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Calibration and assessment of channel-specific biases in microarray data with extended dynamical range
Henrik Bengtsson, G?ran J?nsson, Johan Vallon-Christersson
BMC Bioinformatics , 2004, DOI: 10.1186/1471-2105-5-177
Abstract: By scanning the same spotted oligonucleotide microarray at different photomultiplier tube (PMT) gains, we have identified a channel-specific bias present in two-channel microarray data. For the scanners analyzed it was in the range of 15–25 (out of 65,535). The observed bias was very stable between subsequent scans of the same array although the PMT gain was greatly adjusted. This indicates that the bias does not originate from a step preceding the scanner detector parts. The bias varies slightly between arrays. When comparing estimates based on data from the same array, but from different scanners, we have found that different scanners introduce different amounts of bias. So do various image analysis methods. We propose a scanning protocol and a constrained affine model that allows us to identify and estimate the bias in each channel. Backward transformation removes the bias and brings the channels to the same scale. The result is that systematic effects such as intensity dependent log-ratios are removed, but also that signal densities become much more similar. The average scan, which has a larger dynamical range and greater signal-to-noise ratio than individual scans, can then be obtained.The study shows that microarray scanners may introduce a significant bias in each channel. Such biases have to be calibrated for, otherwise systematic effects such as intensity dependent log-ratios will be observed. The proposed scanning protocol and calibration method is simple to use and is useful for evaluating scanner biases or for obtaining calibrated measurements with extended dynamical range and better precision. The cross-platform R package aroma, which implements all described methods, is available for free from http://www.maths.lth.se/bioinformatics/ webcite.The microarray technology provides a way of simultaneously measuring transcript abundances of 103 – 105 genes from one or more cell or tissue samples. A microarray, also known as a gene chip, has well defined region
Normalization of array-CGH data: influence of copy number imbalances
Johan Staaf, G?ran J?nsson, Markus Ringnér, Johan Vallon-Christersson
BMC Genomics , 2007, DOI: 10.1186/1471-2164-8-382
Abstract: Here we demonstrate that copy number imbalances correlate with intensity in array-CGH data thereby causing problems for conventional normalization methods. We propose a strategy to circumvent these problems by taking copy number imbalances into account during normalization, and we test the proposed strategy using several data sets from the analysis of cancer genomes. In addition, we show how the strategy can be applied to conveniently define adaptive sample-specific boundaries between balanced copy number, losses, and gains to facilitate management of variation in tissue heterogeneity when calling copy number changes.We highlight the importance of considering copy number imbalances during normalization of array-CGH data, and show how failure to do so can deleteriously affect data and hamper interpretation.Microarray-based techniques for genome-wide investigation of copy number aberrations (CNAs) have recently gained much attention. Initially employing arrays developed for gene expression analysis [1], or low-density arrays produced from large-insert genomic clones such as bacterial artificial chromosomes (BACs) [2], the application has evolved rapidly. Currently, specialized high-density arrays with oligonucleotide probes or probes derived from BAC clones are predominately used. Two-channel array-based comparative genomic hybridization (aCGH) is a direct successor to conventional metaphase CGH [3]. In both cases, DNA from two samples are differentially labeled with fluorescent dyes and co-hybridized to immobilized genomic capture probes. By use of aCGH, DNA derived from tumor tissue can be compared with reference DNA, e.g., normal whole blood DNA, and genomic imbalances can effectively be investigated. The main advantage of aCGH over conventional CGH is the increased resolution achieved by microarrays with a large number of individual probes, routinely up to hundreds of thousands, covering the entire genome [4]. The power of aCGH has been demonstrated in tumor studi
Non-coding antisense transcription detected by conventional and single-stranded cDNA microarray
Johan Vallon-Christersson, Johan Staaf, Anders Kvist, Patrik Medstrand, ?ke Borg, Carlos Rovira
BMC Genomics , 2007, DOI: 10.1186/1471-2164-8-295
Abstract: Up to 88% of expressed protein coding loci displayed concurrent expression from the complementary strand. Antisense transcription is cell specific and showed a strong tendency to be positively correlated to the expression of the sense counterparts. Even if their expression is wide-spread, detected antisense signals seem to have a limited distorting effect on sense profiles obtained with double-stranded probes.Antisense transcription in humans can be far more common than previously estimated. However, it has limited influence on expression profiles obtained with conventional cDNA probes. This can be explained by a biological phenomena and a bias of the technique: a) a co-ordinate sense and antisense expression variation and b) a bias for sense-hybridization to occur with more efficiency, presumably due to variable exonic overlap between antisense transcripts.Non-coding RNAs have recently been reported as more common, more diverse, and accredited more important functions than previously anticipated [1-3]. Among the most abundant non-coding transcripts, there is a group called natural antisense transcripts (NATs) that carries regions of perfect complementarity to protein coding (sense) RNAs [4-7]. In silico studies of available transcript sequence data have found that up to 24% of human protein coding loci also encode cis-NATs [8,9]. However, antisense transcripts tend to be poly(A) negative and nuclear localized [10]. If this is true, the abundance of NATs (cis and trans) may be higher yet, since nuclear non-polyadenylated transcripts are underrepresented in transcript sequence databases.This fact may have important implications for researchers, not only because of their potential biological function but they may also turn out to be influential on the interpretation of large experimental data sets. For instance, the cDNA microarray technique has been used in genome-wide expression studies to address basic questions about gene function and in the pursuit of a more prec
BASE - 2nd generation software for microarray data management and analysis
Johan Vallon-Christersson, Nicklas Nordborg, Martin Svensson, Jari H?kkinen
BMC Bioinformatics , 2009, DOI: 10.1186/1471-2105-10-330
Abstract: The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE.BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se webcite under the terms of the GPLv3 license.Microarray techniques produce large amounts of data in many different formats and experiment sizes are growing with more samples analysed in each experiment. Samples are collected over long time and microarray analysis is performed asynchronously and re-analysed as more samples are hybridised. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. Particularly for microarray service facilities, where researchers deposit samples for experimentation, information tracking becomes vital for a subsequent data delivery back to the researchers. To meet the information tracking and data analysis challenges involved in microarray experiments we reimplemented the obsolete BASE version 1.2 (BASE1) [1].BASE (BioArray Software Environment) is a MIAME (Minimum Information About a Microarray Experiment guidelines) [2] compliant application designed for mic
BioArray Software Environment (BASE): a platform for comprehensive management and analysis of microarray data
Lao H Saal, Carl Troein, Johan Vallon-Christersson, Sofia Gruvberger, ?ke Borg, Carsten Peterson
Genome Biology , 2002, DOI: 10.1186/gb-2002-3-8-software0003
Abstract: Microarrays are emerging as one of the most exciting and promising technologies for biological research and clinical practice [1]. The technology has been utilized in various applications such as the profiling of mRNA [2] and protein levels [3], elucidating protein-DNA interactions [4], assessment of DNA copy number [5], and detection of methylated sequences [6], and today is accessible to even relatively small laboratories. Typically, arrays contain 5,000 to 45,000 reporters, each of which has dozens of biological (for example, gene name, sequence, function) and quality control (QC; for example, sequence verification, purity, number of gel bands) annotations. Each array can be used to analyze up to two biomaterials, each of which can have any number of biological annotations (for example, in vitro treatments, clinical follow-up, mutation status), and in a single hybridization, data spanning tens of megabytes are generated. Whereas microarrays have shed light on many biological processes and disease states, for us [7,8,9,10] and others, a significant bottleneck remains the analysis of hybridization data in the context of biomaterial and reporter annotations. There are a number of separate software systems that individually address some of the needs, such as databases and applications for clustering and visualization of microarray data [11,12,13,14,15,16,17,18], public databases that contain reporter information [19,20,21], commercial laboratory information management systems (LIMS), and various storage methods (such as lab notebooks, clinical charts and public and private databases) for recording biomaterial annotations. However, to our knowledge there are no unified systems capable of organizing all the information surrounding microarray experimentation and which also integrate this information with tools for the analysis of quantified microarray hybridization data.To address these needs, we developed a system called BioArray Software Environment (BASE) that provid
Tasquinimod (ABR-215050), a quinoline-3-carboxamide anti-angiogenic agent, modulates the expression of thrombospondin-1 in human prostate tumors
Anders Olsson, Anders Bj?rk, Johan Vallon-Christersson, John T Isaacs, Tomas Leanderson
Molecular Cancer , 2010, DOI: 10.1186/1476-4598-9-107
Abstract: One of the most significant differentially expressed genes both in vitro and in vivo after exposure to tasquinimod, was thrombospondin-1 (TSP1). The up-regulation of TSP1 mRNA in LNCaP tumor cells both in vitro and in vivo correlated with an increased expression and extra cellular secretion of TSP1 protein. When nude mice bearing CWR-22RH human prostate tumors were treated with oral tasquinimod, there was a profound growth inhibition, associated with an up-regulation of TSP1 and a down- regulation of HIF-1 alpha protein, androgen receptor protein (AR) and glucose transporter-1 protein within the tumor tissue. Changes in TSP1 expression were paralleled by an anti-angiogenic response, as documented by decreased or unchanged tumor tissue levels of VEGF (a HIF-1 alpha down stream target) in the tumors from tasquinimod treated mice.We conclude that tasquinimod-induced up-regulation of TSP1 is part of a mechanism involving down-regulation of HIF1α and VEGF, which in turn leads to reduced angiogenesis via inhibition of the "angiogenic switch", that could explain tasquinimods therapeutic potential.During the last decades, development of new cancer treatments that are capable of inhibiting tumor growth by inhibition of the blood supply has received great attention [1,2]. The quinoline compound tasquinimod [ABR-215050; CAS number 254964-60-8; 4-hydroxy-5-methoxy-N,1-dimethyl-2-oxo-N-[(4-trifluoromethyl) phenyl]-1,2-dihydroquinoline-3-carboxamide] has emerged as a candidate [3], by virtue of its pharmacological profile with anti-angiogenic and anti-tumor potency in experimental human prostate cancer models [4,5]. Thrombospondin-1 (TSP1) is a 450 kDa glycoprotein initially found in platelets, but also synthesized and secreted by many normal and transformed cells. TSP1 has been shown to be a potent natural inhibitor of tumor progression and metastases via inhibition of angiogenesis and migration or by activation of TGFβ (for review see [6-8]). Several mechanisms have been propos
Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios
Johan Staaf, Johan Vallon-Christersson, David Lindgren, Gunnar Juliusson, Richard Rosenquist, Mattias H?glund, ?ke Borg, Markus Ringnér
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-409
Abstract: We demonstrate an asymmetry in the detection of the two alleles for each SNP, which deleteriously influences both allelic proportions and copy number estimates. The asymmetry is caused by a remaining bias between the two dyes used in the Infinium II assay after using the normalization method in Illumina's proprietary software (BeadStudio). We propose a quantile normalization strategy for correction of this dye bias. We tested the normalization strategy using 535 individual hybridizations from 10 data sets from the analysis of cancer genomes and normal blood samples generated on Illumina Infinium II 300 k version 1 and 2, 370 k and 550 k BeadChips. We show that the proposed normalization strategy successfully removes asymmetry in estimates of both allelic proportions and copy numbers. Additionally, the normalization strategy reduces the technical variation for copy number estimates while retaining the response to copy number alterations.The proposed normalization strategy represents a valuable tool that improves the quality of data obtained from Illumina Infinium arrays, in particular when used for LOH and copy number variation studies.Genomic copy number alterations (CNA) and allelic imbalances are common events in the development of cancer and certain genetic disorders [1,2]. The introduction of whole genome genotyping (WGG) arrays based on single nucleotide polymorphism (SNP) genotyping [3,4] allows for combined DNA copy number (SNP-CGH) and loss-of-heterozygosity (LOH) analysis at high resolution [5]. Currently, two major SNP array platforms are in use, Affymetrix GeneChip arrays [6] and Illumina BeadChips [7]. The Infinium assay for Illumina BeadChips is based on allele-specific hybridization coupled with primer extension of genomic DNA using primers directly surrounding the SNP on randomly ordered bead arrays [4]. The Infinium assay has been further developed into allele-specific single base extension using two color labeling with the Cy3 and Cy5 fluorescent dy
Segmentation-based detection of allelic imbalance and loss-of-heterozygosity in cancer cells using whole genome SNP arrays
Johan Staaf, David Lindgren, Johan Vallon-Christersson, Anders Isaksson, Hanna G?ransson, Gunnar Juliusson, Richard Rosenquist, Mattias H?glund, ?ke Borg, Markus Ringnér
Genome Biology , 2008, DOI: 10.1186/gb-2008-9-9-r136
Abstract: Cancer development involves genomic aberrations such as gene copy number gains or losses and allele-specific imbalances [1]. Array-based comparative genomic hybridization (aCGH) [2] has, since its introduction, become a widely adopted tool for identification and quantification of DNA copy number alterations (CNAs) in tumor genomes [3]. The introduction of whole genome genotyping (WGG) arrays based on single nucleotide polymorphism (SNP) genotyping [4,5] allows for combined DNA copy number (SNP-CGH) and loss-of-heterozygosity (LOH) analysis at high resolution [6]. Current SNP arrays can genotype several hundreds of thousands of SNPs simultaneously. LOH analysis has in the past been a vital tool for the discovery of chromosomal regions harboring tumor-suppressor genes when inactivated by the classic mechanism of allelic loss [7]. LOH occurs as a consequence of reduction in copy number in a diploid genome but it may also appear as copy number-neutral LOH resulting from uniparental disomy or mitotic recombination events. The latter type of changes is not detectable by conventional aCGH platforms. Moreover, increases in copy number due to, for example, mono-allelic amplification may falsely be detected as LOH [8]. Therefore, by combining LOH and copy number analysis, regions of LOH derived from either copy number loss or neutral events may be identified. Conventional LOH studies compare the genotype of a tumor to its matched constitutional genotype. Current generations of WGG arrays have been reported to provide sufficiently high marker density to infer regions of LOH by the absence of heterozygous loci without the use of a matched control [9]. However, the increased marker density disqualifies the assumption of independence between allele calls of adjacent SNPs due to linkage disequilibrium. This may lead to detection of non-tumor specific homozygous regions based solely on the marker density. In the absence of a matched normal, haplotype correction methods may be requi
Molecular subtypes of breast cancer are associated with characteristic DNA methylation patterns
Karolina Holm, Cecilia Hegardt, Johan Staaf, Johan Vallon-Christersson, G?ran J?nsson, H?kan Olsson, ?ke Borg, Markus Ringnér
Breast Cancer Research , 2010, DOI: 10.1186/bcr2590
Abstract: We analysed methylation status of 807 cancer-related genes in 189 fresh frozen primary breast tumours and four normal breast tissue samples using an array-based methylation assay.Unsupervised analysis revealed three groups of breast cancer with characteristic methylation patterns. The three groups were associated with the luminal A, luminal B and basal-like molecular subtypes of breast cancer, respectively, whereas cancers of the HER2-enriched and normal-like subtypes were distributed among the three groups. The methylation frequencies were significantly different between subtypes, with luminal B and basal-like tumours being most and least frequently methylated, respectively. Moreover, targets of the polycomb repressor complex in breast cancer and embryonic stem cells were more methylated in luminal B tumours than in other tumours. BRCA2-mutated tumours had a particularly high degree of methylation. Finally, by utilizing gene expression data, we observed that a large fraction of genes reported as having subtype-specific expression patterns might be regulated through methylation.We have found that breast cancers of the basal-like, luminal A and luminal B molecular subtypes harbour specific methylation profiles. Our results suggest that methylation may play an important role in the development of breast cancers.Breast cancer is a complex and heterogeneous disease and one of the leading causes of death among women. Tumourigenesis is a multistep process resulting from the accumulation of genetic alterations such as mutations, rearrangements and copy number variations, but also epigenetic alterations such as promoter methylation and histone modification [1,2]. DNA methylation plays an essential role in development, chromosomal stability, and for maintaining gene expression states [1]. DNA methylation occurs when methyl groups are added to cytosines in CpG dinucleotides, leading to a closed chromatin conformation and gene silencing. CpGs are often found at increased frequ
The HER2-Encoded miR-4728-3p Regulates ESR1 through a Non-Canonical Internal Seed Interaction
Inga Newie, Rolf S?kilde, Helena Persson, Dorthe Grabau, Natalia Rego, Anders Kvist, Kristoffer von Stedingk, H?kan Axelson, ?ke Borg, Johan Vallon-Christersson, Carlos Rovira
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0097200
Abstract: Since the early 1980s remarkable progress has been made in understanding the role of the HER2 locus in carcinogenesis, but many details of its regulatory network are still elusive. We recently reported the finding of 367 new human microRNA (miRNA) genes of which one, mir-4728, is encoded in an intron of the HER2 gene. Here, we confirm that the HER2 oncogene is a bi-functional locus encoding the membrane receptor and a functional miRNA gene. We further show that miR-4728-3p has alternative functionalities depending on the region used for interaction with its target; the canonical seed between nucleotides 2–8 or a novel, more internal seed shifted to nucleotides 6–12. Analysis of public data shows that this internal seed region, although rare compared to the far more abundant canonical 2–8 seed interaction, can also direct targeted down-regulation by other miRNAs. Through the internal seed, miR-4728-3p regulates expression of estrogen receptor alpha, an interaction that would have remained undetected if classic rules for miRNA-target interaction had been applied. In summary, we present here an alternative mode of miRNA regulation and demonstrate this dual function of the HER2 locus, linking the two major biomarkers in breast cancer.
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