent human- and tick-specific operons and paralogs, and anti-sense transcripts that suggest novel expression regulation processes. Seven virB2 paralogs (of the bacterial type IV secretion system) showed human or tick cell dependent transcription. Previously unrecognized genes and coding sequences were identified, as were the expressed p44/msp2 (major surface proteins) paralogs (of 114 total), through elevated signal produced to the unique hypervariable region of each – 2/114 in HL-60, 3/114 in HMEC-1, and none in ISE6.ConclusionUsing these methods, whole genome transcription profiles can likely be generated for Ap, as well as other obligate intracellular organisms, in any host cells and for all stages of the cell infection process. Visual representation of comprehensive transcription data alongside an annotated map of the genome renders complex transcription into discernable patterns.

Dual roles of the nuclear cap-binding complex and SERRATE in pre-mRNA splicing and microRNA processing in Arabidopsis thaliana

The processing of Arabidopsis thaliana microRNAs (miRNAs) from longer primary transcripts (pri-miRNAs) requires the activity of several proteins, including DICER-LIKE1 (DCL1), the double-stranded RNA-binding protein HYPONASTIC LEAVES1 (HYL1), and the zinc finger protein SERRATE (SE). It has been noted before that the morphological appearance of weak se mutants is reminiscent of plants with mutations in ABH1/CBP80 and CBP20, which encode the two subunits of the nuclear cap-binding complex. We report that, like SE, the cap-binding complex is necessary for proper processing of pri-miRNAs. Inactivation of either ABH1/CBP80 or CBP20 results in decreased levels of mature miRNAs accompanied by apparent stabilization of pri-miRNAs. Whole-genome tiling array analyses reveal that se, abh1/cbp80, and cbp20 mutants also share similar splicing defects, leading to the accumulation of many partially spliced transcripts. This is unlikely to be an indirect consequence of improper miRNA processing or other mRNA turnover pathways, because introns retained in se, abh1/cbp80, and cbp20 mutants are not affected by mutations in other genes required for miRNA processing or for nonsense-mediated mRNA decay. Taken together, our results uncover dual roles in splicing and miRNA processing that distinguish SE and the cap-binding complex from specialized miRNA processing factors such as DCL1 and HYL1.

Identifying Markers of Embryo Quality: Brg1 Regulates Transcriptional Activation of Stat3 Target Genes in ES Cells and Preimplantation Embryos.

Identifying markers of embryo quality is essential in selecting the highest quality embryos in IVF clinics, and in evaluating various biologic regiments for oocyte therapy. Epigenetic regulators such as DNA methyltransferases (DNMTs), histone methyltransferases (HMTs), histone acetylases (HATs) and chromatin-remodeling enzymes are all candidate markers because their function is essential for proper gene expression in developing embryos. While epigenetic regulatory mechanisms are involved in many cellular functions, these mechanisms mainly remain elusive in the preimplantation embryo. Previously we showed that LIF and IL-6 supplemented during mouse oocyte IVM induces cumulus cell expansion and enhances oocyte competence as assayed by delivery rate of pups. LIF and IL-6 induce nuclear translocation of Stat3, binding to target promoters, and activation of transcription. Brahma-related gene 1 (Brg1), an ATPase subunit of the SWI/SNF chromatin-remodeling complex, has been shown to be essential for recruitment of Stat3 to a subset of IL-6 inducible genes. SWI/SNF complexes contain multiple subunits and regulate gene expression by remodeling chromatin at promoters and regulatory elements. Brg1 knockout mice fail to develop beyond the preimplantation stage, and do not hatch or implant in vivo. We recapitulated the Brg1 null phenotype using RNAi and showed that blastocysts fail to expand and hatch in vitro. To interrogate genome-wide regions of gene promoters occupied by Brg1, we performed Brg1 chromatin immunoprecipitation (ChIP) and microarray (ChIP on chip) analysis using embryonic stem cells (ES cells). ES cells emulate pluripotent cells of the preimplantation embryo and are therefore an ideal in vitro model system to identify markers of embryo quality and to validate studies in oocytes and preimplantation embryos. For example, chromatin immunoprecipitation (ChIP) and tiling array analysis (ChIP on chip) is currently not possible using oocytes and preimplantation embryos due to the scarcity of material. However, ES cells provide sufficient material to evaluate genome-wide binding regions of epigenetic regulators. Brg1 ChIP-chip target genes identified in this study were compared with potential Stat3 targets compiled from published microarray experiments performed on ES cells cultured in the presence or absence of LIF, and Stat3 dominant-negative ES cells. Our results show that Brg1 occupies a subset of Stat3 bound promoters in ES cells, including genes highly expressed and repressed in ES cells. Our data depicts a dual role for Brg1 as an activator and repressor of transcription by mediating chromatin accessibility. The dual role of transcriptional regulators as repressors and activators of transcription is in agreement with studies showing that pluripotency associated transcription factors such as Oct4, Sox2, and Nanog co-occupy genes both expressed and repressed in ES cells.

Genomic profiling and expression studies reveal both positive and negative activities for the Drosophila Myb–MuvB/dREAM complex in proliferating cells

Myb-MuvB (MMB)/dREAM is a nine-subunit complex first described in Drosophila as a repressor of transcription, dependent on E2F2 and the RBFs. Myb, an integral member of MMB, curiously plays no role in the silencing of the test genes previously analyzed. Moreover, Myb plays an activating role in DNA replication in Drosophila egg chamber follicle cells. The essential functions for Myb are executed as part of MMB. This duality of function lead to the hypothesis that MMB, which contains both known activator and repressor proteins, might function as part of a switching mechanism that is dependent on DNA sites and developmental context. Here, we used proliferating Drosophila Kc tissue culture cells to explore both the network of genes regulated by MMB (employing RNA interference and microarray expression analysis) and the genomic locations of MMB following chromatin immunoprecipitation (ChIP) and tiling array analysis. MMB occupied 3538 chromosomal sites and was promoter-proximal to 32% of Drosophila genes. MMB contains multiple DNA-binding factors, and the data highlighted the combinatorial way by which the complex was targeted and utilized for regulation. Interestingly, only a subset of chromatin-bound complexes repressed genes normally expressed in a wide range of developmental pathways. At many of these sites, E2F2 was critical for repression, whereas at other nonoverlapping sites, Myb was critical for repression. We also found sites where MMB was a positive regulator of transcript levels that included genes required for mitotic functions (G2/M), which may explain some of the chromosome instability phenotypes attributed to loss of Myb function in myb mutants.

A physical model for tiling array analysis

Chromatin immunoprecipitation (ChIP) is a powerful experimental approach to identify in vivo binding sites of sequence-specific transcription factors (TFs). These experiments are designed to specifically enrich DNA fragments that are bound to the TF. Tiling arrays have become more and more popular for the identification of these DNA fragments. However, many studies showed that only a fraction of the identified DNA fragments contains bona fide binding sites for the TF, suggesting that indirect binding mechanisms play a very important role. We explored the possibility that the lack of binding sites can also be explained by problems in identifying ChIP-enriched DNA fragments from the measured intensities. We derived a physical model that explains some (but not all) variation of the measured probe intensities of Affymetrix tiling arrays. We used the physical model to estimate the probe-specific behavior and corrected for it. Subsequently, we developed a method to identify ChIP-enriched DNA fragments. We termed it physical model for tiling array analysis (PMT). We applied PMT to the data of ChIP-chip experiments interrogating chromosome 21 and 22 of the human genome for binding of the TFs MYC, SP1 and P53. Almost all regions recovered by PMT showed evidence for sequence-specific binding of the TFs.

Microarray blob-defect removal improves array analysis

New generation Affymetrix oligonucleotide microarrays often have blob-like image defects that will require investigators to either repeat their hybridization assays or analyze their data with the defects left in place. We investigated the effect of analyzing a spike-in experiment on Affymetrix ENCODE tiling arrays in the presence of simulated blobs covering between 1 and 9% of the array area. Using two different ChIP-chip tiling array analysis programs (Affymetrix tiling array software, TAS, and model-based analysis of tiling arrays, MAT), we found that even the smallest blob defects significantly decreased the sensitivity and increased the false discovery rate (FDR) of the spike-in target prediction. We introduced a new software tool, the microarray blob remover (MBR), which allows rapid visualization, detection and removal of various blob defects from the .CEL files of different types of Affymetrix microarrays. It is shown that using MBR significantly improves the sensitivity and FDR of a tiling array analysis compared to leaving the affected probes in the analysis. The MBR software and the sample array .CEL files used in this article are available at: http://liulab.dfci.harvard.edu/Software/MBR/MBR.htm

“Getting Started In…”: A Series Not to Miss

In recent decades, computational biology has established itself as a critical part of biomedical research and as an ever-growing and highly interdisciplinary field. It seems that every year, new areas of research appear—sequence analysis now includes SNP detection and whole genome alignments, gene expression microarray data can be analyzed in concert with interaction networks, and protein structures can be used to predict potential drug targets. This diversity and development of bioinformatics has led to an increasing number of approaches and techniques that require understanding of areas as diverse as biology and computer science, medicine and statistics, chemistry and applied mathematics. With the knowledge required to explore each area of computational biology, the barrier grows for those trying to enter it. So how can one start learning about tiling array analysis or text mining in biology? What should a new graduate student read before analyzing his first microarray? How can a machine learning researcher find out what interesting problems in bioinformatics she may address with probabilistic graphical models? We hope that help is on the way. This month, PLoS Computational Biology and the International Society for Computational Biology begin a series of short, practical articles for students and active researchers who want to learn more about new areas of computational biology and are unsure where or how to start. The aim of each article in the “Getting Started in…” series is to introduce the essentials: define the area and what it is about, highlight the debates and issues of relevance, and provide directions to the most relevant books, articles, or Web sites to find out more. The series will not include review articles or detailed tutorials; these are available in the Education section of the Journal. Rather, each “Getting Started in…” article will aim to be a cache of “go to” information for someone for whom the field is completely new. We hope each part of the series, written by experts in areas as diverse as data integration and phylogeny reconstruction, will be as invaluable as receiving an e-mail from a colleague who takes time and thought to offer the best advice and the essential introduction to his or her area of research. The first expert to inform, motivate, and inspire readers to consider a new direction is Dr. Xiaole Shirley Liu, who introduces tiling microarrays. As the series progresses, we can look forward to learning about text mining and probabilistic graphical models, to name a few topics. We hope you find this new series useful and enjoyable.